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Table of Contents

June 2026

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Young children are at high risk of severe outcomes due to pneumonia. The World Health Organization has established criteria to help guide their referral to hospital, but improved clinical decision tools are needed to ensure that children at risk are not missed. In this issue, Patrick Staunton and colleagues, using data from Malawi, report the development of a machine learning model that predicts hospitalization of young children within seven days of initial presentation with pneumonia in a primary care setting. The model outperformed existing risk prediction tools, suggesting that its clinical implementation may benefit early identification of children with severe respiratory disease.

Image Credit: cottonbro studio; pexels

Editorial

Improving suicide prevention in men

Seena Fazel

Policy Forum

The data transparency crisis in research: Lessons from systematic reviews and meta-analyses

Saul Martin-Rodriguez, Rodrigo Fernandez-Gonzalo, David Moher

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Prenatal exposure to asthma medications and risk of neurodevelopmental disorders and educational difficulties: A systematic review and meta-analysis

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Huangdong Li, Ziyu Zhu, Shaopeng Yang, Weijing Cheng, Shaoying Tan, Zhuoyao Xin, Lei Zhang, Zhuoting Zhu, Shida Chen, Wenyong Huang, Wei Wang

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