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Predictor variables for post-discharge mortality modelling in infants: a protocol development project

Brooklyn R Nemetchek, Li(Danny) Liang, Niranjan Kissoon, Mark J Ansermino, Jerome Kabakyenga, Pascal M Lavoie, Susan Fowler-Kerry, Matthew O Wiens

Abstract


Background: Over two-thirds of the five million annual deaths in children under five occur in infants, mostly in developing countries and many after hospital discharge. However, there is a lack of understanding of which children are at higher risk based on early clinical predictors. Early identification of vulnerable infants at high-risk for death post-discharge is important in order to craft interventional programs.
Objectives: To determine potential predictor variables for post-discharge mortality in infants less than one year of age who are likely to die after discharge from health facilities in the developing world.
Methods: A two-round modified Delphi process was conducted, wherein a panel of experts evaluated variables selected from a systematic literature review. Variables were evaluated based on (1) predictive value, (2) measurement reliability, (3) availability, and (4) applicability in low-resource settings.
Results: In the first round, 18 experts evaluated 37 candidate variables and suggested 26 additional variables. Twenty-seven variables derived from those suggested in the first round were evaluated by 17 experts during the second round. A final total of 55 candidate variables were retained.
Conclusion: A systematic approach yielded 55 candidate predictor variables to use in devising predictive models for post-discharge mortality in infants in a low-resource setting.

Keywords: Candidate predictor variables, pediatrics, neonatal, infants, prediction, post-discharge mortality, sepsis.




AJOL African Journals Online