Severe infection among young infants in Dhaka, Bangladesh: effect of case definition on incidence estimates

ABSTRACT Introduction Heterogeneity in definitions of severe infection, sepsis and serious bacterial infection (SBI) in young infants limits the comparability of randomized controlled trials (RCTs) of infection prevention interventions. To inform the design of severe infection prevention RCTs for young infants in low-resource settings, we estimated the incidence of severe infection in an observational cohort of Bangladeshi infants aged 0-60 days and examined the effect of variations in case definitions on incidence estimates. Methods In 2020-2022, 1939 infants born generally healthy were enrolled at two hospitals in Dhaka, Bangladesh. Severe infection cases were identified through up to 12 scheduled community health worker home visits from 0-60 days of age or through caregiver self-referral. The primary severe infection case definition combined physician documentation of standardized clinical signs and/or diagnosis of sepsis/SBI, plus either a positive blood culture or parenteral antibiotic treatment for ≥5 days. Incidence rates were estimated for the primary severe infection definition, the World Health Organization (WHO) definition of possible SBI, blood culture-confirmed infection, and five alternative severe infection definitions. Results Severe infection incidence per 1000 infant-days was 1.2 (95% CI 0.97-1.4) using the primary definition, 0.84 (0.69-1.0) using the WHO definition of possible SBI, and 0.026 (0.0085-0.081) using blood culture-confirmed infection. One-third of cases met criteria for the primary severe infection definition through physician diagnosis of sepsis/SBI rather than the standardized clinical signs, and 85% of cases were identified following caregiver self-referral despite frequent scheduled study visits. Conclusions Severe infection incidence in young infants varied considerably by case definition. A severe infection definition that requires physician documentation of standardized clinical signs may miss a substantial proportion of cases identified by physician diagnosis of sepsis/SBI. In settings where health facilities are accessible, frequently scheduled home assessments by study personnel to identify severe infection in infants may not be necessary. What is already known on this topic Researchers aiming to design a randomized controlled trial (RCT) for severe infection prevention or treatment in young infants require a clinically precise and feasible case definition of severe infection. A previous systematic review of neonatal sepsis definitions used in RCTs identified a diverse range, including culture-confirmed sepsis, a combination of clinical signs and culture-confirmation, and a combination of clinical signs and laboratory investigation results. Incidence estimates of various severe infection case definitions that can be operationalized in low- and middle-income countries (LMICs) are needed to determine the feasibility of using these definitions in severe infection prevention and treatment RCTs for young infants in these settings. What this study adds We provide incidence estimates of severe infection in young infants born generally healthy in Dhaka, Bangladesh, during the first 60 days of age using case definitions based on different combinations of clinical signs, antibiotic treatment and microbiologic criteria. We demonstrate that the incidence estimates of severe infection in young infants vary considerably depending on whether a permissive or stringent case definition is adopted. We also demonstrate that in this study, most severe infection cases were identified following caregiver self-referral rather than during scheduled home assessments by study personnel. How this study might affect research, practice or policy Our findings may inform the design of future severe infection prevention RCTs in young infants in LMICs by 1) providing incidence estimates of various candidate case definitions, and 2) supporting the planning of optimal outcome surveillance systems that balance the identification of severe infection cases with operational costs.

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