Impact of frailty on short term outcomes, resource use, and readmissions after transcatheter mitral valve repair: A national analysis. - Joseph Hadaya; Zachary Tran; Yas Sanaiha; Esteban Aguayo; Vishal Dobaria; Marcella Calfon Press; Peyman Benharash (PLoS ONE, 2021)
Background Treatment options for mitral regurgitation range from diuretic therapy, to surgical and interventional strategies including TMVR in high-risk surgical candidates. Frailty has been associated with inferior outcomes following hospitalizations for heart failure and in open cardiac surgery. Objective The purpose of the present study was to evaluate the impact of frailty on clinical outcomes and resource use following transcatheter mitral valve repair (TMVR). Methods Adults undergoing TMVR were identified using the 2016-2018 Nationwide Readmissions Database, and divided into Frail and Non-Frail groups. Frailty was defined using a derivative of the Johns Hopkins Adjusted Clinical Groups frailty indicator. Generalized linear models were used to assess the association of frailty with in-hospital mortality, complications, nonhome discharge, hospitalization costs, length of stay, and non-elective readmission at 90 days. Average marginal effects were used to quantify the impact of frailty on predicted mortality. Results Of 18,791 patients undergoing TMVR, 11.6% were considered frail. The observed mortality rate for the overall cohort was 2.2%. After adjustment, frailty was associated with increased odds of in-hospital mortality (AOR 1.8, 95% CI 1.2-2.6), corresponding to an absolute increase in risk of mortality of 1.1%. Frailty was associated with a 2.7-day (95% CI 2.1-3.2) increase in postoperative LOS, and $18,300 (95% CI 14,400-22,200) increment in hospitalization costs. Frail patients had greater odds (4.4, 95% CI 3.6-5.4) of nonhome discharge but similar odds of non-elective 90-day readmission. Conclusions Frailty is independently associated with inferior short-term clinical outcomes and greater resource use following TMVR. Inclusion of frailty into existing risk models may better inform choice of therapy and shared decision-making.