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Prevalence of malnutrition and associated risk factors among patients admitted to the intensive care unit of a tertiary university teaching hospital in Kigali, Rwanda: A cross-sectional study


Eugene Tuyishime
Irénée Niyongombwa
Irénée David Karenzi
Jean d’Arc Bisimwa
Jean Bonaventure Uwineza
Faustin Ntirenganya
Egide Abahuje
Jennifer Rickard

Abstract

Background: Malnutrition in critically ill patients is associated with increased risk of infections, prolonged hospitalization, and mortality. This study aimed to determine the prevalence of malnutrition, risk factors for malnutrition, and the association between malnutrition and outcomes among patients admitted to the intensive care unit (ICU) at the University Teaching Hospital of Kigali.


Methods: This was a cross-sectional study of ICU patients at a Rwandan referral hospital. Clinical and demographic features were collected for all patients. Malnutrition was assessed using ASPEN (American Society for Parenteral and Enteral Nutrition) guidelines. Risk factors for malnutrition were determined using multivariate logistic regression with cluster analysis by diagnosis.


Results: Over the study period, we enrolled 147 patients. Malnutrition was identified in 32 patients (22%) upon ICU admission. Multivariate analysis revealed the following factors as associated with malnutrition: trauma (adjusted odds ratio [aOR], 8.48; 95% confidence interval [CI], 2.30-31.21; P=0.001), obstetric or gynaecologic diagnosis (aOR, 7.96; 95% CI, 1.72-36.94; P=0.008), acute abdomen (aOR, 7.85; 95% CI, 1.76; 35.08; P=0.007), other diagnoses (aOR, 12.74; 95% CI, 3.99-40.62; P<0.001), age >65 years (aOR, 3.18; 95% CI, 2.39-4.23; P<0.001), and female gender (aOR, 2.62; 95% CI, 1.09-6.34; P=0.032). The presence of malnutrition at the time of ICU admission was not associated with increased odds of mortality or ICU length of stay.


Conclusions: Malnutrition is common among patients admitted to the ICU at the University Teaching Hospital of Kigali. Underlying diagnoses and patient demographics can identify patients at high risk of malnutrition who should be targeted for early and aggressive nutritional support.


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eISSN: 2073-9990