A novel Inflammation-Nutrition risk score (INRS) and its related nomogram model to predict radiological bronchiectasis in patients after tuberculosis infection in Wuhan, China

Abstract

Background Tuberculosis infection (TBI) is an important cause of bronchiectasis (BE). Exploring the risk factors of radiological BE (RBE) may improve the identification of high-risk populations of RBE after TB infection. The present study aimed to develop a novel inflammation-nutrition risk score (INRS) and RBE nomogram model to identify the high-risk population of RBE after TBI. Methods The present study recruited 2015 patients after TBI from two centers. Patients after TBI (N = 1825) from the Wuhan Jinyintan Hospital cohort were used to construct the INRS and RBE nomogram model. In addition, an independent external validation set from the Wuhan Union Hospital (N = 190) validated them. Results INRS was constructed based on PNI, HALP score, Lg (SII), and CAR. Additionally, Age ≥ 60 years old (OR:1.19, P = 0.030), Smoker (OR:1.71, P = 0.009), COPD (OR:3.13, P < 0.001), RDW.CV ≥ 12.8 (OR:1.09, P = 0.005), ALB < 35.5 (OR:1.04, P = 0.003), and INRS ≥ 1.86 (OR:5.04, P = < 0.001) were independent risk factors of RBE in patients after TBI. The RBE nomogram model to identify the high-risk RBE population was successfully established and showed a strong discriminative ability, accuracy, and clinical utility in development, internal validation, and external validation sets. Conclusion In patients after TBI, INRS may be a useful predictive biomarker for RBE, and the RBE nomogram model is a convenient and efficient tool for follow-up management for preventing RBE.