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Table 3 Clinical performance and programmatic impact of three diagnosis algorithms

From: Performance and impact of GeneXpert MTB/RIF® and Loopamp MTBC Detection Kit® assays on tuberculosis case detection in Madagascar

Algorithm

TP

TN

FP

FN

Sensitivity

Specificity

PPV

NPV

Molecular testing

Additional case notification

Total case notification

LR+

LR-

n

n

n

n

% (95% CI)

% (95% CI)

% (95% CI)

% (95% CI)

n (%)

n

n

Algorithm 1

 Smear (n = 514)

148

310

3

53

73.6 (67.1–79.3)

99.0 (97.1–99.8)

98.0 (94.1–99.6)

85.4 (81.4–88.7)

0 (0)

N/A

151

76.8

0.3

Algorithm 2

 GeneXpert MTB/RIF® (n = 509)

174

300

8

27

86.6 (81.1–90.7)

97.4 (94.9–98.8)

95.6 (91.4–97.9)

91.7 (88.2–94.3)

509 (100.0)

31

182

33.3

0.1

 Loopamp MTBC Detection Kit® (n = 517)

170

311

5

31

84.6 (78.9–89.0)

98.4 (96.2–99.4)

97.1 (93.3–99.0)

90.9 (87.4–93.6)

517 (100.0)

24

175

53.5

0.2

Algorithm 3

 Smear - followed by GeneXpert MTB/RIF® (n = 506)

177

295

10

24

88.1 (82.8–91.9)

96.7 (94.0–98.3)

94.7 (90.3–97.2)

92.5 (89.0–94.9)

358 (70.1)

36

187

26.9

0.1

 Smear - followed by Loopamp MTBC Detection Kit® (n = 514)

177

307

6

24

88.1 (82.8–91.9)

97.5 (95.0–98.8)

96.7 (92.9–98.7)

92.8 (89.4–95.1)

366 (71.2)

32

183

45.9

0.1