Assembling a global database of child pneumonia studies to inform WHO pneumonia management algorithm: Methodology and applications

Bin Nisar, Y (通讯作者),World Hlth Org, Dept Maternal Newborn Child & Adolescent Hlth & A, Geneva, Switzerland.
2022
Background The existing World Health Organiza-tion (WHO) pneumonia case management guide-lines rely on clinical symptoms and signs for identify-ing, classifying, and treating pneumonia in children up to 5 years old. We aimed to collate an individual patient-level data set from large, high-quality pre-ex-isting studies on pneumonia in children to identify a set of signs and symptoms with greater validity in the diagnosis, prognosis, and possible treatment of childhood pneumonia for the improvement of cur-rent pneumonia case management guidelines. Methods Using data from a published systematic review and expert knowledge, we identified stud-ies meeting our eligibility criteria and invited inves-tigators to share individual-level patient data. We collected data on demographic information, general medical history, and current illness episode, includ-ing history, clinical presentation, chest radiograph findings when available, treatment, and outcome. Data were gathered separately from hospital-based and community-based cases. We performed a narra-tive synthesis to describe the final data set. Results Forty-one separate data sets were includ-ed in the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) database, 26 of which were hospital-based and 15 were commu-nity-based. The PREPARE database includes 285 839 children with pneumonia (244 323 in the hospital and 41 516 in the community), with detailed de-scriptions of clinical presentation, clinical progres-sion, and outcome. Of 9185 pneumonia-related deaths, 6836 (74%) occurred in children <1 year of age and 1317 (14%) in children aged 1-2 years. Of the 285 839 episodes, 280 998 occurred in chil-dren 0-59 months old, of which 129 584 (46%) were 2-11 months of age and 152 730 (54%) were males. Conclusions This data set could identify an improved specific, sensitive set of criteria for diagnosing clin-ical pneumonia and help identify sick children in need of referral to a higher level of care or a change of therapy. Field studies could be designed based on insights from PREPARE analyses to validate a potential revised pneumonia algorithm. The PREPARE methodology can also act as a model for disease database assembly.
JOURNAL OF GLOBAL HEALTH
卷号:12
ISSN:2047-2978|收录类别:SCIE
语种
英语
来源机构
University of Edinburgh; Kwame Nkrumah University Science & Technology; Sharda University; National University of Sciences & Technology - Pakistan; Rawalpindi Medical College; King George's Medical University; University of Bergen; Tribhuvan University; Department of Biotechnology (DBT) India; Translational Health Science & Technology Institute (THSTI); Aga Khan University; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Indian Council of Medical Research (ICMR); ICMR - National Institute of Virology (NIV); The World Bank; University of London; University College London; South African Medical Research Council; University of Witwatersrand; National Research Foundation - South Africa; University of Witwatersrand; University of Basel; Swiss Tropical & Public Health Institute; Centro de Educacion Medica e Investigaciones Clinicas (CEMIC); Hospital de Ninos Doctor Ricardo Gutierrez; Pfizer; Centers for Disease Control & Prevention - USA; Pakistan Institute of Medical Sciences; Boston University; Baylor College of Medicine; University of Kwazulu Natal; Universitas Padjadjaran; Karolinska Institutet; All India Institute of Medical Sciences (AIIMS) New Delhi; State University System of Florida; Florida International University; Research Institute for Tropical Medicine - Philippines; University of Witwatersrand; Post Graduate Institute of Medical Education & Research (PGIMER), Chandigarh; Johns Hopkins University; Johns Hopkins Medicine; Harvard University; Boston Children's Hospital; Harvard Medical School; Mongolian Academy of Sciences; Queensland University of Technology (QUT); Datta Meghe Institute of Medical Sciences - Deemed to be University; National Institutes of Health (NIH) - USA; Research Institute for Health Sciences (IICS); Universidad Nacional de Asuncion; Johns Hopkins University; Aga Khan University; Innlandet Hospital Trust; Ministry of Public Health - Thailand; Mahidol University; CHU Lyon; Ecole Normale Superieure de Lyon (ENS de LYON); UDICE-French Research Universities; Universite Claude Bernard Lyon 1; Chinese Academy of Medical Sciences - Peking Union Medical College; Peking Union Medical College; Chinese Academy of Medical Sciences - Peking Union Medical College; Peking Union Medical College; Liverpool School of Tropical Medicine; World Health Organization
资助机构
Bill & Melinda Gates Foundation(Bill & Melinda Gates FoundationCGIAR)
资助信息
This study was funded by the Bill & Melinda Gates Foundation (#INV-007927) through a grant to the World Health Organization. The funders had no role in the study design or in the collection, analysis, or interpretation of the data. The funders did not write the report and had no role in the decision to submit the paper for publication.
被引频次(WOS)
0
被引频次(其他)
0
180天使用计数
0
2013以来使用计数
0
EISSN
2047-2986
出版年
2022
DOI
10.7189/jogh.12.04075
WOS学科分类
Public, Environmental & Occupational Health
学科领域
循证公共卫生