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Predicting hospital stay, mortality and readmission in people admitted for hypoglycaemia: prognostic models derivation and validation

Zaccardi, Francesco; Webb, David R.; Davies, Melanie J.; Dhalwani, Nafeesa N.; Gray, Laura J.; Chatterjee, Sudesna; Housley, Gemma; Shaw, Dominick; Hatton, James W.; Khunti, Kamlesh

Predicting hospital stay, mortality and readmission in people admitted for hypoglycaemia: prognostic models derivation and validation Thumbnail


Authors

Francesco Zaccardi

David R. Webb

Melanie J. Davies

Nafeesa N. Dhalwani

Laura J. Gray

Sudesna Chatterjee

Gemma Housley

James W. Hatton

Kamlesh Khunti



Abstract

Aims/hypothesis: Hospital admissions for hypoglycaemia represent a significant burden on individuals with diabetes and have a substantial economic impact on healthcare systems. To date, no prognostic models have been developed to predict outcomes following admission for hypoglycaemia. We aimed to develop and validate prediction models to estimate risk of inpatient death, 24 h discharge and one month readmission in people admitted to hospital for hypoglycaemia.
Methods: We used the Hospital Episode Statistics database, which includes data on all hospital admission to National Health Service hospital trusts in England, to extract admissions for hypoglycaemia between 2010 and 2014. We developed, internally and temporally validated, and compared two prognostic risk models for each outcome. The first model included age, sex, ethnicity, region, social deprivation and Charlson score (‘base’ model). In the second model, we added to the ‘base’ model the 20 most common medical conditions and applied a stepwise backward selection of variables (‘disease’ model). We used C-index and calibration plots to assess model performance and developed a calculator to estimate probabilities of outcomes according to individual characteristics.
Results: In derivation samples, 296 out of 11,136 admissions resulted in inpatient death, 1789/33,825 in one month readmission and 8396/33,803 in 24 h discharge. Corresponding values for validation samples were: 296/10,976, 1207/22,112 and 5363/22,107. The two models had similar discrimination. In derivation samples, C-indices for the base and disease models, respectively, were: 0.77 (95% CI 0.75, 0.80) and 0.78 (0.75, 0.80) for death, 0.57 (0.56, 0.59) and 0.57 (0.56, 0.58) for one month readmission, and 0.68 (0.67, 0.69) and 0.69 (0.68, 0.69) for 24 h discharge. Corresponding values in validation samples were: 0.74 (0.71, 0.76) and 0.74 (0.72, 0.77), 0.55 (0.54, 0.57) and 0.55 (0.53, 0.56), and 0.66 (0.65, 0.67) and 0.67 (0.66, 0.68). In both derivation and validation samples, calibration plots showed good agreement for the three outcomes. We developed a calculator of probabilities for inpatient death and 24 h discharge given the low performance of one month readmission models.
Conclusions/interpretation: This simple and pragmatic tool to predict in-hospital death and 24 h discharge has the potential to reduce mortality and improve discharge in people admitted for hypoglycaemia.

Citation

Zaccardi, F., Webb, D. R., Davies, M. J., Dhalwani, N. N., Gray, L. J., Chatterjee, S., …Khunti, K. (2017). Predicting hospital stay, mortality and readmission in people admitted for hypoglycaemia: prognostic models derivation and validation. Diabetologia, 60(6), 1007-1015. https://doi.org/10.1007/s00125-017-4235-1

Journal Article Type Article
Acceptance Date Feb 6, 2017
Online Publication Date Mar 17, 2017
Publication Date 2017
Deposit Date May 17, 2018
Publicly Available Date May 17, 2018
Journal Diabetologia
Print ISSN 0012-186X
Electronic ISSN 0012-186X
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 60
Issue 6
Pages 1007-1015
DOI https://doi.org/10.1007/s00125-017-4235-1
Keywords Epidemiology ; Hypoglycaemia ; Inpatient ; Mortality ; Prognostic model
Public URL https://nottingham-repository.worktribe.com/output/870814
Publisher URL https://link.springer.com/article/10.1007%2Fs00125-017-4235-1

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