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dc.contributor.authorWiens, M O
dc.contributor.authorKumbakumba, E
dc.contributor.authorAnsermino, J M
dc.contributor.authorSinger, J
dc.contributor.authorKissoon, N
dc.contributor.authorWong, H
dc.contributor.authorNdamira, A
dc.contributor.authorKabakyenga, J
dc.contributor.authorKiwanuka, J
dc.contributor.authorZhou, G
dc.date.accessioned2022-05-24T13:05:10Z
dc.date.available2022-05-24T13:05:10Z
dc.date.issued2015
dc.identifier.citationWiens, M. O., Kumbakumba, E., Larson, C. P., Ansermino, J., Singer, J., Kissoon, N., ... & Zhou, G. (2015). Postdischarge mortality in children with acute infectious diseases: derivation of postdischarge mortality prediction models. BMJ open, 5(11), e009449.en_US
dc.identifier.urihttp://ir.must.ac.ug/xmlui/handle/123456789/2034
dc.description.abstractObjectives: To derive a model of paediatric postdischarge mortality following acute infectious illness. Design: Prospective cohort study. Setting: 2 hospitals in South-western Uganda. Participants: 1307 children of 6 months to 5 years of age were admitted with a proven or suspected infection. 1242 children were discharged alive and followed up 6 months following discharge. The 6-month follow-up rate was 98.3%. Interventions: None. Primary and secondary outcome measures: The primary outcome was postdischarge mortality within 6 months following the initial hospital discharge. Results: 64 children died during admission (5.0%) and 61 died within 6 months of discharge (4.9%). Of those who died following discharge, 31 (51%) occurred within the first 30 days. The final adjusted model for the prediction of postdischarge mortality included the variables mid-upper arm circumference (OR 0.95, 95% CI 0.94 to 0.97, per 1 mm increase), time since last hospitalisation (OR 0.76, 95% CI 0.61 to 0.93, for each increased period of no hospitalisation), oxygen saturation (OR 0.96, 95% CI 0.93 to 0·99, per 1% increase), abnormal Blantyre Coma Scale score (OR 2.39, 95% CI 1·18 to 4.83), and HIV-positive status (OR 2.98, 95% CI 1.36 to 6.53). This model produced a receiver operating characteristic curve with an area under the curve of 0.82. With sensitivity of 80%, our model had a specificity of 66%. Approximately 35% of children would be identified as high risk (11.1% mortality risk) and the remaining would be classified as low risk (1.4% mortality risk), in a similar cohort. Conclusions: Mortality following discharge is a poorly recognised contributor to child mortality. Identification of at-risk children is critical in developing postdischarge interventions. A simple prediction tool that uses 5 easily collected variables can be used to identify children at high risk of death after discharge. Improved discharge planning and care could be provided for high-risk children.en_US
dc.language.isoen_USen_US
dc.publisherBMJ Openen_US
dc.subjectPostdischarge mortalityen_US
dc.subjectInfectionsen_US
dc.subjectChildrenen_US
dc.subjecthospital dischargeen_US
dc.titlePostdischarge mortality in children with acute infectious diseases: derivation of postdischarge mortality prediction modelsen_US
dc.typeArticleen_US


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