New Risk-Prediction Model Predicts Mortality Risk in TEER Patients

A risk-prediction model incorporating age and identified clinical characteristics may help predict mortality risk in patients receiving transcatheter edge-to-edge repair (TEER) to treat severe mitral regurgitation (MR), according to a study published Feb. 7 in the Journal of the American College of Cardiology.

Sergio Raposeiras-Roubin, MD, PhD, et al., used the international MIVNUT Registry to create and validate a user-friendly risk model, known as MitraScore, to predict mortality risk among TEER patients. A derivation cohort consisted of 1,109 patients who received TEER between 2012 and 2020 at 12 sites in Europe and Canada. The patients were followed from the time of the procedure through November 2020. The primary endpoint was all-cause mortality. Secondary endpoints included the composite of mortality and heart failure (HF) readmission, cardiovascular mortality, and one-year improvement in the NYHA functional class. External validation was performed in a cohort of 725 patients from the GIOTTO registry.

In a median follow-up period of 1.6 years, 354 patients (31.9%) died and 315 (28.4%) were readmitted for HF. The researchers identified eight independent predictors of mortality: age ≥75 years, anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2, left ventricular ejection fraction <40%, peripheral artery disease, chronic obstructive pulmonary disease, high diuretic dose, and no treatment with renin- angiotensin system inhibitors.

For the risk model, one point was assigned to each independent predictor of mortality, with the sum of all points estimating mortality risk. The relative risk of mortality increased by 55% with each additional point (Hazard Ratio [HR]: 1.55; 95% Confidence Interval [CI]: 1.44-1.67; p<0.001).

The model showed adequate performance in the derivation cohort (c-statistic: 0.70, 95% CI: 0.66-0.73), and discrimination and calibration for mortality prediction was higher than those of the EuroSCORE II (c-statistic: 0.61) or the Society of Thoracic Surgeons score (c-statistic: 0.66). In addition, the model adequately predicted HF readmission and was correlated with the probability of improved NYHA class. In external validation, the model maintained adequate discrimination and calibration, with good predictive accuracy for mortality, cardiovascular death, and HF readmission.

According to the researchers, the study “represents an important step forward toward better and more objective risk estimation of TEER patients.” They conclude that the MitraScore model is a simple algorithm to predict mortality in TEER patients and may help support clinical decision-making, noting that “prospective validation of this score in practice remains desirable.”

In an accompanying editorial comment, Mohamad Alkhouli, MD, FACC, et al., write that the development of the MitraScore “represents a momentous step towards improving the triaging of patients referred for TEER.” They add that additional research is “needed to construct and validate practical but rigorous risk-predication tools that can inform our decisions in the ever-expanding field of [structural heart disease] interventions.”

Clinical Topics: Dyslipidemia, Heart Failure and Cardiomyopathies, Valvular Heart Disease, Vascular Medicine, Atherosclerotic Disease (CAD/PAD), Lipid Metabolism, Novel Agents, Acute Heart Failure, Mitral Regurgitation

Keywords: Anemia, Registries, Diuretics, Cardiology, Angiotensins, Heart Failure, Clinical Decision-Making, Peripheral Arterial Disease, Pulmonary Disease, Chronic Obstructive, Ventricular Function, Left, Stroke Volume, Risk, Renin, Patient Readmission, Mitral Valve Insufficiency, Glomerular Filtration Rate

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