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Cover of Risk stratification tools for predicting bleeding events in people with atrial fibrillation

Risk stratification tools for predicting bleeding events in people with atrial fibrillation

Atrial fibrillation: diagnosis and management

Evidence reviews E&F

NICE Guideline, No. 196

Authors

.

London: National Institute for Health and Care Excellence (NICE); .
ISBN-13: 978-1-4731-4043-1
Copyright © NICE 2021.

1. Effectiveness of risk stratification tools for predicting bleeding in people with atrial fibrillation

1.1. Review question: What is the most clinically and cost-effective risk stratification tool for predicting bleeding in people with atrial fibrillation?

1.2. Introduction

Anticoagulation is the therapy with the greatest influence on prognostic outcomes for patients with atrial fibrillation. Anticoagulation,however, is associated with significant risk for major haemorrhage, from one to seven per cent per annum in clinical trials. For the majority of patients with AF the benefits of anticoagulation outweigh this risk.

The risk of major haemorrhage varies among populations with AF and there is a potential to reduce harm further by identifying patients at high risk for whom to proceed with caution, particularly as many risk factors for haemorrhage on anticoagulation are modifiable. There are over twenty schemes & methods (including modifications), published, that attempt to quantify the risk of major haemorrhage on anticoagulation.The predicted risk of haemorrhage for an individual is not precise. It needs to be interpreted in context as many of the factors that increase risk of bleeding also increase the risk of embolic stroke.

The intention of this chapter is to evaluate which is the most clinical and cost effective method and to develop guidance as to how this informs clinical practice.

1.3. PICO table

For full details see the review protocol in appendix A.

1.4. Methods and process

This evidence review was developed using the methods and process described in Developing NICE guidelines: the manual.89Methods specific to this review question are described in the review protocol in appendix A.

This review is not a ‘prognostic accuracy’ review, but is instead a review of trials that have compared later health outcomes in people randomised to different prediction tools. Tools with differing prognostic accuracies may differ in their influence on later health outcomes through stimulating a more or less appropriate treatment approach. Whilst accuracy is not measured directly in such randomised trials, the advantage of such studies is that they demonstrate clinical efficacy. In contrast a prognostic accuracy study can only demonstrate the intrinsic predictive accuracy of the tool and is unable to show how that the accuracy affects health outcomes. However such randomised trials are not commonly undertaken, and may provide equivocal results, and so a prognostic accuracy review has also been undertaken.

Declarations of interest were recorded according to NICE’s 201889conflicts of interest policy.

1.5. Clinical evidence

1.5.1. Included studies

No relevant comparative clinical studies comparing bleeding risk tools with HAS-BLED were identified.

See also the study selection flow chart in appendix C, study evidence tables in appendix D, forest plots in appendix E and GRADE tables in appendix H.

1.5.2. Excluded studies

See the excluded studies list in appendix I.

1.5.3. Summary of clinical studies included in the evidence review

No studies were included

1.5.4. Quality assessment of clinical studies included in the evidence review

Not applicable.

See appendix F for full GRADE tables.

1.6. Economic evidence

1.7. Included studies

No relevant health economic studies were identified.

1.8. Excluded studies

No health economic studies that were relevant to this question were excluded due to assessment of limited applicability or methodological limitations.

See also the health economic study selection flow chart in appendix G.

1.8.1. Unit costs

Outlined in Table 2is a description of each risk tool and any additional healthcare resources required. As demonstrated in the table most risk tools require a review of the person’s medical history and in some cases computer access to complete algorithms. Only the ABC bleeding risk score required additional tests (biomarker assays), which would be an additional cost to the NHS.

2. Accuracy of risk stratification tools for predicting bleeding events in people with atrial fibrillation

2.1. Introduction

See evidence review E.

2.2. Review question: What is the most accurate risk stratification tool for predicting bleedingevents in people with atrial fibrillation?

For full details see review protocol in Appendix A.

2.3. Clinical evidence

We searched for cohort studies covering the validation of risk assessment tools for bleeding in people with AF. 54studies evaluating the accuracy of bleedingrisk tools for people with atrial fibrillation were included in the review3, 5, 8, 11, 14, 19-21, 23, 25, 30-33, 36-39, 41, 52, 54, 56-58, 63, 65, 71, 74, 77, 88, 90, 91, 95, 103, 110, 113-117, 119, 120, 125, 126, 128, 135-138, 142, 146, 147, 154, 158whichare summarised in Table 4 below.The different risk schemes are outlined in Table 3.Evidence from these studies is summarised in the GRADE clinical evidence profilesbelow (Tables 4-13). See also the study selection flow chart in Appendix B, study evidence tables in Appendix E, forest plots in Appendix D, and excluded studies list in Appendix H.

This review evaluates the accuracy of the risk tools to predict bleeding, with reference to their discriminatory capabilities (sensitivity, specificity, and C statistics), calibration statistics and Atrial fibrillation update the Net Reclassification Index. The reference standard was the incidence (or not) of major bleeding (or other bleeding categories) at follow up.Only studies where all patients were anticoagulated (or where an anticoagulated sub-group were a separately analysed) were included; this was because the aim of the review is to establish which tool can best predict bleeding in those people who are taking anticoagulation.

Analyses were by cohort rather than study; that is, where a study included separate analyses for different OACs, these were analysed as separate cohorts (as if they were separate studies). This approach facilitated sub-grouping for different OACs if heterogeneity was detected.

For sub-grouping by OAC, cohorts were categorised into 1) VKA cohorts, 2) Mixed VKA/DOAC/unclear category cohorts and 3) DOACcohorts. For sub-grouping by antiplatelets use, cohorts were categorised into 1) cohorts with <33% on antiplatelets/NSAIDs/aspirin, 2)cohorts with >33%on antiplatelets, and 3) cohorts where the number on antiplatelets were not reported.

Separate analyses were performed for 1) major bleeding, 2) clinically relevant bleeding and 3) intracranial bleeding. Data concerning other forms of bleeding were not analysed in this review as they were deemed to overlap with these 3 categories, though available dataare outlined in the clinical evidence tables.

Summary of included studies

2.3.1. Discriminationfor MAJOR BLEEDING

2.3.2. Calibrationfor MAJOR BLEEDING

Calibration waspredominantlyreportedwith graphical rather than numerical data. Hence this section has been dealt with narratively.

Several studies merely reported a non-comparative‘adequate’calibration, usuallybased on a Hosmer-Lemeshow p value >0.05. ‘Adequate’ goodness of fit was thus described for ATRIA4, 14, 63, HAS-BLED4, 14, 63, 71, HEMORRHAGES4, 14, 63, 71, ORBIT14, Shireman71, mOBRI/Beyth71, Kuijer71and ABC11, 23, 54. It was not possible, based on these data, to compare thelevels of calibration acrossthese tools.

However, some studies performed a relative, albeit qualitatively described,evaluation, which was based on inspection of calibration plots. Hilkens, 201758stated that ORBIT had a better calibration at 2 years than HEMORRHAGES, ATRIA, Shireman and HAS-BLED. ORBIT was also regarded as better calibrated than HAS-BLED and ATRIA by fourfurther studies,77, 91, 114, 158although Mori, 201988did not note a difference.ATRIA was identified as the least wellcalibrated by twoof the studies91, 158but better than HAS-BLED by one114. Proietti 2018114noted that whilst ORBIT had the best calibration over all risk strata, HEMORRHAGES tended to underestimate risk, particularly in patients with a higher predicted risk, whereas ATRIA and HAS-BLED tended to over-estimate bleeding risk. Similarly, O’Brien91noted that whilst ORBIT was good at predicting risk in all risk strata, HAS-BLED tended to have worse calibration in low-risk strata, and ATRIA performed badly at mostrisk strata. Claxton, 201823evaluated the calibration of the Anticoagulation-specific bleeding score (ASBS) alone, demonstrating good calibration. Calibration plots are shown below.

Note that Lip, 201877, Mori, 201988and Yao, 2017158only used DOACcohorts, but O’Brien, 201591and Claxton, 201823used a mixed cohort. Both Hilkens, 201758and Proietti, 2018114contained separate cohorts of patients taking dabigatran and warfarin, but it appears that the plots reproduced below were from their total, mixed, cohort. It should also be noted that Proietti 2018114failed to specify if calibration data referredto major bleeding, although major bleedingis assumedto be the most likely bleeding

Image niceng196er4f1

Source: Calibration plot in Claxton, 201823. This was for the Anticoagulation-specific bleeding score and was based on a mixed (VKA and DOAC) cohort.

Image niceng196er4f2

Source: Calibration plot in Hilkens, 201758. This was based on a mixed (VKA and DOAC) cohort.

Image niceng196er4f3

Source: Calibration plot in Proietti et al. 2018114(bleeding risk scores calibration between derivation cohorts and RE-LY cohort events rates). This probably relates to their total, mixed, cohort.

Image niceng196er4f5

Source: Calibration plot in Lip, 201877. This was based on an exclusively DOAC-using cohort.

Image niceng196er4f6

Source: Calibration plot in Yao, 2017158. This was based on an exclusively DOAC-using cohort.

2.3.3. Net Reclassification improvementfor MAJOR BLEEDING

Several studies reported the Net Reclassification Improvement (NRI). This is expressed in terms of one (index) risk tool to another (comparator) risk tool, and gives a score between −2 and +2 (with +2 representing the best possible performance of the index tool relative to the comparator, and −2 the worst). The score represents the net improvement of the index test relative to the comparator in terms of the proportion of true cases (judged by later development of bleeding) that are correctly up-classified by the tool (relative to any false negative classifications yielded by the comparator), and the proportion of false cases (judged by the lack of later bleeding) that are correctly down-classified by the tool (relative to any false positive classifications yielded by the comparator). Meanwhile, incorrect up-classification or incorrect down-classification of the index relative to the comparator convey negative scores to the NRI, and so if a score is negative overall this indicates the index is less accurate than the comparator.

2.3.4. Discrimination for CLINICALLY RELEVANT BLEEDING

2.3.5. Calibration for CLINICALLY RELEVANT BLEEDING

Calibration was poorly reported in most papers, with all papers merely reporting the p value for Hosmer-Lemeshow statistics and proving a qualitative assessment of the relative calibration between tools. All studies simply reported a non-comparative ‘adequate’ calibration, usually based on a Hosmer-Lemeshow p value >0.05. ‘Adequate’ goodness of fit was thus described for ATRIA,4, 14, 63HAS-BLED,4, 14, 63, 71HEMORRHAGES4, 14, 63and ORBIT14. It was not possible, based on these data, to compare thelevels of calibration between these tools.

2.3.6. Net Reclassification improvement for CLINICALLY RELEVANT BLEEDING

2.3.7. Discrimination for INTRACRANIAL HEMORRHAGE

2.3.8. Calibration for INTRACRANIAL HEMORRHAGE

Proietti et al 2018114reported that the ORBIT score had best agreement between predicted and observed risks, that ATRIA had worst agreement and thatATRIA and HAS-BLED tended to overestimate the risk of bleeding. Meanwhile, HEMORRHAGES tended to underestimate bleeding risk. However it was unclear if this related specifically to intracranial bleeding.

2.3.9. Net Reclassification improvement for INTRACRANIAL HEMORRHAGE

2.4. Economic evidence

2.4.1. Included studies

No relevant health economic studies were identified.

2.4.2. Excluded studies

No health economic studies that were relevant to this question were excluded due to assessment of limited applicability or methodological limitations.

See also the health economic study selection flow chart in appendix D.

2.4.3. Unit costs

See 1.8.1.

2.5. The committee’s discussion of the evidence

2.5.1. Interpreting the evidence

2.5.1.1. The outcomes that matter most

No clinical evidence was generated by thereviewon the effectiveness of risk stratification tool for predicting bleeding. The committee discussed the predictive accuracy evidence only, as this was felt to be sufficient to inform recommendations relevant to the most appropriate methods to predict bleeding in people with AF, without the need for any consensus recommendations or research recommendations pertaining to the effectivenessreview.

The committee agreed that the most critical predictive accuracy outcome measures for decision-making were calibration data. This was because the committee agreed that the best use of bleeding risk tools was as a means to guide a shared patient/clinician plan for alleviating reversible risk factors for bleeding; such a plan would require an accurate measure of absolute risk, the accuracy of which is best measured by calibration outcome data. Accurate binary decision-thresholds, such as those measured by discrimination outcome data (C statistics or sensitivity/specificity) were regarded as less critical, given that bleeding risk tools were not regarded as a decision aid for anticoagulant use (see second paragraph in section2.5.1.3). Net reclassification improvement (NRI) data, although also less critical than calibration data, was regarded as slightly more important than C statistics or sensitivity/specificity because of its propensity to sensitively differentiate the accuracy of different tools.

2.5.1.2. The quality of the evidence

Evidence was generally deemed low or very low quality. Risk of bias was serious or very serious due to unclear methodology in terms of blinding of risk tool and outcome data, and in many studies the follow up time was short (<5 years) or involved few events (<100). The quality was also affected by serious or very serious heterogeneity.

2.5.1.3. Benefits and harms

The benefit of an accurate estimation of bleeding risk is that this may prompt appropriate and directed alleviation of any reversible causes of bleeding, as well as allowing appropriate levels of vigilance during anticoagulation. One possible disadvantage (harm) of using bleeding risk tools is underestimating bleeding risk, which may lead to insufficient attention to preventable risk factors and insufficient monitoring. Another potential harm is over-estimating bleeding risk, which can lead to unnecessary over-vigilance and possibly reluctance on the part of the patient (and maybe clinician) to commence anticoagulation. Thus using accurate bleeding risk prediction tools was seen by the committee as vital to maximise benefits and minimise harms.

The committee discussed the commonly observed clinical practice of using the bleeding risk score as a counterbalance to the stroke risk score, which tends to be done in order to facilitate binary decisions about initiating anticoagulation. The drawbacks of this were discussed. Comparisons of the actual bleeding and stroke risk tool scores were regarded by the committee as largely meaningless, given the varying significance of scores across different tools. In addition, comparison of absolute stroke and bleeding risks (derived from the scores) was also regarded as potentially misleading in the context of a decision to anti-coagulate, because bleeding risk includes the risk of bleeding events of lower severity than a stroke. Thus, for example, the committee noted that an equal absolute risk of stroke and bleeding would not necessarily represent equipoise, as the two competing events might not be of comparable severity. Any assessment of risk must also weigh up the probability of an event occurring and consider the consequences of the event occurring. The committee reiterated the importance of using a bleeding risk tool to inform plans to reduce reversible causes of bleeding and to maintain appropriate levels of vigilanceduring anticoagulation, and that it should not be used as a threshold-based tool to determine if anticoagulation should take place.

The committee noted the importance of respecting any decision by an individual not to take anticoagulants. The committee were aware of the recommendations on tailoring healthcare services to the individual in the NICE guideline on patient experience of adult services (CG138).

Committee discussion focussed on tools where the weight of evidence was sufficient to warrant a recommendation. Therefore for tools that had been investigated in only one or two smaller studies, relatively little consideration was given to their possible useeven if predictive accuracy was encouraging. In addition, for those tools with larger amountsof evidence, the clearly less effective tools such as HEMORRHAGES(which had poorer calibration than ORBIT, HASBLED and ATRIA, as well as inferior discriminationand NRI)were given less consideration. Discussion focussed on three main tools: ORBIT, HAS-BLED and ATRIA, with the emphasis, as previously justified, on calibration data.

The calibration evidence suggested that ORBIT was better than HASBLED and ATRIA inaccurately predictingrisk of major bleeding. This was found in both mixed cohorts and DOAC-only cohorts. Importantly, ORBIT was better calibrated at all, and particularly higher, levels of risk. Given the relevance of calibration outcomes to the intended use of the tools - allowing an informed discussion about reversing modifiable risk factors and having an appropriate level of monitoring as a result of an accurate assessment of absolute risk - this finding was an important factor in the recommendation decision. Discrimination data were also discussed, and the committee agreed that the C statistics data supported the calibration data’s indication that ORBIT was the most appropriate tool. Although the C-statisticsevidence suggested little to choose between HAS-BLED, ATRIA and ORBIT for people on VKAs, the C statisticsevidence suggested that ORBIT was the most accurate tool to use for patients on DOACs. The committee noted that around 90% of patients were currently on DOACS, and that this proportion would continue to increase with time. Hence this supported ORBIT beingregarded as the most appropriate bleeding risk tool for current and future patients.The sensitivity and specificity data at the established thresholds suggested that HAS-BLED and other tools might be more sensitive than ORBIT in predicting who will bleed whilst on anticoagulants, but this was counterbalanced bythe greater specificity of ORBIT. In contrast to the situation when predicting strokes, reduced sensitivity of bleeding risk prediction was not regarded as a serious problem because failure to detect high bleeding risk would not necessarily change decisions. This was because prediction of bleeding would not be used to withhold anticoagulants; instead, the risk prediction would be used as an objective aid to discussion with the patient about the need to modify bleeding risks and to be vigilant about possible bleeding. Meanwhile, the NRI evidence was fairly equivocal, suggesting similarities between ORBIT and HAS-BLED, and the committee felt that it did not negate the calibration evidence that ORBIT was the most appropriate tool.

There was some discussion about a two-tier recommendation – recommending ORBIT for people on DOACs and continuing with HAS-BLED for those patients restricted to VKAs (given that HAS-BLED appears to be as accurate, based on discrimination data, as ORBIT and ATRIA in VKA populations). This idea was rejected, partly because it was believed that the people who would currently be given VKAs would tend to be different from the VKA populations in the included studies. The VKA study populations tended to be fairly typical samples of people with NVAF, because VKAs were the principal anticoagulant therapy available at the time of these studies. In contrast, patients currently being given VKAs would tend to be atypical (for example, people with serious renal dysfunction). The committee therefore believed that the evidence suggesting HAS-BLED might be appropriate for people on VKAs was not relevant to current users of VKAs. In addition, ORBIT was superior when measured by calibration outcomes in mixed cohorts. Given the greater relevance of calibration outcomes to the purported usage of bleeding risk tools, this strongly supported the decision to recommend ORBIT for all patients.

In addition to recommending ORBIT as a bleeding prediction tool, the committee also made recommendations on addressing the modifiable bleeding risk factors inherent in ORBIT, as well as the modifiable bleeding risk factors listed in the 2014 recommendations. Although the 2014 bleeding risk factors were related to the HAS-BLED, all were still thought to be relevant to a shared clinical decision on alleviating bleeding risk factors. Reversible causes of anaemia were listed as an additional modifiable risk factor as anaemia is a component of the ORBIT tool.

The committee were of the opinion that the decision to withhold anticoagulation because of concerns over bleeding risk meant depriving a patient of a treatment which, were it not for the bleeding risk, might have been of benefit in stroke prevention. As a number of factors contributing to bleeding risk are dynamic and also potentially correctable, the committee considered that the decision to withhold anticoagulation should not be made in perpetuity but should be subject to regular review and reconsideration as appropriate. They also thought it important that both the review and the outcome of the review should be documented.The committee expressed concern that anticoagulation was often erroneously not initiated due to a perceived high risk of falls, even though a very large number of falls (in excess of 300 per year) are known to be necessary to significantly increase the risk of bleeding. In addition, the committee noted that old age is often used as a reason to not anti-coagulate, even though age is already a factor in the bleeding risk tools used (and therefore would already be accounted for). Therefore the 2014 recommendation that anticoagulation should not be withheld because of the risk of falling was maintained, with an additional note that age should also not be a factor encouraging non-anticoagulation. The committee discussed referring to frailty in the recommendation but given it is so difficult to define they decided against this.

2.5.1.4. Cost effectiveness and resource use

No relevant health economic analyses were identified for this review. The committee discussed the different resource use for the different tests, in particular it was noted that ORBIT required knowledge of whether a patient had reduced haemoglobin or haematocrit. This was not part of the HAS-BLED score, the previously recommended bleeding risk tool, and so would be a change from current practice. The committee noted however that this should be available from patient history and so is unlikely to require additional NHS resource.

The committee also discussed the importance of using the most accurately calibratedbleeding tool as this would help to accurately identify individuals at higher risk of bleeding and therefore prompt the physicians to modify any bleeding risk factors and ensure adequate monitoring is provided. A more accurate tool, as demonstrated with the calibration data presented for ORBIT, would ensure the correct patients are being monitored and so NHS resources would be used more efficiently. That is only those who are truly at higher risk of bleeding are being monitored.

The committee agreed that there was sufficient clinical evidence of superiority for ORBIT to warrant an inevitablechange in practice.It involves measuring some parameters, such as haemoglobin and haematocrit, that are not included in the HAS-BLED tool used in current practice. However, the committee agreed that these factors would be measured routinely for people starting anticoagulation, regardless of the risk tool used, so extra resources are unlikely to be needed.

2.5.2. Other factors the committee took into account

Thecommitteenoted that people from black and ethnic minoritygroups do have a greater risk of stroke but the relationship with atrial fibrillation is unclear. For example, it is not clearif it Atrial fibrillation update isthe presence of comorbidities or ethnic group, or an interaction beween these, that increases the risk of stroke. The committee also noted that a greater proportion of people from black and ethnic minority groups are undiagnosed compared to the general population. This is in part related to who is targeted for screening which is outside of the remit of this guideline.

The use of the ORBIT score is a change in practice, and may lead to some implementation hurdles. One potential problem is that ORBIT does not measure all of the modifiable risk factors previously included in HAS-BLED. At first sight this appears to imply additional testing is needed to ensure that all modifiable risk factors are measured. We would argue that whether ORBIT or HAS-BLED are used does not actually change the amount of modifiable risk factor investigations that need to be carried out by the investigating clinician. For example, full blood count, labile INR, blood pressure, liver function tests and renal function tests will need to be carried out in either case to evaluate whether current bleeding, increased blood pressure or treatable liver or renal disorders are present, each of which can be treated if needed to reduce bleeding risk. The only difference is that the results of labile INR, blood pressure, liver function tests and renal function tests will feed into informing the HAS-BLED score whereas haemoglobin and renal function results (GFR) will feed into the ORBIT score. This does not make ORBIT any more costly in terms of clinician time and resources, as other variables in ORBIT do not require invasive investigations. It could be argued that if the modifiable risk factors are not part of the tool then clinicians will not be prompted to discuss their modification. This is unlikely provided good practice is observed, as knowledge of the modifiable risk factors of bleeding is a basic clinical skill for any clinician dealing with AF patients, and such prompting should not be necessary. Another potential problem is that recommended bleeding risk evaluation for other conditions (such as venous thromboembolism) does not use ORBIT. This means that if ORBIT is used for AF, another tool (such as HAS-BLED) has to be used for other conditions. We would argue that if other tools need to be used for other conditions this does not constitute a major hurdle for clinicians, as the use of these tools is not difficult, and access to the online versions is straightforward. Nevertheless, to avoid clinician confusion with the unfamiliar tool, there will be a need for an initial transition period when new practices are being learned. This may require re-education in both primary and secondary care, which will have a resource impact, although this will be a time-limited impact, as each clinician will require limited training. Finally, unlike HAS-BLED, ORBIT is not embedded in the GP system. This will initially lead to the need to work outside this system, causing some practical difficulties. It is hoped, however, that ORBIT will eventually become embedded in the GP system. Again, this will have a resource impact, but given that centralised software changes are unlikely to be too difficult, the impact is not believed to be too large. Whilst implementation of ORBIT will provide some challenges, these should be overcome by the advantages of a tool that can provide a more accurate measure of bleeding risk.

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Appendices

Appendix B. Literature search strategies

This literature search strategy was used for the following reviews:

  • What is the most clinically and cost-effective tool for assessing bleeding risk in people with atrial fibrillation?
  • What is the most accurate risk stratification tool for predicting bleeding events in people with atrial fibrillation?

The literature searches for this review are detailed below and complied with the methodology outlined in Developing NICE guidelines: the manual.89

For more information, please see the Methods Report published as part of the accompanying documents for this guideline.

B.1. Clinical search literature search strategy (PDF, 452K)

B.2. Health Economics literature search strategy (PDF, 462K)

Appendix D. Economic article selection

Figure 4. Flow chart of health economic study selection for the guideline (PDF, 153K)

Appendix E. Full GRADE tables(Including individual study data)

Table 24. Clinical evidence profile: accuracy of prediction of Major Bleeding in all risk tools featured in the studies (see table 3). Outcomes split across subgroups are only shown if sub-grouping was able to reduce I2to <50% in all sub-groups. (PDF, 403K)

Table 25. Clinical evidence profile: sensitivity and specificityof prediction of Major Bleeding in all risk tools featured in the studies (see table 3). 95% CIs are given for non-pooled results; for meta-analysed results the 95% credible intervals are given for the pooled effect only. (PDF, 406K)

Table 26. NRI for major bleeding – HAS-BLED versus other tools. (PDF, 245K)

Table 27. NRI for major bleeding – ATRIA versus other tools (PDF, 193K)

Table 28. NRI for major bleeding – HEMORRHAGES versus other tools (PDF, 176K)

Table 29. NRI for major bleeding – ORBIT versus other tools (PDF, 172K)

Table 30. NRI for major bleeding – CHADSVASC versus other tools (PDF, 166K)

Table 31. Clinical evidence profile: accuracy of prediction of CRB in all risk tools featured in the studies (see table 3). Outcomes split across subgroups are only shown if sub-grouping was able to reduce I2 to <50% in all sub-groups. (PDF, 332K)

Table 32. Clinical evidence profile: sensitivity and specificityof prediction of clinically relevant bleedingin all risk tools featured in the studies (see table 3). 95% CIs are given for non-pooled results. (PDF, 331K)

Table 33. NRI for clinically relevant bleeding (PDF, 198K)

Table 34. Clinical evidence profile: accuracy of prediction of ICH in all risk tools featured in the studies (see table 3). Outcomes split across subgroups are only shown if sub-grouping was able to reduce I2 to <50% in all sub-groups. (PDF, 267K)

Table 35. Clinical evidence profile: sensitivity and specificityof prediction of intracranial hemmorhagein all risk tools featured in the studies (see table 3). 95% CIs are given for non-pooled results. (PDF, 210K)

Table 36. NRI for intracranial bleeding (PDF, 156K)

Appendix F. Forest plots

F.1. C statistics

Download PDF (1.1M)

Appendix G. Clinical evidence tables

Download PDF (1.4M)

Appendix H. Risk of bias (PROBAST)

Download PDF (504K)

Appendix I. Economic evidence tables

None.

Appendix J. Excluded clinical studies

No studies were excluded from the review on effectivess.

Table 92. Studies excluded from the clinical reviewRCT (PDF, 179K)

Table 93. Studies excluded from the clinical reviewaccuracy (PDF, 165K)

Appendix K. Excluded economic studies

No studies were excluded from the review on effectivenessof tools to predict bleeding.

No studies were excluded from the review on accuracy of tools to predict bleeding.

Figures

Figure 1. <Insert graphic title here>.

Figure 1<Insert graphic title here>

Source: Calibration plot in O’Brien 201591. This was a mixed cohort.

Tables

Table 1PICO characteristics of review question

PopulationPeople aged over 18 with a diagnosis of AF.
Interventions

Any bleeding risk tool (for example, ATRIA, HEMORRHAGES, ORBIT)

[Note: treat each test using a different threshold as a separate intervention].

ComparisonHAS-BLED (the established method, as recommended by previous version of this guideline)
OutcomesCritical
  • health-related quality of life
  • mortality
  • stroke or thromboembolic complications
  • major bleeding
Study designRandomised controlled trials

Table 2Bleeding risk tools

Risk toolDescriptionAdditional tests required to complete risk tool
ABC bleeding score
-

Age

-

Biomarkers (hematocrit, high sensitivity troponin T (hsTnT), GDF-15)

-

Clinical history (prior bleeding)

Biomarkers.
Orbit bleeding score
-

older age (75+ years)

-

reduced

haemoglobin/haematocrit/history of anaemia

-

bleeding history

-

insufficient kidney function

-

treatment with antiplatelet

None
ATRIA
-

anaemia

-

severe renal disease

-

age ≥75 years

-

any prior haemorrhage diagnosis

-

hypertension history

None
HEMORR2HAGES
-

hepatic or renal disease

-

ethanol (alcohol) abuse

-

malignancy history

-

age >75 years

-

platelet count or function

-

rebleeding risk

-

hypertension (uncontrolled)

-

anaemia

-

genetic factors (CYP2C9 single nucleotide polymorphisms)

-

excessive fall risk

-

stroke history

Genetic testing
HAS-BLED
-

uncontrolled hypertension

-

renal disease - liver disease

-

stroke history

-

prior major bleeding or predisposition to bleeding

-

labile INR

-

age >65

-

concomtant antiplatelets or NSAIDs

-

alcohol excess/abuse

None

Table 3PICO characteristics of review question

Question
PopulationPeople aged >18 with a diagnosis of atrial fibrillation, who are on anticoagulants
Risk tool

Any bleedingrisk tool (e.g HAS-BLED, ORBIT, HEMORRHAGES, ATRIA, etc)

Any other version of HAS-BLEDwith modifications

Target condition or Reference standardLater major bleeding, or other bleeding
Outcomes (in terms of predictive test accuracy, calibration)

Simple diagnostic (prognostic) accuracy outcomes, such as sensitivity and specificity

C-statistic(based on sensitivity and specificity but useful if >1 threshold used).

Calibration outcomes

Reclassification

Study typescohort (external validation, internal validation)
Specific groupsEthnic groups

Table 4Summary of studies included in the review

StudyRisk tool(s)OACConcomitant antiplatelets or NSAIDSPopulationNumber and type of outcome eventsFollow up duration
Apostolakis 20124

HAS-BLED

HEMORRHAGES

ATRIA

Warfarin18%2,293 patients with AF on VKAs, from AMADEUS RCT trial in UK. Age 70, 65% male, 77% hypertension, 20% DM, 13.5% previous stroke, 31% CAD, 18% antiplatelet treatment, TTR 0.57. Drops outs NR. No blinding reported.

39 MB

251 CRB

429 days
Apostolakis 20133

HAS-BLED

CHADS2

CHADSVASC

Warfarin18%As aboveAs aboveAs above
Barnes 20148

CHADS2

CHADSVASC

HEMORRHAGES

HAS-BLED

ATRIA

WarfarinNR2600 patients with NVAF and on warfarin were recruited. USA study. Age 70, 41.7% female, hypertension 75%, DM 25%, CAD 33%, CHF 24.2%, current smoking 6%, renal disease 12%, stroke 11.5%, bleeding diasthesis 31%, HAS-BLED score 2.6, CHADS2 score 3.4. TTR 59.3. Antiplatelets/NSAIDs not reported. No blinding. No data loss reported.100 MB1 year
Berg 201911

HAS-BLED

ABC

Warfarin

Edoxaban

NRPatients enrolled on the ENGAGE AF-TIMI 48 trial, who were therefore taking VKAs or edoxaban. Participation in this sub-study was offered to all enrolled patients until recruitment reached 9000 participantsUnclear3 years
Beshir 201814

mOBRI

CBRM

HEMORRHAGES

HAS-BLED

ATRIA

ORBIT

Warfarin, rivaroxaban, dabigatran35%1017 patients with NVAF and on Warfarin (INR 2–3), dabigatran or rivaroxaban between 2010 and 2015. Malaysia. Age >75: 27%, 52% male, hypertension 82%, IHD 33%, renal impairment 36%, DM 40%, prior stroke/TIA: 22%, CHF: 20%. CHADS2: 2. 35% on antiplatelets. No blinding. 291 lost to follow up from original sample of 1308 patients.

23 MB

76 CRNMB

1 year
Chang 201619

HTI

APTT

Prothrombin time

dabigatran12.50%208 patients (213 enrolled and 5 lost to FU) with NVAF on dabigatran (either 100mg or 150mg/day). Taiwan. Age 74.7, 67.9% male, 36% history of stroke, 24.5% DM, 79.3% hypertension, 18.8% CAD, 16.3% HF, antiplatelets/NSAIDs 12.5%, renal disease 0.5%, history of GI bleeding 23.6%, HAS-BLED 1.8. 5 lost to follow up from original cohort of 213. No blinding.17 MB1 year
Chao 2018a21

Modifiable Bleeding Risk factors score (MBR)

HEMORRHAGES

HAS-BLED

ATRIA

ORBIT

Warfarin22.70%40,450 AF patients (defined as cases where there had been at least 2 confirmed outpatient diagnoses of AF) receiving warfarin between 1998 and 2011 in Taiwan. Age 67.3, male 55.7%, hypertension 67.4%, abnormal renal function 13.2%, stroke 43%, history of bleeding 18%, use of antiplatelets 22.7%, NSAIDs 7.2%, HAS-BLED 2.51. No loss to FU. No blinding reported.

6889 MB

1581 ICH

4.6 years
Chao 2018b20

HAS-BLED baseline

HAS-BLED change from baseline (Delta HAS-BLED)

HAS-BLED follow up

Warfarin2.30%19,566 AF patients on Warfarin and a HAS_BLED score of <2 identified from the NHIRD of Taiwan (1998–2011). Age 63.8, male 57.4%, hypertension 52.6%, abnormal renal function 3.4%, stroke 22.6%, bleeding 6.9%, antiplatelet / NSAID drugs 2.3%. No loss to FU reported. No blinding reported.

3032 MB

671 ICH

4.8 years
Claxton 201823

Anticoagulation-Specific Bleeding Score (ABS)

HAS-BLED

ATRIA

HEMORRHAGES

ORBIT

Warfarin, dabigatran, rivaroxaban and apixabanNR81,285 NVAF patients on Warfarin or DOACs (initiated at baseline). Netherlands. This was an external validation cohort from the Optum Clinformatics database from 2009–2015. For warfarin group (largest) the demographics were: age 73.9, 44% woman, HAS-BLED 2.8, HF 45.5%, CHD: 47.3%, hypertension 89%, DM 39.9%, stroke 33.4%, PAD 25.7%, kidney disease 25.9%, prior GI bleed 16%, prior IC bleed: 2.1%, prior other bleed 16%. No blinding reported. No loss to follow up (as retrospective). No data on antiplatelets/NSAIDS3238 MB1 year
Dalgaard 201925

GARFIELD-AF

HAS-BLED

UnclearUnclear51,180 Danish patients on OACs from the Danish Nationwide registries. Aged 18 or older with NVAF. Excluded patients with rheumatic valve disease or valve surgery.1492 MB (but unclear if some had ICH)1 year
Elvira-Ruiz, 202030

HAS-BLED

ORBIT

ATRIA

HAS-BLEDwith existence of aortic stenosis (AS)

ORBITwith AS

ATRIAwith AS

Mixed VKA and DOACS (results not sub-grouped)17.7%2,880 NVAF patients initiating oral anticoagulants; age 77; 51.1% women; 49.3% permanent AF; hypertension 85.5%; DM 33.9%; CHADSVASC 4; HASBLED 2; ATRIA 3; ORBIT 1.185 MB18 months
Esteve Pastor 201631

HAS-BLED

ORBIT

VKA and DOACS10.90%1276 patients with chronic NVAF on VKA or DOAC for at least 6 months before enrolment (FANTASIIA population). SPAIN. There was another cohort of 406 patients in this paper that underwent electrical cardioversion, and they are not included in this extraction. Age 74, 44% male, 80.6% hypertensive, 30% HF, 29.3% DM, 6.6% VD, 12.9% previous embolism, 3.8% previous bleeding, 10% renal impairment, 1.3% liver impairment, 77.4% VKA, 22.6% DOACs, 10.9% on NSAIDS / antiplatelets. HAS-BLED score: 2. TTR 60.9. No blinding. No loss to FU reported.46 MB1 year
Esteve-Pastor 2017a5

ABC-bleedingCrC

HAS-BLED

VKAsNR1,120 patients with paroxysmal, persistent or permanent AF, stable on VKAs (INR 2–3). Spain. Age 76, 49.5% male, 82% hypertension, 27%DM, 33% dyslipidaemia, 15.5% current smoker, 31.2% HF, 19.6% CAD, 19% previous stroke, 8.4% previous bleeding. TTR at 6 months 80, CHADSVASC 4, HAS-BLED 2, ABC 16.5. Number on antiplatelets – not reported. No loss to FU reported. No blinding.

207 MB

65 ICH

85 GIB

6.5 years
Esteve-Pastor 2017b32

HAS-BLED

Modifiable bleeding risk factors score

VKAs21.40%

4576 patients with paroxysmal, persistent or permanent AF. 2283 on warfarin and 2293 on Idraparinux. Taken from the multinational AMADEUS database. Spain. Age 71, 66.5% male, 21.4% on anti-platelets or NSAID, 77% hypertensive, 20%DM, 23% HF, 31% CAD, 13% previous stroke, TTR 58, CHADSVASC 3, HAS-BLED 2, Modifiable bleeding risks score 1. No loss to FU reported. Assessors BLINDED.

113 MB

597 CRB

347 days
Fang 201133

ATRIA

Outpatient Bleeding Index

Kuijer et al.

Kearon et al.

HEMORRHAGES

Shireman

Riete risk scheme

WarfarinNR3063 patients in the validation cohort, taken from 9,186 patients with NVAF on warfarin (median exposure 3.5 years), taken from the ATRIA study (USA). AF defined as any ICD-9 codes. Demographic data not given for validation cohort. No blinding or loss to FU reported.154 MB3 years
Fox 201736

GARFIELD AF

Risk

HAS-BLED

VKA and DOACNR25,285 patients with AF that were on OACs. 8804 on DOACs and 16,491 on VKAs. Details of the characteristics of these patients are not reported. No blinding reported.625 MB3 years
Friberg 201237

HAS-BLED

HEMORRHAGES

WarfarinNR48, 599 patients with AF (defined by ICD-10 code 1489 with or without subscales A-F) using Warfarin at baseline identified from the Swedish National Discharge Registry. Demographic data stated to be in supplementary file but not available in that file who were on warfarin. This subset was taken from an overall cohort of 170 291 which included those not on anticoagulants. No blinding reported.1.9 MB per 100 patient years1.5 years
Gage 200638

Landefeld and Goldman and Beyth et al.

Kuijer et al.

Kearon et al.

HEMORRHAGES

Warfarin7.40%1604 medicare beneficiaries on NRAF (USA) with chart-confirmed AF on warfarin. 69.2% aged > 75 years, 7.9% hepatic or renal disease, 4.8% malignancy, 37.2% previous stroke, 0.4% uncontrolled hypertension. Also on Aspirin: 7.04%. No blinding or loss to FU reported.4.9 MB per 100 patient yearsUnclear but approx. 1 year
Gallego 201239HAS-BLEDAcenocoumarol16.60%965 consecutive anticoagulated people with permanent or paroxysmal AF, with at least 6 months of anticoagulation with acenocoumarol (INR 2–3). 50% male, mean age 76, hypertension 57%, DM 25.5%, HF 36.5%, prev. stroke/TIA 19%, renal impairment 10%, CAD 4%, hypercholesterolemia 31%, current smoking 14%, previous bleeding 8.5%, median HAS-BLED 2, CHADS2 score 2. Antiplatelet therapy 16.6%. 95 died during FU. No blinding reported.75MB861 days
Garcia-Fernandez 201741

vWF

HAS-BLED

HAS-BLED + vWF

VKA17.80%1215 patients with NVAF on VKA at INR 2–3. Age 76, male 49.3%, hypertension 82.5%, DM 26.4%, HF 31.1%, IHD 19%, previous stroke 18.4%, previous bleeding 8.4%, renal disease 10.3%, antiplatelet drugs 17.8%, HAS-BLED score 2. No loss to FU or blinding reported.222MB2373 days
Hijazi 201456

CHADSVASC

CHADSVASC with TnT

apixaban and warfarin28–34%14,897 patients with AF on apixaban or warfarin, from the ARISTOTLE trial. Likely to be a multinational multi-centre trail but not reported. Ranges of baseline data given as data given for different categories of TnT. Age 64–74, male 53.8–74.6%, CHF 28–47%, hypertension 87%, DM 18–32%, Prior stroke/TIA 16–21%, MI 6–19%. Aspirin 28–34%. Warfarin 53.2–55.7%. BLINDED ASSESORS of BLEEDING. No loss to FU reported.674 MB1.9 years
Hijazi 201456

HAS-BLED

HAS-BLED with TnI

apixaban and warfarin29–34%14,821 patients with AF on apixaban or warfarin, from the ARISTOTLE trial. Overlap with Hijazi, 201457in terms of sample, but this study used a different risk tool. Likely to be a multinational multi-centre trial but not reported. Ranges of baseline data given as data given for different categories of TnI. Age 66–72, male 6–70%, CHF 24–51%, hypertension 87%, DM 21–28%, Prior stroke/TIA 16–21%, MI 6–19%. Aspirin 29–34%. Warfarin 49.9–56.5%. BLINDED assessors. No loss to FU reported.674 MB1.9 years
Hijazi 201654

HAS-BLED

ORBIT

ABC-bleeding

ABC-bleeding (cTnl-hs)

ABC-bleeding (cystatin C)

ABC-bleeding (CKD-EPI)

warfarin and dabigatran (SEP ANALYSES)44%External validation in 8468 patients with AF (67% permanent or persistent) randomised to dabigatran and warfarin in the multinational RE-LY trial. Age 72, 26% women, 44% on antiplatelets or NSAISs, 8% current smokers, 22% DM, 79% hypertension, 29% CHF, 13% previous clinically relevant bleeding, 19% previous stroke/TIA, 17% previous MI, 4% previous PAD, 19% vascular disease, Renal function CKD-EPI 68.2. ASSESSOR BLINDING. No loss to FU reported.463 MB1.9 years
Hijazi 201752

HAS-BLED

ORBIT

(with or without GDF-15)

warfarin and dabigatran36–41%8,474 AF patients (with at least 1 additional risk factor for stroke) taken from the RE-LY study, on dabigatran or warfarin. Baseline characteristics given as ranges as sub-grouped by GDF-15. Age 69–75, male 61–67%, sbp 130, DM 11–35%, HF 25–34%, hypertension 78–80%, previous stroke/TIA 20–22%, prior MI 12–21%, prev PAD/MI/CAD 23–38%, aspirin 36–41%. CHADS2 >3 22–43%. No blinding/loss to FU reported.458 MB1.9 years
Hilkens 201758

HEMORRHAGERS

Shireman

HAS_BLED

ATRIA

ORBIT (score)

ORBIT (equation)

warfarin and dabigatran (SEP ANALYSES)NR3623 patients with AF on warfarin or dabigatran, from the RE-LY trial in Holland. No baseline data available. No report of blinding/loss to FU.266 MB2 years
Jaspers Focks 201663

HAS-BLED

ATRIA

HEMORRHAGES

VKA4.10%1157 AF patients aged >80 years, using a VKA from 2011–2014 in the Netherlands. Median age 84, 42.6% male, 37 months on VKA, 65.8% hypertension, 22% previous stroke/TIA, 9.8% LVEF<40%, 26.6% CAD, 25.7% DM, 21.8% previous bleeding, 5.3% recent or active malignancy, 4.1% on antiplatelets and 2.1% on NSAIDS. HAS-BLED score 2.23. No blinding reported. 735 completed 3 year follow up (367 patients died and 55 patients moved out of the area or discontinued VKA treatment77 MB30 months
Jover 201265CHADSVASCacenocoumarol17%933 patients with permanent or paroxysmal NVAF on acenocoumarol OAC (INR 2–3) for at least 6 months. Age 76, 46% male, 85% hypertension, 27% DM, 32% hypercholesterolemia, 14% current smokers, 39% CHF, 20% prior stroke/TIA, 20% CAD, 9% PAD, 17% on antiplatelets. CHADS2 score 2, CHADSVASC score 4. No blinding reported. No loss to FU reported.80 MB2.5 years
Lip 201171

HAS-BLED

Shireman

HEMORRHAGE

Beyth et al.

Kuijer et al.

warfarinNR7,329 people with NVAF on warfarin or ximelagatran. Taken from the SPORTIF III and V cohorts (Multinational cohort). Following data are for those who developed a major bleed/no major bleed: age 73.9/70.9, female 31/31%, paroxysmal AF 11/12%, hypertension 77/77%, DM 29/23%, CAD 50/45%, LV dysfunction 44/36%, stroke/TIA 26/21%, CHADS 2.6/2.2.Blinded assessors.136 MB499 days
Lip 201474SAME-TT2R2VKAs17%4,637 patients with AF (n=572 had valvular AF) who were receiving OACs. FRANCE. Mean age 71, 35% female, 60% HF, 28% CAD, 12% previous MI, 6% previous CABG, 44% hypertensive, 9% previous stroke, 9% renal insufficiency. 17% on antiplatelets, 15% on Aspirin, 6% clopidogrel, 4% DAT. Mean CHADSVASC score 3.2, Mean HAS-BLED score 1.6. Not blinded.144 MB1016 days
Lip 201877

HAS-BLED

ATRIA

ORBIT

DOACS39.10%57,930 patients with NVAF on DOACs. Taken from 3 Danish nationwide databases. Age 73.5, female 44.6%, HF 22.5%, DM 15.2%, Vascular diseases 16.2%, hypertension 59%, CPD 13.3%, prior bleeding 14.2%, kidney diseases 3.4%, Aspirin use 39.1%, NSAIDs 22.4%. Not blinded. Loss to FU not reported.2.41 /100 person-years1 year
Mori, 201988

ORBIT

HAS-BLED

DOACS21.5%2216 patients with NVAF using DOACs; 63.6% male; median age 73 years; median CHADS2 2; hypertension 73.5%; DM 27.9%; Dyslipidaemia 65.2%; eGFR 64.9; CAD 19.8%; PAD 7.1%; HF 23.7%; prior stroke 20.2%; prior bleeding 27.1%; antiplatelets 21.5%93 MB315 days
Nielsen 201690

HAS-BLED

Recalibrated HAS-BLED (2 points for previous haemorrhagic stroke instead of 1 point)

unclearNRUnknown number of OAC-treated patients from a cohort of 210,299 patients with AF taken from 3 Danish patient registries from 1999 to 2013. Demographic data for the sub-group having OACs is not reported4.73 MB per 100 person yearsUnclear
O’Brien 201591

ORBIT

HAS-BLED

ATRIA-bleeding

rivaroxaban and warfarinNR14,264 patients with AF on either rivaroxaban (20mg daily) or Warfarin. This was the external validation cohort, comprising patients from the ROCKET-AF. Demographics of this external validation sample not reported.772 MB1.9 years
Olesen 201195

HAS-BLED

HEMORRHAGES

VKA33%44, 771 patients with AF receiving OACs in Denmark during 1997–2006. Demographic data given as two values as separate data for those with major bleeding / those without. Age 74.6 / 71.2, male 66.8 / 61.2 %, HASBLED score 2.5–2, HF 24.4/19.8%, hypertension 51.6/49.5%, DM 11.4/9.5%, Stroke 22.3/17.4, Renal disease 8.2/4.6%, Vascular disease 18.6/14.8%, Bleeding history 22.6/8.2%, antiplatelet drugs 33% / 25.5%, NSAIDs 22.8/19.1%.2051 MB1 year
Pisters 2010103

HAS-BLED

HEMORRHAGES

Unspecified OACsNR1956 patients on OACs only with NVAF (validation cohort). Data not given for this validation cohort subset.1.75 MB/100 patients years1 year
Poli 2017110

HAS-BLED

HAS-BED (HAS-BLED but without labile INR score)

CHADS2

CHADSVASC

warfarin and DOACs16.50%4579 patients with AF on DOACS (n=1048) or VKAs (n=3531) on START register in Italy. Age 76, 55% men, 15% HF, 80% hypertensive, 20% DM, 18% CAD, 6% PAD, 43% moderate renal impairment (eGFR 30–60 ml/min), 15% previous stroke/TIA, 3.4% history of major bleeding, TTR 67, concomitant antiplatelet drugs 16.5%, dual antiplatelet therapy 1.3%.115 MB1.4 years
Prochaska 2018113

HAS-BLED

HAS-BLED with a point for sustained AF

Simplified HAS-BLED

VKA - phenprocoumon18.30%1089 patients with medical and electrophysiological evidence of AF, and on VKAs, as part of the thrombEVAL cohort. Denmark. The following baseline data is separated into paroxysmal (n=398) and sustained (n=691) sub-groups by the paper: male 63/63%, age 72/75, DM 30/33%, Family history of MI/stroke 44.5/42%, hypertension 83/81.6%, CKD 24/27%, CAD 43.6/46.7%, HF 43.5/55.2%, history of major bleeding 6.8/6.2%, history of stroke/TIA 16.7/18.7%, MI 21.8/20.8%, PAD 16.1/17.5%, aspirin 18.3/15.1150 CRB (includes MB and CRNMB)3 years
Proietti 2016116

HAS-BLED

ORBIT

ATRIA

HEMORRAGES

ORBIT with TTR <65% (adding one point to score if <65%)

ATRIA with TTR <65% (adding one point to score if <65%)

HEMORRAGES with TTR <65% (adding one point to score if <65%)

warfarin19.90%3551 patients receiving warfarin in the pooled population dataset from the SPORTIF III and V studies with AF. De-identified datasets with patient-level information for the SPORTIF trials were obtained directly from Astra Zeneca, and all the analyses were performed independent of the company. All patients assigned to the warfarin treatment arms and with available data for the clinical variables used to calculate the four bleeding prediction scores were included in the present analysis. The majority of patients were male (69.5%) and the median [IQR] age was 72 [66–77] years. HAS-BLED score >3: 71%. 706/3551 (19.9%) treated concomitantly with aspirin. 20.1% VKA naïve at baseline prior to VKA initiation.162 MB1.6 years
Proietti 2018a114

HAS-BLED

ORBIT

ATRIA

HEMORRHAGES

dabigatran 110mg, 150mg and warfarin (SEP ANALYSESfor C statistics but mixed for sensitivity/spe cificity)40%18,113 patients with AF on dabigatran (110 or 150 mg) or warfarin in the RE-LY trial. Multinational cohort. Age 72, 36% female, 79% hypertension, DM 23%, CAD 28%, prev stroke 22%, symptomatic HF 27%, VKA naïve 50%, anti-platelets 40%, CHADS2 2. BLINDED ASSESSORS.1182 MB2 years
Proietti 2018b115

HAS-BLED

GARFIELD

warfarin19.90%3550 AF patients enrolled on the SPORTIF III trial who were on Warfarin. Age 72, 30.5% female, 76.7% hypertension, 23.5% DM, 44.3% CAD, 20.6% stroke/TIA, 37.3% HF, 5.6% previous bleeding, 25.9% CKD, 19.9% aspirin use. TTR 68.1. HAS-BLED: 3. 804 patients interrupted Warfarin during the follow up period. BLINDED ASSESSORS.

127 MB

168 major/CRNMB

1.56 years
Quinn 2016117

CHADS2

CHADSVASC

ATRIA

HAS-BLED

warfarinNR13,559 patients with AF who were on and off warfarin. No demographic data provided.unclearunclear
Rivera-Caravaca 2017120

HEMORRHAGES

HAS-BLED

ATRIA

ORBIT

VKAs18%1361 patients – same patients as Roldan 2017128- with AF who were taking VKA OACs (acenocoumarol), in Spain. Age 76, 49% male, 82% hypertensive, 27% DM, 19% previous stroke/TIA, 19% CAD, 31% HF, 7% PAD, 10% renal impairment, 33% hypercholesterolemia, 8% previous bleeding episode, 4% alcohol abuse, 1% hepatic disease, 8% cancer. Median HAS-BLED score of 2250 MB6.5 years
Rivera-Caravaca, 2019119

HAS-BLED

HAS-BLED with 1 to 6 added biomarkers

VKAs18.4%940 patients who were taking VKA OACs (IRR 2–3), in Spain. Age 76, 50.6% male, 82% hypertensive, 26.2% DM, 18.8% previous stroke/TIA, 19.8% CAD, 30.4% HF, 10.6% renal impairment, 33.3% hypercholesterolemia, Median HAS-BLED score of 2172MB6.5 years
Roldan 2013a125

HAS-BLED

ATRIA

acenocoumarol17%937 consecutive patients with AF receiving anticoagulant therapy with INR from 2–3. 49% male, mean age 76, 82% hypertension, 25% DM, 37% HF, 19% stroke, 10% renal impairment, 19% CAD, 9% previous bleeding, 17% antiplatelet therapy. Median HAS-BLED score of 2, median CHADS2 score of 2.79 MB952 days
Roldan 2013b126

HAS-BLED

CHADS

CHADSVASC

acenocoumarol18%1370 consecutive patients with AF receiving anticoagulant therapy with INR from 2–3. 49% male, mean age 76, 19% stroke, 10% renal impairment, 18% CAD, 9% previous bleeding, 18% antiplatelet therapy. Median HAS-BLED score of 2, median CHADS2 score of 2.114 MB996 days
Roldan 2017128

HAS-BLED

Modified HAS-BLED (including vWF, high sensitivity troponin T, N-terminal fragment B-type natriuretic peptide, high sensitivity IL-6, time in therapeutic range and modification of diet in renal disease

CHADS-VASC

Modified

CHADSVASC (as above)

VKAs18%1361 consecutive patients with AF who were taking VKA OACs (acenocoumarol), in Spain. Age 76, 49% male, 82% hypertensive, 27% DM, 19% previous stroke/TIA, 19% CAD, 31% HF, 7% PAD, 10% renal impairment, 33% hypercholesterolemia, 8% previous bleeding episode, 4% alcohol abuse, 1% hepatic disease, 8% cancer. 18% antiplatelet therapy. Median HAS-BLED score of 2250 MB7.49 years
Schwartz, 2019135Modified HAS-BLEDVKAs and DOACSNRData from 9819 patients with AF who were on DOACs or VKAs were retrieved from the Northwestern Healthcare system’s Enterprise Database Warehouse. The data allowed identification of bleeding outcomes, and calculation of prior HAS-BLED scores. Mean age 67.6 for white patients and 63.1 for non-white patients. Mean CHADSVASC was 2.4 in whites and 2.2 in non-whites604 MB971 days
Senoo 2016a136

HAS-BLED

ORBIT

IdraparinuxNR2283 patients with AF on non-warfarin OAC. UK. Age 70. No other details of demographics reported.

74 MB

346 CRB

311 days
Senoo 2016b137

HAS-BLED

ORBIT

ATRIA

Also with TTR for NRI analysis of ORBIT and ATRIAS only

warfarin16.50%2293 patients with AF warfarin OAC. UK. Age 71, 65.5% male, paroxysmal AF 35.5%, persistent AF 9.3%, permanent AF 54.9%, hypertension 77%, HF 24%, DM 20%, CAD 31%, Stroke/TIA 25%, TTR 58%, Aspirin 16.5%;NSAIDS 5.4%.CHASVASC of 0–2: 28.8%, HAS-BLED 2.

39 MB

251 CRB

Unclear but probably < 1 year
Serna 2018138

HAS-BLED

GEN /HAS-BLED (added point if patient carrying VKORC1 allele and CYP2C9*3 polymorphisms)

acenocoumarol (VKA)NR652 consecutive ASF patients stable on VKAs (INR 2–3) for 6 months. Spain. Age 76, 48.6% male, 82.8% hypertension, 24.2% DM, 18.7% history of stroke/TIA, 18.4% CAD, 31.9% hypercholesterolemia, 34.5% HF, 9.2% renal impairment, 1.5% hepatic impairment, 8.3% previous bleeding. HAS-BLED score 2. No data on antiplatelets.106 MB7.6 years
Siu 2014142HAS-BLEDwarfarinNR1912 patients with NVAF (not defined) who received OACs (Warfarin). Mean age 73, 47% female, 55.8% hypertensive, 24% DM, 1.8% renal failure on dialysis, 24% HF, 24% CAD, 6.3% PAD, 29.6% prior stroke/TIA, prior IC haemorrhage 2.1%. Mean CHADSVASC 3.3. No data on antiplatelets30 ICH3.19 years
Steinberg 2016146

ATRIA

HAS-BLED

warfarin and dabigatranNR7420 AF patients on OACs, out of an original cohort of 9715 from the ORBIT-AF trial. USA. Ranges for baseline data given as different data given for people in low, intermediate and high risk categories. Age 73–77, female 40–46%, hypertension 83–87%, diabetes 28–38%, previous GI bleed 5.7–16%, CAD 32–48%, Prior stroke/TIA 14–26%, CHF 30–46%, HAS-Bled 1.61–2.17, CHADS2 2.17–2.81. No data on antiplatelets.632 MBUnclear
Suzuki 2014147

HAS-BLED

Modified

HAS_BLED (renal dysfunction defined by eGFR <60, with exclusion of the ‘elderly’ factor because eGFR is calculated based on patient age)

warfarin36.9–50%231 NVAF patients on warfarin for at least 1 year. Demographics given as ranges as only reported for sub-groups of eGFR: age 68–74, 63.1–80% male, hypertension 53.2 to 64.4%, CAD 14.4 to 16.7%, CHF: 20 to 25.2%, dyslipidaemia 28.8 to 36.7%, eGFR 12.7 to 74.3 mL/min/1.73m2) antiplatelet drugs 36.9 to 50%. TTR 56.9 to 65.1%.44 MB7.1 years
Wang 2016154HAS-BLEDdabigatran and warfarin (SEP ANALYSES)NR21,934 adults with AF who were starting dabigatran (30%) or Warfarin. Patients were on a healthcare claims database in USA. Demographic data given for those on Warfarin (n=15418): Age 65, female 34%, 27% CHF, 31% DM, 93% hypertensive, 20% prior stroke, 22% PVD. 43% with HAS-BLED score of 3 or more. 32% with CHADS2 score of 3 or more.4.6 MB per 100 patient years5 months
Yao 2017158

CHADSVASC

CHADS

HAS-BLED

ORBIT

ATRIA

DOACS (results not sub-grouped)7%39, 539 patients with NVAF from USA insurance database (OptumsLabs Data Warehouse) who had started DOACs between 2010 and 2015. Age 71, 42% female, 20% non-white, 28% HF, 86% hypertension, 34% DM, 14% previous strokes/TIA, 48% vascular disease, 7% stage II or IV CKD, 4% abnormal liver function, 9% previous major bleeding, 7% using antiplatelets, 5% using NSAIDs, 28% had had previous warfarin exposure. HAS-BLED: 2115 MB0.6 years

MB=major bleeding, CRB= clinically relevant bleeding, CRNMB= clinically relevant non-major bleeding, ICH= Intracranial hemorrhage

Table 5Summary of risk tools and their constituent variables

Risk toolVariables and scoringBleeding risk interpretation (where applicable)
ABC-bleedingPrior bleeding, age, hs-troponin, GDF-15 and Hb. Continuous values inputted (where appropriate) and a probability score derived by algorithm.Score is the 1 year risk of major bleeding
ABC bleeding CrCABC-bleeding with creatinine clearance replacing GDF-15
ABC-bleeding CKD-EPIABC-bleeding with CKD-EPI biomarker added to the scheme
ABC-bleeding cTnl-hsABC-bleeding with cTnl-hs biomarker added to the scheme
ABC-bleeding cystatin CABC-bleeding with cystatin C biomarker added to the scheme
Anticoagulation-specific Bleeding Score (ABS)The 1-year risk of bleeding can be calculated as 1 - (0.98101) Exp[0.02306(Age - 70.1736) + 0.29958(Kidney Disease −0.13244) + 0.19215(COPD −0.31286)+ 0.23529(Prior Bleed −0.21338) +0.32257(Anemia −0.24892) + 0.21811(Heart Failure-0.33899)+ 0.22599(Antiplatelet-0.16341) + 0.15944 (Diuretics-0.4518) + 0.2111(Diabetes Mellitus-0.31686) + 0.16806 (Cancer-0.16955) - 0.28572 (Antiarrhythmic −0.11919) + 0.13743(Ischemic stroke - 0.26681) + 0.10269(Coronary Artery Disease −0.40768) - 0.04775(Male Sex-0.59637) −0.30127 (Dabigatran) + 0.01299(Rivaroxaban) - 0.52426(Apixaban)]1 year risk of bleeding yielded
APTTBiomarker: activated partial thromboplastin timeNo pre-set thresholds provided in paper
ATRIAAnaemia (3 points), severe renal disease (eGFR <30) (3 points), age >75 years (2 points), any prior bleeding (1 point), hypertension history (1 point)

Low: 0–3

Moderate: 4

High: 5 or more

ATRIA with ASATRIA with existence of aortic stenosis added inas a risk factor to the scheme
ATRIA with TTR (<65% TTR)ATRIA with time in therapeutic range of <65% added in as a risk factor to the scheme
BeythSee mOBRI
CBRMSee Shireman
CHADS2One point each for CHF, hypertension, age 75 of older, and DM, and 2 points for prior stroke or TIA.Score 0=low risk; score 1–2=intermediate risk; score 3 to 6=high risk
CHADSVASCOne point for female sex, history of CHF, history of hypertension, history of vascular disease or history of DM. 2 points for history of stroke/TE. Age <65=0 points, 65–74=1 point, >75=2 points. Maximum score 9 points.Low risk =0 points; 1 point=low/moderate; >2 points moderate/high
CHADSVASC with TnTCHADSVASC with TnT levels added in to the scheme
GARFIELD/ GARFIELD AFAge, pulse, systolic blood pressure, history of vascular disease, history of bleeding, heart failure, renal disease and use of OACs.Score is a measure of bleeding risk
GDF-15Biomarker: levels of Growth Differentiation Factor 15
GEN/HAS-BLEDHAS-BLED with added point if patient carrying VKORC1 allele and CYP2C9*3 polymorphisms
HAS-BEDHAD-BLED with elimination of labile INR factor.
HAS-BLEDHypertension, abnormal renal/liver function (1 point each), stroke, bleeding history or predisposition, labile INR, elderly drugs/alcohol concomitantly (1 point each). Maximum 9 points

Low: 0

Moderate: 1–2

High: 3 or more

HAS-BLED with ASHAS-BLED with existence of aortic stenosis added inas a risk factor to the scheme
HAS-BLED with GDF-15HAS-BLED with GDF biomarker added to the scheme
HAS-BLED with point for sustained AFHAS-BLED with additional factor of ‘sustained AF in the presence of HF’.
HAS-BLED with TnIHAS-BLED with TnT levels added in to the scheme
HAS-BLED with VWFHAS-BLED with Van Willebrandlevels added into the scheme
HAS-BLED with no labile INR and no stroke/TIA componentHAS-BLED with no labile INR and no stroke/TIA component
HAS-BLED + VWF + NT-proBNPHAS-BLED with Van Willebrand levels and N-terminal pro-B-type natriuretic peptide added into the scheme
HAS-BLED + VWF + NT-proBNP + IL-6HAS-BLED with Van Willebrand levels and N-terminal pro-B-type natriuretic peptide and Interleukin-6 added into the scheme
HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin THAS-BLED with Van Willebrand levels and N-terminal pro-B-type natriuretic peptide and Interleukin-6 and Troponin T added into the scheme
HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin T + BTPHAS-BLED with Van Willebrand levels and N-terminal pro-B-type natriuretic peptide and Interleukin-6 and Troponin T and Beta trace protein added into the scheme
HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin T + BTP + soluble fibrin monomer complexHAS-BLED with Van Willebrand levels and N-terminal pro-B-type natriuretic peptide and Interleukin-6 and Troponin T and Beta trace protein and soluble fibrin monomer complex added into the scheme
HEMORRHAGES

Hepatic or renal disease (1 point)

Ethanol abuse (1 point)*

Malignancy (1 point)

Older age >75 yrs (1 point)

Reduced platelet count or function (1 point)

Re-bleeding risk (2 points)

Hypertension (1 point)

Anaemia (1 point)

Genetic factors (1 point)

Excessive fall risk or neuropsychiatric disease (1 point)

Stroke (1 point)

Low: 0–1

Intermediate: 2–3

High: 4 and above

HEMORRHAGES with TTR (<65% TTR)HEMORRHAGES with time in therapeutic range of <65% added in as a risk factor to the scheme
HTIBiomarker: Hemoclot thrombin inhibitor levelsNo pre-set thresholds provided in paper
Kearon 2003

Age >65yrs (1 point)

Prior stroke (1 point)

Prior peptic ulcer disease (1 point)

Prior GI bleeding (1 point)

Creatinine >1.5 mg/dl (1 point)

Anemia or thrombocytopenia (1 point)

Liver disease (1 point)

Diabetes mellitus (1 point)

Antiplatelet therapy (1 point)

Low: 0–1

Intermediate:2

High 3 or more

Kuijer 1999

Age >60 yrs (1.6 points)

Female (1.3 points)

Malignancy (2.2 points)

Low: 0

Intermediate 1–2

High 3 or more

Landefield and Goldman and BeythSee mOBRI
MBRFSSee MBR
mOBRI (also known as Landefield and Goldman and Beyth, or simply Beyth)Age > 65 years, GI bleed in past 2 weeks, previous stroke, comorbidities (recent MI, Hct <30%, diabetes, creatinine >1.5 ml/l) with 1 point for presence of each risk factor

Low: 0

Moderate; 1–2

High: 3 or more

MBR (Modifiable Bleeding Risk factors score)Defined as the cumulative number of modifiable bleeding risk factors of each patient according to the 2016 ESC guideline, including hypertension, medication predisposing to bleeding, and excess alcohol. 1 point for each.Score ranges from 0–3.
Modified CHADSVASCCHADSVASC with vWF, high sensitivity troponin T, N-terminal fragment B-type natriuretic peptide, high sensitivity IL-6, time in therapeutic range and modification of diet in renal disease
Modified HAS-BLED (multiple additions using biomarkers)HAS-BLED with addition ofvWF, high sensitivity troponin T, N-terminal fragment B-type natriuretic peptide, high sensitivity IL-6, time in therapeutic range and modification of diet in renal disease
Modified HAS-BLED (single change of renal dysfunction threshold)HAS-BLED with modification of the renal impairment factor (from eGFR <30 to eGFR <60)
ORBITOlder age (75 years and above) (1point), reduced hemoglobin, hematocrit, or history of anemia (2 points), bleeding history: (2 points), insufficient kidney function (eGFR below 60 mL/min/1.73 m2)(1 point), treatment with an antiplatelet agent (1 point).

Low: 0–2

Moderate:3

High: 4 or more

ORBIT with ASORBIT with existence of aortic stenosis added inas a risk factor to the scheme
ORBIT with GDF-15ORBIT with GDF-15 levels added into the scheme
ORBIT with TTR (<65% TTR)ORBIT with time in therapeutic range of <65% added in as a risk factor to the scheme
Outpatient bleeding Index (OBI)

Age >65 yrs (1 point)

Prior stroke (1 point)

Prior GI bleeding (1 point)

Recent MI, diabetes mellitus, hematocrit <30%, creatinine >1.5 mg/dl (1 point if any of the above)

Low: 0

Intermediate 1–2

High 3 or more

Prothrombin timeBiomarker: Prothrombin timeNo pre-set thresholds provided in paper
Riete

Recent major bleeding (□15 days before thrombotic event) (2 points)

Creatinine >1.2 mg/dl (1.5 points)

Anemia (1.5 points)

Malignancy (1 point)

Clinically overt pulmonary embolism (1 point)

Age >75 yrs (1 point)

Low: 0

Intermediate: 1–4

High: >4

Same TTRSum of points after addition of one point for female sex, age <60 years, medical history of >2 comorbidities (amongst hypertension, DM, CAD/MI, PAD, CHF, previous CVA, pulmonary disease and hepatic/renal disease, treatment and 2 points each for smoking and non-white race.

Low:0–1

Moderate: 2

High >2

Shireman 2006 (also known as CBRM)

Age >70 yrs

Female

Remote bleeding event

Recent bleeding event

Alcohol or drug abuse

Diabetes mellitus

Anemia (Hct <30% during index hospitalization)

Antiplatelet drugs (aspirin, clopidogrel, or ticlodipine at discharge)

Risk score = 0.49 (age >70) + 0.32 (female)

+ 0.58 (remote bleed) + 0.62 (recent bleed)

+ 0.71 (alcohol/drug abuse) + 0.27 (diabetes)

+ 0.86 (anemia) + 0.32 (antiplatelet use)

Low <1.07

Intermediate >1.07, <2.19

High >2.19

Simplified HAS-BLEDHAS-BLED, containing only the factors of age >65 years, history of major bleeding, and sustained AF in the presence of heart failure
TnIBiomarker: Troponin I levels
TnTBiomarker: Troponin T levels
vWFBiomarker: levels of plasma glycoprotein von Willebrand factor

Table 6Clinical evidence profile: accuracy of prediction of Major Bleedingin all risk tools featured in the studies (see table 3). Outcomes split across subgroups are only shown if sub-grouping was able to reduce I2to <50% in all sub-groups

Risk toolNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecision

Area Under Curve Individual study effects [point estimate (95% Cis) ]

Pooled effect/range/median

Quality
HAS-BLED47532,442Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPOOLED RESULT: Random effect: 0.62 (0.61–0.64) [I2=94%]VERY LOW
Modified HASBLED13519819Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecision

0.60(0.55–0.66)(‘Non-white’ participants)

0.57(0.55–0.60) (‘white’ participants)

VERY LOW
HAS-BLED with AS12880Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.68(0.66–0.70)MODERATE
HAS-BLED with GDF-1518474Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecision0.69(0.67–0.72)VERY LOW
HAS-BLED with vWF21215Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionPOOLED RESULT: Fixed effect: 0.62 (0.60–0.64) [I2=6%]MOD
HAS-BLED + VWF + NT-proBNP1940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.64(0.61–0.67)MOD
HAS-BLED + VWF + NT-proBNP + IL-61940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.64(0.61–0.67)MOD
HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin T1940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.64(0.61–0.67)MOD
HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin T + BTP1940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.64(0.60–0.67)MOD
HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin T + BTP + soluble fibrin monomer complex1940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.64(0.60–0.67)MOD
GEN/HAS-BLED1652Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.65(0.61–0.68)MOD
Modified HAS-BLED (multiple additions using biomarkers)11361Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.60(0.56–0.64)MOD
Modified HAS-BLED (single change of renal dysfunction threshold)1231Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.67(0.57–0.75)VERY LOW
HAS-BED14579Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.58(0.53–0.64)LOW
HAS-BLED with TnI114,821Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.63LOW
HEMORRHA GES19240,995Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPOOLED RESULT: Random effect: 0.63 (0.60–0.66) [I2=97%]VERY LOW
HEMORRHA GES with TTR (<65% TTR)24912Serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionMedian: 0.65VERY LOW
ATRIA23286,664Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPOOLED RESULT: Random effect: 0.64 (0.61–0.66) [I2=97%]VERY LOW
ATRIA with AS12880Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.67(0.66–0.69)MODERATE
ATRIA with TTR (<65% TTR)24912Serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionMedian: 0.68VERY LOW
ORBIT21270,606Very serious risk of biasaVery serious riskof inconsistencybNo serious indirectnessNo serious imprecisionPOOLED RESULT: Random effect: 0.64 (0.61–0.67) [I2=97%]VERY LOW
ORBIT with AS12880Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.68(0.67–0.70)MODERATE
ORBIT with TTR (<65% TTR)24912Serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionMedian: 0.67VERY LOW
ORBIT with GDF-1518474Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.71(0.68–0.73)VERY LOW
CHADS2561,647Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPOOLED RESULT: Random effect: 0.61 (0.57–0.64) [I2=85%]VERY LOW
CHADSVASC824,402Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPOOLED RESULT: Random effect: 0.59 (0.54–0.64) [I2=92%]VERY LOW
Modified CHADSVASC11361Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.56(0.53–0.60)MOD
CHADSVASC with TnT114,897Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.63(0.61–0.65)LOW
GARFIELD362,172Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPooled effect: Random effects 0.60 (0.56–0.65); I2=96%VERY LOW
GARFIELD subgrouped by OAC - VKA13550Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.56(0.54–0.58)LOW
GARFIELD subgrouped by OAC – Mixed VKA/DOACs17442Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.61(0.59–0.63)LOW
GARFIELD subgrouped by antiplatelets - <33% with antiplatelets13550Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.56(0.54–0.58)LOW
GARFIELD subgrouped by antiplatelets – unknown % with antiplatelets17442Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.61(0.59–0.63)LOW
ABC-bleeding316869Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessSerious imprecisioncPOOLED RESULT: Random effect: 0.69(0.65–0.74) [I2=85%]VERY LOW
ABC-bleeding Subgrouped by OAC - VKA12814Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.65(0.61–0.70)VERY LOW
ABC-bleeding Subgrouped by OAC - Mixed18705Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.69(0.66–0.71)[Mixed]VERY LOW
ABC-bleeding Subgrouped by OAC - NOACs15350Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.74(0.71–0.76)[DOAC]VERY LOW
ABC-bleeding CrC11120Serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.52(0.49–0.55)LOW
ABC-bleeding cTnl-hs28164Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessSerious imprecisioncPOOLED RESULT: Random effect: 0.70 (0.61–0.78) [I2=92%]VERY LOW
ABC-bleeding cTnl-hs subgrouped by OAC - VKA12814Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.65(0.61–0.70VERY LOW
ABC-bleeding cTnl-hs subgrouped by OAC - DOAC15350Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.74(0.71–0.76)LOW
ABC-bleeding cystatin C28164Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessSerious imprecisioncPOOLED RESULT: Random effect: 0.68 (0.65–0.72) [I2=90.6%]VERY LOW
ABC-bleeding cystatin C subgrouped by OAC - VKA12814Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.60(0.54–0.66)LOW
ABC-bleeding cystatin C subgrouped by OAC - DOAC15350Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.72(0.68–0.75)VERY LOW
ABC-bleeding CKD-EPI28164Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessSerious imprecisioncPOOLED RESULT: Random effect: 0.70 (0.68–0.72) [I2=79%]VERY LOW
ABC-bleeding CKD-EPI subgrouped by OAC - VKA12814Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.65(0.60–0.69)LOW
ABC-bleeding CKD-EPI subgrouped by OAC - DOAC15350Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.71(0.69–0.74)VERY LOW
vWF11215Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.61(0.57–0.65)MOD
ABS181285Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc

0.67(0.65–0.68)[warfarin], 0.72(0.69–0.76)[dabigatran]

0.70(0.68–0.73)[rivaroxaban]

0.72(0.67–0.77) [apixaban]

VERY LOW
OBI13063Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.59(0.58–0.611LOW
Kuijer38332Very serious risk of biasaSerious risk of inconsistencybNo serious indirectnessNo serious imprecisionPOOLED EFFECT: Random effects: 0.54 (0.51–0.58) [I2=72%]VERY LOW
Kearon24667Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionMedian: 0.675LOW
Riete13063Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.68(0.65–0.70)LOW
Shireman / CBRM512385Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPOOLED EFFECT: Random effect: 0.64(0.59–0.69) [I2=80%]VERY LOW
mOBRI/Lande field and Goldman and Beyth / Beyth38762Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionPOOLED EFFECT: Fixed effect: 0.56(0.51–0.60) [I2=0%].LOW
TnT114,897Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.62(0.60–0.64)LOW
TnI114,821Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.60LOW
GDF-1518474Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.67(0.65–0.69)LOW
MBR140,450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.53(0.52–0.53)LOW
HTI1208Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.65LOW
Prothrombin time1208Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.54(0.47–0.62)VERY LOW
Same TTR14637Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.55 (0.54–0.57)LOW
APTT1208Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision0.58(0.50–0.69)LOW

Pooling (meta-analysis) was carried out if there were at least two studies per risk tool with confidence intervals. RevMan was used to carry out the analyses. If pooling was not possible for risk tools with >1 data point then the range and median value of the study point estimates were recorded. If there were only one data point then only the result from the study was recorded.

a)

Risk of bias was assessed using the PROBAST checklist(see Appendix F).Risk of bias was serious for some risk tools because fewof the studiesreported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the rest of the risk tools because manystudieswith the aforementioned limitations also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Where data were pooled, an I2of 50–74% was deemed serious inconsistency and an I2of 75% or above was deemed very serious inconsistency. If no pooling were possible, inconsistency was assessed by inspection of the degree of overlap of confidence intervals between studies: if one of more Cis did not overlap then a rating of serious inconsistency was given. Reasons for heterogeneity between studiesmay include geographical/cultural/ethnic differences. Clinically the studies appeared reasonably homogeneous, with similar rates of hypertension, diabetes and former stroke.

c)

The judgement of precision was based on the spread of confidence interval around two clinical thresholds: C statisticsof 0.5 and 0.7. The threshold of 0.5 marked the boundary between no predictive value better than chance and a predictive value better than chance. The threshold of 0.7 marked the boundary above which the committee might consider recommendations. If the 95% Cis crossed one of these thresholds a rating of serious imprecision was given and if they crossed both of these thresholds a rating of very serious imprecision as given.

Table 7Clinical evidence profile: sensitivity and specificityof prediction of Major Bleeding in all risk tools featured in the studies (see table 3). 95% CIs are given for non-pooled results; for meta-analysed results the 95% credible intervals are given for the pooled effect only

Risk toolNo of COHORTSnSensitivity (threshold denotes the ‘positive’ score – i.e. the score indicating a high risk of bleeding)Specificity (threshold denotes the ‘positive’ score – i.e. the score indicating a high risk of bleeding)Risk of biasInconsistencyIndirectnessImprecisionQuality
HAS-BLED at threshold of ≥17128791Pooled sensitivity: 0.979(0.941–0.993)Pooled specificity: 0.070(0.027–0.174)Sensitivity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessNo serious imprecisionVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessSerious imprecisioncVERY LOW
HAS-BLED at threshold of ≥210177728Pooled sensitivity: 0.793(0.570–0.919)Pooled specificity: 0.396(0.207–0.624)Sensitivity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessVery serious imprecisioncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessSerious imprecisioncVERY LOW
HAS-BLED at threshold of ≥313170197Pooled sensitivity: 0.512(0.385–0.637)Pooled specificity: 0.679(0.554–0.782)Sensitivity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessSerious imprecisioncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessNo serious imprecisionVERY LOW
HAS-BLED at threshold of ≥4135250.543(0.453–0.632)0.591(0.575–0.608)Sensitivity
Very serious risk of biasaNANo serious indirectnessSerious imprecisioncVERY LOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Modified HASBLED135at threshold of ≥1198190.925 (0.902–0.945)0.1504(0.143–0.158)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Modified HASBLED135at threshold of ≥2198190.644(0.604–0.682)0.4937(0.483–0.5040Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessSerious imprecisioncVERY LOW
Modified HASBLED135at threshold of ≥3198190.311(0.275–0.349)0.826(0.819–0.834)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
HEMORRHAGES at threshold of ≥137406Pooled sensitivity: 0.919(0.658–0.985)Pooled specificity: 0.167(0.037–0.5207)Sensitivity
Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisoncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
HEMORRHAGES at threshold of ≥2660023Pooled sensitivity: 0.631(0.417–0.798)Pooled specificity: 0.549(0.349–0.734))Sensitivity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
HEMORRHAGES at threshold of ≥325138

0.478(0.354–0.603)

0.171 (0.112–0.250)

0.739(0.716–0.761)

0.886(0.874–0.896)

Sensitivity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessNo serious imprecisionVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessNo serious imprecisionVERY LOW
ATRIA at threshold of ≥14103289Pooled sensitivity: 0.955(0.864–0.986)Pooled specificity: 0.132(0.061–0.259)Sensitivity
Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisoncVERY LOW
Specificity
Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisoncVERY LOW
ATRIA at threshold of >25103289Pooled sensitivity: 0.685(0.450–0.848)Pooled specificity: 0.539(0.354–0.716)Sensitivity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
Specificity
Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisoncVERY LOW
ATRIA at threshold of ≥33101023Pooled sensitivity: 0.571(0.212–0.856)Pooled specificity: 0.638(0.35446–0.861)Sensitivity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessNo serious imprecisionVERY LOW
ATRIA at threshold of ≥46111338Pooled sensitivity: 0.259(0.096–0.513)Pooled specificity: 0.874(0.714–0.941)Sensitivity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessNo serious imprecisonVERY LOW
ORBIT at threshold of ≥14103302Pooled sensitivity: 0.804(0.610–0.916)Pooled specificity: 0.381(0.217–0.574)Sensitivity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessVery serious imprecisoncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
ORBIT at threshold of ≥24103302Pooled sensitivity: 0.460(0.233–0.692)Pooled specificity: 0.716(0.528–0.849)Sensitivity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessSerious imprecisoncVERY LOW
ORBIT at threshold of ≥38114895Pooled sensitivity: 0.340(0.213–0.493)Pooled specificity: 0.845(0.766–0.900)Sensitivity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessNo serious imprecisonVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencyaNo serious indirectnessNo serious imprecisonVERY LOW
CHADS2 at threshold of ≥11395390.991(0.981–0.998)0.084(0.081–0.086)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
CHADS2 at threshold of ≥21395390.865(0.836–0.889))0.341(0.336–0.346)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
CHADS2 at threshold of ≥31395390.552(0.513–0.590)0.776(0.775–0.779)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
CHADSVASC at threshold of ≥11395390.998(0.992–1.00)0.385(0.366–0.404)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
CHADSVASC at threshold of ≥21395390.984(0.970–0.992)0.129(0.125–0.132)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
CHADSVASC at threshold of ≥31395390.929(0.907–0.948)0.271(0.267–0.276)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
ABC-bleedingCrCat threshold of ≥2%111200.835(0.778–0.884)0.194(0.169–0.221)Sensitivity
Serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
Specificity
Serious risk of biasaNANo serious indirectnessNo serious imprecisonLOW
HTIat threshold >117 ng/ml12080.59[no raw data or 95% Cis reported in paper]0.71[no raw data or 95% Cis reported in paper]Sensitivity
Very serious risk of biasaNANo serious indirectnessNALOW
Specificity
Very serious risk of biasaNASNo serious indirectnessNALOW

Pooling (meta-analysis) was carried out if there were at least three studies per risk tool with confidence intervals. RevMan and WinBugs were used to carry out the analyses. If pooling was not possible for risk tools with >1 data point then the range and median value of the study point estimates were recorded. If there were only one data point then only the result from the study was recorded.

a)

Risk of bias was assessed using the PROBAST checklist. Risk of bias was serious for some risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the rest of the risk tools because many studies with the aforementioned limitations also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Where data were pooled, inconsistency was assessed by visual inspection of the sensitivity/specificity plots, or data (if 2 studies). The evidence was downgraded by 1 increment if there was no overlap of 95% confidence intervals. For single studies no evaluation was made and ‘not applicable’ was recorded.Subgrouping to attempt to resolve heterogeneity was not carried out because there would always be <3 studies in any of the constituent sub-group categories, making it not possible to do a further meta-analysis within each sub-group.

c)

Imprecision was assessed based on inspection of the confidence region in the meta-analysis or, where meta-analysis has not been conducted, assessed according to the range of confidence intervals in the individual studies. The evidence was downgraded by 1 increment when the confidence interval around the point estimate crossed one of the clinical thresholds (0.90 or 0.60 for sensitivity and 0.5 and 0.1 for specificity), and downgraded by 2 increments when the confidence interval around the point estimate crossed both of the clinical thresholds. The upper clinical threshold marked the point above which recommendations would be possible, and the lower clinical threshold marked the point below which the tool would be regarded as of little clinical use.

Table 8NRI for major bleeding – HAS-BLED versus other tools

Prediction tool comparisonNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecisionNRI(95% CI)Quality
HAS-BLED v HEMORRHAGES550,051Very serious risk of biasaSerious inconsistencybNo serious indirectnessSerious imprecisioncPooled: Random effects NRI: + 0.080(−0.030to +0.190); I2= 69%VERY LOW
HAS-BLED v ATRIA650,988Very serious risk of biasaSerious inconsistencybNo serious indirectnessSerious imprecisioncPooled: Random effects NRI: + 0.070(−0.020to +0.160); I2= 52%VERY LOW
HAS-BLED v MBR140450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.056 (0.043 to 0.068)LOW
HAS-BLED v CHADS2317529Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionPooled fixed effect NRI: +0.440(+0.250to +0.630); I2=0%LOW
HAS-BLED v ORBIT346284Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionPooled fixed effect NRI: +0.050(+0.040to +0.070); I2=0%LOW
HAS-BLED v CHADSVASC35518Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionPooled fixed effect NRI: +0.37 (+0.21 to +0.52); I2=0%LOW
HAS-BLED v ABC18705Serious risk of biasaNoserious inconsistencyNo serious indirectnessSerious imprecisionc−0.138(−0.080to 0.228)LOW
HAS-BLED v ABC CrC11120Serious risk of biasaNoserious inconsistencyNo serious indirectnessSerious imprecisionc+0.137(−0.010to 0.290)LOW
HAS-BLED v GARFIELD13550Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc+0.042(−0.087 to 0.189)VERY LOW
HAS-BLED v HAS-BLED with vWF22155Serious risk of biasaVery serious inconsistencybNo serious indirectnessSerious imprecisioncPooled random effect NRI: −0.12 (−0.33 to +0.09); I2=92%VERY LOW
HAS-BLED v HAS-BLED + VWF + NT-proBNP1940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.201(−0.329 to −0.002)MOD
HAS-BLED v HAS-BLED + VWF + NT- proBNP + IL-61940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.192(−0.325to −0.001)MOD
HAS-BLED v HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin T1940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.194(−0.337 to −0.003)MOD
HAS-BLED v HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin T + BTP1940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.196(−0.327 to −0.005)MOD
HAS-BLED v HAS-BLED + VWF + NT-proBNP + IL-6 + Troponin T + BTP + soluble fibrin monomer complex1940Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.203(−0.342 to −0.004)MOD
HAS-BLED v Recalibrated HAS-BLED1UnknownVery serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.090(−0.123 to −0.0480)LOW
HAS-BLED v modified HAS-BLED (including multiple biomarkers)11361Serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc+0.062 (−0.020to 0.140)LOW
HAS-BLED v modified HAS-BLED (including new renal dysfunction definition)1231Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.500(−0.820to −0.180)LOW
HAS-BLED v GEN/HAS_BLES1652Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.044(0.010to 0.080)MOD
HAS-BLED vs HAS-BLED with AS12880Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.0481(p=0.034)MOD
a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for most risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the Framingham risk tool because the study concerned also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Inconsistency was serious if I2 was 50–74% and very serious if 75% of higher

c)

Imprecision serious if the 95% CIs crossed zero.

Table 9NRI for major bleeding – ATRIA versus other tools

Prediction tool comparisonNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecisionNRI(95% CI)Quality
ATRIA v CHADS2216159Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionMEDIAN: +0.43LOW
ATRIA v ORBIT13551Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNA+0.0355LOW
ATRIA v CHADSVASC242139Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionMEDIAN:+0.32LOW
ATRIA v HEMORRHAGES512664Very serious risk of biasaVery serious inconsistencybNo serious indirectnessSerious imprecisioncPooled random effect NRI: +0.090(−0.080to +0.207); I2=83%VERY LOW
ATRIA v OBI13063Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNA+0.505LOW
ATRIA v Kuijer13063Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNA+0.566LOW
ATRIA v Kearon13063Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNA+0.277LOW
ATRIA v Shireman13063Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNA+0.344LOW
ATRIA v Riete13063Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNA+0.448LOW
ATRIA v ATRIA with TTR<65%34005Very serious risk of biasaSerious inconsistencybNo serious indirectnessNo serious imprecisionPooled random effect NRI: −0.230(−0.410to −0.040); I2=64%VERY LOW
ATRIA v MBR140450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecision+0.007 (−0.014 to 0.027)LOW
ATRIA vs ATRIA with AS12880Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.0645(p=0.025)MOD
a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for most risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the Framingham risk tool because the study concerned also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Inconsistency was serious if I2 was 50–74% and very serious if 75% of higher

c)

Imprecision serious if the 95% CIs crossed zero.

Table 10NRI for major bleeding – HEMORRHAGES versus other tools

Prediction tool comparisonNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecisionNRI(95% CI)Quality
HEMORRHAGES v CHADS212600Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.540(0.220to 0.860)LOW
HEMORRHAGES v CHADSVASC12600Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.590(0.240to 0.940)LOW
HEMORRHAGES v ORBIT13551Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNA−0.216LOW
HEMORRHAGES v HEMORRHAGES with TTR<65%21712Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecisionMEDIAN: −0.161MOD
HEMORRHAGES v MBR140450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc+0.012 (−0.007 to 0.032)VERY LOW
a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for most risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the Framingham risk tool because the study concerned also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Inconsistency was serious if I2 was 50–74% and very serious if 75% of higher

c)

Imprecision serious if the 95% CIs crossed zero.

Table 11NRI for major bleeding – ORBIT versus other tools

Prediction tool comparisonNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecisionNRI(95% CI)Quality
ORBIT v ORBIT with TTR<65%34009Very serious risk of biasaVery serious inconsistencybNo serious indirectnessSerious imprecisioncPooled random effect NRI: −0.21(−0.44 to 0.02); I2=77%VERY LOW
ORBIT v CHADSVASC139539Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNA+0.010LOW
ORBIT v MBR140450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc0.000 (−0.021 to 0.021)VERY LOW
ORBIT vs ORBIT with AS12880Serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecision−0.014(p=0.170)VERY LOW
a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for most risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the Framingham risk tool because the study concerned also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Inconsistency was serious if I2 was 50–74% and very serious if 75% of higher

c)

Imprecision serious if the 95% CIs crossed zero.

Table 12NRI for major bleeding – CHADSVASC versus other tools

Prediction tool comparisonNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecisionNRI(95% CI)Quality
CHADSVASCv CHADS2355698Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisioncMEDIAN: +0.040VERY LOW
CHADSVASC v modified CHADSVASC (including multiple biomarkers)11361Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc+0.0026 (−0.020to 0.030)VERY LOW
a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for most risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the Framingham risk tool because the study concerned also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Inconsistency was serious if I2 was 50–74% and very serious if 75% of higher

c)

Imprecision serious if the 95% CIs crossed zero.

Table 13Clinical evidence profile: accuracy of prediction of CRBin all risk tools featured in the studies (see table 3). Outcomes split across subgroups are only shown if sub-grouping was able to reduce I2 to <50% in all sub-groups

Risk toolNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecision

Area Under Curve Individual study effects [point estimate (95% Cis) ]

Pooled effect/range/median

Quality
HAS-BLED818258Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPooled result: Random effect: 0.56(0.54–0.59). I2=83%VERY LOW
HEMORRHAGES34467Very serious risk of biasaSerious risk of inconsistencybNo serious indirectnessNo serious imprecisionPooled effect: Random effects 0.56 (0.52–0.60); I2=64%VERY LOW
HEMORRHAGES subgrouped by OAC - VKA23450Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecisionPooled effect: fixed effect 0.54(0.51–0.56); I2=0%LOW
HEMORRHAGES subgrouped by OAC – Mixed VKA/D OAC11157Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.61(0.55–0.68)LOW
HEMORRHAGES subgrouped by antiplatelets - <33%23450Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecisionPooled effect: fixed effects 0.54(0.51–0.56); I2=0%LOW
HEMORRHAGES subgrouped by antiplatelets - >33%11157Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.61(0.55–0.68)LOW
ATRIA46760Very serious risk of biasaSerious risk of inconsistencybNo serious indirectnessSerious imprecisionPooled effect: Random Effects 0.52 (0.49–0.56); I2=63%VERY LOW
ATRIA subgrouped by OAC - VKA35743Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessSerious imprecisioncPooled effect: Fixed effects 0.51(0.49–0.53); I2=0%VERY LOW
ATRIA subgrouped by OAC – Mixed VKA/DOACs11017Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.61(0.54–0.67)LOW
ATRIA subgrouped by antiplatelets – <33%35743Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessSerious imprecisioncPooled effect: Fixed effects 0.51(0.49–0.53); I2=0%VERY LOW
ATRIA subgrouped by antiplatelets – >33%11017Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.61(0.54–0.67)LOW
ORBIT35593Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPooled effect: Random Effects 0.57(0.52–0.61); I2=73%VERY LOW
ORBIT subgrouped by antiplatelets - <33%12293Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessSerious imprecisionc0.52(0.48–0.56)VERY LOW
ORBIT subgrouped by antiplatelets - >33%11017Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.61(0.54–0.68)LOW
ORBIT subgrouped by antiplatelets – not reported12283Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.58(0.55–0.61)LOW
CHADS212293Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessSerious imprecisionc0.51(0.47–0.55)VERY LOW
CHADSVASC12293Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessSerious imprecisionc0.53(0.49–0.57)VERY LOW
GARFIELD13550Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.57(0.55–0.58)LOW
MBRFS14576Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.53(0.52–0.54)LOW
mOBRI11017Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.56(0.50–0.62)LOW
CBRM/Shireman11017Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.58(0.54–0.62)LOW
Simplified HAS-BLED11089Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.642(0.60–0.68)LOW
HAS-BLED with point for sustained AF11089Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.61(0.57–0.65)LOW

GRADE was conducted with emphasis on C statistics as this was the primary measure discussed in decision making.

Pooling (meta-analysis) was carried out if there were at least two studies per risk tool with confidence intervals. RevMan was used to carry out the analyses. If pooling was not possible for risk tools with >1 data point then the range and median value of the study point estimates were recorded. If there were only one data point then only the result from the study was recorded.

a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for some risk tools because few of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the rest of the risk tools because many studies with the aforementioned limitations also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Where data were pooled, an I2of 50–74% was deemed serious inconsistency and an I2of 75% or above was deemed very serious inconsistency. If no pooling were possible, inconsistency was assessed by inspection of the degree of overlap of confidence intervals between studies: if one of more Cis did not overlap then a rating of serious inconsistency was given. Reasons for heterogeneity between studies may include geographical/cultural/ethnic differences. Clinically the studies appeared reasonably homogeneous, with similar rates of hypertension, diabetes and former stroke.

c)

The judgement of precision was based on the spread of confidence interval around two clinical thresholds: C statisticsof 0.5 and 0.7. The threshold of 0.5 marked the boundary between no predictive value better than chance and a predictive value better than chance. The threshold of 0.7 marked the boundary above which the committee might consider recommendations. If the 95% Cis crossed one of these thresholds a rating of serious imprecision was given and if they crossed both of these thresholds a rating of very serious imprecision as given.

Table 14Clinical evidence profile: sensitivity and specificityof prediction of clinically relevant bleedingin all risk tools featured in the studies (see table 3). 95% CIs are given for non-pooled results

Risk toolNo of COHORTSnSensitivity (threshold denotes the ‘positive’ score – i.e. the score indicating a high risk of bleeding)Specificity (threshold denotes the ‘positive’ score – i.e. the score indicating a high risk of bleeding)Risk of biasInconsistencyIndirectnessImprecisionQuality
HAS-BLED at threshold ≥124566Mediand: 0.913(0.880–0.940)Mediand: 0.171(0.160–0.190Sensitivity
Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisioncVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessNo serious imprecisionVERY LOW
HAS-BLED at threshold ≥224566Mediand: 0.496(0.440–0.550)Mediand: 0.686(0.670–0.710)Sensitivity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessNo serious imprecisionVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessNo serious imprecisionVERY LOW
HAS-BLED at threshold ≥324566Mediand: 0.110(0.080–0.150)Mediand: 0.950(0.940–0.960)Sensitivity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessNo serious imprecisionVERY LOW
Specificity
Very serious risk of biasaSerious inconsistencybNo serious indirectnessNo serious imprecisionVERY LOW
ATRIA at threshold ≥1122680.879(0.832–0.917)0.113(0.099–0.128)Sensitivity
Very serious risk of biasaNANo serious indirectnessSerious imprecisioncVERY LOW
Specificity
Very serious risk of biasaNANo serious indirectnessSerious imprecisioncVERY LOW
ATRIA at threshold ≥2122680.411(0.349–0.475)0.583(0.561–0.605)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Hemmorhages at threshold ≥1122680.742(0.683–0.795)0.353(0.332–0.374)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Hemmorhages at threshold ≥2122680.266(0.212–0.326)0.779(0.770–0.788)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
ORBIT at threshold ≥1122830.734(0.684–0.779)0.388(0.367–0.411)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
ORBIT at threshold ≥2122830.283(0.236–0.3340.812(0.793–0.829)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
CHADS2 at threshold ≥1122930.972(0.943–0.988)30.0230(0.170–0.305)3Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
CHADS2 at threshold ≥2122930.637(0.575–0.697)0.385(0.364–0.406)Sensitivity
Very serious risk of biasaNANo serious indirectnessSerious imprecisioncVERY LOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
CHADSVASC at threshold ≥2122930.936(0.899–0.963)0.079(0.069–0.093)Sensitivity
Very serious risk of biasaNANo serious indirectnessSerious imprecisioncVERY LOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
CHADSVASC at threshold ≥3122930.753(0.695–0.805)0.292(0.273–0.313)Sensitivity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW
Specificity
Very serious risk of biasaNANo serious indirectnessNo serious imprecisionLOW

Pooling (meta-analysis) was carried out if there were at least three studies per risk tool with confidence intervals. RevMan and WinBugs were used to carry out the analyses. If pooling was not possible for risk tools with >1 data point then the range and median value of the study point estimates were recorded. If there were only one data point then only the result from the study was recorded.

a)

Risk of bias was assessed using the PROBAST checklist. Risk of bias was serious for some risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the rest of the risk tools because many studies with the aforementioned limitations also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Where data were pooled, inconsistency was assessed by visual inspection of the sensitivity/specificity plots, or data (if 2 studies). The evidence was downgraded by 1 increment if there was no overlap of 95% confidence intervals. For single studies no evaluation was made and ‘not applicable’ was recorded.

c)

Imprecision was assessed based on inspection of the confidence region in the meta-analysis or, where meta-analysis has not been conducted, assessed according to the range of confidence intervals in the individual studies. The evidence was downgraded by 1 increment when the confidence interval around the point estimate crossed one of the clinical thresholds (0.90 or 0.60 for sensitivity and 0.5 and 0.1 for specificity), and downgraded by 2 increments when the confidence interval around the point estimate crossed both of the clinical thresholds. The upper clinical threshold marked the point above which recommendations would be possible, and the lower clinical threshold marked the point below which the tool would be regarded as of little clinical use.

d)

For unpooled data the median value was given (of data with 95% CIs). If there were an even number of data points in the unpooled data, the data point chosen in the central pair was the one with lower sensitivity, with its paired specificity.

Table 15NRI for clinically relevant bleeding

Prediction tool comparisonNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecisionNRI(95% CI)Quality
HAS-BLED v HEMORRHAGES23450Very serious risk of biasaVery serious inconsistencybNo serious indirectnessSerious imprecisioncPooled: Random effects NRI: + 0.030(−0.130to +0.180); I2= 89%VERY LOW
HAS-BLED v ATRIA23450Very serious risk of biasaVery serious inconsistencybNo serious indirectnessSerious imprecisioncPooled: Random effects NRI: + 0.040(−0.150to +0.220); I2= 92%VERY LOW
ATRIA v HEMORRHAGES23450Very serious risk of biasaVery serious inconsistencybNo serious indirectnessSerious imprecisioncPooled: Random effects NRI: + 0.060(−0.060to +0.190); I2 = 81%VERY LOW
HAS-BLED v CHADS212293Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.130(0.050to 0.210)LOW
HAS-BLED v GARFIELD13550Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc−0.033(−0.129 to 0.094)VERY LOW
HAS-BLED v CHADSVASC12293Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.130(0.050to 0.210)LOW
HAS-BLED v ORBIT12283Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.156(0.043 to 0.27)MOD
ATRIA v ATRIA +TTR12293Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.260 (−0.480to −0.040)LOW
ORBIT v ORBIT + TTR12293Serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.260 (−0.480to −0.040)MOD
a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for most risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the Framingham risk tool because the study concerned also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Inconsistency was serious if I2 was 50–74% and very serious if 75% of higher

c)

Imprecision serious if the 95% CIs crossed zero.

Table 16Clinical evidence profile: accuracy of prediction of ICHin all risk tools featured in the studies (see table 3). Outcomes split across subgroups are only shown if sub-grouping was able to reduce I2 to <50% in all sub-groups

Risk toolNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecision

Area Under Curve Individual study effects [point estimate (95% Cis) ]

Pooled effect/range/median

Quality
HAS-BLED7110,194Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPooled effect: Random effects 0.56(0.53–0.60); I2=83%VERY LOW
HAS-BLED subgrouped by antiplatelets - <33%140,450Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.53(0.51–0.54)LOW
HAS-BLED subgrouped by antiplatelets - >33%318.113Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecisionPooled effect: Fixed effects 0.56(0.52–0.60); I2=0%LOW
HAS-BLED subgrouped by antiplatelets – not reported351631Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecisionPooled effect: Fixed effects 0.59(0.58–0.61); I2=0%LOW
HEMORRHAGES5107,162Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPooled effect: Random effects: 0.58(0.52–0.64); I2=93%VERY LOW
HEMORRHAGES subgrouped by antiplatelets – <33%140,450Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.53(0.51–0.54)LOW
HEMORRHAGES subgrouped by antiplatelets – >33%318,113Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecisionPooled effect: Fixed effects 0.59(0.55–0.63); I2=0%LOW
HEMORRHAGES subgrouped by antiplatelets – not reported148,599Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.62(0.60–0.64)LOW
ATRIA458,563Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPooled effect: Random effects 0.56(0.50–0.61); I2=75%VERY LOW
ATRIA subgrouped for antiplatelets - <33%140,450Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessSerious imprecisionc0.50(0.49–0.52)VERY LOW
ATRIA subgrouped for antiplatelets - >33%318.113Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecisionPooled effect: Fixed effects 0.58(0.54–0.63); I2=0%LOW
ORBIT458,563Very serious risk of biasaVery serious risk of inconsistencybNo serious indirectnessNo serious imprecisionPooled effectRandom effects 0.58(0.50–0.67); I2=91%VERY LOW
ORBIT subgrouped for antiplatelets - <33%140,450Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessserious imprecisionc0.50(0.48–0.51)VERY LOW
ORBIT subgrouped for antiplatelets - >33%318,113Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecisionPooled effect: Fixed effects 0.62(0.58–0.66); I2=0%LOW
ABCBleeding CrC11120Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessSerious imprecisionc0.47(0.40–0.53)VERY LOW
MBR140450Very serious risk of biasaNo serious risk of inconsistencyNo serious indirectnessNo serious imprecision0.52(0.50–0.53)LOW

GRADE was conducted with emphasis on C statisticsas this was the primary measure discussed in decision making.

Pooling (meta-analysis) was carried out if there were at least two studies per risk tool with confidence intervals. RevMan was used to carry out the analyses. If pooling was not possible for risk tools with >1 data point then the range and median value of the study point estimates were recorded. If there were only one data point then only the result from the study was recorded.

a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for some risk tools because few of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the rest of the risk tools because many studies with the aforementioned limitations also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Where data were pooled, an I2of 50–74% was deemed serious inconsistency and an I2of 75% or above was deemed very serious inconsistency. If no pooling were possible, inconsistency was assessed by inspection of the degree of overlap of confidence intervals between studies: if one of more Cis did not overlap then a rating of serious inconsistency was given. Reasons for heterogeneity between studies may include geographical/cultural/ethnic differences. Clinically the studies appeared reasonably homogeneous, with similar rates of hypertension, diabetes and former stroke.

c)

The judgement of precision was based on the spread of confidence interval around two clinical thresholds: C statistics of 0.5 and 0.7. The threshold of 0.5 marked the boundary between no predictive value better than chance and a predictive value better than chance. The threshold of 0.7 marked the boundary above which the committee might consider recommendations. If the 95% Cis crossed one of these thresholds a rating of serious imprecision was given and if they crossed both of these thresholds a rating of very serious imprecision as given.

Table 17Clinical evidence profile: sensitivity and specificityof prediction of intracranial haemmorhagein all risk tools featured in the studies (see table 3). 95% CIs are given for non-pooled results

Risk toolNo of COHORTSnSensitivity (threshold denotes the ‘positive’ score – i.e. the score indicating a high risk of bleeding)Specificity (threshold denotes the ‘positive’ score – i.e. the score indicating a high risk of bleeding)Risk of biasInconsistencyIndirectnessImprecisionQuality
HAS-BLEDat threshold ≥310.538(0.410–0.660)0.572(0.540–0.600)Sensitivity
Serious risk of biasaNANo serious indirectnesSerious imprecisioncLOW
Specificity
Serious risk of biasaNANo serious indirectnesNo serious imprecisionMOD
ABCCrC at threshold ≥2%10.785(0.670–0.880)0.186(0.160–0.210)Sensitivity
Serious risk of biasaNANo serious indirectnesNo serious imprecisionMOD
Specificity
Serious risk of biasaNANo serious indirectnesNo serious imprecisionMOD

Pooling (meta-analysis) was carried out if there were at least three studies per risk tool with confidence intervals. RevMan and WinBugs were used to carry out the analyses. If pooling was not possible for risk tools with >1 data point then the range and median value of the study point estimates were recorded. If there were only one data point then only the result from the study was recorded.

a)

Risk of bias was assessed using the PROBAST checklist. Risk of bias was serious for some risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the rest of the risk tools because many studies with the aforementioned limitations also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Where data were pooled, inconsistency was assessed by visual inspection of the sensitivity/specificity plots, or data (if 2 studies). The evidence was downgraded by 1 increment if there was no overlap of 95% confidence intervals. For single studies no evaluation was made and ‘not applicable’ was recorded.

c)

Imprecision was assessed based on inspection of the confidence region in the meta-analysis or, where meta-analysis has not been conducted, assessed according to the range of confidence intervals in the individual studies. The evidence was downgraded by 1 increment when the confidence interval around the point estimate crossed one of the clinical thresholds (0.90 or 0.60 for sensitivity and 0.5 and 0.1 for specificity), and downgraded by 2 increments when the confidence interval around the point estimate crossed both of the clinical thresholds. The upper clinical threshold marked the point above which recommendations would be possible, and the lower clinical threshold marked the point below which the tool would be regarded as of little clinical use.

Table 18NRI for intracranial bleeding

Prediction tool comparisonNo of COHORTSnRisk of biasInconsistencyIndirectnessImprecisionNRI(95% CI)Quality
HAS-BLED v HEMORRHAGES140,450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc+0.030(−0.001 to 0.060)VERY LOW
HAS-BLED v ATRIA140,450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.060(0.026 to 0.093)LOW
HAS-BLED V ORBIT140,450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision+0.048(0.013 to 0.082)LOW
HAS-BLED v MBR140,450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc+0.007(−0.018 to 0.033)VERY LOW
HAS-BLED v ABCCrC11120Serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc+0.139(−0.010to 0.290)LOW
MBR v HEMORRHAGES140,450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc−0.022(−0.062 to 0.017)VERY LOW
MBR v ATRIA140,450Very serious risk of biasaNo serious inconsistencyNo serious indirectnessNo serious imprecision−0.052(−0.094 to −0.011)LOW
MBR v ORBIT140,450Serious risk of biasaNo serious inconsistencyNo serious indirectnessSerious imprecisionc−0.040(−0.083 to 0.002)LOW
a)

Risk of bias was assessed using the PROBAST checklist (see Appendix F).Risk of bias was serious for most risk tools because none of the studies reported any blinding of assessors for risk tool data and outcome status, and most did not report loss to follow up, although follow up and number of events were appropriate. Risk of bias was very serious for the Framingham risk tool because the study concerned also had insufficient numbers of events (<100) and/or inappropriately short follow up times (<5 years) to be able to accurately predict risk.

b)

Inconsistency was serious if I2 was 50–74% and very serious if 75% of higher

c)

Imprecision serious if the 95% CIs crossed zero.

Final

Evidence review

Developed by the National Guideline Centre, Royal College of Physicians

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