Prevalence of and characteristics associated with in-hospital mortality in a Ugandan neurology ward

Monica M Diaz, Xin Hu, Brenda T Fenton, Ivan Kimuli, Allison Lee, Hayley Lindsey, Jeffrey K Bigelow, Samuel Maiser, Hamada H Altalib, Jason J Sico, Monica M Diaz, Xin Hu, Brenda T Fenton, Ivan Kimuli, Allison Lee, Hayley Lindsey, Jeffrey K Bigelow, Samuel Maiser, Hamada H Altalib, Jason J Sico

Abstract

Background: While the burden of neurologic illness in developing countries is increasing, less is known about mortality among patients admitted to sub-Saharan African hospitals with neurologic disease. We sought to characterize the rate and patient-level predictors of in-hospital mortality in a Ugandan Neurology ward.cc.

Methods: Data was prospectively collected on 335 patients admitted to the Neurology ward of Mulago Hospital, Kampala, Uganda. Kaplan-Meier survival curves and multivariate COX proportional hazard modeling were used to assess survival.

Results: Within our sample (n = 307), 35.8% received no diagnosis at time of hospital admission. Stroke (27.3%), head trauma (19.6%), and malaria (16.0%) were the most common diagnoses. Among the 56 (18.5%) patients who died during the index hospitalization, the most common diagnosis at admission and at death was stroke. Adjusted regression analysis showed that patients without a diagnosis at time of death (HR = 7.01 [2.42-20.35], p < .001) and those with diagnoses of infections (HR = 5.21 [2.16-12.58], p = <.001), stroke (HR = 2.69 [1.20-6.04], p = .017), or head trauma (HR = 3.39, [1.27-9.07], p = 0.15) had worse survival.

Conclusions: In-hospital mortality affected nearly 20% of the cohort, with worse survival among those without a diagnosis and with infections, stroke, head trauma. Future work should identify reasons for increased mortality among these high-risk groups and implement targeted interventions.

Keywords: Global neurology; Head trauma; Neurological illness; Neurological infections; Stroke; Uganda.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Kaplan Meier Survival Curves. A. Kaplan Meier Survival Curves by age group (N = 302). B. Kaplan Meier Survival Curves by occupation (N = 223)a. C. Kaplan Meier Survival Curves by discharge diagnosis of stroke (N = 196)a. D. Kaplan Meier Survival Curves by discharge diagnosis of infectious disease (N = 196)a. (B,C,D) legend: a Missing groups and patients missing follow-up time were not counted in Kaplan Meier analysis

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