Development of Scoring and Stratification of Severe Lung Involvement in Multidrug-Resistant Pulmonary Tuberculosis Patients

Background and Objective: The probability of the presence of risk factors and clinical outcomes in multidrug-resistant pulmonary tuberculosis subjects is undermined. A clinical prediction model was established based on radiological examination. To assess the effectiveness of the prediction model and strengthen both the diagnostic and prognostic applications, we developed and validated a scoring system employing radiological examination. Materials and Methods: The radiological grading categorized severe lung involvement. The study recorded the patient’s hemogram and medical history. Radiological grading and clinical investigations were chosen as dependent variables and independent variables, respectively. Data were analyzed using bivariate logistic regression with p<0.2 and multivariate logistic regression analysis with p<0.05. Independent predictor variables and their regression coefficient (β) evaluated. The constant in this study was based on the Framingham study. Results: Hematological changes were observed in the grading of lung severity using ANOVA. The regression analysis identified a history of multidrug-resistant tuberculosis (p = 0.0001) and resistance to more than one anti-tubercular drug (p = 0.026) and a few parameters of hemogram as predictors for an intense lung infection. This study segregated the study subjects into risk categories and evaluated the performance of the scoring system. Conclusion: The score developed helps in stratifying the patients at severe risk of lung involvement alerting the healthcare professional for patients’ better pharmaceutical care.