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Common data elements for predictors of pediatric sepsis: A framework to standardize data collection

BACKGROUND: Standardized collection of predictors of pediatric sepsis has enormous potential to increase data compatibility across research studies. The Pediatric Sepsis Predictor Standardization Working Group collaborated to define common data elements for pediatric sepsis predictors at the point o...

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Autores principales: Mawji, Alishah, Li, Edmond, Chandna, Arjun, Kortz, Teresa, Akech, Samuel, Wiens, Matthew O., Kissoon, Niranjan, Ansermino, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192005/
https://www.ncbi.nlm.nih.gov/pubmed/34111209
http://dx.doi.org/10.1371/journal.pone.0253051
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author Mawji, Alishah
Li, Edmond
Chandna, Arjun
Kortz, Teresa
Akech, Samuel
Wiens, Matthew O.
Kissoon, Niranjan
Ansermino, Mark
author_facet Mawji, Alishah
Li, Edmond
Chandna, Arjun
Kortz, Teresa
Akech, Samuel
Wiens, Matthew O.
Kissoon, Niranjan
Ansermino, Mark
author_sort Mawji, Alishah
collection PubMed
description BACKGROUND: Standardized collection of predictors of pediatric sepsis has enormous potential to increase data compatibility across research studies. The Pediatric Sepsis Predictor Standardization Working Group collaborated to define common data elements for pediatric sepsis predictors at the point of triage to serve as a standardized framework for data collection in resource-limited settings. METHODS: A preliminary list of pediatric sepsis predictor variables was compiled through a systematic literature review and examination of global guideline documents. A 5-round modified Delphi that involved independent voting and active group discussions was conducted to select, standardize, and prioritize predictors. Considerations included the perceived predictive value of the candidate predictor at the point of triage, intra- and inter-rater measurement reliability, and the amount of time and material resources required to reliably collect the predictor in resource-limited settings. RESULTS: We generated 116 common data elements for implementation in future studies. Each common data element includes a standardized prompt, suggested response values, and prioritization as tier 1 (essential), tier 2 (important), or tier 3 (exploratory). Branching logic was added to the predictors list to facilitate the design of efficient data collection methods, such as low-cost electronic case report forms on a mobile application. The set of common data elements are freely available on the Pediatric Sepsis CoLab Dataverse and a web-based feedback survey is available through the Pediatric Sepsis CoLab. Updated iterations will continuously be released based on feedback from the pediatric sepsis research community and emergence of new information. CONCLUSION: Routine use of the common data elements in future studies can allow data sharing between studies and contribute to development of powerful risk prediction algorithms. These algorithms may then be used to support clinical decision making at triage in resource-limited settings. Continued collaboration, engagement, and feedback from the pediatric sepsis research community will be important to ensure the common data elements remain applicable across a broad range of geographical and sociocultural settings.
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spelling pubmed-81920052021-06-10 Common data elements for predictors of pediatric sepsis: A framework to standardize data collection Mawji, Alishah Li, Edmond Chandna, Arjun Kortz, Teresa Akech, Samuel Wiens, Matthew O. Kissoon, Niranjan Ansermino, Mark PLoS One Research Article BACKGROUND: Standardized collection of predictors of pediatric sepsis has enormous potential to increase data compatibility across research studies. The Pediatric Sepsis Predictor Standardization Working Group collaborated to define common data elements for pediatric sepsis predictors at the point of triage to serve as a standardized framework for data collection in resource-limited settings. METHODS: A preliminary list of pediatric sepsis predictor variables was compiled through a systematic literature review and examination of global guideline documents. A 5-round modified Delphi that involved independent voting and active group discussions was conducted to select, standardize, and prioritize predictors. Considerations included the perceived predictive value of the candidate predictor at the point of triage, intra- and inter-rater measurement reliability, and the amount of time and material resources required to reliably collect the predictor in resource-limited settings. RESULTS: We generated 116 common data elements for implementation in future studies. Each common data element includes a standardized prompt, suggested response values, and prioritization as tier 1 (essential), tier 2 (important), or tier 3 (exploratory). Branching logic was added to the predictors list to facilitate the design of efficient data collection methods, such as low-cost electronic case report forms on a mobile application. The set of common data elements are freely available on the Pediatric Sepsis CoLab Dataverse and a web-based feedback survey is available through the Pediatric Sepsis CoLab. Updated iterations will continuously be released based on feedback from the pediatric sepsis research community and emergence of new information. CONCLUSION: Routine use of the common data elements in future studies can allow data sharing between studies and contribute to development of powerful risk prediction algorithms. These algorithms may then be used to support clinical decision making at triage in resource-limited settings. Continued collaboration, engagement, and feedback from the pediatric sepsis research community will be important to ensure the common data elements remain applicable across a broad range of geographical and sociocultural settings. Public Library of Science 2021-06-10 /pmc/articles/PMC8192005/ /pubmed/34111209 http://dx.doi.org/10.1371/journal.pone.0253051 Text en © 2021 Mawji et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mawji, Alishah
Li, Edmond
Chandna, Arjun
Kortz, Teresa
Akech, Samuel
Wiens, Matthew O.
Kissoon, Niranjan
Ansermino, Mark
Common data elements for predictors of pediatric sepsis: A framework to standardize data collection
title Common data elements for predictors of pediatric sepsis: A framework to standardize data collection
title_full Common data elements for predictors of pediatric sepsis: A framework to standardize data collection
title_fullStr Common data elements for predictors of pediatric sepsis: A framework to standardize data collection
title_full_unstemmed Common data elements for predictors of pediatric sepsis: A framework to standardize data collection
title_short Common data elements for predictors of pediatric sepsis: A framework to standardize data collection
title_sort common data elements for predictors of pediatric sepsis: a framework to standardize data collection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192005/
https://www.ncbi.nlm.nih.gov/pubmed/34111209
http://dx.doi.org/10.1371/journal.pone.0253051
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