ArticleEpidemiology and infection2017
Predicting treatment failure, death and drug resistance using a computed risk score among newly diagnosed TB patients in Tamaulipas, Mexico.
Article in Epidemiology and infection, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 4 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 4 syntheses or guidelines pooled it, 32 citations in OpenAlex.
- Effect of alcohol consumption on relapse outcomes among tuberculosis patients: A systematic review and meta-analysis.Frontiers in public health · 2022Pooled it
- Malnutrition assessment methods in adult patients with tuberculosis: a systematic review.BMJ open · 2021Pooled it
- Systematic review of prediction models for pulmonary tuberculosis treatment outcomes in adults.BMJ open · 2021Pooled it
- Pooled it
- Accuracy of the Phenotypic 1G Test to Detect Mycobacterium tuberculosis and Drug Resistance From Sputa in the US-Mexico Border.The Journal of infectious diseases · 2026Article
- Tuberculosis treatment outcomes and associated factors at Alemgena Health Center, Sebeta, Oromia, Ethiopia.PloS one · 2024Article
- Deep learning on longitudinal CT scans: automated prediction of treatment outcomes in hospitalized tuberculosis patients.iScience · 2023Article
- Development and validation of a prediction model for unsuccessful treatment outcomes in patients with multi-drug resistance tuberculosis.BMC infectious diseases · 2023Article
- Prognostication of treatment non-compliance among patients with multidrug-resistant tuberculosis in the course of their follow-up: a logistic regression-based machine learning algorithm.Frontiers in digital health · 2023Article
- A Scoring System Based on Laboratory Parameters and Clinical Features to Predict Unfavorable Treatment Outcomes in Multidrug- and Rifampicin-Resistant Tuberculosis Patients.Infection and drug resistance · 2023Article
- A Score to Predict the Risk of Major Adverse Drug Reactions Among Multi-Drug Resistant Tuberculosis Patients in Southern Ethiopia, 2014-2019.Infection and drug resistance · 2022Article
- Development and Validation of a Nomogram for the Prediction of Unfavorable Treatment Outcome Among Multi-Drug Resistant Tuberculosis Patients in North West Ethiopia: An Application of Prediction Modelling.Infection and drug resistance · 2022Article
- Article
- Interferon gamma release assays for detection of latent Mycobacterium tuberculosis in older Hispanic people.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021Article
- Risk factor for 31-day unplanned readmission to hospital in patients with pulmonary tuberculosis in China.Saudi medical journal · 2021Article
- A risk score for prediction of poor treatment outcomes among tuberculosis patients with diagnosed diabetes mellitus from eastern China.Scientific reports · 2021Article
- Article
- Diabetes screen during tuberculosis contact investigations highlights opportunity for new diabetes diagnosis and reveals metabolic differences between ethnic groups.Tuberculosis (Edinburgh, Scotland) · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
The purpose of this study was to develop a method for identifying newly diagnosed tuberculosis (TB) patients at risk for TB adverse events in Tamaulipas, Mexico. Surveillance data between 2006 and 2013 (8431 subjects) was used to develop risk scores based on predictive modelling. The final models revealed that TB patients failing their treatment regimen were more likely to have at most a primary school education, multi-drug resistance (MDR)-TB, and few to moderate bacilli on acid-fast bacilli smear. TB patients who died were more likely to be older males with MDR-TB, HIV, malnutrition, and reporting excessive alcohol use. Modified risk scores were developed with strong predictability for treatment failure and death (c-statistic 0·65 and 0·70, respectively), and moderate predictability for drug resistance (c-statistic 0·57). Among TB patients with diabetes, risk scores showed moderate predictability for death (c-statistic 0·68). Our findings suggest that in the clinical setting, the use of our risk scores for TB treatment failure or death will help identify these individuals for tailored management to prevent these adverse events. In contrast, the available variables in the TB surveillance dataset are not robust predictors of drug resistance, indicating the need for prompt testing at time of diagnosis.
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Registered trials
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