Key result
A derived clinical risk model accurately predicted the composite outcome of death and unplanned cardiac hospitalization for patients on the cardiac surgery waitlist, with an area under the curve of 0.83 at 15 days in the validation cohort.
Why the study?
Waitlist management is challenging, and prolonged wait times for cardiac surgery are linked to unplanned hospitalizations, requiring a clinical risk model to guide evidence-based resource allocation.
Cohort (n=62,375)
Yes
Effect estimate: AUC 0.83 at 15 days in the validation cohort
A newly derived and validated clinical risk model accurately predicts the risk of death and unplanned cardiac hospitalization for patients awaiting cardiac surgery, providing a tool for evidence-based waitlist triage.
May support waitlist triage in cardiac surgery; hypothesis-generating and requires prospective validation before practice change.
BACKGROUND: Waitlist management is a global challenge. For patients with severe cardiovascular diseases awaiting cardiac surgery, prolonged wait times are associated with unplanned hospitalizations. To facilitate evidence-based resource allocation, we derived and validated a clinical risk model to predict the composite outcome of death and cardiac hospitalization of patients on the waitlist for cardiac surgery. METHODS: We used the CorHealth Ontario Registry and linked ICES health care administrative databases, which have information on all Ontario residents. We included patients 18 years or older who waited at home for coronary artery bypass grafting, valvular or thoracic aorta surgeries between 2008 and 2019. The primary outcome was death or an unplanned cardiac hospitalizaton, defined as nonelective admission for heart failure, myocardial infarction, unstable angina or endocarditis. We randomly divided two-thirds of these patients into derivation and one-third into validation data sets. We derived the model using a multivariable Cox proportional hazard model with backward stepwise variable selection. RESULTS: Among 62 375 patients, 41 729 patients were part of the derivation data set and 20 583 were part of the validation data set. Of the total, 3033 (4.9%) died or had an unplanned cardiac hospitalization while waiting for surgery. The area under the curve of our model at 15, 30, 60 and 89 days was 0.85, 0.82, 0.81 and 0.80, respectively, in the derivation cohort and 0.83, 0.80, 0.78 and 0.78, respctively, in the validation cohort. The model calibrated well at all time points. INTERPRETATION: We derived and validated a clinical risk model that provides accurate prediction of the risk of death and unplanned cardiac hospitalization for patients on the cardiac surgery waitlist. Our model could be used for quality benchmarking and data-driven decision support for managing access to cardiac surgery.
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Sun et al. (2021) conducted a cohort in Severe cardiovascular diseases awaiting cardiac surgery (n=62,375). Cardiac surgery waitlist was evaluated on Composite of death or unplanned cardiac hospitalization (AUC 0.83 at 15 days in the validation cohort). A derived clinical risk model accurately predicted the composite outcome of death and unplanned cardiac hospitalization for patients on the cardiac surgery waitlist, with an area under the curve of 0.83 at 15 days in the validation cohort.
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