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Development and validation of a pragmatic prediction model (READMIT score) for estimating 12-month hospital
Tunn Ren Tay1, Mon Hnin Tun2, Anthony Yii1
1Department of Respiratory and Critical Care Medicine, Changi General Hospital, Singapore; Duke-NUS Medical School, Singapore.
Background:
Hospital readmissions after asthma exacerbations contribute substantially to healthcare burden. Deployment of resource-intensive interventions to reduce readmission requires risk stratification, but few prediction models have been developed specifically for asthma-related hospital readmission.
Objective:
To develop and validate a prediction model to estimate the risk of asthma-related hospital readmission within 12 months of discharge.
Methods:
We conducted a retrospective cohort study of 1451 patients admitted for asthma to Changi General Hospital between 2018 and 2021. Predictor selection for the multivariable model was performed using least absolute shrinkage and selection operator logistic regression of candidate predictors. Performance was evaluated in a temporal-validation cohort from the same hospital during 2022-2023 and an external cohort from Singapore General Hospital during 2015-2020. A simplified points-based risk (READMIT) score was derived from the final model.
Results:
The final model incorporated nine predictors - chronic Rhinitis, Emergency Department visit, prior hospital Admission, Depression, Multimorbidity (obstructive sleep apnoea, gastro-oesophageal reflux, bronchiectasis), Inhaled long-acting muscarinic antagonist, systemic corticosteroid Treatment. In the development cohort, the model demonstrated good discrimination (AUC 0.748, 95% CI 0.711-0.785) with satisfactory calibration. Discrimination remained good in the external cohort (AUC 0.737, 95% CI 0.712-0.762). Although absolute risk was overestimated in the external cohort, recalibration for baseline readmission rate improved the accuracy of predicted risks. The simplified READMIT score performed comparably to the full model with clear separation of observed risks.
Conclusions:
We developed and externally validated the READMIT score, a pragmatic nine-factor prediction tool for stratifying 12-month asthma-related hospital readmission risk.