Retrospective study reveals diverse clinical profiles in hospitalized malaria cases, indicating high severe malaria rates.
Background/Objectives: Malaria remains a major cause of hospitalization in rural Madagascar, yet data on in-hospital clinical presentation, management, and patient outcomes remain limited. Methods: We conducted a three-year retrospective study (2023–2025) at a rural district hospital in Ambatoboeny, Madagascar, including patients of all ages hospitalized with malaria confirmed by rapid diagnostic testing and microscopy. Sociodemographic, clinical, laboratory, and treatment data were extracted from routine records. Length of hospital stay (LOS) was analyzed continuously and categorized as ≤2, 3–4, or ≥5 days. Seasonal admission patterns and factors associated with LOS were assessed using chi-square or Fisher’s exact tests, and associations with rainfall seasonality were explored using Spearman’s correlation. Results: Among 134 hospitalized patients, median age was 15 years (interquartile range (IQR) 7–25) and 52.2% were female. Plasmodium falciparum predominated (94.0%), while mixed-species infections were identified in 6.0% of cases; 20.1% of cases were classified as severe malaria, including 10.4% with cerebral malaria. Co-infections were frequent (52.2%), most commonly Schistosoma haematobium infection (14.2%) and typhoid fever (12.7%). Intravenous artesunate was initiated in 97.8% of patients; all received paracetamol and 94.8% received intravenous fluids. Median LOS was 2 days (IQR 2–3); 12.7% had prolonged hospitalization (≥5 days). Prolonged LOS was significantly associated with cerebral malaria, high parasitemia (≥5%), blood transfusion, and age < 15 years (all p ≤ 0.034), while co-infection and nutritional status were not. Conclusions: Hospitalized malaria in rural Madagascar presents with heterogeneous clinical phenotypes and a high burden of co-infections. Prolonged LOS is primarily driven by markers of severe disease and supportive care requirements, underscoring the need for early severity recognition and resource planning in low-resource hospitals.
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