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Table 1 Mean, ranges and number of reviewed studies for sensitivity and specificity estimates of physician-certified verbal autopsy for selected causes of death, among hospital-based deaths

From: Comparison of physician-certified verbal autopsy with computer-coded verbal autopsy for cause of death assignment in hospitalized patients in low- and middle-income countries: systematic review

 

Sensitivity

Specificity

 

Mean (%)

Range

Number of studies

Mean (%)

Range

Number of studies

Infections and parasitic diseases and maternal deaths

Tuberculosis

39

18 to 62

3

97

93 to 99

2

HIV/AIDS

59a

0 to 61

3

90a

0 to 96

3

Diarrheal diseasesb

38a

0 to 75

2

96

94 to 99

2

Malariab

60a

0 to 67

2

89a

0 to 100

2

Pneumonia

42

18 to 75

4

93

84 to 99

3

Maternal deaths

63

-

1

100

-

1

Neonatal conditions

    

Prematurity or low birth weight

48

-

1

95

-

1

Birth asphyxia or birth trauma

43

-

1

90

-

1

Neonatal infections

31

11 to 50

2

100

99 to 100

2

Noncommunicable diseases

Nutritional conditions

33a

0 to 58

2

94

87 to 99

2

Digestive cancers

82a

56 to 96

3

100

99 to 100

2

Respiratory cancers

84

80 to 89

2

99

-

1

Other cancers

61a

27 to 95

5

99

98 to 99

2

Heart disease

39

16 to 64

3

98

98 to 99

2

Stroke

71

63 to 82

3

95

94 to 97

2

Chronic respiratory diseases

61

60 to 62

2

98

-

1

Cirrhosis of the liver

58

45 to 71

2

98

-

1

Other digestive diseases

36

21 to 52

2

99

-

1

Renal or endocrine diseases

32

13 to 54

3

99

99 to 99.4

2

Injuries

Road traffic accidents

97

97 to 98

2

100

-

1

Other injuries

57

35.3 to 74

3

100

99 to 100

2

  1. aMedian was used instead of means due to outlier values in the ranges of estimates. However, the medians and means yielded similar results (that is, the pooled studies gave PCVA a sensitivity mean of 80.1% and a median of 81.9% for ascertaining digestive cancers). bAlthough two studies were used to generate results for these CODs, the studies provided results for several population sub-samples.