Postdischarge mortality in children with acute infectious diseases: derivation of postdischarge mortality prediction models. Issue 11 (25th November 2015)

• Record Type: Journal Article
• Authors: Wiens, M O; Kumbakumba, E; Larson, C P; Ansermino, J M; Singer, J; Kissoon, N; Wong, H; Ndamira, A; Kabakyenga, J; Kiwanuka, J; Zhou, G
• Is Part Of: BMJ open. Volume 5:Issue 11(2015)
• Publication Date: 2015-11-25
• Subjects: PAEDIATRICS -- EPIDEMIOLOGY; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2015-009449
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objectives: 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.