Comprehensive Diagnostic Testing Identifies Diverse Aetiologies of Acute Febrile Illness Among Hospitalised Children and Adults in Sri Lanka: a Prospective Cohort Study

Abstract

Introduction Acute febrile illness (AFI) is a common cause of hospital admissions in tropical settings. Identifying AFI aetiology is essential for guiding clinicians’ diagnoses and developing diagnostic and management guidelines. We used rigorous, gold-standard testing for diverse viral and bacterial pathogens to confirm the aetiology of AFI in southern Sri Lanka. Methods We prospectively enrolled children and adults with AFI admitted to Teaching Hospital Karapitiya, Galle, the largest tertiary care hospital in Southern Province, Sri Lanka from June 2012 to May 2013. We obtained sociodemographic and clinical data, an acute blood sample, a nasopharyngeal sample, and a urine sample at enrolment and a convalescent blood sample 2–4 weeks later. Laboratory testing was conducted for dengue, respiratory viruses, leptospirosis, scrub typhus, spotted fever group (SFG) and typhus group (TG) rickettsioses and Q fever. Results A total of 976 patients were enrolled and a convalescent visit was completed in 878 (90.0%). Median age was 26.9 (14.2–41.4) years and the majority were male (628, 64.3%). A viral or bacterial aetiology was identified in 660 (67.6%). A viral aetiology was identified in 534 (54.7%), including 388 (39.8%) with dengue and 171 (17.5%) with respiratory viruses. Bacterial infection was found in 138 (14.1%) and included leptospirosis (79, 8.1%), SFG (17, 1.7%), TG (7, 0.7%), scrub typhus (53, 5.4%) and Q fever (5, 0.5%). Antibiotics were prescribed at enrolment for 45.5% with viral infections and 62.3% with bacterial infection. Overall, sensitivity of clinical diagnosis was low at approximately 50%. Conclusion We identified an aetiology of AFI in two-thirds of patients in a setting where malaria is non-endemic. Sensitivity of clinical diagnosis was low, with overuse of antibiotics for viral infections and underuse of antibiotics for bacterial infections. Diagnostic algorithms for AFI may help improve clinical management in this and comparable settings with diverse AFI aetiologies.