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A new model predicts in-hospital mortality following transcatheter aortic valve replacement (TAVR), according to a multi-center study.

While the C statistic was a modest 0.67, that was better model discrimination "than that for previously reported models that have been used in the population undergoing TAVR," , of University of Florida College of Medicine-Jacksonville, and colleagues reported online in JAMA Cardiology.

With an in-hospital mortality occurring in 5.3% of patients, the independent predictors incorporated into the model were:

• Age (odds ratio 1.13, 95% confidence interval 1.06-1.20)
• Hemodialysis (OR 3.25, 95% CI 2.42-4.37)
• New York Heart Association class IV heart failure (OR 1.25, 95% CI 1.03-1.52)
• Severe chronic lung disease (OR 1.67, 95% CI 1.35-2.05)
• Nonfemoral access site (OR 1.96, 95% CI 1.65-2.33)
• Procedural acuity categories 2 (OR 1.57, 95% CI 1.20-2.05), 3 (OR 2.70, 95% CI 2.05-3.55), and 4 (OR 3.34, 95% CI 1.59-7.02)

Glomerular filtration rate (OR 0.93, 95% CI 0.91-0.95) had a negative association with in-hospital mortality, on the other hand.

"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 concluded.

Yet "the model results should not dictate which patients are candidates for TAVR; rather, the model should be used as one element in the selection process to be considered in concert with history, physical examination, laboratory information, and clinical judgment," they conceded. "The model may also provide useful information for patient counseling."

The model is now being incorporated into the Transcatheter Valve Therapy (TVT) Registry software, according to Edwards and colleagues.

In an accompanying editorial, two clinicians called it premature to use the model to compare TAVR with alternative strategies, such as surgical aortic valve replacement or conservative therapy.

"While it may be tempting to compare risks estimated from two models (e.g., TVTR risk and STS-PROM) to help decide which type of treatment to pursue, an undertaking of this nature is likely to be fraught with limitations," , and , both of Brigham and Women's Hospital in Boston, wrote.

Even so, the pair called the model a "small yet important step" to better decision-making with patients.

The data was compiled from 13,718 consecutive U.S. patients getting TAVR between 2011 and 2014. Individuals were enrolled in the Society of Thoracic Surgeons/American College of Cardiology (STS/ACC) TVT Registry.

Edwards' group noted that the TVT Registry was the "ideal" source of their data, as the Centers for Medicaid and Medicare Services had specified that TAVR reimbursement rest indirectly on participation in the registry. "This stipulation indicates that virtually all patients with TAVR are entered into this registry, thereby creating a real-world database of the TAVR experience," they added.

However, the investigators admitted that they were unable to account for all possible risk factors, including frailty indicators, such that other covariates may eventually emerge.

The editorialists suggested many other limitations to the model: "To this list should be added the lack of clarity regarding the process by which expert opinion (rather than incorporation of new findings from data analysis) drove development of the model and the absence of information regarding major in-hospital cardiac (need for permanent pacemaker or implantable defibrillator, atrial fibrillation, and cardiac arrest) and noncardiac (stroke and macular access) complications, as well as patient-oriented outcomes (functional status and quality of life)."

Nonetheless, "it is encouraging to note the TVT Registry investigators plan to refine their model further, with the ultimate goal of creating a tool that provides a fuller picture of anticipated survival and functional outcomes for the TAVR population, the demographics of which may change considerably in the years ahead."