HealthDay News — A clinical risk model can predict the risk of death and unplanned cardiac hospitalization for patients waiting for cardiac surgery, according to a study published in the Aug. 30 issue of CMAJ, the journal of the Canadian Medical Association.

Louise Y. Sun, M.D., from the University of Ottawa in Canada, and colleagues 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 between 2008 and 2019. The patients were randomly divided into derivation and validation data sets (two-thirds [41,729 patients] and one-third [20,583 patients], respectively). The model was derived using a multivariable Cox proportional hazard model with backward stepwise variable selection.

The researchers found that 4.9 percent of the patients died or had an unplanned cardiac hospitalization while waiting for surgery. At 15, 30, 60, and 89 days, the area under the curve of the model 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, respectively, in the validation cohort. At all time points the model calibrated well.


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“Our model can be used to provide decision support for referring physicians and the surgery-anesthesiology team, as well as health care administrators, through time-dependent, individualized risk prediction,” the authors write. “It could also be used in quality benchmarking and to compare wait-time metrics across centers.”

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