Background Acute undifferentiated febrile illness (AUFI) presents major diagnostic and therapeutic challenges in tropical regions, particularly in resource-limited settings. We prospectively evaluated the etiology, clinical characteristics, diagnostic predictors, and outcomes of AUFI among adult patients admitted to a tertiary care center in Central India. Methodology We conducted a prospective observational study of consecutive adult patients hospitalized with AUFI between May 2024 and September 2025. All patients underwent standardized clinical evaluation and routine laboratory testing, including leukocyte counts, platelet counts, liver enzymes (alanine aminotransferase, aspartate aminotransferase), and C-reactive protein (CRP). Targeted diagnostic assays were performed for dengue, malaria, leptospirosis, enteric fever, and scrub typhus. Univariate analyses were used to identify clinical and laboratory predictors of specific etiologies, and effect measures were reported where applicable. Results Of the 262 AUFI cases, an etiologic diagnosis was not established in 112 (42.7%) cases. Among diagnosed cases, scrub typhus, dengue, enteric fever, leptospirosis, and malaria were the leading causes. Cases clustered among rural residents (181, 69.1%) and during the monsoon season (188, 71.8% between August and October). Elevated CRP (>50 mg/L) was significantly more frequent in bacterial and rickettsial infections than in viral illness (malaria, 5 (100%); leptospirosis, 14 (77.8%); scrub typhus, 32 (62.7%) vs. dengue, 8 (16.7%). Hepatosplenomegaly was strongly associated with malaria (3 (60%); odds ratio (OR) = 10.1) and was more common in enteric fever (6 (31.6%); OR = 3.29). Conclusions In this cohort of hospitalized adults with AUFI, a substantial proportion remained undiagnosed, contributing disproportionately to mortality. Certain clinical signs (such as eschar and hepatosplenomegaly) and routine laboratory markers (particularly CRP) provided valuable discriminatory power, helping to distinguish bacterial and rickettsial infections from viral causes. These findings support the integration of pragmatic clinical and biomarker-based algorithms into empiric management strategies, especially in resource-constrained tropical settings.
Rathod et al. (Sun,) studied this question.