Benchmarking the dental implant evidence on MEDLINE
- PMID: 11151577
Benchmarking the dental implant evidence on MEDLINE
Abstract
The purpose of this study was to estimate the quantity of dental implant literature available on MEDLINE for evidence-based clinical decision-making and to identify its location. A search strategy based on Medical Subject Headings for dental implants was developed to examine MEDLINE using the Ovid Web Gateway search engine. Sensitive and specific methodologic search filters identified 4 categories of information: etiology, diagnosis, therapy, and prognosis. The results were then subdivided by year to identify trends and sorted to identify the sources of publications. The searches identified 4,655 articles published in English between 1989 and 1999 on human dental implants on MEDLINE. The mean number of articles (+/- SD) per year ranged from 15 +/- 11 for specific searches to 107 +/- 50 for sensitive searches. The number of articles increased by 14% to 43% each year for the sensitive search. When subdivided by clinical category, the mean numbers of articles per year for sensitive and specific searches were, respectively: diagnosis 12 +/- 7.5 and 1.5 +/- 1.6, etiology 58 +/- 33 and 1.9 +/- 2.5, therapy 23 +/- 15 and 0.3 +/- 0.5, and prognosis 67 +/- 33 and 12 +/- 8.3. Four dental journals account for approximately half of these publications. These results provide 6 key central findings: (1) there appears to be a substantial literature of clinically relevant information on implants upon which to base clinical decisions; (2) the implant literature is significantly biased toward articles addressing prognosis; (3) to stay current, one would need to read between 1 and 2 articles per week 52 weeks per year, and this number increases significantly each year; (4) approximately 50% of the articles were published in 4 journals, whereas the remainder reside in approximately 97 other journals, making it difficult to stay current; (5) these trends reaffirm the need for lifelong learning; (6) these trends also suggest the need for computer-based clinical knowledge systems.
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