Postdischarge mortality in children with acute infectious diseases: derivation of postdischarge mortality prediction models

M O Wiens, E Kumbakumba, C P Larson, J M Ansermino, J Singer, N Kissoon, H Wong, A Ndamira, J Kabakyenga, J Kiwanuka, G Zhou, M O Wiens, E Kumbakumba, C P Larson, J M Ansermino, J Singer, N Kissoon, H Wong, A Ndamira, J Kabakyenga, J Kiwanuka, G Zhou

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.

Keywords: EPIDEMIOLOGY; PAEDIATRICS.

Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Figures

Figure 1
Figure 1
Consort diagram of study flow.
Figure 2
Figure 2
Performance of the primary prediction model derived with data from admission (AUC, area under the curve; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating characteristic; Sens, sensitivity; Spec, specificity).

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