Aims Our aim was to develop a machine learning (ML)-based risk stratification system to predict 1-, 2-, 3-, 4-, and 5-year all-cause mortality from pre-implant parameters of patients undergoing cardiac resynchronization therapy (CRT). Methods and results Multiple ML models were trained on a retrospective database of 1510 patients undergoing CRT implantation to predict 1- to 5-year all-cause mortality. Thirty-three pre-implant clinical features were selected to train the models. The best performing model [SEMMELWEIS-CRT score (perSonalizEd assessMent of estiMatEd risk of mortaLity With machinE learnIng in patientS undergoing CRT implantation)], along with pre-existing scores (Seattle Heart Failure Model, VALID-CRT, EAARN, ScREEN, and CRT-score), was tested on an independent cohort of 158 patients. There were 805 (53%) deaths in the training cohort and 80 (51%) deaths in the test cohort during the 5-year follow-up period. Among the trained classifiers, random forest demonstrated the best performance. For the prediction of 1-, 2-, 3-, 4-, and 5-year mortality, the areas under the receiver operating characteristic curves of the SEMMELWEIS-CRT score were 0.768 (95% CI: 0.674–0.861; P < 0.001), 0.793 (95% CI: 0.718–0.867; P < 0.001), 0.785 (95% CI: 0.711–0.859; P < 0.001), 0.776 (95% CI: 0.703–0.849; P < 0.001), and 0.803 (95% CI: 0.733–0.872; P < 0.001), respectively. The discriminative ability of our model was superior to other evaluated scores. Conclusion The SEMMELWEIS-CRT score (available at semmelweiscrtscore.com) exhibited good discriminative capabilities for the prediction of all-cause death in CRT patients and outperformed the already existing risk scores. By capturing the non-linear association of predictors, the utilization of ML approaches may facilitate optimal candidate selection and prognostication of patients undergoing CRT implantation.

Background: The relative importance of variables explaining sex-related differences in outcomes is scarcely explored in patients undergoing cardiac resynchronization therapy (CRT). We sought to implement and evaluate machine learning (ML) algorithms for the prediction of 1- and 3-year all-cause mortality in CRT patients. We also aimed to assess the sex-specific differences in predictors of mortality utilizing ML.Methods: Using a retrospective registry of 2,191 CRT patients, ML models were implemented in 6 partially overlapping patient subsets (all patients, females, or males with 1- or 3-year follow-up). Each cohort was randomly split into training (80%) and test sets (20%). After hyperparameter tuning in the training sets, the best performing algorithm was evaluated in the test sets. Model discrimination was quantified using the area under the receiver-operating characteristic curves (AUC). The most important predictors were identified using the permutation feature importances method.Results: Conditional inference random forest exhibited the best performance with AUCs of 0.728 (0.645–0.802) and 0.732 (0.681–0.784) for the prediction of 1- and 3-year mortality, respectively. Etiology of heart failure, NYHA class, left ventricular ejection fraction, and QRS morphology had higher predictive power, whereas hemoglobin was less important in females compared to males. The importance of atrial fibrillation and age increased, while the importance of serum creatinine decreased from 1- to 3-year follow-up in both sexes.Conclusions: Using ML techniques in combination with easily obtainable clinical features, our models effectively predicted 1- and 3-year all-cause mortality in CRT patients. Sex-specific patterns of predictors were identified, showing a dynamic variation over time.

Aims Patients with a pacemaker or implantable cardioverter-defibrillator are often considered for cardiac resynchronization therapy (CRT). However, limited comprehensive data are available regarding their long-term outcomes. Methods and results Our retrospective registry included 2524 patients [1977 (78%) de novo, 547 (22%) upgrade patients] with mild to severe symptoms, left ventricular ejection fraction ≤35%, and QRS ≥ 130ms. The primary outcome was the composite of all-cause mortality, heart transplantation (HTX), or left ventricular assist device (LVAD) implantation; secondary endpoints were death from any cause and post-procedural complications. In our cohort, upgrade patients were older [71 (65–77) vs. 67 (59–73) years; P < 0.001], were less frequently females (20% vs. 27%; P = 0.002) and had more comorbidities than de novo patients. During the median follow-up time of 3.7 years, 1091 (55%) de novo and 342 (63%) upgrade patients reached the primary endpoint. In univariable analysis, upgrade patients exhibited a higher risk of mortality/HTX/LVAD than the de novo group [hazard ratio (HR): 1.41; 95% confidence interval (CI): 1.23–1.61; P < 0.001]. However, this difference disappeared after adjusting for covariates (adjusted HR: 1.12; 95% CI: 0.86–1.48; P = 0.402), or propensity score matching (propensity score-matched HR: 1.10; 95% CI: 0.95–1.29; P = 0.215). From device-related complications, lead dysfunction (3.1% vs. 1%; P < 0.001) and pocket infections (3.7% vs. 1.8%; P = 0.014) were more frequent in the upgrade group compared to de novo patients. Conclusion In our retrospective analysis, upgrade patients had a higher risk of all-cause mortality than de novo patients, which might be attributable to their more significant comorbidity burden. The occurrence of lead dysfunction and pocket infections was more frequent in the upgrade group.

Aims Preferring side branch of coronary sinus during cardiac resynchronization therapy (CRT) implantation has been empirical due to the limited data on the association of left ventricular (LV) lead position and long-term clinical outcome. We evaluated the long-term all-cause mortality by LV lead non-apical positions and further characterized them by interlead electrical delay (IED). Methods and results In our retrospective database, 2087 patients who underwent CRT implantation were registered between 2000 and 2018. Those with non-apical LV lead locations were classified into anterior (n = 108), posterior (n = 643), and lateral (n = 1336) groups. All-cause mortality was assessed by Kaplan-Meier and Cox analyses. Echocardiographic response was measured 6 months after CRT implantation. During the median follow-up time of 3.7 years, 1150 (55.1%) patients died-710 (53.1%) with lateral, 78 (72.2%) with anterior, and 362 (56.3%) with posterior positions. When we investigated the risk of all-cause mortality, there was a significantly lower rate of death in patients with lateral LV lead location when compared with those with an anterior (P < 0.01) or posterior (P < 0.01) position. Multivariate analysis after adjustment for relevant clinical covariates such as age, sex, ischaemic aetiology, left bundle branch block morphology, atrial fibrillation, and device type revealed consistent results that lateral position is associated with a significant risk reduction of all-cause mortality when compared with anterior [hazard ratio 0.69; 95% confidence interval (CI) 0.55-0.87; P < 0.01] or posterior (hazard ratio 0.84; 95% CI 0.74-0.96; P < 0.01) position. When echocardiographic response was evaluated within the lateral group, patients with an IED longer than 110 ms (area under the receiver operating characteristic curve, 0.63; 95% CI 0.53-0.73; P = 0.012) showed 2.1 times higher odds of improvement in echocardiographic response 6 months after the implantation. Conclusions In this study, we proved in a real-world patient population that after CRT implantation, lateral LV lead location was associated with long-term mortality benefit and is superior to both anterior and posterior positions. Moreover, patients with this position showed the greatest echocardiographic response over 110 ms IED.

Data on the relevance of anemia in heart failure (HF) patients with an ejection fraction (EF) > 40% by subgroup—preserved (HFpEF), mildly reduced (HFmrEF) and the newly defined recovered EF (HFrecEF)—are scarce. Patients with HF symptoms, elevated NT-proBNP, EF ≥ 40% and structural abnormalities were registered in the HFpEF-HFmrEF database. We described the outcome of our HFpEF-HFmrEF cohort by the presence of anemia. Additionally, HFrecEF patients were also selected from HFrEF patients who underwent resynchronization and, as responders, reached 40% EF. Using propensity score matching (PSM), 75 pairs from the HFpEF-HFmrEF and HFrecEF groups were matched by their clinical features. After PMS, we compared the survival of the HFpEF-HFmrEF and HFrecEF groups. Log-rank, uni-and multivariate regression analyses were performed. From 375 HFpEF-HFmrEF patients, 42 (11%) died during the median follow-up time of 1.4 years. Anemia (HR 2.77; 95%CI 1.47–5.23; p < 0.01) was one of the strongest mortality predictors, which was also confirmed by the multivariate analysis (aHR 2.33; 95%CI 1.21–4.52; p = 0.01). Through PSM, the outcomes for HFpEF-HFmrEF and HFrecEF patients with anemia were poor, exhibiting no significant difference. In HFpEF-HFmrEF, anemia was an independent mortality predictor. Its presence multiplied the mortality risk in those with EF ≥ 40%, regardless of HF etiology.