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.

Wilczynski et al. BMC Medicine 2005 3:7   doi:10.1186/1741-7015-3-7

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