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. 2018 Dec;18(4):1214-1225.
doi: 10.4314/ahs.v18i4.43.

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

Brooklyn R Nemetchek  1 , Li Danny Liang  2 , Niranjan Kissoon  3   4   5 , J Mark Ansermino  4   6   5 , Jerome Kabakyenga  7   8 , Pascal M Lavoie  3   4 , Susan Fowler-Kerry  1 , Matthew O Wiens  6   5   7
Affiliations

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

Brooklyn R Nemetchek et al. Afr Health Sci. 2018 Dec.

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; infants; neonatal; pediatrics; post-discharge mortality; prediction; sepsis.

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Figures

Figure 1
Figure 1
Flow diagram of delphi process
See this image and copyright information in PMC

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