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. 2013 Nov;36(11):3566-72.
doi: 10.2337/dc13-0452. Epub 2013 Sep 11.

A prediction model for adverse outcome in hospitalized patients with diabetes

Krishnarajah Nirantharakumar  1 , Karla Hemming, Parth Narendran, Tom Marshall, Jamie J Coleman
Affiliations

A prediction model for adverse outcome in hospitalized patients with diabetes

Krishnarajah Nirantharakumar et al. Diabetes Care. 2013 Nov.

Abstract

Objective: There are no formal prognostic models predicting adverse outcomes (excessive length of stay or mortality) in hospitalized patients with diabetes. In this study, we aimed to develop a prediction model that will help identify patients with diabetes who are most likely to have an adverse event during their hospital stay.

Research design and methods: Analysis was based on 25,118 admissions with diabetes to University Hospital Birmingham, Birmingham, U.K., over 4 years (2007-2010). Adverse events are defined as either excessive length of stay or inpatient mortality. Key predictors were variables that are often available in the first 72 h of admission and included demographic characteristics, clinical pathological test results, and use of insulin. Models were constructed using logistic regression, discrimination and calibration was assessed, and internal validation was carried out.

Results: The model performed well with an area under the curve (AUC) of 0.802 with only a mild reduction being noted in the internal validation (AUC 0.798). At a cutoff value of 25% probability of having an adverse outcome the sensitivity was 76%, specificity was 70%, and the positive predictive value was 49%. If it is used for a case-finding approach limiting to noncritical care settings, then at the same cutoff value, two-thirds (sensitivity 69%) of the admissions with adverse outcomes could potentially be identified.

Conclusions: Once externally validated, we suggest that our model will be a useful tool for identifying diabetic patients who are at risk for poor outcomes when admitted to hospital.

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Figures

Figure 1
Figure 1
Receiver operating characteristic (ROC) curves for model comparison and assessment of discrimination.
See this image and copyright information in PMC

References

    1. Bruno A, Gregori D, Caropreso A, Lazzarato F, Petrinco M, Pagano E. Normal glucose values are associated with a lower risk of mortality in hospitalized patients. Diabetes Care 2008;31:2209–2210 - PMC - PubMed
    1. Diabetes National Health Service. National diabetes inpatient audit 2010 [article online], 2011. Available from http://www.diabetes.nhs.uk/information_and_data/diabetes_audits/national... Accessed 21 August 2012
    1. Yorkshire and Humber Public Health Observatory. Mortality among inpatients with diabetes [article online], 2012. Available from http://www.yhpho.org.uk/default.aspx?RID=139172 Accessed 1 February 2013
    1. McAlister FA, Majumdar SR, Blitz S, Rowe BH, Romney J, Marrie TJ. The relation between hyperglycemia and outcomes in 2,471 patients admitted to the hospital with community-acquired pneumonia. Diabetes Care 2005;28:810–815 - PubMed
    1. Pomposelli JJ, Baxter JK, 3rd, Babineau TJ, et al. Early postoperative glucose control predicts nosocomial infection rate in diabetic patients. JPEN J Parenter Enteral Nutr 1998;22:77–81 - PubMed

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