A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis

Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8-7.9), age ≥50 years (OR 2.9, 95% CI 1.7-4.8), bilateral lung involvement (OR 2.5, 95% CI 1.4-4.4), ≥1 significant comorbidity-HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease-(OR 2.3, 95% CI 1.3-3.8), and hemoglobin <12 g/dL (OR 1.8, 95% CI 1.1-3.1). A tuberculosis risk assessment tool (TReAT) was developed, stratifying patients with low (score ≤2), moderate (score 3-5) and high (score ≥6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment.