Postdischarge mortality in children with acute infectious diseases: derivation of postdischarge mortality prediction models
| dc.contributor.author | Wiens, M O | |
| dc.contributor.author | Kumbakumba, E | |
| dc.contributor.author | Ansermino, J M | |
| dc.contributor.author | Singer, J | |
| dc.contributor.author | Kissoon, N | |
| dc.contributor.author | Wong, H | |
| dc.contributor.author | Ndamira, A | |
| dc.contributor.author | Kabakyenga, J | |
| dc.contributor.author | Kiwanuka, J | |
| dc.contributor.author | Zhou, G | |
| dc.date.accessioned | 2022-05-24T13:05:10Z | |
| dc.date.available | 2022-05-24T13:05:10Z | |
| dc.date.issued | 2015 | |
| dc.description.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. | en_US |
| dc.identifier.citation | Wiens, 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.uri | http://ir.must.ac.ug/handle/123456789/2034 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | BMJ Open | en_US |
| dc.subject | Postdischarge mortality | en_US |
| dc.subject | Infections | en_US |
| dc.subject | Children | en_US |
| dc.subject | hospital discharge | en_US |
| dc.title | Postdischarge mortality in children with acute infectious diseases: derivation of postdischarge mortality prediction models | en_US |
| dc.type | Article | en_US |
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