Prognosis of Clinical Pneumonia in Undernourished Children in Rural Gambia

Background: Undernutrition significantly increases the risk of severe infections and mortality in children under five, particularly in low- and middle-income countries. Pneumonia, a leading cause of childhood death, is especially dangerous in undernourished children, yet predictive tools to identify those at highest risk are lacking. Objective: To assess the prognosis of clinical pneumonia in undernourished children in rural Gambia and to develop simple, implementable prognostic algorithms for early identification of children at risk for poor outcomes. Methods: This study analyzed a subset of children enrolled in a larger prospective cohort designed to identify biomarkers of bacterial pneumonia. Children aged 2–59 months with clinical pneumonia were recruited from two rural Gambian hospitals. Clinical and anthropometric data were collected at baseline, during hospitalization, and at 30-day follow-up. Undernutrition was defined using WHO weight-for-height and height-for-age z-scores. Prognostic outcomes included death, prolonged hospital stay (≥7 days), post-discharge care-seeking, and clinical decline. Logistic regression and classification tree models were used to identify predictors of poor prognosis. Results: Among the children analyzed, 91% were undernourished, and 45% had moderate to severe wasting or stunting. Moderate-severe undernutrition was associated with a threefold increased risk of poor prognosis (adjusted OR 2.59; 95% CI: 1.54–4.35), with wasting showing a stronger association with mortality than stunting (OR 10.6 vs. 3.0). Three predictive algorithms were developed using combinations of anthropometric, clinical, and laboratory parameters, with sensitivities ranging from 84% to 90%. Conclusion: Moderate to severe undernutrition, particularly wasting, is a strong predictor of poor outcomes in children with pneumonia. Simple clinical algorithms incorporating age, nutritional status, and key clinical signs can help prioritize care in resource-limited settings. Further validation is warranted to enable their broader implementation.