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


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2021
Historique:
received: 25 11 2020
accepted: 27 05 2021
entrez: 10 6 2021
pubmed: 11 6 2021
medline: 12 11 2021
Statut: epublish

Résumé

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. 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. 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 34111209
doi: 10.1371/journal.pone.0253051
pii: PONE-D-20-35664
pmc: PMC8192005
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0253051

Subventions

Organisme : NIAID NIH HHS
ID : K23 AI144029
Pays : United States
Organisme : Wellcome Trust
Pays : United Kingdom

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Références

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Auteurs

Alishah Mawji (A)

Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada.
Centre for International Child Health, BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada.

Edmond Li (E)

School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada.

Arjun Chandna (A)

Cambodia Oxford Medical Research Unit, Angkor Hospital for Children, Siem Reap, Cambodia.
Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom.

Teresa Kortz (T)

Department of Pediatrics, Institute of Global Health Sciences, University of California, San Francisco, California, United States of America.

Samuel Akech (S)

Kenya Medical Research Institute/Wellcome Trust Research Programme, Nairobi, Kenya.

Matthew O Wiens (MO)

Centre for International Child Health, BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada.

Niranjan Kissoon (N)

Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.

Mark Ansermino (M)

Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada.
Centre for International Child Health, BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada.

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