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dc.contributor.authorNemetchek, Brooklyn R
dc.contributor.authorLiang, Li(Danny)
dc.contributor.authorKissoon, Niranjan
dc.contributor.authorAnsermino, J Mark
dc.contributor.authorKabakyenga, Jerome
dc.contributor.authorLavoie, Pascal M
dc.contributor.authorKerry, Susan Fowler
dc.contributor.authorWiens, Matthew O
dc.date.accessioned2022-05-25T07:35:21Z
dc.date.available2022-05-25T07:35:21Z
dc.date.issued2018
dc.identifier.citationNemetchek, B. R., Liang, L. D., Kissoon, N., Ansermino, M. J., Kabakyenga, J., Lavoie, P. M., ... & Wiens, M. O. (2018). Predictor variables for post-discharge mortality modelling in infants: a protocol development project. African Health Sciences, 18(4), 1214-1225.en_US
dc.identifier.urihttp://ir.must.ac.ug/xmlui/handle/123456789/2036
dc.description.abstractBackground: 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 was 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.en_US
dc.description.sponsorshipThrasher Research Funden_US
dc.language.isoen_USen_US
dc.publisherAfrican Health Sciencesen_US
dc.subjectCandidate predictor variablesen_US
dc.subjectPediatricsen_US
dc.subjectNeonatalen_US
dc.subjectInfantsen_US
dc.subjectPredictionen_US
dc.subjectPost-discharge mortalityen_US
dc.subjectSepsisen_US
dc.titlePredictor variables for post-discharge mortality modelling in infants: a protocol development projecten_US
dc.typeArticleen_US


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