Development and Validation of a Dynamic Risk Prediction System for Constipation in Patients with Amyotrophic Lateral Sclerosis

Abstract

Abstract Although constipation is a common non-motor symptom in patients with amyotrophic lateral sclerosis (ALS), it is poorly valued. Moreover, there is a bidirectional effect between constipation and neuropsychiatric and sleep disturbances. Thus, these symptoms are better treated simultaneously. Therefore, this study aimed to develop and validate a model for predicting the risk of constipation in ALS patients, to help clinicians identify and treat constipation early. Data of 118 ALS admissions from an observational prospective cohort, were analyzed. Demographic data as well as related scale scores were obtained. The LASSO regression model was used to select factors. Multivariate logistic regression analysis revealed age, family history of constipation, total ALSFRS-R score, site of onset, total PSQI score, and depressed, were identified as significant predictors of the risk of constipation in ALS patients. The prediction model was validated to have good accuracy (Hosmer–Lemeshow test: χ2 = 11.11, P > 0.05) and discrimination (AUC = 0.856, 95% CI: 0.784–0.928). DCA and CIC showed that the nomogram model had excellent clinical performance. In brief, a web-based ALS constipation risk calculator with good predictive performance was constructed to identify patients at high risk of constipation and to allow early intervention in a clinical context.