Predicting referral need for febrile children in low-resource community settings in South and Southeast Asia

Area of Science:

• Global Health
• Pediatric Infectious Diseases
• Clinical Decision Support

Background:

• Accurate referral of febrile children in resource-limited settings is challenging.
• Current World Health Organization (WHO) danger signs lack sufficient accuracy, leading to missed severe cases and over-referrals.

Purpose of the Study:

• To develop and validate clinical prediction models for improved referral decisions in children with acute febrile illness.
• To compare the performance of novel models against existing WHO criteria.

Main Methods:

• Developed and validated prediction models using data from 3,405 children (aged 1-59 months) across seven hospitals in five Asian countries.
• Utilized simple clinical parameters, pulse oximetry, and the biomarker soluble TREM1 (sTREM1).
• Externally validated models using Cambodian data.

Main Results:

• A model with simple clinical parameters showed higher sensitivity (74.7%) and specificity (99.1%) than WHO criteria (55.5% sensitivity, 82.6% specificity) for identifying severe disease risk.
• Incorporating pulse oximetry or sTREM1 significantly increased sensitivity to over 88%.
• The pulse oximetry model reduced referral rates threefold and demonstrated cost-effectiveness.

Conclusions:

• Clinical prediction models, especially those incorporating pulse oximetry, offer a more accurate and cost-effective approach to triage febrile children in low-resource settings.
• These models can significantly improve referral decisions, enhancing care for severe febrile illnesses.
• Further evaluation in community-based trials is warranted.