Portal de Periódicos da CAPES

Digital Chest Radiography Enhances Screening Efficiency for Pulmonary Tuberculosis in Primary Health Clinics in South Africa

2021; Oxford University Press; Volume: 74; Issue: 9 Linguagem: Inglês

10.1093/cid/ciab644

1537-6591

Nishila Moodley, Kavindhran Velen, Amashnee Saimen, Noor Mahomed Zakhura, Gavin Churchyard, Salome Charalambous,

Infectious Diseases and Tuberculosis

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.