Predictive Model Developed for In-Hospital Mortality in TAVR
Covariates include age, glomerular filtration rate, hemodialysis, severe chronic lung disease
THURSDAY, March 10, 2016 (HealthDay News) -- A predictive model has been developed and validated for in-hospital mortality among patients undergoing transcatheter aortic valve replacement (TAVR); the findings were published online March 9 in JAMA Cardiology.
Fred H. Edwards, M.D., from the University of Florida College of Medicine in Jacksonville, and colleagues used patient data from a national registry for 13,718 patients undergoing TAVR to develop a statistical model that will predict in-hospital mortality after TAVR. The model was validated using 6,868 records for consecutive patients undergoing TAVR.
The researchers found that in-hospital mortality occurred in 5.3 percent of patients. The C-statistic for discrimination was 0.67 and 0.66, respectively, in the development and validation groups. Covariates in the final model included age (odds ratio [OR], 1.13), glomerular filtration rate per 5-unit increments (OR, 0.93), hemodialysis (OR, 3.25), New York Heart Association functional class IV (OR, 1.25), severe chronic lung disease (OR, 1.67), nonfemoral access site (OR, 1.96), and procedural acuity categories 2, 3, and 4 (ORs, 1.57, 2.70, and 3.34, respectively). No significant difference was seen between the model calibration line and the ideal calibration line.
"This model should be a valuable adjunct for patient counseling, local quality improvement, and national monitoring for appropriateness of selection of patients for TAVR," the authors write.
Several authors disclosed financial ties to the pharmaceutical and medical device industries.