search
for
 About Bioline  All Journals  Testimonials  Membership  News


African Health Sciences
Makerere University Medical School
ISSN: 1680-6905
EISSN: 1680-6905
Vol. 16, No. 1, 2016, pp. 162-169
Bioline Code: hs16023
Full paper language: English
Document type: Research Article
Document available free of charge

African Health Sciences, Vol. 16, No. 1, 2016, pp. 162-169

 en Selecting candidate predictor variables for the modelling of post-discharge mortality from sepsis: a protocol development project.
Wiens, Matthew O.; Kissoon, Niranjan; Kumbakumba, Elias; Singer, Joel; Moschovis, Peter P.; Ansermino, J. Mark; Ndamira, Andrew; Kiwanuka, Julius & Larson, Charles P.

Abstract


Background: Post-discharge mortality is a frequent but poorly recognized contributor to child mortality in resource limited countries. The identification of children at high risk for post-discharge mortality is a critically important first step in addressing this problem.
Objectives: The objective of this project was to determine the variables most likely to be associated with post-discharge mortality which are to be included in a prediction modelling study.
Methods: A two-round modified Delphi process was completed for the review of a priori selected variables and selection of new variables. Variables were evaluated on relevance according to (1) prediction (2) availability (3) cost and (4) time required for measurement. Participants included experts in a variety of relevant fields.
Results: During the first round of the modified Delphi process, 23 experts evaluated 17 variables. Forty further variables were suggested and were reviewed during the second round by 12 experts. During the second round 16 additional variables were evaluated. Thirty unique variables were compiled for use in the prediction modelling study.
Conclusion: A systematic approach was utilized to generate an optimal list of candidate predictor variables for the incorporation into a study on prediction of pediatric post-discharge mortality in a resource poor setting.

Keywords
Candidate predictor variables; pediatrics, prediction; post-discharge mortality; sepsis

 
© Copyright 2016 - African Health Sciences

Home Faq Resources Email Bioline
© Bioline International, 1989 - 2024, Site last up-dated on 01-Sep-2022.
Site created and maintained by the Reference Center on Environmental Information, CRIA, Brazil
System hosted by the Google Cloud Platform, GCP, Brazil