Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.

Skip to main content

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).

From: EMBASE search strategies for identifying methodologically sound diagnostic studies for use by clinicians and researchers

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)

  1. *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.