Activities of Daily Living, Hypoxemia, and Lymphocytes Score for Predicting Mortality Risk in Patients With Pulmonary TB

A clinically applicable mortality risk prediction system for pulmonary TB may improve treatment outcomes, but no easy-to-calculate and accurate score has yet been reported. The aim of this study was to construct a simple and objective disease severity score for patients with pulmonary TB. Does a clinical score consisting of simple objective factors predict the mortality risk of patients with pulmonary TB? The data set from our previous prospective study that recruited patients newly diagnosed with pulmonary TB was used for the development cohort. Patients for the validation cohort were prospectively recruited between March 2021 and September 2022. The primary end point was all-cause in-hospital mortality. Using Cox proportional hazards regression, a mortality risk prediction model was optimized in the development cohort. The disease severity score was developed by assigning integral points to each variate. The data from 252 patients in the development cohort and 165 patients in the validation cohort were analyzed, of whom 39 (15.5%) and 17 (10.3%), respectively, died in the hospital. The disease severity score (named the AHL score) included three clinical parameters: activities of daily living (semi-dependent, 1 point; totally dependent, 2 points); hypoxemia (1 point), and lymphocytes (< 720/μL, 1 point). This score showed good discrimination with a C statistic of 0.902 in the development cohort and 0.842 in the validation cohort. We stratified the score into three groups (scores of 0, 1-2, and 3-4), which clearly corresponded to low (0% and 1.3%), intermediate (13.5% and 8.9%), and high (55.8% and 39.3%) mortality risk in the development and validation cohorts. The easy-to-calculate AHL disease severity score for patients with pulmonary TB was able to categorize patients into three mortality risk groups with great accuracy. University Hospital Medical Information Network Center; No. UMIN000012727 and No. UMIN000043849; URL: www.umin.ac.jp