Tilburg Frailty Indicator Predicts Death and Rehospitalization after Cardiac Resynchronization Therapy in Patients with Heart Failure

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Emerging evidence suggests that the Tilburg Frailty Indicator (TFI) score may help with prognosis stratification following cardiac resynchronization therapy (CRT) implantation. Nonetheless, the specific associations between the TFI score and post-procedural mortality or rehospitalization remain elusive. Methods Patients with HF who underwent CRT at Henan Provincial People’s Hospital, the First Affiliated Hospital of Xinjiang Medical University, and Henan Provincial Chest Hospital, completed the TFI questionnaire preoperatively, and had complete clinical records were retrospectively enrolled between January 2022 and May 2024. Cox proportional hazards regression analyses were used to evaluate the association between the TFI score and both all-cause mortality and HF-related rehospitalization following CRT implantation. This association was visualized using restricted cubic spline (RCS) curves. The predictive value of the TFI score for these outcomes was further assessed using a random survival forest (RSF) approach. Results The TFI score was an independent predictor of all-cause mortality (Hazard Ratio [HR]1.39 [95% Confidence Interval [CI] 1.27–1.52], p < 0.001) and one-year HF-related rehospitalization (HR 1.28 [95% CI 1.18–1.39], p < 0.001) following CRT implantation. In the frailty cohort, there was a significantly lower survival probability ( p < 0.0001), with a near-linear positive relationship between the HR and TFI score ( p for non-linearity = 0.5709), and the TFI score emerged as the most important variable for predicting all-cause mortality. Patients with frailty experienced more HF-related rehospitalizations at the 1-year follow-up ( p < 0.0001), with a similarly near-linear positive association with TFI scores ( p for non-linearity = 0.1658), which was also the most important predictive variable. Conclusions The TFI score emerged as the most significant independent predictor of mortality and rehospitalization following CRT implantation in patients with HF. Health sciences/Cardiology Health sciences/Diseases Health sciences/Medical research Health sciences/Risk factors Heart failure Cardiac resynchronization therapy Tilburg Frailty Indicator Frailty Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Heart failure (HF) has become an increasingly significant health concern, with substantial morbidity and mortality driven by the aging global population. It not only severely affects patients’ quality of life but also places a considerable financial strain on healthcare systems [ 1 – 3 ]. With a deeper understanding of the disease’s pathophysiological mechanisms and the development of more effective clinical interventions, prognosis has markedly improved over the years. Evidence indicates that cardiac resynchronization therapy (CRT) can alleviate symptoms and reduce mortality in patients with chronic HF who meet the indications after optimized medical treatment [ 4 – 6 ]. Nevertheless, the benefits of CRT are not equally observed across all patient groups. Studies have shown that approximately 30% of patients experience poor outcomes, with a high incidence of death and rehospitalization following CRT implantation [ 7 , 8 ]. Therefore, identifying factors that influence prognosis after CRT in patients with HF is particularly important, given the substantial cost, invasive nature, and significant procedural risks associated with this approach. Frailty is a medical syndrome characterized by reduced tolerance to stressors and increased vulnerability to adverse events due to diminished physiological reserve across multiple systems [ 9 ]. Its incidence and prevalence are higher in patients with HF than in the general population, and it contributes to both the onset and progression of HF [ 10 ]. Evidence suggests a bidirectional association, with HF patients having a sixfold higher risk of developing frailty compared to those without HF, while frail individuals have a sevenfold higher risk of developing HF than non-frail individuals [ 11 , 12 ]. Moreover, the coexistence of HF and frailty is associated with significantly worse clinical outcomes, including higher mortality and rehospitalization rates [ 13 – 17 ]. Multiple assessment tools have been developed to evaluate frailty in patients with HF, including the Fried frailty Phenotype, Frailty Index, and the Tilburg Frailty Indicator (TFI) questionnaire [ 18 – 21 ]. Notably, the TFI questionnaire adopts a multidimensional framework and quantifies frailty across physical, psychological, and social domains, aligning with the complex pathophysiology of HF, in which psychosocial factors significantly influence outcomes. Conversely, the Fried frailty Phenotype focuses solely on physical decline, while the Frailty Index often lacks standardized social and psychological components. Although the prognostic value of the TFI score for outcomes following CRT in patients with HF has been suggested in isolated studies [ 19 , 22 ], its specific associations with all-cause mortality and HF-related rehospitalization remain poorly understood. To that end, the present study aims to explore the specific association between the TFI score and outcomes following CRT implantation. 2. Methods 2.1. Study population Patients with HF who underwent cardiac resynchronization therapy with either a pacemaker (CRT-P) or a defibrillator (CRT-D) at Henan Provincial People’s Hospital, the First Affiliated Hospital of Xinjiang Medical University, and Henan Provincial Chest Hospital were retrospectively screened for inclusion from January 2022 to May 2024. The implantation procedure followed standard technical specifications, with selective placement of the left ventricular (LV) lead in the lateral branch of the coronary sinus to activate the lateral free wall of the LV. Indications for CRT implantation were based on current guidelines [ 6 ], including New York Heart Association (NYHA) functional class II–IV, left bundle branch block morphology with a QRS duration > 130 ms, and a left ventricular ejection fraction (LVEF) ≤ 35% despite optimal pharmacological therapy [ 6 ]. Patients with a history of other cardiac implantable devices or with incomplete frailty assessments (either unperformed or undocumented), as well as those with missing baseline or follow-up data, were excluded from the study. This research was carried out in compliance with the Declaration of Helsinki and was approved by the Henan Provincial People's Hospital Ethics Committee (number 159 (2025)). All methods were carried out in accordance with relevant guidelines and regulations, and Informed consent was obtained from all subjects. 2.2. Frailty assessment Frailty was assessed prior to CRT implantation using the TFI questionnaire. This questionnaire includes 15 items spanning three dimensions: physical (8 items), psychological (4 items), and social (3 items). A total score of 5 or higher indicates the presence of frailty, with higher scores reflecting greater severity. 2.3. Study variables Baseline characteristics were obtained from electronic health records. Demographic variables included sex, age, and body mass index (BMI). Medical variables comprised comorbidities (hypertension, diabetes, hyperlipidemia, and ischemic heart disease), heart rate and systolic blood pressure at hospital admission, biochemical laboratory parameters (hemoglobin, serum creatinine, and serum potassium), left ventricular ejection fraction (LVEF), QRS duration, NYHA class, and medical treatments, including β-blockers, angiotensin receptor neprilysin inhibitors (ARNI), angiotensin receptor blockers (ARB), angiotensin-converting enzyme inhibitors (ACEI), spironolactone, furosemide, and digoxin. 2.4. Endpoints The primary endpoint of this study was all-cause mortality during follow-up. The secondary endpoint was HF-related rehospitalization within one year after CRT implantation. Follow-up concluded in December 2024, with endpoint events documented through hospital and outpatient medical records, supplemented by telephone or WeChat communication. Participants who did not complete the minimum 12-month follow-up or had missing outcome data were excluded from the final analysis. 2.5. Statistical analysis Normally distributed variables were presented as mean ± standard deviation and compared using Student’s t-test, while skewed variables were described as median (interquartile range, 25th-75th percentile) and compared using the Mann-Whitney U test. Categorical variables were expressed as frequencies and percentages (n [%]), with group comparisons performed using χ² tests or Fisher’s exact tests. Univariable and multivariable Cox proportional hazards regression analyses were used to calculate hazard ratios (HR) and their corresponding 95% confidence intervals (95% CI) for the association between TFI score and both all-cause mortality and HF-related rehospitalization following CRT implantation. Kaplan–Meier curves were used to illustrate survival free from all-cause mortality and HF-related rehospitalization, with comparisons made using the log-rank test. Restricted cubic spline (RCS) curves were employed to assess the associations between TFI score and both all-cause mortality and HF-related rehospitalization after CRT implantation. Furthermore, the random survival forest (RSF) method was applied to evaluate the importance of the TFI score in predicting these outcomes in HF patients undergoing CRT. All statistical analyses were performed using RStudio (RStudio, Inc.) and SPSS version 25.0 (SPSS Inc.). A two-tailed p -value < 0.05 was considered statistically significant. 3. Results A total of 387 patients were ultimately enrolled in this study, of whom 190 (47.9%) met the frailty criteria, with a median TFI score of 7 (interquartile range 5–8). Compared to non-frail patients, those with frailty were older ( p = 0.020), included more females ( p < 0.001), had lower systolic blood pressure ( p = 0.012), lower serum potassium levels ( p = 0.001), a higher proportion of NYHA class III–IV (p = 0.001), and lower LVEF ( p = 0.020). Detailed baseline characteristics for both cohorts are summarized in Table 1 . Table 1 Baseline clinical characteristics of two groups. Characteristic Frailty (190) Non-frailty (n = 197) p value TFI score 7(5, 8) 3(2, 4) < 0.001 Age (y) 66.5 ± 10.1 64.0 ± 11.0 0.020 Sex: female 58 (30.5%) 28 (14.2%) < 0.001 BMI 24.8 ± 3.5 25.4 ± 3.2 0.112 Hypertension 96 (50.5%) 92(46.7%) 0.452 Diabetes 49 (25.8%) 51 (25.9%) 0.982 hyperlipidemia 91 (47.9%) 82 (41.6%) 0.215 Ischemic heart disease 84 (44.2%) 76 (38.6%) 0.261 Systolic blood pressure 124.2 ± 25.3 130.6 ± 24.8 0.012 Heart rate 86.7 ± 18.1 87.2 ± 13.4 0.741 Hemoglobin (g/L) 138.7 ± 17.2 140.5 ± 16.5 0.297 Serum creatinine (mmol/L) 70.3 ± 19.7 70.8 ± 18.7 0.807 Potassium (mmol/L) 3.9 ± 0.4 4.1 ± 0.4 0.001 Pro BNP (pg/ml) 4243.2 ± 516.1 3466.3 ± 401.8 150ms 120 (63.2%) 124 (62.9%) 0.965 ACEI or ARB or ARNI 148 (77.9%) 158 (80.2%) 0.577 β-blockers 156 (82.1%) 163 (82.7%) 0.869 Spironolactone 177 (93.2%) 187 (94.9%) 0.463 Furosemide 32 (16.8%) 32 (16.2%) 0.874 Digoxin 43 (22.6%) 36 (18.3%) 0.288 TFI: Tilburg Frailty Indicator, BMI: body mass index, BNP: B-type naturietic peptide, NYHA: New York Heart Association functional class, LVEF: left ventricle ejection fraction, ACEI: angiotensin converting enzyme inhibitors, ARB: angiotensin receptor blocker, ARNI: angiotensin receptor neprilysin inhibitor. The median follow-up duration was 21 months (interquartile range 15–27), during which 44 patients experienced all-cause mortality. Univariable Cox regression analysis identified TFI score, advanced age, ischemic heart disease, serum potassium levels, and NYHA class III–IV as significant predictors of all-cause mortality (p < 0.05). These variables were included in a multivariable Cox proportional hazards model, which showed that TFI score (HR 1.39 [95% CI 1.27–1.52], p < 0.001) and NYHA class III–IV (HR 2.01 [95% CI 1.01–4.01], p = 0.048) were independent predictors of all-cause mortality after adjustment (Table 2 ). Using the same univariable-multivariable Cox regression approach, TFI score (HR 1.28 [95% CI 1.18–1.39], p < 0.001) also emerged as an independent predictor of 1-year HF-related rehospitalization following CRT implantation, after adjusting for baseline comorbidities and biochemical variables (Table 3 ). Table 2 Univariate and multivariate Cox regression analysis for risk of all-cause death. Univariate analysis multivariate analysis HR [95%CI] p HR [95%CI] p TFI score 1.44 [1.31–1.57] < 0.001 1.39 [1.27–1.52] < 0.001 Age (y) 1.03 [1.00-1.06] 0.033 1.03 [1.00-1.06] 0.101 Sex: female 1.22 [0.63–2.37] 0.566 BMI 0.91 [0.83–1.01] 0.069 Hypertension 1.11 [0.61–2.01] 0.731 Diabetes 1.47 [0.78–2.78] 0.235 hyperlipidemia 0.73 [ 0.39–1.35] 0.310 Ischemic heart disease 2.18 [1.19–3.98] 0.011 1.76 [0.95–3.24] 0.073 Systolic blood pressure 0.99 [0.98-1.00] 0.209 Heart rate 0.99 [0.98–1.01] 0.528 Hemoglobin 0.99 [0.97-1.00] 0.078 Serum creatinine 1.00 [0.98–1.01] 0.747 Potassium 0.45 [0.22–0.91] 0.026 0.75 [0.39–1.47] 0.408 Pro BNP (pg/ml) 1.00 [1.00–1.00] 0.302 NYHA III-IV 3.05 [1.57–5.93] 0.001 2.01 [1.01–4.01] 0.048 LVEF (%) 1.04 [0.95–1.13] 0.405 QRS > 150ms 1.13 [0.61–2.10] 0.690 ACEI or ARB or ARNI 1.46 [0.65–3.28] 0.356 β-blockers 1.37 [0.58–3.25] 0.471 Spironolactone 1.35 [0.33–5.56] 0.682 Furosemide 1.82 [0.91–3.61] 0.088 Digoxin 1.04 [0.50–2.17] 0.910 TFI: Tilburg Frailty Indicator, BMI: body mass index, NYHA: New York Heart Association functional class, LVEF: left ventricle ejection fraction, ACEI: angiotensin converting enzyme inhibitors, ARB: angiotensin receptor blocker, ARNI: angiotensin receptor neprilysin inhibitor. Table 3 Univariate and multivariate Cox regression analysis for HF-related rehospitalization Univariate analysis multivariate analysis HR [95%CI] p HR [95%CI] p TFI score 1.30 [1.22–1.39] < 0.001 1.28 [1.18–1.39] < 0.001 Age (y) 1.02 [1.00-1.04] 0.028 1.01 [0.99–1.04] 0.206 Sex: female 1.53 [0.97–2.41] 0.068 BMI 0.99 [0.93–1.05] 0.679 Hypertension 0.92 [0.61–1.38] 0.673 Diabetes 0.88 [0.54–1.43] 0.597 hyperlipidemia 0.70 [ 0.45–1.06] 0.093 Ischemic heart disease 1.98 [1.31–2.99] 0.001 1.82 [1.20–2.76] 0.005 Systolic blood pressure 1.00 [0.99–1.01] 0.386 Heart rate 0.99 [0.98-1.00] 0.184 Hemoglobin 0.99 [0.97-1.00] 0.010 0.99 [0.98-1.00] 0.118 Serum creatinine 1.00 [0.99–1.01] 0.926 Potassium 1.04 [0.65–1.66] 0.866 Pro BNP (pg/ml) 1.00 [1.00–1.00] 150ms 1.22 [0.79–1.89] 0.369 ACEI or ARB or ARNI 1.14 [0.67–1.93] 0.628 β-blockers 1.19 [0.67–2.11] 0.548 Spironolactone 1.09 [0.44–2.69] 0.848 Furosemide 1.58 [0.97–2.57] 0.068 Digoxin 0.92 [0.55–1.55] 0.758 TFI: Tilburg Frailty Indicator, BMI: body mass index, NYHA: New York Heart Association functional class, LVEF: left ventricle ejection fraction, ACEI: angiotensin converting enzyme inhibitors, ARB: angiotensin receptor blocker, ARNI: angiotensin receptor neprilysin inhibitor. During follow-up, 34 deaths occurred among frail patients compared to 10 in the non-frail group, resulting in a significantly lower survival probability in the frailty cohort (Fig. 1 A; log-rank test, p < 0.0001). Restricted cubic spline analysis demonstrated a near-linear positive relationship between TFI scores and the HR for all-cause mortality (Fig. 1 B; p for non-linear = 0.5709). The RSF method identified the TFI score as the most important variable for predicting all-cause mortality in HF patients undergoing CRT implantation (Fig. 2 ). Within one year following CRT implantation, patients with frailty experienced 63 HF-related rehospitalization events compared to 28 in non-frail patients (Fig. 3 A; log-rank test, p < 0.0001). The association between TFI scores and the hazard ratio for HF-related rehospitalization was approximately linear (Fig. 3 B; p for non-linear = 0.1658). The RSF method identified the TFI score as the most important variable for predicting 1-year HF-related rehospitalization in HF patients undergoing CRT implantation (Fig. 4 ). 4. Discussion Herein, we found that the TFI score was a significant independent predictor of all-cause mortality and 1-year HF-related rehospitalization following CRT implantation in patients with HF. Moreover, the hazard ratios for these events increased nearly linearly with each unit increase in TFI score, with the TFI score being the most significant variable among all evaluated predictors. The rising prevalence of chronic conditions such as diabetes, hypertension, and coronary artery disease, combined with improved survival rates among patients with heart disease, has driven a sustained global increase in HF incidence, particularly in aging populations [ 1 – 3 ]. Frailty, a medical syndrome characterized by reduced physiological reserve and impaired stress resilience, shares pathophysiological mechanisms with HF through aging-related processes. Epidemiological studies report frailty prevalence ranging from 30% to 74% in chronic HF cohorts, strongly correlating with HF severity [ 23 – 26 ]. In the present study, 47.9% of HF patients with LVEF ≤ 35% met frailty criteria, consistent with published rates of 31% to 47% in populations with LVEF < 40% [ 26 ]. Frailty accelerates HF progression, leading to worse prognosis, severe functional impairment, reduced quality of life, and higher all-cause mortality. A previous meta analysis reported a 69% increase in all-cause mortality risk in patients with both frailty and HF. [ 13 ]. Vidán et al. reported a 45% increase in mortality per unit rise in the Fried frailty phenotype score [ 24 ]. Meanwhile, Bottle et al. found that 39% of HF patients with frailty experienced at least one rehospitalization within a 1-year follow-up [ 16 ]. Our findings corroborate these trends; the TFI score was a significant predictor of all-cause mortality and 1-year HF-related rehospitalization following CRT implantation in patients with HF. Frail patients exhibited a 4.02-fold higher mortality and a 2.57-fold higher rehospitalization rate, with hazard ratios increasing nearly linearly across TFI scores. Notably, the TFI score was the most important predictor of prognosis among all evaluated variables. We attribute this to the physiological decline in frail patients, including sarcopenia, cognitive impairment, and dysregulation of inflammatory pathways, which impairs the myocardial response to CRT and diminishes the efficacy of cardiac resynchronization [ 27 ]. Frailty can impair physical function and mobility, limiting patients’ participation in rehabilitation and adherence to management guidelines, which may worsen outcomes [ 28 , 29 ]. It is also associated with neuroendocrine and immune alterations that lead to inflammation, oxidative stress, and autonomic dysregulation [ 20 – 32 ]. These factors may contribute to cardiac remodeling and deterioration following CRT. The TFI score quantifies frailty across physical, psychological, and social domains that influence CRT response. In the physical domain, sarcopenia may impair ventricular-arterial coupling, reducing cardiac output augmentation after CRT. Psychological factors such as depression and anxiety can increase the risk of ventricular arrhythmias through autonomic dysregulation. In addition, low social support may be associated with poorer adherence to device monitoring. To our knowledge, this is the first study to quantify the relationship between TFI score and mortality and rehospitalization gradient post-CRT. Furthermore, ischemic heart disease and advanced NYHA class, established predictors of CRT mortality, likely reflect reduced viable myocardium, consistent with prior mechanistic studies [ 7 , 8 , 33 , 34 ]. Despite the established efficacy of CRT in improving cardiac function, concomitant frailty substantially modifies its therapeutic effectiveness. Therefore, integrating multidimensional frailty assessment into pre-implantation evaluation is imperative. Systematic frailty phenotyping could refine patient selection algorithms for CRT implantation and improve prognostic stratification. Moreover, implementing intensified follow-up protocols with early targeted interventions, such as nutritional optimization and reduction of polypharmacy, may help mitigate adverse outcomes in this high-risk subgroup [ 35 ]. Nonetheless, this study has several limitations that should be taken into account. First, as a retrospective observational study, it may be subject to imbalances due to the limited sample size. Second, methodological differences in frailty assessment tools could introduce significant heterogeneity in outcome measurement, limiting comparability across studies. Third, longitudinal changes in frailty following CRT implantation were not systematically evaluated, potentially obscuring dynamic interactions between device-mediated reverse remodeling and frailty progression. Lastly, specific interventions targeting frailty were not addressed in the present study. 5. Conclusion The TFI score was strongly associated with all-cause mortality and 1-year HF-related rehospitalization following CRT implantation in patients with HF. Moreover, these unfavorable outcomes showed a nearly linear relationship with increasing frailty scores. Declarations Author's contribution: Shujuan Dong, and Baopeng Tang designed the study. Shujuan Dong collected, analyzed the data statistically, and wrote the main manuscript text. All authors contributed to the writing of this manuscript. Availability of data: Baopeng Tang could be contacted if the data from this study was requested. Conflict of interest: There was no conflict of interest between authors. References Global national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 392 (10159), 1789–1858 (2018). Virani, S. S. et al. Heart disease and stroke statistics–2020 update: a report from the American Heart Association. Circulation 141 (9), e139–e596 (2020). Roger, V. L. Epidemiology of Heart Failure: A Contemporary Perspective. Circ. Res. 128 (10), 1421–1434 (2021). Tang, A. S. et al. Cardiac–resynchronization therapy for mild–to–moderate heart failure. N Engl. J. Med. 363 (25), 2385–2395 (2010). Ruschitzka, F. et al. Cardiac resynchronization therapy in heart failure with a narrow QRS complex. N Engl. J. Med. 369 , 13951405 (2013). Glikson, M. et al. 2021 ESC Guidelines on cardiac pacing and cardiac resynchronization therapy. Eur. Heart J. 42 (35), 3427–3520 (2021). Abreu, A. et al. Predictors of response to cardiac resynchronization therapy: A prospective cohort study. Rev. Port Cardiol. 36 (6), 417–425 (2017). Naqvi, S. Y. et al. Non-response to Cardiac Resynchronization Therapy. Curr. Heart Fail. Rep. 15 (5), 315–321 (2018). Fried, L. P. et al. Frailty in older adults: evidence for a phenotype. J. Gerontol. Biol. Sci. Med. Sci. 56 (3), M146–156 (2001). Vitale, C. et al. Heart Failure Association/European Society of Cardiology position paper on frailty in patients with heart failure. Eur. J. Heart Fail. 21 (11), 1299–1305 (2019). Shinmura, K. Cardiac senescence, heart failure, and frailty: a triangle in elderly people. Keio J. Med. 65 (2), 25–32 (2016). Talha, K. M. et al. Frailty and heart failure: State-of-the-art review. J. Cachexia Sarcopenia Muscle . 14 (5), 1959–1972 (2023). Yang, X. et al. Impact of frailty on mortality and hospitalization in chronic heart failure: a systematic review and meta–analysis. J. Am. Heart Assoc. 7 (23), e008251 (2018). Sanders, N. A. et al. The frailty syndrome and outcomes in the TOPCAT trial. Eur. J. Heart Fail. 20 (11), 1570–1577 (2018). Zhang, Y. et al. Frailty and clinical outcomes in heart failure: a systematic review and meta–analysis. J. Am. Med. Dir. Assoc. 19 (11), 1003–1008e1 (2018). Bottle, A. et al. Frailty and co–morbidity predict first hospitalisation after heart failure diagnosis in primary care: population–based observational study in England. Age Ageing . 48 (3), 347–354 (2019). Uchmanowicz, I. et al. Frailty and the risk of all–cause mortality and hospitalization in chronic heart failure: a meta–analysis. ESC Heart Fail. 7 (6), 3427–3437 (2020). Dominguez-Rodriguez, A. et al. The impact of frailty in older patients with non-ischaemic cardiomyopathy after implantation of cardiac resynchronization therapy defibrillator. Europace 17 (4), 598–602 (2015). Mlynarska, A. et al. Modified frailty as a novel factor in predicting the response to cardiac resynchronization in the elderly population. Clin. Interv Aging . 14 , 437–443 (2019). Milner, A. et al. Utility of the Modified Frailty Index to Predict Cardiac Resynchronization Therapy Outcomes and Response. Am. J. Cardiol. 125 (7), 1077–1082 (2020). Son, Y. J. et al. Prevalence and factors associated with pre-frailty and frailty among Korean older adults with heart failure. J. Adv. Nurs. 78 (10), 3235–3246 (2022). Mlynarska, A., Mlynarski, R. & Golba, K. S. Frailty as a predictor of negative outcomes after cardiac resynchronization therapy. Pacing Clin. Electrophysiol. 41 (6), 572–577 (2018). Khan, H. et al. Frailty and risk for heart failure in older adults: the health, aging, and body composition study. Am. Heart J. 166 (5), 887–894 (2013). Vidán, M. T. et al. Prevalence and prognostic impact of frailty and its components in non–dependent elderly patients with heart failure. Eur. J. Heart Fail. 18 (7), 869–875 (2016). Kleipool, E. E. et al. Frailty in older adults with cardiovascular disease: cause, effect or both ? Aging Dis. 9 (3), 489–497 (2018). Sze, S. et al. Identification of frailty in chronic heart failure. JACC Heart Fail. 7 (4), 291–302 (2019). Pandey, A. et al. Frailty Is Intertwined With Heart Failure: Mechanisms, Prevalence, Prognosis, Assessment, and Management. JACC Heart Fail. 7 (12), 1001–1011 (2019). Bencivenga, L. et al. Role of frailty on cardiac rehabilitation in hospitalized older patients. Aging Clin. Exp. Res. 34 (11), 2675–2682 (2022). Tsukakoshi, D. et al. Clinical perspectives on cardiac rehabilitation after heart failure in elderly patients with frailty: a narrative review. Ther. Clin. Risk Manag . 18 , 1009–1028 (2022). Yao, X., Li, H. & Leng, S. X. Inflammation and immune system alterations in frailty. Clin. Geriatr. Med. 27 (1), 79–87 (2011). Clegg, A. & Hassan-Smith, Z. Frailty and the endocrine system. Lancet Diabetes Endocrinol. 6 (9), 743–752 (2018). Debain, A. et al. Frail older adults are more likely to have auto nomic dysfunction: a systematic review and meta-analysis. Ageing Res. Rev. 87 , 101925 (2023). Rickard, J. et al. Predictors of response to cardiac resynchronization therapy: A systematic review. Int. J. Cardiol. 225 , 345–352 (2016). Linde, C. et al. Predictors of short-term clinical response to cardiac resynchronization therapy. Eur. J. Heart Fail. 19 (8), 1056–1063 (2017). McDonagh, T. A. et al. ESC scientific document Group. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur. Heart J. 42 , 3599–3726 (2021). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7847402","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":558305749,"identity":"804404b1-2d5c-443b-af16-7d63ca905096","order_by":0,"name":"Shujuan Dong","email":"","orcid":"","institution":"the First Affiliated Hospital of Xinjiang Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shujuan","middleName":"","lastName":"Dong","suffix":""},{"id":558305750,"identity":"4ee39e5c-151c-450d-82e7-908c0cf7f76e","order_by":1,"name":"Baopeng 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16:19:03","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":31373,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7847402/v1/2dc75a20834301a0cd9d1a5b.png"},{"id":98246304,"identity":"112c5f4e-6c4a-4584-813c-d99d0d1e971d","added_by":"auto","created_at":"2025-12-15 16:18:58","extension":"xml","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95556,"visible":true,"origin":"","legend":"","description":"","filename":"0dcd454c1b964624a792096fd95773de1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7847402/v1/d3bebb072fd5f0c9d93c1c56.xml"},{"id":98246419,"identity":"75c185aa-da71-4daf-8433-f38b53f28efa","added_by":"auto","created_at":"2025-12-15 16:19:02","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":105267,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7847402/v1/dfe041e77a25fcab03067ed3.html"},{"id":98246296,"identity":"efa39ba0-c4ea-43dd-a580-525536102bdd","added_by":"auto","created_at":"2025-12-15 16:18:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55869,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between frailty and all-cause mortality. A. Kaplan–Meier survival curves comparing patients with and without frailty. B. Restricted cubic spline analysis illustrating the association between TFI scores and the hazard ratio for all-cause mortality.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7847402/v1/52e7fc0e033b85c757e85023.png"},{"id":98246341,"identity":"86a75181-748b-49e1-bbf4-8d6acb7c17bf","added_by":"auto","created_at":"2025-12-15 16:19:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32308,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of all-cause mortality risk in HF patients with CRT implantation using random survival forest. (Left) Error rate of the random survival forest model. (Right) Ranking of variable importance based on out-of-bag estimation.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7847402/v1/c03543784f64c05efc0e1946.png"},{"id":98246322,"identity":"59657822-e607-41e2-89c0-d67e2f08de97","added_by":"auto","created_at":"2025-12-15 16:18:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":47780,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between frailty and HF-related rehospitalization. A. Kaplan–Meier curves comparing survival without HF-related rehospitalization within 1 year after CRT implantation, according to frailty status. B. Restricted cubic spline analysis showing the association between TFI scores and the hazard ratio for HF-related rehospitalization.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7847402/v1/d9457f80599e980daf15a195.png"},{"id":98246220,"identity":"ea54e46e-6e8c-4b38-b7e5-5cc9b4527a51","added_by":"auto","created_at":"2025-12-15 16:18:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":31561,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of 1-year HF-related rehospitalization risk in HF patients following CRT implantation using random survival forest. (Left) Error rate of the random survival forest model. (Right) Ranking of variable importance based on out-of-bag estimation.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7847402/v1/110fc84f7158db086d069c87.png"},{"id":100364130,"identity":"c2ff146d-205c-4cec-9ff4-8cca09e6339e","added_by":"auto","created_at":"2026-01-16 07:52:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":940041,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7847402/v1/2f777538-c431-4260-a9d0-46a74430c441.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Tilburg Frailty Indicator Predicts Death and Rehospitalization after Cardiac Resynchronization Therapy in Patients with Heart Failure","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHeart failure (HF) has become an increasingly significant health concern, with substantial morbidity and mortality driven by the aging global population. It not only severely affects patients\u0026rsquo; quality of life but also places a considerable financial strain on healthcare systems [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. With a deeper understanding of the disease\u0026rsquo;s pathophysiological mechanisms and the development of more effective clinical interventions, prognosis has markedly improved over the years. Evidence indicates that cardiac resynchronization therapy (CRT) can alleviate symptoms and reduce mortality in patients with chronic HF who meet the indications after optimized medical treatment [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Nevertheless, the benefits of CRT are not equally observed across all patient groups. Studies have shown that approximately 30% of patients experience poor outcomes, with a high incidence of death and rehospitalization following CRT implantation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, identifying factors that influence prognosis after CRT in patients with HF is particularly important, given the substantial cost, invasive nature, and significant procedural risks associated with this approach.\u003c/p\u003e \u003cp\u003eFrailty is a medical syndrome characterized by reduced tolerance to stressors and increased vulnerability to adverse events due to diminished physiological reserve across multiple systems [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Its incidence and prevalence are higher in patients with HF than in the general population, and it contributes to both the onset and progression of HF [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Evidence suggests a bidirectional association, with HF patients having a sixfold higher risk of developing frailty compared to those without HF, while frail individuals have a sevenfold higher risk of developing HF than non-frail individuals [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Moreover, the coexistence of HF and frailty is associated with significantly worse clinical outcomes, including higher mortality and rehospitalization rates [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMultiple assessment tools have been developed to evaluate frailty in patients with HF, including the Fried frailty Phenotype, Frailty Index, and the Tilburg Frailty Indicator (TFI) questionnaire [\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Notably, the TFI questionnaire adopts a multidimensional framework and quantifies frailty across physical, psychological, and social domains, aligning with the complex pathophysiology of HF, in which psychosocial factors significantly influence outcomes. Conversely, the Fried frailty Phenotype focuses solely on physical decline, while the Frailty Index often lacks standardized social and psychological components. Although the prognostic value of the TFI score for outcomes following CRT in patients with HF has been suggested in isolated studies [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], its specific associations with all-cause mortality and HF-related rehospitalization remain poorly understood. To that end, the present study aims to explore the specific association between the TFI score and outcomes following CRT implantation.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study population\u003c/h2\u003e \u003cp\u003ePatients with HF who underwent cardiac resynchronization therapy with either a pacemaker (CRT-P) or a defibrillator (CRT-D) at Henan Provincial People\u0026rsquo;s Hospital, the First Affiliated Hospital of Xinjiang Medical University, and Henan Provincial Chest Hospital were retrospectively screened for inclusion from January 2022 to May 2024. The implantation procedure followed standard technical specifications, with selective placement of the left ventricular (LV) lead in the lateral branch of the coronary sinus to activate the lateral free wall of the LV. Indications for CRT implantation were based on current guidelines [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], including New York Heart Association (NYHA) functional class II\u0026ndash;IV, left bundle branch block morphology with a QRS duration\u0026thinsp;\u0026gt;\u0026thinsp;130 ms, and a left ventricular ejection fraction (LVEF)\u0026thinsp;\u0026le;\u0026thinsp;35% despite optimal pharmacological therapy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Patients with a history of other cardiac implantable devices or with incomplete frailty assessments (either unperformed or undocumented), as well as those with missing baseline or follow-up data, were excluded from the study. This research was carried out in compliance with the Declaration of Helsinki and was approved by the Henan Provincial People's Hospital Ethics Committee (number 159 (2025)). All methods were carried out in accordance with relevant guidelines and regulations, and Informed consent was obtained from all subjects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Frailty assessment\u003c/h2\u003e \u003cp\u003eFrailty was assessed prior to CRT implantation using the TFI questionnaire. This questionnaire includes 15 items spanning three dimensions: physical (8 items), psychological (4 items), and social (3 items). A total score of 5 or higher indicates the presence of frailty, with higher scores reflecting greater severity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Study variables\u003c/h2\u003e \u003cp\u003eBaseline characteristics were obtained from electronic health records. Demographic variables included sex, age, and body mass index (BMI). Medical variables comprised comorbidities (hypertension, diabetes, hyperlipidemia, and ischemic heart disease), heart rate and systolic blood pressure at hospital admission, biochemical laboratory parameters (hemoglobin, serum creatinine, and serum potassium), left ventricular ejection fraction (LVEF), QRS duration, NYHA class, and medical treatments, including β-blockers, angiotensin receptor neprilysin inhibitors (ARNI), angiotensin receptor blockers (ARB), angiotensin-converting enzyme inhibitors (ACEI), spironolactone, furosemide, and digoxin.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Endpoints\u003c/h2\u003e \u003cp\u003eThe primary endpoint of this study was all-cause mortality during follow-up. The secondary endpoint was HF-related rehospitalization within one year after CRT implantation. Follow-up concluded in December 2024, with endpoint events documented through hospital and outpatient medical records, supplemented by telephone or WeChat communication. Participants who did not complete the minimum 12-month follow-up or had missing outcome data were excluded from the final analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e \u003cp\u003eNormally distributed variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and compared using Student\u0026rsquo;s t-test, while skewed variables were described as median (interquartile range, 25th-75th percentile) and compared using the Mann-Whitney U test. Categorical variables were expressed as frequencies and percentages (n [%]), with group comparisons performed using χ\u0026sup2; tests or Fisher\u0026rsquo;s exact tests. Univariable and multivariable Cox proportional hazards regression analyses were used to calculate hazard ratios (HR) and their corresponding 95% confidence intervals (95% CI) for the association between TFI score and both all-cause mortality and HF-related rehospitalization following CRT implantation. Kaplan\u0026ndash;Meier curves were used to illustrate survival free from all-cause mortality and HF-related rehospitalization, with comparisons made using the log-rank test. Restricted cubic spline (RCS) curves were employed to assess the associations between TFI score and both all-cause mortality and HF-related rehospitalization after CRT implantation. Furthermore, the random survival forest (RSF) method was applied to evaluate the importance of the TFI score in predicting these outcomes in HF patients undergoing CRT. All statistical analyses were performed using RStudio (RStudio, Inc.) and SPSS version 25.0 (SPSS Inc.). A two-tailed \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA total of 387 patients were ultimately enrolled in this study, of whom 190 (47.9%) met the frailty criteria, with a median TFI score of 7 (interquartile range 5\u0026ndash;8). Compared to non-frail patients, those with frailty were older (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020), included more females (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), had lower systolic blood pressure (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012), lower serum potassium levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), a higher proportion of NYHA class III\u0026ndash;IV (p\u0026thinsp;=\u0026thinsp;0.001), and lower LVEF (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020). Detailed baseline characteristics for both cohorts are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline clinical characteristics of two groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrailty\u003c/p\u003e \u003cp\u003e(190)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-frailty\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;197)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTFI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(5, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(2, 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex: female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (30.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (14.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 (50.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (25.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (25.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (47.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82 (41.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (44.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (38.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124.2\u0026thinsp;\u0026plusmn;\u0026thinsp;25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130.6\u0026thinsp;\u0026plusmn;\u0026thinsp;24.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.7\u0026thinsp;\u0026plusmn;\u0026thinsp;18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138.7\u0026thinsp;\u0026plusmn;\u0026thinsp;17.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum creatinine (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.3\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.8\u0026thinsp;\u0026plusmn;\u0026thinsp;18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePro BNP (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4243.2\u0026thinsp;\u0026plusmn;\u0026thinsp;516.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3466.3\u0026thinsp;\u0026plusmn;\u0026thinsp;401.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA III-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104 (54.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (38.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQRS\u0026thinsp;\u0026gt;\u0026thinsp;150ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (63.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124 (62.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI or ARB or ARNI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (77.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158 (80.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.577\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156 (82.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e163 (82.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpironolactone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e177 (93.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187 (94.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.463\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFurosemide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (16.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigoxin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (22.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eTFI: Tilburg Frailty Indicator, BMI: body mass index, BNP: B-type naturietic peptide, NYHA: New York Heart Association functional class, LVEF: left ventricle ejection fraction, ACEI: angiotensin converting enzyme inhibitors, ARB: angiotensin receptor blocker, ARNI: angiotensin receptor neprilysin inhibitor.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe median follow-up duration was 21 months (interquartile range 15\u0026ndash;27), during which 44 patients experienced all-cause mortality. Univariable Cox regression analysis identified TFI score, advanced age, ischemic heart disease, serum potassium levels, and NYHA class III\u0026ndash;IV as significant predictors of all-cause mortality (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These variables were included in a multivariable Cox proportional hazards model, which showed that TFI score (HR 1.39 [95% CI 1.27\u0026ndash;1.52], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and NYHA class III\u0026ndash;IV (HR 2.01 [95% CI 1.01\u0026ndash;4.01], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048) were independent predictors of all-cause mortality after adjustment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Using the same univariable-multivariable Cox regression approach, TFI score (HR 1.28 [95% CI 1.18\u0026ndash;1.39], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) also emerged as an independent predictor of 1-year HF-related rehospitalization following CRT implantation, after adjusting for baseline comorbidities and biochemical variables (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate Cox regression analysis for risk of all-cause death.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003emultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR [95%CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR [95%CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTFI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.44 [1.31\u0026ndash;1.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.39 [1.27\u0026ndash;1.52]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.03 [1.00-1.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.03 [1.00-1.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex: female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.22 [0.63\u0026ndash;2.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91 [0.83\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.11 [0.61\u0026ndash;2.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.47 [0.78\u0026ndash;2.78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.73 [ 0.39\u0026ndash;1.35]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.18 [1.19\u0026ndash;3.98]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.76 [0.95\u0026ndash;3.24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99 [0.98-1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99 [0.98\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99 [0.97-1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum creatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 [0.98\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.45 [0.22\u0026ndash;0.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.75 [0.39\u0026ndash;1.47]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePro BNP (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 [1.00\u0026ndash;1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA III-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.05 [1.57\u0026ndash;5.93]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.01 [1.01\u0026ndash;4.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.04 [0.95\u0026ndash;1.13]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQRS\u0026thinsp;\u0026gt;\u0026thinsp;150ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.13 [0.61\u0026ndash;2.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI or ARB or ARNI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.46 [0.65\u0026ndash;3.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.37 [0.58\u0026ndash;3.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpironolactone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.35 [0.33\u0026ndash;5.56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFurosemide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.82 [0.91\u0026ndash;3.61]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigoxin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.04 [0.50\u0026ndash;2.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eTFI: Tilburg Frailty Indicator, BMI: body mass index, NYHA: New York Heart Association functional class, LVEF: left ventricle ejection fraction, ACEI: angiotensin converting enzyme inhibitors, ARB: angiotensin receptor blocker, ARNI: angiotensin receptor neprilysin inhibitor.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate Cox regression analysis for HF-related rehospitalization\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003emultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR [95%CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR [95%CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTFI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.30 [1.22\u0026ndash;1.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.28 [1.18\u0026ndash;1.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02 [1.00-1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.01 [0.99\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex: female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.53 [0.97\u0026ndash;2.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99 [0.93\u0026ndash;1.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92 [0.61\u0026ndash;1.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.88 [0.54\u0026ndash;1.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.70 [ 0.45\u0026ndash;1.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.98 [1.31\u0026ndash;2.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.82 [1.20\u0026ndash;2.76]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 [0.99\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99 [0.98-1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99 [0.97-1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99 [0.98-1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum creatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 [0.99\u0026ndash;1.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.04 [0.65\u0026ndash;1.66]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePro BNP (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 [1.00\u0026ndash;1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00 [1.00\u0026ndash;1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA III-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.80 [1.19\u0026ndash;2.74]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.54 [1.01\u0026ndash;2.36]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01 [0.96\u0026ndash;1.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQRS\u0026thinsp;\u0026gt;\u0026thinsp;150ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.22 [0.79\u0026ndash;1.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI or ARB or ARNI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.14 [0.67\u0026ndash;1.93]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.19 [0.67\u0026ndash;2.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpironolactone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.09 [0.44\u0026ndash;2.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFurosemide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.58 [0.97\u0026ndash;2.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigoxin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92 [0.55\u0026ndash;1.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eTFI: Tilburg Frailty Indicator, BMI: body mass index, NYHA: New York Heart Association functional class, LVEF: left ventricle ejection fraction, ACEI: angiotensin converting enzyme inhibitors, ARB: angiotensin receptor blocker, ARNI: angiotensin receptor neprilysin inhibitor.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDuring follow-up, 34 deaths occurred among frail patients compared to 10 in the non-frail group, resulting in a significantly lower survival probability in the frailty cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA; log-rank test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Restricted cubic spline analysis demonstrated a near-linear positive relationship between TFI scores and the HR for all-cause mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB; p for non-linear\u0026thinsp;=\u0026thinsp;0.5709). The RSF method identified the TFI score as the most important variable for predicting all-cause mortality in HF patients undergoing CRT implantation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWithin one year following CRT implantation, patients with frailty experienced 63 HF-related rehospitalization events compared to 28 in non-frail patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA; log-rank test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The association between TFI scores and the hazard ratio for HF-related rehospitalization was approximately linear (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB; p for non-linear\u0026thinsp;=\u0026thinsp;0.1658). The RSF method identified the TFI score as the most important variable for predicting 1-year HF-related rehospitalization in HF patients undergoing CRT implantation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eHerein, we found that the TFI score was a significant independent predictor of all-cause mortality and 1-year HF-related rehospitalization following CRT implantation in patients with HF. Moreover, the hazard ratios for these events increased nearly linearly with each unit increase in TFI score, with the TFI score being the most significant variable among all evaluated predictors.\u003c/p\u003e \u003cp\u003eThe rising prevalence of chronic conditions such as diabetes, hypertension, and coronary artery disease, combined with improved survival rates among patients with heart disease, has driven a sustained global increase in HF incidence, particularly in aging populations [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Frailty, a medical syndrome characterized by reduced physiological reserve and impaired stress resilience, shares pathophysiological mechanisms with HF through aging-related processes. Epidemiological studies report frailty prevalence ranging from 30% to 74% in chronic HF cohorts, strongly correlating with HF severity [\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In the present study, 47.9% of HF patients with LVEF\u0026thinsp;\u0026le;\u0026thinsp;35% met frailty criteria, consistent with published rates of 31% to 47% in populations with LVEF\u0026thinsp;\u0026lt;\u0026thinsp;40% [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrailty accelerates HF progression, leading to worse prognosis, severe functional impairment, reduced quality of life, and higher all-cause mortality. A previous meta analysis reported a 69% increase in all-cause mortality risk in patients with both frailty and HF. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Vid\u0026aacute;n et al. reported a 45% increase in mortality per unit rise in the Fried frailty phenotype score [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Meanwhile, Bottle et al. found that 39% of HF patients with frailty experienced at least one rehospitalization within a 1-year follow-up [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Our findings corroborate these trends; the TFI score was a significant predictor of all-cause mortality and 1-year HF-related rehospitalization following CRT implantation in patients with HF. Frail patients exhibited a 4.02-fold higher mortality and a 2.57-fold higher rehospitalization rate, with hazard ratios increasing nearly linearly across TFI scores. Notably, the TFI score was the most important predictor of prognosis among all evaluated variables. We attribute this to the physiological decline in frail patients, including sarcopenia, cognitive impairment, and dysregulation of inflammatory pathways, which impairs the myocardial response to CRT and diminishes the efficacy of cardiac resynchronization [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Frailty can impair physical function and mobility, limiting patients\u0026rsquo; participation in rehabilitation and adherence to management guidelines, which may worsen outcomes [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It is also associated with neuroendocrine and immune alterations that lead to inflammation, oxidative stress, and autonomic dysregulation [\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These factors may contribute to cardiac remodeling and deterioration following CRT.\u003c/p\u003e \u003cp\u003eThe TFI score quantifies frailty across physical, psychological, and social domains that influence CRT response. In the physical domain, sarcopenia may impair ventricular-arterial coupling, reducing cardiac output augmentation after CRT. Psychological factors such as depression and anxiety can increase the risk of ventricular arrhythmias through autonomic dysregulation. In addition, low social support may be associated with poorer adherence to device monitoring. To our knowledge, this is the first study to quantify the relationship between TFI score and mortality and rehospitalization gradient post-CRT. Furthermore, ischemic heart disease and advanced NYHA class, established predictors of CRT mortality, likely reflect reduced viable myocardium, consistent with prior mechanistic studies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the established efficacy of CRT in improving cardiac function, concomitant frailty substantially modifies its therapeutic effectiveness. Therefore, integrating multidimensional frailty assessment into pre-implantation evaluation is imperative. Systematic frailty phenotyping could refine patient selection algorithms for CRT implantation and improve prognostic stratification. Moreover, implementing intensified follow-up protocols with early targeted interventions, such as nutritional optimization and reduction of polypharmacy, may help mitigate adverse outcomes in this high-risk subgroup [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNonetheless, this study has several limitations that should be taken into account. First, as a retrospective observational study, it may be subject to imbalances due to the limited sample size. Second, methodological differences in frailty assessment tools could introduce significant heterogeneity in outcome measurement, limiting comparability across studies. Third, longitudinal changes in frailty following CRT implantation were not systematically evaluated, potentially obscuring dynamic interactions between device-mediated reverse remodeling and frailty progression. Lastly, specific interventions targeting frailty were not addressed in the present study.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe TFI score was strongly associated with all-cause mortality and 1-year HF-related rehospitalization following CRT implantation in patients with HF. Moreover, these unfavorable outcomes showed a nearly linear relationship with increasing frailty scores.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor\u0026apos;s contribution:\u003c/strong\u003e Shujuan Dong, and Baopeng Tang designed the study. Shujuan Dong collected, analyzed the data statistically, and wrote the main manuscript text. All authors contributed to the writing of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data:\u0026nbsp;\u003c/strong\u003eBaopeng Tang\u0026nbsp;could be contacted if the data from this study was requested.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThere was no conflict of interest between authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlobal national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990\u0026ndash;2017: a systematic analysis for the Global Burden of Disease Study 2017. \u003cem\u003eLancet\u003c/em\u003e \u003cb\u003e392\u003c/b\u003e (10159), 1789\u0026ndash;1858 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVirani, S. S. et al. Heart disease and stroke statistics\u0026ndash;2020 update: a report from the American Heart Association. \u003cem\u003eCirculation\u003c/em\u003e \u003cb\u003e141\u003c/b\u003e (9), e139\u0026ndash;e596 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoger, V. L. Epidemiology of Heart Failure: A Contemporary Perspective. \u003cem\u003eCirc. Res.\u003c/em\u003e \u003cb\u003e128\u003c/b\u003e (10), 1421\u0026ndash;1434 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang, A. S. et al. Cardiac\u0026ndash;resynchronization therapy for mild\u0026ndash;to\u0026ndash;moderate heart failure. \u003cem\u003eN Engl. J. Med.\u003c/em\u003e \u003cb\u003e363\u003c/b\u003e (25), 2385\u0026ndash;2395 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuschitzka, F. et al. Cardiac resynchronization therapy in heart failure with a narrow QRS complex. \u003cem\u003eN Engl. J. Med.\u003c/em\u003e \u003cb\u003e369\u003c/b\u003e, 13951405 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlikson, M. et al. 2021 ESC Guidelines on cardiac pacing and cardiac resynchronization therapy. \u003cem\u003eEur. Heart J.\u003c/em\u003e \u003cb\u003e42\u003c/b\u003e (35), 3427\u0026ndash;3520 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbreu, A. et al. Predictors of response to cardiac resynchronization therapy: A prospective cohort study. \u003cem\u003eRev. Port Cardiol.\u003c/em\u003e \u003cb\u003e36\u003c/b\u003e (6), 417\u0026ndash;425 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaqvi, S. Y. et al. Non-response to Cardiac Resynchronization Therapy. \u003cem\u003eCurr. Heart Fail. Rep.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e (5), 315\u0026ndash;321 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFried, L. P. et al. Frailty in older adults: evidence for a phenotype. \u003cem\u003eJ. Gerontol. Biol. Sci. Med. Sci.\u003c/em\u003e \u003cb\u003e56\u003c/b\u003e (3), M146\u0026ndash;156 (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVitale, C. et al. Heart Failure Association/European Society of Cardiology position paper on frailty in patients with heart failure. \u003cem\u003eEur. J. Heart Fail.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e (11), 1299\u0026ndash;1305 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShinmura, K. Cardiac senescence, heart failure, and frailty: a triangle in elderly people. \u003cem\u003eKeio J. Med.\u003c/em\u003e \u003cb\u003e65\u003c/b\u003e (2), 25\u0026ndash;32 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTalha, K. M. et al. Frailty and heart failure: State-of-the-art review. \u003cem\u003eJ. Cachexia Sarcopenia Muscle\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e (5), 1959\u0026ndash;1972 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang, X. et al. Impact of frailty on mortality and hospitalization in chronic heart failure: a systematic review and meta\u0026ndash;analysis. \u003cem\u003eJ. Am. Heart Assoc.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e (23), e008251 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanders, N. A. et al. The frailty syndrome and outcomes in the TOPCAT trial. \u003cem\u003eEur. J. Heart Fail.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e (11), 1570\u0026ndash;1577 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, Y. et al. Frailty and clinical outcomes in heart failure: a systematic review and meta\u0026ndash;analysis. \u003cem\u003eJ. Am. Med. Dir. Assoc.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e (11), 1003\u0026ndash;1008e1 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBottle, A. et al. Frailty and co\u0026ndash;morbidity predict first hospitalisation after heart failure diagnosis in primary care: population\u0026ndash;based observational study in England. \u003cem\u003eAge Ageing\u003c/em\u003e. \u003cb\u003e48\u003c/b\u003e (3), 347\u0026ndash;354 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUchmanowicz, I. et al. Frailty and the risk of all\u0026ndash;cause mortality and hospitalization in chronic heart failure: a meta\u0026ndash;analysis. \u003cem\u003eESC Heart Fail.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e (6), 3427\u0026ndash;3437 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDominguez-Rodriguez, A. et al. The impact of frailty in older patients with non-ischaemic cardiomyopathy after implantation of cardiac resynchronization therapy defibrillator. \u003cem\u003eEuropace\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e (4), 598\u0026ndash;602 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMlynarska, A. et al. Modified frailty as a novel factor in predicting the response to cardiac resynchronization in the elderly population. \u003cem\u003eClin. Interv Aging\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e, 437\u0026ndash;443 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMilner, A. et al. Utility of the Modified Frailty Index to Predict Cardiac Resynchronization Therapy Outcomes and Response. \u003cem\u003eAm. J. Cardiol.\u003c/em\u003e \u003cb\u003e125\u003c/b\u003e (7), 1077\u0026ndash;1082 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSon, Y. J. et al. Prevalence and factors associated with pre-frailty and frailty among Korean older adults with heart failure. \u003cem\u003eJ. Adv. Nurs.\u003c/em\u003e \u003cb\u003e78\u003c/b\u003e (10), 3235\u0026ndash;3246 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMlynarska, A., Mlynarski, R. \u0026amp; Golba, K. S. Frailty as a predictor of negative outcomes after cardiac resynchronization therapy. \u003cem\u003ePacing Clin. Electrophysiol.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e (6), 572\u0026ndash;577 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan, H. et al. Frailty and risk for heart failure in older adults: the health, aging, and body composition study. \u003cem\u003eAm. Heart J.\u003c/em\u003e \u003cb\u003e166\u003c/b\u003e (5), 887\u0026ndash;894 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVid\u0026aacute;n, M. T. et al. Prevalence and prognostic impact of frailty and its components in non\u0026ndash;dependent elderly patients with heart failure. \u003cem\u003eEur. J. Heart Fail.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e (7), 869\u0026ndash;875 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKleipool, E. E. et al. Frailty in older adults with cardiovascular disease: cause, effect or both ? \u003cem\u003eAging Dis.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e (3), 489\u0026ndash;497 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSze, S. et al. Identification of frailty in chronic heart failure. \u003cem\u003eJACC Heart Fail.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e (4), 291\u0026ndash;302 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePandey, A. et al. Frailty Is Intertwined With Heart Failure: Mechanisms, Prevalence, Prognosis, Assessment, and Management. \u003cem\u003eJACC Heart Fail.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e (12), 1001\u0026ndash;1011 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBencivenga, L. et al. Role of frailty on cardiac rehabilitation in hospitalized older patients. \u003cem\u003eAging Clin. Exp. Res.\u003c/em\u003e \u003cb\u003e34\u003c/b\u003e (11), 2675\u0026ndash;2682 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsukakoshi, D. et al. Clinical perspectives on cardiac rehabilitation after heart failure in elderly patients with frailty: a narrative review. \u003cem\u003eTher. Clin. Risk Manag\u003c/em\u003e. \u003cb\u003e18\u003c/b\u003e, 1009\u0026ndash;1028 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYao, X., Li, H. \u0026amp; Leng, S. X. Inflammation and immune system alterations in frailty. \u003cem\u003eClin. Geriatr. Med.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e (1), 79\u0026ndash;87 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClegg, A. \u0026amp; Hassan-Smith, Z. Frailty and the endocrine system. \u003cem\u003eLancet Diabetes Endocrinol.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e (9), 743\u0026ndash;752 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDebain, A. et al. Frail older adults are more likely to have auto nomic dysfunction: a systematic review and meta-analysis. \u003cem\u003eAgeing Res. Rev.\u003c/em\u003e \u003cb\u003e87\u003c/b\u003e, 101925 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRickard, J. et al. Predictors of response to cardiac resynchronization therapy: A systematic review. \u003cem\u003eInt. J. Cardiol.\u003c/em\u003e \u003cb\u003e225\u003c/b\u003e, 345\u0026ndash;352 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLinde, C. et al. Predictors of short-term clinical response to cardiac resynchronization therapy. \u003cem\u003eEur. J. Heart Fail.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e (8), 1056\u0026ndash;1063 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcDonagh, T. A. et al. ESC scientific document Group. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. \u003cem\u003eEur. Heart J.\u003c/em\u003e \u003cb\u003e42\u003c/b\u003e, 3599\u0026ndash;3726 (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Heart failure, Cardiac resynchronization therapy, Tilburg Frailty Indicator, Frailty","lastPublishedDoi":"10.21203/rs.3.rs-7847402/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7847402/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFrailty in patients with heart failure (HF) is associated with significantly adverse clinical outcomes. Emerging evidence suggests that the Tilburg Frailty Indicator (TFI) score may help with prognosis stratification following cardiac resynchronization therapy (CRT) implantation. Nonetheless, the specific associations between the TFI score and post-procedural mortality or rehospitalization remain elusive.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatients with HF who underwent CRT at Henan Provincial People\u0026rsquo;s Hospital, the First Affiliated Hospital of Xinjiang Medical University, and Henan Provincial Chest Hospital, completed the TFI questionnaire preoperatively, and had complete clinical records were retrospectively enrolled between January 2022 and May 2024. Cox proportional hazards regression analyses were used to evaluate the association between the TFI score and both all-cause mortality and HF-related rehospitalization following CRT implantation. This association was visualized using restricted cubic spline (RCS) curves. The predictive value of the TFI score for these outcomes was further assessed using a random survival forest (RSF) approach.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe TFI score was an independent predictor of all-cause mortality (Hazard Ratio [HR]1.39 [95% Confidence Interval [CI] 1.27\u0026ndash;1.52], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and one-year HF-related rehospitalization (HR 1.28 [95% CI 1.18\u0026ndash;1.39], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) following CRT implantation. In the frailty cohort, there was a significantly lower survival probability (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with a near-linear positive relationship between the HR and TFI score (\u003cem\u003ep\u003c/em\u003e for non-linearity\u0026thinsp;=\u0026thinsp;0.5709), and the TFI score emerged as the most important variable for predicting all-cause mortality. Patients with frailty experienced more HF-related rehospitalizations at the 1-year follow-up (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with a similarly near-linear positive association with TFI scores (\u003cem\u003ep\u003c/em\u003e for non-linearity\u0026thinsp;=\u0026thinsp;0.1658), which was also the most important predictive variable.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe TFI score emerged as the most significant independent predictor of mortality and rehospitalization following CRT implantation in patients with HF.\u003c/p\u003e","manuscriptTitle":"Tilburg Frailty Indicator Predicts Death and Rehospitalization after Cardiac Resynchronization Therapy in Patients with Heart Failure","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 16:16:27","doi":"10.21203/rs.3.rs-7847402/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"701e9f29-7225-4f3b-8c4f-e6d351c2312c","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59429396,"name":"Health sciences/Cardiology"},{"id":59429397,"name":"Health sciences/Diseases"},{"id":59429398,"name":"Health sciences/Medical research"},{"id":59429399,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-01-12T13:39:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-15 16:16:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7847402","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7847402","identity":"rs-7847402","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}