دورية أكاديمية
Evaluation of chest X-ray with automated interpretation algorithms for mass tuberculosis screening in prisons: a cross-sectional study.
| العنوان: | Evaluation of chest X-ray with automated interpretation algorithms for mass tuberculosis screening in prisons: a cross-sectional study. |
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| المؤلفون: | Soares TR; Faculty of Health Sciences of Federal University of Grande Dourados, Dourados, MS, Brazil., Oliveira RD; Faculty of Health Sciences of Federal University of Grande Dourados, Dourados, MS, Brazil.; Nursing School, State University of Mato Grosso do Sul, Dourados, MS, Brazil., Liu YE; Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, United States of America., Santos ADS; Faculty of Health Sciences of Federal University of Grande Dourados, Dourados, MS, Brazil., Santos PCPD; Faculty of Health Sciences of Federal University of Grande Dourados, Dourados, MS, Brazil., Monte LRS; Nursing School, State University of Mato Grosso do Sul, Dourados, MS, Brazil., Oliveira LM; Oswaldo Cruz Foundation, Campo Grande, MS, Brazil., Park CM; Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.; Department of Radiology, Seoul National University Hospital, Seoul, Korea., Hwang EJ; Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.; Department of Radiology, Seoul National University Hospital, Seoul, Korea., Andrews JR; Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, United States of America., Croda J; Oswaldo Cruz Foundation, Campo Grande, MS, Brazil.; Department of Epidemiology of Microbial Diseases, Yale University School of Public Health, New Haven, CT, United States of America.; School of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil. |
| المصدر: | Lancet regional health. Americas [Lancet Reg Health Am] 2022 Nov 04; Vol. 17, pp. 100388. Date of Electronic Publication: 2022 Nov 04 (Print Publication: 2023). |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Ltd Country of Publication: England NLM ID: 9918232503006676 Publication Model: eCollection Cited Medium: Internet ISSN: 2667-193X (Electronic) Linking ISSN: 2667193X NLM ISO Abbreviation: Lancet Reg Health Am Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Original Publication: [Oxford] : Elsevier Ltd., [2021]- |
| مستخلص: | Background: The World Health Organization (WHO) recommends systematic tuberculosis (TB) screening in prisons. Evidence is lacking for accurate and scalable screening approaches in this setting. We aimed to assess the accuracy of artificial intelligence-based chest x-ray interpretation algorithms for TB screening in prisons. Methods: We performed prospective TB screening in three male prisons in Brazil from October 2017 to December 2019. We administered a standardized questionnaire, performed a chest x-ray in a mobile unit, and collected sputum for confirmatory testing using Xpert MTB/RIF and culture. We evaluated x-ray images using three algorithms (CAD4TB version 6, Lunit version 3.1.0.0 and qXR version 3) and compared their accuracy. We utilized multivariable logistic regression to assess the effect of demographic and clinical characteristics on algorithm accuracy. Finally, we investigated the relationship between abnormality scores and Xpert semi-quantitative results. Findings: Among 2075 incarcerated individuals, 259 (12.5%) had confirmed TB. All three algorithms performed similarly overall with area under the receiver operating characteristic curve (AUC) of 0.88-0.91. At 90% sensitivity, only LunitTB and qXR met the WHO Target Product Profile requirements for a triage test, with specificity of 84% and 74%, respectively. All algorithms had variable performance by age, prior TB, smoking, and presence of TB symptoms. LunitTB was the most robust to this heterogeneity but nonetheless failed to meet the TPP for individuals with previous TB. Abnormality scores of all three algorithms were significantly correlated with sputum bacillary load. Interpretation: Automated x-ray interpretation algorithms can be an effective triage tool for TB screening in prisons. However, their specificity is insufficient in individuals with previous TB. Funding: This study was supported by the US National Institutes of Health (grant numbers R01 AI130058 and R01 AI149620) and the State Secretary of Health of Mato Grosso do Sul. Competing Interests: The authors declare no conflict of interest. (© 2022 The Author(s).) |
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| معلومات مُعتمدة: | R01 AI130058 United States AI NIAID NIH HHS; R01 AI149620 United States AI NIAID NIH HHS |
| فهرسة مساهمة: | Keywords: Automated interpretation; Diagnostics; Prisons; Tuberculosis; X-ray |
| تواريخ الأحداث: | Date Created: 20230213 Latest Revision: 20231027 |
| رمز التحديث: | 20240628 |
| مُعرف محوري في PubMed: | PMC9904090 |
| DOI: | 10.1016/j.lana.2022.100388 |
| PMID: | 36776567 |
| قاعدة البيانات: | MEDLINE |
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