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Table 4 Top 3-performing Combination of Terms with the Best Sensitivity (keeping Specificity ≥50%), Specificity (keeping Sensitivity ≥50%), and Best Optimization of Sensitivity and Specificity (based on abs [sensitivity-specificity]<1%) for Detecting Studies of Causation in EMBASE in 2000

From: Developing optimal search strategies for detecting clinically sound and relevant causation studies in EMBASE

Search Strategy OVID search* Sensitivity (%) (n = 215) Specificity (%) (n = 27,554) Precision (%)† Accuracy (%) (n = 27,769)
Top 3-performing combination of terms with best Sensitivity
risk:.mp. OR exp methodology OR exp epidemiology 91.6 (87.9 to 95.3) 60.9 (60.3 to 61.4) 1.8 (1.6 to 2.0) 61.1 (60.5 to 61.7)
risk:.tw. OR exp methodology OR exp epidemiology 91.2 (87.4 to 95.0) 63.0 (62.4 to 63.6) 1.9 (1.6 to 2.2) 63.2 (62.6 to 63.8)
risk:.mp. OR exp methodology OR exp mortality 90.7 (86.8 to 94.6) 65.1 (64.5 to 65.7) 2.0 (1.7 to 2.3) 65.3 (64.7 to 65.8)
Top 3-performing combination of terms with best Specificity
cohort.tw. OR relative risk:.tw. 53.0 (46.4 to 59.7) 94.6 (94.4 to 94.9) 7.1 (5.9 to 8.4) 94.3 (94.0 to 94.6)
confidence interval.tw. OR relative risk:.tw. 50.7 (44.0 to 57.4) 94.5 (94.2 to 94.7) 6.7 (5.4 to 7.9) 94.1 (93.8 to 94.4)
OR relative risk:.tw. OR cohort:.tw. 53.5 (46.8 to 60.2) 94.4 (94.1 to 94.6) 6.9 (5.7 to 8.1) 94.1 (93.8 to 94.3)
Top 3-performing combination of terms with best optimization of Sensitivity and Specificity
risk.tw. OR mortalit:.tw, OR cohort.tw. 81.9 (76.7 to 87.0) 81.4 (80.9 to 81.8) 3.3 (2.8 to 3.8) 81.4 (80.9 to 81.8)
risk:.tw. OR cohort:.mp. OR confidence interval:.tw. 81.9 (76.7 to 87.0) 81.2 (80.8 to 81.7) 3.3 (2.8 to 3.8) 81.3 (80.8 to 81.7)
risk.tw. OR mortalit:.tw. OR cohort:.tw 81.9 (76.7 to 87.0) 81.2 (80.8 to 81.7) 3.3 (2.8 to 3.8) 81.2 (80.8 to 81.7)
  1. *Search strategies are reported using Ovid's search engine syntax for EMBASE.
  2. †Denominator varies by row.
  3. : = truncation; mp = multiple posting – term appears in title, abstract, or subject heading; exp = explode, a search term that automatically includes closely related indexing terms; tw = textword (word or phrase appears in title or abstract).