Accuracy of digital chest x-ray analysis with artificial intelligence software as a triage and screening tool in hospitalized patients being evaluated for tuberculosis in Lima, Peru.

Tuberculosis (TB) transmission in healthcare facilities is common in high-incidence countries. Yet, the optimal approach for identifying inpatients who may have TB is unclear. We evaluated the diagnostic accuracy of qXR (Qure.ai, India) computer-aided detection (CAD) software versions 3.0 and 4.0 (v...

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Main Authors: Amanda M Biewer (Author), Christine Tzelios (Author), Karen Tintaya (Author), Betsabe Roman (Author), Shelley Hurwitz (Author), Courtney M Yuen (Author), Carole D Mitnick (Author), Edward Nardell (Author), Leonid Lecca (Author), Dylan B Tierney (Author), Ruvandhi R Nathavitharana (Author)
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Published: Public Library of Science (PLoS), 2024-01-01T00:00:00Z.
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100 1 0 |a Amanda M Biewer  |e author 
700 1 0 |a Christine Tzelios  |e author 
700 1 0 |a Karen Tintaya  |e author 
700 1 0 |a Betsabe Roman  |e author 
700 1 0 |a Shelley Hurwitz  |e author 
700 1 0 |a Courtney M Yuen  |e author 
700 1 0 |a Carole D Mitnick  |e author 
700 1 0 |a Edward Nardell  |e author 
700 1 0 |a Leonid Lecca  |e author 
700 1 0 |a Dylan B Tierney  |e author 
700 1 0 |a Ruvandhi R Nathavitharana  |e author 
245 0 0 |a Accuracy of digital chest x-ray analysis with artificial intelligence software as a triage and screening tool in hospitalized patients being evaluated for tuberculosis in Lima, Peru. 
260 |b Public Library of Science (PLoS),   |c 2024-01-01T00:00:00Z. 
500 |a 2767-3375 
500 |a 10.1371/journal.pgph.0002031 
520 |a Tuberculosis (TB) transmission in healthcare facilities is common in high-incidence countries. Yet, the optimal approach for identifying inpatients who may have TB is unclear. We evaluated the diagnostic accuracy of qXR (Qure.ai, India) computer-aided detection (CAD) software versions 3.0 and 4.0 (v3 and v4) as a triage and screening tool within the FAST (Find cases Actively, Separate safely, and Treat effectively) transmission control strategy. We prospectively enrolled two cohorts of patients admitted to a tertiary hospital in Lima, Peru: one group had cough or TB risk factors (triage) and the other did not report cough or TB risk factors (screening). We evaluated the sensitivity and specificity of qXR for the diagnosis of pulmonary TB using culture and Xpert as primary and secondary reference standards, including stratified analyses based on risk factors. In the triage cohort (n = 387), qXR v4 sensitivity was 0.91 (59/65, 95% CI 0.81-0.97) and specificity was 0.32 (103/322, 95% CI 0.27-0.37) using culture as reference standard. There was no difference in the area under the receiver-operating-characteristic curve (AUC) between qXR v3 and qXR v4 with either a culture or Xpert reference standard. In the screening cohort (n = 191), only one patient had a positive Xpert result, but specificity in this cohort was high (>90%). A high prevalence of radiographic lung abnormalities, most notably opacities (81%), consolidation (62%), or nodules (58%), was detected by qXR on digital CXR images from the triage cohort. qXR had high sensitivity but low specificity as a triage in hospitalized patients with cough or TB risk factors. Screening patients without cough or risk factors in this setting had a low diagnostic yield. These findings further support the need for population and setting-specific thresholds for CAD programs. 
546 |a EN 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n PLOS Global Public Health, Vol 4, Iss 2, p e0002031 (2024) 
787 0 |n https://journals.plos.org/globalpublichealth/article/file?id=10.1371/journal.pgph.0002031&type=printable 
787 0 |n https://doaj.org/toc/2767-3375 
856 4 1 |u https://doaj.org/article/ff493b7d60084111a08a3be5b40f1b18  |z Connect to this object online.