Evaluation of chest X-ray with automated interpretation algorithms for mass tuberculosis screening in prisons: a cross-sectional study

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.

Burnout syndrome in nursing professionals from urgency and emergency services

Objetivo: Analisar como os estudos científicos descrevem a síndrome de Burnout em profissionais de enfermagem de serviços de urgência e emergência. Métodos: Revisão integrativa de literatura realizada através das bases de dados BDENF, IBECS, LILACS, MEDLINE e SciELO, por meio dos descritores: esgotamento profissional and enfermagem. Das 3087 publicações selecionadas pelos descritores, apenas 11 artigos atenderam os critérios de inclusão e exclusão. Resultados: Dentre os artigos selecionados, 07 tratavam do estresse; 04 falavam da qualidade de vida e lazer; 01 abordava sobre os sintomas somáticos associados ao Burnout e 03 detalhavam sobre a síndrome de Burnout, abordando os fatores preditores e as dimensões sintomatológicas de acordo com o Maslach Burnout Inventory. Conclusão: Esse estudo é importante para que população, profissionais e gestores adquiram conhecimento acerca da síndrome, podendo contribuir para o desenvolvimento de estratégias de enfrentamento, que irão minimizar os riscos de desencadeamento do Burnout. Descritores: Esgotamento profissional, Enfermagem, Síndrome.