ArticleClinical research in cardiology : official journal of the German Cardiac Society2026
Modified essential frailty toolset for risk stratification in transcatheter mitral and tricuspid valve repair.
Article in Clinical research in cardiology : official journal of the German Cardiac Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundCurrent guidelines recommend frailty assessment for risk stratification of candidates for transcatheter mitral and tricuspid valve repair (TMTVR), but it remains unclear which frailty score is most appropriate.
methodsIn a retrospective monocentric analysis of patients who received TMTVR, a modified version of the essential frailty toolset (EFT) was calculated from four categories: gait speed, cognitive impairment, hemoglobin, and serum albumin. Cox proportional hazards models were used to examine the association between EFT frailty and all-cause mortality.
resultsA total of 206 patients were analyzed; median age was 76 [72-82] years, and 55% were male. According to the EFT, 49 patients (24%) were non-frail, 127 patients (62%) were pre-frail, and 30 patients (15%) were frail. Estimated survival at 2 years was 88 ± 5% for non-frail patients, 74 ± 5% for pre-frail patients, and 62 ± 10% for frail patients, with a hazard ratio of 1.54 (95% CI 1.16-2.04; p = 0.003) per standard deviation of EFT score. This association remained virtually unchanged when adjusted for other risk factors and Fried physical frailty, but disappeared when adjusted for the multidimensional prognostic index (MPI), which is based on a comprehensive geriatric assessment. A stepwise approach using EFT in all patients and MPI only in pre-frail EFT patients resulted in two risk categories with a 4.4-fold (95% CI 2.3-9.4) difference in 2-year mortality between categories.
conclusionsThe EFT has prognostic value for patients undergoing TMTVR. Due to its simplicity, the EFT could serve as a first-line frailty assessment tool to guide therapeutic decision-making, potentially in a stepwise approach with MPI.
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