dc.creatorBert-Dulanto, Aimée
dc.creatorAlarcón-Braga, Esteban A.
dc.creatorCastillo-Soto, Ana
dc.creatorEscalante-Kanashiro, Raffo
dc.date.accessioned2022-01-04T15:42:49Z
dc.date.accessioned2024-05-07T02:36:20Z
dc.date.available2022-01-04T15:42:49Z
dc.date.available2024-05-07T02:36:20Z
dc.date.created2022-01-04T15:42:49Z
dc.date.issued2021-01-01
dc.identifier00195707
dc.identifier10.1016/j.ijtb.2021.10.007
dc.identifierhttp://hdl.handle.net/10757/658441
dc.identifierIndian Journal of Tuberculosis
dc.identifier2-s2.0-85118709310
dc.identifierSCOPUS_ID:85118709310
dc.identifierS0019570721002298
dc.identifier0000 0001 2196 144X
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9327396
dc.description.abstractBackground: Pulmonary tuberculosis is a highly prevalent disease in low-income countries; clinical prediction tools allow healthcare personnel to catalog patients with a higher risk of death in order to prioritize medical attention. Methodology: We conducted a literature search on prognostic models aimed to predict mortality in patients diagnosed with pulmonary tuberculosis. We included prospective and retrospective studies where prognostic models predicting mortality were either developed or validated in patients diagnosed with pulmonary tuberculosis. Three reviewers independently assessed the quality of the included studies using the PROBAST tool (Prediction model study Risk of Bias Assessment Tool). A narrative review of the characteristics of each model was conducted. Results: Six articles (n = 3553 patients) containing six prediction models were included in the review. Most studies (5 out of 6) were retrospective cohorts, only one study was a prospective case-control study. All the studies had a high risk of bias according to the PROBAST tool in the overall assessment. Regarding the applicability of the prediction models, three studies had a low concern of applicability, two high concern and one unclear concern. Five studies developed new prediction rules. In general, the presented models had a good discriminatory ability, with areas under the curve fluctuating between 0.65 up to 0.91. Conclusion: None of the prognostic models included in the review accurately predict mortality in patients with pulmonary tuberculosis, due to great heterogeneity in the population and a high risk of bias.
dc.languageeng
dc.publisherTuberculosis Association of India
dc.relationhttps://www.sciencedirect.com/science/article/abs/pii/S0019570721002298
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.sourceUniversidad Peruana de Ciencias Aplicadas (UPC)
dc.sourceRepositorio Academico - UPC
dc.sourceIndian Journal of Tuberculosis
dc.subjectMortality
dc.subjectPrognostic models
dc.subjectPulmonary tuberculosis
dc.subjectSystematic review
dc.subjectTuberculosis
dc.titlePredicting mortality in pulmonary tuberculosis: A systematic review of prognostic models
dc.typeinfo:eu-repo/semantics/article


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