DEVELOPMENT AND INTERNAL EVALUATION OF MODELS FOR PREDICTING PROLONGED HOSPITALISATION AMONG PATIENTS WITH SICKLE CELL DISEASE IN A PUBLIC UNIVERSITY HOSPITAL IN GHANA

Background: Prolonged hospitalisation is an important burden among patients with sickle cell disease (SCD), with implications for healthcare utilisation and patient and caregiver burden. Early prediction may support timely clinical and resource-management interventions. Objective: To identify factors associated with prolonged hospitalisation among patients with SCD and compare the predictive performance of multivariable logistic regression with five supervised machine-learning algorithms. Methods: This retrospective study included SCD inpatients aged [≥]16 years admitted to the University o

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