Table 1.

Single Term with the Best Sensitivity, Best Specificity, and Best Optimization of Sensitivity and Specificity for Detecting Studies of Diagnosis in EMBASE in 2000. Values are percentages (95% confidence intervals).

Search term OVID search*	Sensitivity (n = 97)	Specificity (n = 27672)	Precision†	Accuracy (n = 27769)
Best sensitivity (keeping specificity ≥ 50%) di.fs.	91.8 (86.3 to 97.2)	76.4 (75.9 to 76.9)	1.4 (1.1 to 1.6)	76.5 (76.0 to 77.0)
Best specificity (keeping sensitivity ≥ 50%) specificity.tw.	62.9 (53.5 to 72.5)	98.2 (98.1 to 98.4)	11.0 (8.4 to 13.6)	98.1 (97.9 to 98.3)
Best Optimization of Sensitivity & Specificity‡ diagnos:.mp.	89.7 (83.6 to 95.7)	84.7 (84.3 to 85.2)	2.0 (1.6 to 2.4)	84.8 (84.3 to 85.2)

*Search strategies are reported using Ovid's search engine syntax for EMBASE. †Denominator varies by row. ‡Based on the lowest possible absolute difference between sensitivity and specificity. di = diagnosis; fs = floating subheading; tw = textword (word or phrase appears in title or abstract); : = truncation; mp = multiple posting – term appears in title, abstract, or subject heading. Sensitivity = the proportion of high quality articles for that topic that are retrieved; specificity = the proportion of low quality articles not retrieved; precision = the proportion of retrieved articles that are of high quality; accuracy = the proportion of all articles that are correctly classified.