Methodological rigor of prognostic models for predicting in-hospital paediatric mortality in low- and middle-income countries: a systematic review protocol
Wellcome Open Res
Introduction: In low- and middle-income countries (LMICs) where healthcare resources are often limited, making decisions on appropriate treatment choices is critical in ensuring reduction of paediatric deaths as well as instilling proper utilisation of the already constrained healthcare resources. Well-developed and validated prognostic models can aid in early recognition of potential risks thus contributing to the reduction of mortality rates. The aim of the planned systematic review is to identify and appraise the methodological rigor of multivariable prognostic models predicting in-hospital paediatric mortality in LMIC in order to identify statistical and methodological shortcomings deserving special attention and to identify models for external validation. Methods and analysis: This protocol has followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols. A search of articles will be conducted in MEDLINE, Google Scholar, and CINAHL (via EbscoHost) from inception to 2019 without any language restriction. We will also perform a search in Web of Science to identify additional reports that cite the identified studies. Data will be extracted from relevant articles in accordance with the Cochrane Prognosis Methods’ guidance; the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies. Methodological quality assessment will be performed based on prespecified domains of the Prediction study Risk of Bias Assessment Tool. Ethics and dissemination: Ethical permission will not be required as this study will use published data. Findings from this review will be shared through publication in peer-reviewed scientific journals and, presented at conferences. It is our hope that this study will contribute to the development of robust multivariable prognostic models predicting in-hospital paediatric mortality in low- and middle-income countries. Registration: PROSPERO ID CRD42018088599; registered on 13 February 2018.
Ogero, M., Sarguta, R., Malla, L., Aluvaala, J., Agweyu, A., Akech, S.
Pages:106, Volume:5, Edition:7/30/2020, Date,
Notes:Ogero, Morris|Sarguta, Rachel|Malla, Lucas|Aluvaala, Jalemba|Agweyu, Ambrose|Akech, Samuel|eng|MR/R006083/1/MRC_/Medical Research Council/United Kingdom|England|2020/07/30 06:00|Wellcome Open Res. 2020 May 27;5:106. doi: 10.12688/wellcomeopenres.15955.1. eCollection 2020.
ISBN: 2398-502X (Print)|2398-502X (Linking) Permanent ID: PMC7364185 Accession Number: 32724864
Author Address: Health Service Unit, KEMRI / Wellcome Trust Research Programme, Nairobi, P.O Box 43640-00100, Kenya.|School of Mathematics, University of Nairobi, Nairobi, P. O. Box 30197 – 00100, Kenya.