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This study aims to assess in-hospital mortality and its predictors among people with diabetes in Lubumbashi.

April 18, 2026International Journal of General Medicine1 citationsOpen Access

In-Hospital Mortality and Predictors Among People with Diabetes in Lubumbashi, Democratic Republic of the Congo: A Prospective Observational Study

BKBerthe KamaloUniversity of Lubumbashi JMJacques MusungUniversity of Lubumbashi GYGeorges YumbaUniversity of Lubumbashi

Key Points

This study aims to assess in-hospital mortality and its predictors among people with diabetes in Lubumbashi.
Conducted a prospective observational cohort study over 20 months in three hospitals.
Enrolled 324 adults with confirmed diabetes, followed from admission until discharge or death.
Collected sociodemographic, clinical, laboratory, and treatment data
Performed Kaplan–Meier analysis for survival estimation and Cox regression for mortality predictors.
In-hospital mortality rate was 12.7%, with 41 deaths among 324 patients.
Mean time to death for deceased patients was 4.9 days.
Independent mortality predictors included older age, stroke, hyperosmolar hyperglycemic state, meningoencephalitis, chronic kidney disease, and sepsis.

Abstract

Background: Diabetes mellitus (DM) is a growing public health challenge in sub-Saharan Africa, where limited diagnostic capacity and delayed care contribute to high morbidity and mortality. However, data on in-hospital mortality determinants among people with diabetes in the Democratic Republic of the Congo (DRC) are scarce. This study assessed in-hospital mortality and predictors among people with diabetes admitted to tertiary hospitals in Lubumbashi. Methods: A prospective observational cohort study was conducted over 20 months (January 2022–August 2023) in three hospitals in Lubumbashi. A total of 324 adults (≥ 18 years) with confirmed DM were enrolled and prospectively followed from hospital admission until discharge or death. Sociodemographic, clinical, laboratory, and treatment-related data were collected using standardised forms. The primary outcome was in-hospital mortality within 60 days of admission. Kaplan–Meier analysis was performed to estimate 60-day survival, and the Log rank test was used to compare survival distributions. Cox proportional hazards regression identified independent predictors of mortality, with adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs) reported. Results: Of the 324 hospitalised people with diabetes, 41 deaths occurred, yielding an in-hospital mortality rate of 12.7%. The deceased patients had a mean time to death of 4.9± 4.1 days. The overall restricted mean survival time for the cohort was 53.0± 1.0 days. Several factors were independently associated with increased mortality: older age (aHR=1.05; 95% CI: 1.03– 1.09; p< 0.001), stroke (aHR=4.53; 95% CI: 1.64– 12.55; p=0.004), hyperosmolar hyperglycemic state (aHR=3.15; 95% CI: 1.16– 8.60; p=0.025), meningoencephalitis (aHR=5.84; 95% CI: 1.60– 21.24; p=0.007), chronic kidney disease (aHR=5.20; 95% CI: 1.43– 18.89; p=0.012), and sepsis (aHR=5.85; 95% CI: 2.57– 13.34; p< 0.001). Conclusion: In-hospital mortality among people with diabetes in Lubumbashi is substantial and comparable to rates reported in other African settings. Mortality is strongly associated with advanced age, acute neurological events, severe metabolic derangements, infectious complications, and chronic kidney disease. Keywords: diabetes mellitus, in-hospital mortality, predictors, Cox regression, complications, Lubumbashi, Democratic Republic of the Congo

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