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Heart Lung Circ. 2015 Nov;24(11):1068-73. doi: 10.1016/j.hlc.2015.04.168. Epub 2015 May 7.

An Absolute Risk Prediction Model to Determine Unplanned Cardiovascular Readmissions for Adults with Chronic Heart Failure.

Author information

1
The University of Sydney, Sydney Nursing School, Sydney, NSW, Australia. Electronic address: vasiliki.betihavas@sydney.edu.au.
2
The University of Western Sydney, School of Nursing and Midwifery, Sydney, NSW Australia & Intensive Care Liverpool Hospital, University of NSW, Sydney, NSW Australia.
3
Centre for Cardiovascular and Chronic Care, University of Technology, Sydney, NSW, Australia.
4
St Vincent's Hospital, Sydney, NSW, Australia and Victor Chang Cardiac Research Institute, Sydney, NSW, Australia.
5
Preventative Health, Baker IDI Heart and Diabetes Institute, Melbourne, Vic, Australia.
6
School of Nursing, Johns Hopkins University, Washington, DC, USA.

Abstract

BACKGROUND:

Frequent readmissions are a hallmark of chronic heart failure (CHF). We sought to develop an absolute risk prediction model for unplanned cardiovascular readmissions following hospitalisation for CHF.

METHODS:

An inception cohort was obtained from the WHICH? trial, a prospective, multi-centre randomised controlled trial which was a head-to-head comparison of the efficacy of a home-based intervention versus clinic-based intervention for adults with CHF. A Cox's proportional hazards model (taking into account the competing risk of death) was used to develop a prediction model. Bootstrap methods were used to identify factors for the final model. Based on these data a nomogram was developed.

RESULTS:

Of the 280 participants in the WHICH? trial 37 (13%) were readmitted for a cardiovascular event (including CHF) within 28 days, and a further 149 (53%) were readmitted within 18 months for a cardiovascular event. In the proposed competing risk model, factors associated with an increased risk of hospitalisation for CHF were: age (HR 1.07, 95% CI 0.90-1.26) for each 10-year increase in age; living alone (HR 1.09, 95% CI 0.74-1.59); those with a sedentary lifestyle (HR 1.44, 95% CI, 0.92-2.25) and the presence of multiple co-morbid conditions (HR 1.69, 95% CI 0.38-7.58) for five or more co-morbid conditions (compared to individuals with one documented co-morbidity). The C-statistic of the final model was 0.80.

CONCLUSION:

We have developed a practical model for individualising the risk of short-term readmission for CHF. This model may provide additional information for targeting and tailoring interventions and requires future prospective evaluation.

KEYWORDS:

Heart failure; Hospitalisation; Risk assessment; Risk factors; Risk model

PMID:
26048319
DOI:
10.1016/j.hlc.2015.04.168
[Indexed for MEDLINE]

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