ABSTRACT
BACKGROUND: Optimized tuberculosis (TB) screening in high burden settings is essential for case finding. We evaluated digital chest X-ray with computer-aided detection (CAD) software (d-CXR) for identifying undiagnosed TB in three primary health clinics in South Africa. METHODS: The cross-sectional study consented adults who were sequentially screened for TB using the World Health Organization (WHO) 4 symptom questionnaire and d-CXR. Participants reporting ≥1 TB symptom and/or CAD score ≥60 (suggestive of TB) provided 2 spot sputum for Xpert MTB/RIF Ultra (Xpert Ultra) and liquid culture testing, respectively. TB yield (proportion of screened tested positive) and number needed to test (NNT; no of tests to identify one TB patient) were calculated. Risk factors for microbiologically confirmed or presumed (on radiological grounds) were determined. RESULTS: Among 3041 participants, 45% (1356 of 3041) screened positive on either d-CXR or symptoms. TB yield was 2.3% (71 of 3041) using Xpert Ultra and 2.7% (82 of 3041) using Xpert Ultra plus culture. Modelled TB yield (identified by Xpert Ultra) by screening approach was: 1.9% (59 of 3041) for d-CXR alone, 2.0% (62 of 3041) for symptoms alone and 2.3% (71 of 3041) for both. The NNT was 9.7 for d-CXR, 17.8 for symptoms and 19.1 for d-CXR and/or symptom. Males, those with previous TB, untreated HIV or unknown HIV status, and acute illness were at higher risk of developing TB. CONCLUSION: d-CXR screening identified a similar yield of undiagnosed TB compared to symptom-based screening, however required fewer diagnostic tests. Due to its objective nature, d-CXR screening may improve case detection in clinics.
