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article · Endocrinology Diabetes & Metabolism

Clinical Predictors of Time to Hospital Discharge in Children With New‐Onset Diabetic Ketoacidosis in Zambia: A Retrospective Cohort Study

Abstract

ABSTRACT Background and Aims Diabetic ketoacidosis (DKA) at type 1 diabetes diagnosis is common in low‐resource settings and associated with prolonged hospitalisation. We aimed to identify determinants of time to discharge among children with new‐onset DKA in Zambia. Methods We conducted a retrospective cohort study of children aged 0–16 years with newly diagnosed T1DM and DKA at the University Teaching Hospital, Lusaka (2018–2023). The primary outcome was time to discharge (days). We used Kaplan–Meier with log‐rank tests and Cox regression. To address proportional hazards (PH) violation, we fitted a stratified Cox model (stratified by HbA1c, vomiting and DKA severity) for PH validation and a granulated Cox model with DKA severity (mild, moderate, severe) to estimate independent effects. PH was verified using Schoenfeld residuals. Results Among 353 children (mean age 8.3 years, SD 4.6), median stay was 5 days (IQR 4–8). Log‐rank tests showed significant differences in discharge probability by DKA severity (χ 2 = 70.32, p < 0.001) and vomiting (χ 2 = 30.35, p < 0.001). In the granulated model, DKA severity was the strongest predictor of delayed discharge (moderate: HR = 0.01, p < 0.001; severe: HR = 0.01, p < 0.001), while infection was associated with faster discharge (HR = 1.51, p < 0.001). Ketonuria lost significance after DKA adjustment (HR = 0.90, p = 0.770), indicating a marker not an independent predictor. The stratified model confirmed PH satisfaction (global test χ 2 = 5.62, df = 7, p = 0.584). Age, sex, polyuria, family history and residence were not significant. Conclusions DKA severity is the strongest independent predictor of prolonged hospital stay in children with new‐onset DKA. Ketonuria is a useful bedside marker but lacks independent effect beyond severity. Infection independently predicts faster discharge. These findings could inform risk stratification and resource allocation in similar settings.

Research topics

  • Diabetes and associated disorders
  • Diabetes Management and Research
  • Pancreatic function and diabetes

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DOI: 10.1002/edm2.70308

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