search
for
 About Bioline  All Journals  Testimonials  Membership  News


African Health Sciences
Makerere University Medical School
ISSN: 1680-6905
EISSN: 1680-6905
Vol. 18, No. 4, 2018, pp. 1214-1225
Bioline Code: hs18129
Full paper language: English
Document type: Study
Document available free of charge

African Health Sciences, Vol. 18, No. 4, 2018, pp. 1214-1225

 en Predictor variables for post-discharge mortality modelling in infants: a protocol development project
Nemetchek, Brooklyn R; Liang, Li(Danny); Kissoon, Niranjan; Ansermino, J Mark; Kabakyenga, Jerome; Lavoie, Pascal M; Fowler-Kerry, Susan & Wiens, Matthew O

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

 
© Copyright 2018 - Nemetchek et al.

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