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Selecting candidate predictor variables for the modelling of post-discharge mortality from sepsis: a protocol
Matthew O Wiens1, Niranjan Kissoon2, Elias Kumbakumba3
1School of Population and Public Health, University of British Columbia, Vancouver, Canada.
African Health Sciences
|July 1, 2016
Summary
Identifying high-risk children after hospital discharge is crucial in resource-limited settings. This study identified key variables for predicting pediatric post-discharge mortality, aiding in targeted interventions.
Area of Science:
- Pediatric Health
- Global Health
- Epidemiology
Background:
- Post-discharge mortality significantly contributes to child mortality in resource-limited countries.
- Identifying at-risk children post-discharge is essential for intervention.
Purpose of the Study:
- To determine variables associated with post-discharge mortality.
- To inform a prediction modeling study for pediatric post-discharge mortality.
Main Methods:
- A two-round modified Delphi process involving experts was used.
- Variables were evaluated based on prediction relevance, availability, cost, and measurement time.
- A systematic approach was employed to select candidate predictor variables.
Main Results:
- 23 experts evaluated 17 initial variables in the first round.
- An additional 40 variables were suggested and reviewed in the second round.
- Thirty unique variables were compiled for the prediction modeling study.
Conclusions:
- A systematic Delphi process successfully generated an optimal list of predictor variables.
- This list is intended for a study predicting pediatric post-discharge mortality in resource-poor settings.
