Assessing proper patient-reported outcomes after recent discharge in acute heart failure – A Longitudinal Study

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Patient-reported outcome measures (PROMs) offer valuable insights into patient experience and may support treatment decisions. This study aimed to assess PROMs in patients hospitalized for acute decompensated HF at multiple time points after discharge to evaluate the feasibility of repeated PROM assessments and to capture changes in health status, medication management, and quality of life. Methods and Results Consecutive patients hospitalized for decompensated HF completed PROMs at 30 days, 6 months, and 12 months post-discharge. Collected data included demographics, comorbidities, hospitalizations, medication use, and PROMs using the KCCQ-12, PROMIS Physical Function Shortform 4a (PROMIS-4a), and PHQ-2. Generic quality of life was assessed with the EQ-5D. Among 99 patients (median age 66 years, 33% women, 90% NYHA III/IV on admission, 89% rehospitalized for HF within 12 months), all PROM instruments indicated substantial disease burden. Strong parallel reliabilities were observed (Cronbach’s alpha 0.75–0.90). PROMIS-4a was associated with age (p < 0.01) and sex (p = 0.04), while KCCQ-12 was associated with age (p = 0.04). All PROM scores improved during follow-up. Cardiovascular events—including transplantation, rehospitalization, emergency treatment, and therapy failure—did not significantly affect PROM trajectories. Conclusion Repeated assessment of patient-reported outcomes after HF decompensation is feasible. Using one or two PROM instruments may be sufficient, as the measures showed parallel development. Preliminary findings indicate that PROMs capture aspects of patient health not fully explained by HF severity or treatment modalities. Acute heart failure decompensation patient-reported outcomes KCCQ-12 PHQ-2 quality of life longitudinal study Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Heart failure (HF), with its high morbidity and mortality, is associated with a reduced quality of life (QoL) [ 1 ]. Optimal management requires knowledge of the patients’ experience of the disease and patient involvement in care. This includes self-monitoring of signs and symptoms, intensive follow-up, and adherence to a multidisciplinary care plan [ 2 , 3 ]. Patient-reported outcome measures (PROMs) are questionnaires that collect self-reported information about subjective health, such as health-related quality of life, symptoms of anxiety and depression or symptom burden. Their collection may facilitate a more systematic person-centered approach to care in patients with heart failure [ 4 ]. In HF, PROMs and quality of life can be influenced by symptoms (e.g. dyspnoea, orthopnoea, fatigue, edema), by the disease state and its response to therapy, by side effects of therapies (e.g. dizziness), by social and mental limitations (e.g. depression), and by other factors [ 5 ]. About 20 disease-specific PROs have been used and validated in HF patients. The International Consortium for Health Outcomes Measurement (ICHOM) identified reliable and valid PROMs in patients with heart failure to align outcome measurement efforts worldwide [ 6 ]. Although the assessment of PROMs in HF appears to have immediate and rational benefits, they are not routinely used in clinical care. We report the feasibility and the patients’ opinion of implementation of the ICHOM standard set of HF patients as a longitudinal study as well as some main results of PROMs in HF patients after hospitalization due to acute heart failure or decompensation of chronic heart failure. Methods Patients We included patients with acute heart failure or decompensation of chronic heart failure with unplanned hospitalization admitted to the Heart Failure Unit at University Heart and Vascular Center Hamburg between June 2023 and February 2024. This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of the Hamburg Chamber of Physicians. Informed consent was obtained from all individual participants included in the study. All patients were ≥18 years of age, consented to participate and showed at least three clinical signs of heart failure, like dyspnea, peripheral edema, or pulmonary rales ( Supplemental Figure 1 ). Follow-up Clinical and patient-reported data were recorded at four different time points: At discharge from hospital after the end of acute treatment for the index event (T0). 30 days after the index event (T1), the PROM standard set was retrieved and the treatment parameters were recorded. This survey was repeated 6 months (T2) and 12 months (T3) after the index event. In the case of unscheduled presentations, a follow-up visit was performed for all patients and PROMs were recorded. Assessment tools Baseline data included health status, risk factors, treatments and changes in treatment (medication, interventions, surgery), demographic data, survival and hospitalization. The following PROMs according to the ICHOM standard were measured at each follow-up visit. KCCQ-12. The Kansas City Cardiomyopathy Questionnaire (KCCQ) is a new, self-administered, 23-item questionnaire that quantifies physical limitations, symptoms, self-efficacy, social interference and quality of life [8]. Questionnaire clinical summary score (KCCQ-CSS) and sub scores range from 0 to 100, with higher scores indicating fewer symptoms and physical limitations). PHQ-2. The PHQ-2 inquires about the frequency of depressed mood and anhedonia over the past 2 weeks, scoring each as 0 ("not at all") to 3 ("nearly every day"). A PHQ-2 score of 3 points was identified as the optimal cut point for screening purposes [9]. PROMIS physical function-4a . This questionnaire measures disease-specific physical health based on a four-point Likert scale from 1 (“without any difficulty”) to 4 (“with great difficulty”) [10]. Items were added up to a sum scale. EQ5D. The generic health status was examined using the second part of the EuroQol questionnaire (EQ-5D). The second part consists of a visual analogue scale (EQ VAS) with the endpoints labelled ‘best imaginable health state’ at the top and ‘worst imaginable health state’ at the bottom having numerical values of 100 and 0, respectively [11]. For analysis, we used the EQ VAS. Sample size and statistical analysis The primary aim was to investigate the feasibility and implementation of the collection of PROMs in routine clinical practice. The sample size of these pilot studies was calculated according to Vietbauer et al [7]. For all variables, descriptive statistics were computed. Depending on the variables' scale levels, N and % or median and interquartile range are reported. Correlation analysis was performed with Spearman’s rank test. Two-tailed tests of significance were considered to be significant at a p-value <0.05 and highly significant at p <0.01. Group and interaction effects of selected factors on PROMs over time were measured by mixed models. Data were analyzed with IBM SPSS version 24 for Microsoft Windows. Results Patients and Follow-up A total of 144 patients were screened for enrollment, and n = 99 were included into the study during treatment at the Heart Failure Unit. The most frequently reported heart failure symptoms were dyspnea NYHA III or IV (90%) and peripheral edema (79%). The follow-up rate after one month, six months and one year was 80%, 72% and 65% respectively. Within one year, 19 patients (19%) died ( Figure 1, Supplementary Table 1 ). Demographic data, severity of disease and therapy The sample consisted of n = 33 (33%) women. The mean age was 64 years (range 19‑87). Nearly all patients (96%) were German. The majority (59%) were married or lived in a solid partnership. Only 20% were employed. A large majority of 88 patients (89%) had been hospitalized for heart failure within 12 months prior to the current inpatient stay. Of these, 83 patients (84%) had been admitted to the hospital at least once as an emergency or had consulted the emergency department themselves. For 14% of patients it was somewhat difficult to pay their living costs, for 9% very difficult. Comorbidities such as arterial hypertension (74%) diabetes mellitus (42%), chronic lung diseases (21%) and chronic kidney disease (41%) were common. 31% of the patients were overweight and 32% were obese ( Table 1 ). HF with reduced ejection fraction (HFrEF, LVEF ≤ 40%) was most common (66%) while 24% suffered from HF with preserved ejection fraction (HFpEF, LVEF ≥ 50%). HF with mildly reduced ejection fraction (HFmrEF, LVEF 40-49%) was less frequent (10%). Reduced right ventricular function was present in half of the patients (53%). The most common high-grade valve disease was mitral valve regurgitation (23%). The use of heart failure medication was widespread. 88% of patients were taking beta-blockers, 46% SGLT-2 inhibitors, and 62% mineral corticoid receptor antagonists. Sacubitril/Valsartan was prescribed to 52%, ACE inhibitors to 20% and angiotensin II receptor antagonists to 14% (86% took one of the three drugs). Severe side-effects of heart failure medication were reported by 14% of patients. At the time of study enrollment, 15% of patients were receiving positive inotropic therapy. The median duration of hospitalization was 13 days (range 2-257 days). Twenty-three patients (23%) underwent cardiac resynchronization therapy (CRT) and 6% had a Left ventricular assist device. During the inpatient stay, 30% of patients were admitted to the intensive care unit, including five patients (5%) with unplanned admissions. Five patients (5%) received short-term mechanical circulatory support. HF therapy during follow-up The proportion of patients with NYHA class III and IV decreases from 78% to 29% between inclusion and follow-up date ( Table 2 ). Changes in heart failure medication (preparations and dosages of the four most beneficial drugs) were very frequent during follow-up. 20% of patients reported adjustments within the first 30 days, 21% within 6 months of inclusion and 25% within 12 months ( Table 3 ). During follow-up, 3 patients underwent CRT implantation. Five patients underwent LVAD implantation. Within one year, 5 patients underwent heart transplantation and 6 patients underwent valve surgery ( Figure 1 ). Results of PROMS Patients reported a mean KCCQ-12 overall score of 55.2 points (±28.3 points SD) one month after discharge. In the further follow-ups revealed KCCQ-12 overall score raised to 57.2 points (±26.4 points SD) after six months and 62.0 points (±28.5 points SD) after one year. PHQ-2 score ≥3 points was found in 20 patients (25%) after one month, and in 14 patients (18%) after six months. In the last follow-up assessment after 12 months, 13 patients (17%) achieved a PHQ ≥3 points. Mean PROMIS Physical Function Shortform 4a sum score was 12.6 (±4.8 SD) one month after discharge. In the further follow-ups mean sum scores of 13.0 (±4.9 SD) and 13.9 (±4.9 SD) were measured. EQ-5D-VAS showed a mean of 59.2 (±19.6 SD) one month after discharge and 59.1 (±21.7 SD) after six months as well as 62.8 (±21.5 SD) after one year of follow-up ( Figure 2 ). To illustrate longitudinal trajectories, Sankey plots were created for NYHA class, KCCQ-12, PROMIS-4a, and EQ-5D-VAS ( Figure 3 ). These visualizations highlight that most patients showed either relative stability or moderate improvement over 12 months, while a relevant proportion remained in lower categories of function and quality of life. In particular, the KCCQ‑12 and PROMIS-4a plots demonstrated shifts from lower to moderate or higher functional levels, confirming the mean improvements observed in these scores. In contrast, most patients in the EQ-5D-VAS remained in moderate categories, with only a subset reporting higher perceived quality of life over time. Interestingly. Regarding NYHA classification, a marked proportion of patients improved from NYHA III/IV to better classes, whereas only a minority worsened during follow-up. Patient opinion on PROMs One and six months after enrollment, patients were asked for their opinion on the assessment of PROMs. 81% and 87% respectively agreed or strongly agreed that their answers gave a good insight into how they assess various health conditions and limitations caused by their illness. 79% and 81% respectively stated that the questionnaire can help physicians to understand whether the current treatment for heart failure is successful. At both points in the survey, 76% of patients said they would like their heart failure treatment to be adjusted based on their responses. 91% and 96% of patients respectively felt they were adequately informed about the purpose of the questionnaire. Further, only 14% at both follow-up points stated that the questionnaire was too long ( Figure 4 ). Unscheduled visits An unscheduled visit was conducted for n = 9 patients. The most common reasons for unscheduled visits were progressive dyspnea, increasing edema and weakness (n=6 each, 67%). Three patients (33%) reported renal failure and cardiac arrhythmia. Patients with unscheduled visits had significantly lower KCCQ-12 sum scores (p = 0.028). In particular, the subscales 'symptom frequency' (p = 0.014) and 'social limitation' (p = 0.011) showed lower values than in the respective previous measurement. PROMIS Physical Function Shortform 4a sum score showed a similar pattern with significantly lower scors (p = 0.028) whereas the PHQ-2 score and the EQ5D-VAS did not differ significantly. Correlation between PROMs and NYHA class as well as generic PROMs and disease‑specific PROMS We found significant correlation (r = 0.572 to 0.806, p <0.001 each) between the measured values of the sum scores of all four PRO instruments at all measurement times. Interestingly, there was no significant correlation between PROMs and clinical NYHA class. One month after inclusion, there was still a trend towards a correlation of NYHA class with KCCQ-12 overall score (r = -0.217, p = 0.057) and PROMIS Physical Function Shortform 4a sum score (r = ‑0.221, p = 0.053). In contrast, there were strong correlations between the results of the disease-specific and generic PROMs (r = 0.606 to 0.765, p<0.001 each, Supplementary Table 2 ). Reliability of PROMs High parallel test reliabilities were found between the PROMs (standardized Cronbach's alpha 0.75-0.90). The internal consistency was comparable for all measurement times, indicating good retest reliability. A direct measurement of retest reliability using bivariate correlations is not possible due to the longitudinal design of the study. Influence of selected factors on PROMs over time Patients who were hospitalized again due to heart failure within one month of discharge (n = 17, 21%) had a significantly lower PROMIS Physical Function Shortform 4a sum score (p = 0.029) and tended to have lower KCCQ-12 sum score (p = 0.057) and EQ5D-VAS (p = 0.077). Emergency outpatient presentations due to heart failure within 12 months of study entry had no consistent impact on PROMs. Patients who met the composite endpoint of re-hospitalization due to heart failure or death within 12 months of study entry had lower PHQ-2 scores (p = 0.036) and EQ5D-VAS (p = 0.042) and showed a tendency towards lower KCCQ-12 sum score (p = 0.054) at the last study visit. Side effects of heart failure medication perceived as limiting by the patients themselves as well as the etiology of heart failure did not have a significant influence on the PROMs at any time. The patient age showed a general effect on the KCCQ-12 sum score (p = 0.038), which, however, remained constant over the trial visits (p=.884). No effect of patient age was seen in the three other PROMs. Men generally showed higher PROMIS Physical Function Shortform 4a sum scores (p = 0.044), with the effect remaining constant over time. Furthermore, men tended to have higher PHQ-2 scores (p = 0.082), while no influence of sex was found for KCCQ-12 and EQ5D-VAS ( Table 4 ). Mixed linear models were used to assess the effect of heart failure therapies – pharmacological treatment, cardiac surgery, and heart transplantation – on patient-reported outcome measures, adjusted for age and sex. No significant associations were found between therapy type and any PROM, nor were there significant time or interaction effects (all p > 0.05, Supplementary Table 3). Discussion Main findings This feasibility study has three main findings. Repeated collection of patient-reported outcome measures is feasible in patients with severe heart failure during and after an acute decompensation. The instruments evaluated here (PROMIS-4a, KCCQ-12, PHQ-2, EQ-5D) capture collinear information. Depending on the purpose, collection of 1-2 measures may suffice. Changes in patient-reported outcome measures are not highly influenced by heart failure events or heart failure therapies, suggesting that patient-reported outcome measures capture important additional information in patients with severe heart failure. In this study, we longitudinally evaluated the feasibility and results of the ICHOM standard set of PROMs in patients with acute heart failure or decompensated chronic heart failure. A 12‑month follow-up was performed in 65% of patients, 19% of patients had died after 12 months and 16% were lost to follow-up. Over 80% of patients agreed or strongly agreed that their answers gave a good insight into how they assess various health conditions and limitations caused by their illness. Feasibility of repeated PROM collection in patients with severe heart failure Repeated PROM collection was positively perceived by patients. In our study, three quarters of the patients (76%) stated that they would be glad to have their heart failure treatment adapted based on their answers. PROs can facilitate discussions of patient preferences and help engage patients in shared decision-making. Use of PROs to measure values, preferences, or changes in PROs can facilitate provider and patient engagement in timely discussions regarding goals of care. Examples include patient-centered palliative care discussions or, alternatively, discussions regarding interventions such as LVAD or implantable cardioverter-defibrillator therapy. In both cases, understanding the patient's perspective on current HRQOL and perceptions of treatment burden is critical to ensuring shared decision‑making. The results indicate that the promotion of shared decision-making by use of PROs would be mutually beneficial for patients and healthcare providers. How many PROMs are needed? In our study, we used a combination of four PROMs—KCCQ-12, PROMIS Physical Function Shortform 4a, PHQ-2, and EQ-5D—to assess various dimensions of health in patients with acute heart failure or decompensated chronic heart failure. The selection of these instruments reflects the need for a comprehensive yet practical approach to capture the multifaceted nature of the patient experience. Given the complexity of heart failure, which affects physical, emotional, and social well-being, using multiple PROMs allowed us to assess both disease-specific and generic aspects of health. The KCCQ-12 focused on cardiovascular symptoms and limitations, while PROMIS Physical Function assessed physical capacity. The PHQ-2 provided insights into depressive symptoms, and EQ-5D captured overall quality of life. Together, these tools ensured a broad understanding of how heart failure impacts patients across different domains. While these PROMs provided valuable data, we also considered patient burden and feasibility. Despite using four instruments, our study demonstrated that repeated PROM assessments at multiple time points (30 days, 6 months, and 12 months) were well-tolerated by patients, with high levels of engagement. However, it is worth considering that a smaller set of 2-3 PROMs could suffice in future studies without compromising the quality of the data, especially if the focus is on streamlining the assessment process. In conclusion, the combination of these four PROMs allowed us to capture a comprehensive view of health-related quality of life and functional status in heart failure patients. While our findings support the use of multiple PROMs, the number of instruments should be carefully considered based on the study’s goals and the practical considerations of patient burden. A balanced approach, combining disease-specific and generic PROMs, offers an effective way to assess the most relevant aspects of the patient experience. Added information from PROMs in patients with severe heart failure Results of PROMs may support the results of traditional endpoints, but can also weaken them. For instance, in the COAPT trial, transcatheter mitral valve repair determined a one-month mean between-group difference of 16 points in KCCQ overall summary score which was sustained over time [12]. In most pharmacological trials, including the more recent trials on sodium-glucose cotransporter 2 inhibitors, the average treatment effect on KCCQ was <5 points [13]. A notable result was the weak correlation between PROMs and clinical NYHA classification, echoing prior studies that highlight discrepancies between clinician-assigned functional status and patient-reported health status [14]. Further, a recently published study reported worse in-hospital and post-discharge patient-reported health status, but these measures were similar to HFrEF after adjustment for other clinical factors [15]. Further, no significant associations were found between therapy type (heart failure medication, cardiac surgery and interventions as well as heart transplantation). This suggests that therapy modality does not substantially influence patient-reported quality of life or psychological well-being. Variability in PROMs appears to be driven mainly by individual patient characteristics, underscoring the importance of personalized and psychosocially oriented care in heart failure management. Heart failure outcomes and survival have long been advocated as the source of medical truth. Based on our preliminary analyses, clinical outcomes and PROs reflect different aspects of a well‑being in patients with severe heart failure, and therefore both can provide important data to guide treatment decisions, such as treatment selection and evaluation of treatment efficacy. In parallel to minimizing disease progression, improving patient well-being, social functioning and quality of life is an important therapeutic goal. Measuring effects in these domains is the purpose of PROMs. Our feasibility study shows that validated PROMs can be repeatedly collected in patients with severe heart failure. By asking the same questions systematically and reproducibly over time, the PROs can validly and sensitively capture the impact of heart failure on patients' lives. Declines in KCCQ-12 or PROMIS-4a scores, for instance, could signal the need for timely therapeutic adjustments, such as modifying medication regimens or initiating palliative care. Such actionable insights underscore the importance of integrating PROMs into routine workflows, ensuring they directly inform care decisions. The use of PROMs has several limitations. Common comorbidities in patients with HF, such as obesity and lung disease, and psycho-social factors will influence quality of life and therefore affect PROMs independent of heart failure status and therapy. The use of PROMs depends on the patient's willingness and ability to participate. In our study, about a fifth of the patients who underwent screening were excluded because they were unable or unwilling to participate. Most PROMs report continuous outcomes on scales that do not always reflect linear changes. The large number of PRO instruments means that the comparability of results is more limited than for well-defined outcomes such as mortality. The observed collinearity in several validated PROMs suggests that selected PROMs may suffice for assessment of patient well-being over time. In addition, PROs cover many dimensions: symptoms, physical limitations, social limitations and quality of life. The standardization of PROM tools, as exemplified by the ICHOM set, could support cross‑institutional comparisons and improve the consistency of outcome measurement. Conclusion This feasibility study demonstrates that repeated assessment of patient-reported outcomes using validated instruments is possible in patients with severe heart failure. Collinearity of the readouts suggest that careful selection of a limited number of PROMs may allow meaningful and simplified assessment of patient well-being. Changes in PROMs were not related to heart failure therapies or events, highlighting that PROMs measure domains of well-being that are not directly linked to outcome-modifying therapies. These preliminary results underpin the value of PROMs for assessment of the quality of care in patients with heart failure. Declarations Funding: None. 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The patient health questionnaire-2: Validity of a two-item depression screener. Medical Care. 2003;41:1284–1292 https://www.healthmeasures.net/explore-measurement-systems/promis/intro-to-promis/list-of-adult-measures Group EuroQol. EuroQol–a new facility for the measurement of health related quality of life. Health Policy. 1990;16:199–208 Arnold SV, Chinnakondepalli KM, Spertus JA, Magnuson EA, Baron SJ, Kar S, Lim DS, Mishell JM, Abraham WT, Lindenfeld JA, Mack MJ, Stone GW, Cohen DJ. Health status after transcatheter mitral-valve repair in heart failure and secondary mitral regurgitation: COAPT trial. J Am Coll Cardiol. 2019;73:2123–32 Guo Z, Wang L, Yu J, Wang Y, Yang Z, Zhou C. The role of SGLT-2 inhibitors on health-related quality of life, exercise capacity, and volume depletion in patients with chronic heart failure: a meta-analysis of randomized controlled trials. Int J Clin Pharm. 2023;45:547–555 Tran AT, Chan PS, Jones PG, Spertus JA. Comparison of patient self-reported health status with clinician-assigned New York Heart Association Classification. JAMA Network Open. 2020;3:e20141319. Peters AE, Mentz RJ, Sun J-L, Harrington JL, Fudim M, Alhanti B, Hernandez AF, Butler J, Starling RC, Greene SJ. Patient-reported and Clinical Outcomes Among Patients Hospitalized for Heart Failure With Reduced Versus Preserved Ejection Fraction. J Cardiac Fail. 2022;28:1652–1660 Tables Table 1: Baseline characteristics Baseline characteristics (n=99) N ( % ) or Median ( IQR ) Demographic data Age 66 ( 47 – 85 ) Female sex 33 ( 33) Body mass index [kg m -2 ] 28 ( 7 ) Current smoker 6 (6) Former smoker 62 (63) Duration of hospital stay [days] 13 (1 – 29) Left ventricular function – LVEF >50% (HFpEF) 24 ( 24 ) 40-50% (HFmrEF) 10 ( 10 ) <40% (HFrEF) 65 ( 66 ) Right ventricular function – TAPSE Normal (TAPSE ≥16 mm) 33 ( 39 ) Reduced (TAPSE <16 mm) 1 ( 61) Severe valve disorders Severe mitral regurgitation 23 ( 23 ) Severe mitral stenosis 2 ( 2 ) Severe tricuspid regurgitation 14 ( 14 ) Severe aortic valve regurgitation 2 ( 2 ) Severe aortic valve stenosis 3 ( 3 ) Heart failure medication ACE inhibitor 20 (20) Angiotensin II receptor antagonist 14 (14) Beta blockers 87 (88) Mineral corticoid receptor antagonists 61 (62) Sacubitril/Valsartan 51 (52) Loop diuretics 88 (89) SGLT-2 inhibitor 45 (46) Symptoms at inclusion Dyspnoe NYHA III/IV 91 ( 92 ) Orthopnoe 45 ( 45 ) Fatigue 81 ( 82 ) Pulmonary congestion 54 ( 54 ) Peripheral edema 80 ( 81 ) Cervical venous congestion, ascites or intestinal congestion 45 ( 45 ) Morbidity History of Atrial fibrillation 54 ( 55 ) Current treatment because of Myocardial infarction 6 ( 6 ) History of Myocardial infarction 25 ( 25 ) Arterial hypertension 73 ( 74 ) Diabetes mellitus 42 ( 42 ) Chronic lung disease 21 ( 21 ) Renal failure 51 ( 51 ) not requiring dialysis 36 ( 36 ) requiring dialysis 15 ( 15 ) Obesity 32 (32) Devices ICD 19 (19) CRT-P or CRT-D 23 (23) LVAD 6 (6) Details of index hospital stay Cardiac surgery during hospital stay 18 (18) Unplanned ICU stay 5 (5) Mechanical circulatory support (Impella, ECMO, ECMella) 5 (5) Table 2: NYHA class NYHA class Baseline 30 days 6 months 12 months N % N % N % N % NYHA I 3 3.0 9 11.4 11 13.9 11 13.9 NYHA II 19 19.2 39 49.4 31 39.2 29 36.7 NYHA III 42 42.4 20 25.3 23 29.1 21 26.6 NYHA IV 35 35.4 8 10.1 4 5.1 2 2.5 Missing 0 0.0 3 3.8 2 2.8 1 1.6 Total 99 100.0 79 100.0 71 100.0 64 100.0 Table 3: Clinical Follow-up data Clinical follow-up data 30 days 6 months 12 months N % N % N % Rehospitalization due to heart failure 17 21.5 19 26.8 9 14.1 Consultation of the emergency unit due to heart failure 15 19.0 14 19.7 8 12.7 Severe side effects due to heart failure medication 12 15.2 6 8.5 7 10.9 Changes in heart failure medication* - therein… 16 20.3 15 21.1 16 25.0 Additional drug(s) 2 2.5 6 8.5 4 6.3 Medication(s) discontinued 3 3.8 3 4.2 5 7.8 Dose increased 9 11.4 4 5.6 3 4.7 Dose reduced 2 2.5 2 2.8 4 6.3 Changes in diuretic medication - therein… 0 0.0 4 5.6 1 1.6 Additional drug(s) 1 1.3 1 1.4 2 3.1 Medication(s) discontinued 5 6.3 1 1.4 0 0.0 Dose increased 1 1.3 2 2.8 1 1.6 Dose reduced 0 0.0 4 5.6 1 1.6 *”Magic 4” and Vericiguat Table 4: Influence of selected factors on PROMs over time (mixed models ) EQ-5D PROMIS PHQ2 KCCQ-12 Group Interaction Group Interaction Group Interaction Group Interaction ℇ 2 p ℇ 2 p ℇ 2 p ℇ 2 p ℇ 2 p ℇ 2 p ℇ 2 p ℇ 2 p HF medication Side effects <.01 .50 .01 .51 <.01 .65 .01 .52 <.01 .98 <.01 .65 <.01 .88 .02 .32 Patient's age <.01 .73 .02 .40 .12 <.01 .01 .48 .04 .12 .02 .34 .07 .04 <.01 .88 Patient's sex .02 .27 <.01 .85 .06 .04 .01 .44 .05 .08 <.01 .69 .04 .12 <.01 .58 Rehospitalization <.01 .66 .01 .66 .01 .41 <.01 .82 <.01 .75 .01 .54 .02 .28 .01 .50 Rehospitalization or death <.01 .61 <.01 .63 .02 .32 .01 .40 <.01 .78 <.01 .65 .02 .23 .01 .54 Emergency treatment .01 .48 .01 .53 .01 .48 <.01 .88 .03 .23 .01 .59 .04 .13 .01 .49 Additional Declarations No competing interests reported. Supplementary Files SuppFig1.png Figure S1: Flowchart of patient screening and enrollment. This diagram illustrates the recruitment process, including the total number of patients screened, the specific inclusion and exclusion criteria applied, and the final number of participants included in the study. SupplementaryTables.docx 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-8722112","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":587706108,"identity":"57d2d787-03b5-437d-b157-20604c389acc","order_by":0,"name":"Tobias Wagner","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYFAD9gZmIMlMWCEPgnWAZC0SCURqsWdvYJP48euOnPnMN8YGHxis5QjbwnOATbK375mxzO0c48QZDOnGhLVIJLDd4O05nDhDOsf4MA/D4cQGYrTc/NtzuH6G5Bnjw38YDtcTpeU2z4/DCRISPMbJDAyHEwg77MzB9t+yDYcNZ/CkFRv2GKQbErSFvb35sOGbP4flJdgPb5b4UWEtT9AWBgbGBgbGNhjHgAgNEPCHaJWjYBSMglEwEgEADzg37uf+njcAAAAASUVORK5CYII=","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":true,"prefix":"","firstName":"Tobias","middleName":"","lastName":"Wagner","suffix":""},{"id":587706109,"identity":"4ce58911-ad11-4c20-97bc-88640ae379fe","order_by":1,"name":"Linda Zhou","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Linda","middleName":"","lastName":"Zhou","suffix":""},{"id":587706110,"identity":"f9f24435-b39b-4c6a-8e33-b02fa8808e86","order_by":2,"name":"Christina Magnussen","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Christina","middleName":"","lastName":"Magnussen","suffix":""},{"id":587706111,"identity":"9585222d-b76d-458e-9516-239149721365","order_by":3,"name":"Herrmann Reichenspurner","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Herrmann","middleName":"","lastName":"Reichenspurner","suffix":""},{"id":587706112,"identity":"9e4ba39f-baf8-4710-a20d-75c0b34091f8","order_by":4,"name":"Paulus Kirchhof","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Paulus","middleName":"","lastName":"Kirchhof","suffix":""},{"id":587706113,"identity":"055dfabc-4b8f-430f-a171-2348da4f27f8","order_by":5,"name":"Hanno Grahn","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Hanno","middleName":"","lastName":"Grahn","suffix":""}],"badges":[],"createdAt":"2026-01-28 14:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8722112/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8722112/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102297715,"identity":"c5d0b59e-ca65-443d-bf9e-8722b51adb6b","added_by":"auto","created_at":"2026-02-10 10:28:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10874,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInterventional and surgical therapy of heart failure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePercentage of patients who underwent interventional or surgical cardiac therapy one month, six months, and twelve months after the index event.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8722112/v1/a5755ee5720ebfc7218ed0b0.png"},{"id":102297714,"identity":"5a4cda79-6e70-4d3c-9248-6df004f0769d","added_by":"auto","created_at":"2026-02-10 10:28:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":47379,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDevelopment of summarized PROM readouts one year after discharge\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1A\u003c/strong\u003eKCCQ-12 sum scale and subscales physical function, symptom scale, quality of life, and social support. \u003cstrong\u003e1B \u003c/strong\u003eMean PHQ2-score and percentage of patients with PHQ2-score ≥3 pts.\u003cstrong\u003e 1C \u003c/strong\u003eEQ5D visual analogue scale.\u003cstrong\u003e 1D \u003c/strong\u003ePROMIS Physical Function Shortform 4a sum scale.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-8722112/v1/9c8c6b25da30025695dc061d.png"},{"id":102297653,"identity":"dbdb7363-5abf-4e24-b4e0-d39a1d495b65","added_by":"auto","created_at":"2026-02-10 10:28:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":102640,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSankey plots of KCCQ-12, EQ-5D VAS, PROMIS Physical Function Shortform 4a, and NYHA class.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data was aggregated for the Sankey plots. The KCCQ-12 and EQ-5D VAS were divided into tertiles, the PROMIS Physical Function Shortform 4a was divided into quartiles, and the division into four NYHA classes was retained.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8722112/v1/df42e72b81abd93ac6698b7a.png"},{"id":102398609,"identity":"1a69ad19-84b6-4d25-b622-6be9f0f60de2","added_by":"auto","created_at":"2026-02-11 10:24:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":15930,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePatient perception of the patient-reported outcome measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient percepton on PROMs one month after discharge. Answers were dichotomized (agree/strongly agree vs. disagree/strongly disagree).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-8722112/v1/689182baa2af54c4366f632e.png"},{"id":102399438,"identity":"e7dc6835-3745-4949-ae55-29e8c402e51a","added_by":"auto","created_at":"2026-02-11 10:34:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1403172,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8722112/v1/708ab616-df60-4a6b-b3d2-56aebac22fb2.pdf"},{"id":102297789,"identity":"85214c3b-804e-4523-8d8c-c2c3d58e0a95","added_by":"auto","created_at":"2026-02-10 10:29:10","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":75148,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S1: Flowchart of patient screening and enrollment.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis diagram illustrates the recruitment process, including the total number of patients screened, the specific inclusion and exclusion criteria applied, and the final number of participants included in the study.\u003c/p\u003e","description":"","filename":"SuppFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8722112/v1/798dc90d0b56d74d5f4582a9.png"},{"id":102260888,"identity":"837d0411-0c05-4347-ae4c-f6c262f23c91","added_by":"auto","created_at":"2026-02-10 00:35:42","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18840,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8722112/v1/856f0fbb0d74fab555faa054.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing proper patient-reported outcomes after recent discharge in acute heart failure – A Longitudinal Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHeart failure (HF), with its high morbidity and mortality, is associated with a reduced quality of life (QoL) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Optimal management requires knowledge of the patients\u0026rsquo; experience of the disease and patient involvement in care. This includes self-monitoring of signs and symptoms, intensive follow-up, and adherence to a multidisciplinary care plan [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatient-reported outcome measures (PROMs) are questionnaires that collect self-reported information about subjective health, such as health-related quality of life, symptoms of anxiety and depression or symptom burden. Their collection may facilitate a more systematic person-centered approach to care in patients with heart failure [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In HF, PROMs and quality of life can be influenced by symptoms (e.g. dyspnoea, orthopnoea, fatigue, edema), by the disease state and its response to therapy, by side effects of therapies (e.g. dizziness), by social and mental limitations (e.g. depression), and by other factors [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. About 20 disease-specific PROs have been used and validated in HF patients. The International Consortium for Health Outcomes Measurement (ICHOM) identified reliable and valid PROMs in patients with heart failure to align outcome measurement efforts worldwide [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Although the assessment of PROMs in HF appears to have immediate and rational benefits, they are not routinely used in clinical care. We report the feasibility and the patients\u0026rsquo; opinion of implementation of the ICHOM standard set of HF patients as a longitudinal study as well as some main results of PROMs in HF patients after hospitalization due to acute heart failure or decompensation of chronic heart failure.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included patients with acute heart failure or decompensation of chronic heart failure with unplanned hospitalization admitted to the Heart Failure Unit at University Heart and Vascular Center Hamburg between June 2023 and February 2024. This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of the Hamburg Chamber of Physicians. Informed consent was obtained from all individual participants included in the study. All patients were \u0026ge;18 years of age, consented to participate and showed at least three clinical signs of heart failure, like dyspnea, peripheral edema, or pulmonary rales (\u003cem\u003eSupplemental Figure 1\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFollow-up\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical and patient-reported data were recorded at four different time points:\u0026nbsp;\u003c/p\u003e\n\u003col class=\"decimal_type\"\u003e\n \u003cli\u003eAt discharge from hospital after the end of acute treatment for the index event (T0).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e30 days after the index event (T1), the PROM standard set was retrieved and the treatment parameters were recorded.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThis survey was repeated 6 months (T2) and\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e12 months (T3) after the index event.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eIn the case of unscheduled presentations, a follow-up visit was performed for all patients and PROMs were recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment tools\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline data included health status, risk factors, treatments and changes in treatment (medication, interventions, surgery), demographic data, survival and hospitalization. The following PROMs according to the ICHOM standard were measured at each follow-up visit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKCCQ-12.\u0026nbsp;\u003c/strong\u003eThe Kansas City Cardiomyopathy Questionnaire (KCCQ) is a new, self-administered, 23-item questionnaire that quantifies physical limitations, symptoms, self-efficacy, social interference and quality of life [8]. Questionnaire clinical summary score (KCCQ-CSS) and sub scores range from 0 to 100, with higher scores indicating fewer symptoms and physical limitations).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePHQ-2.\u003c/strong\u003e The PHQ-2 inquires about the frequency of depressed mood and anhedonia over the past 2 weeks, scoring each as 0 (\u0026quot;not at all\u0026quot;) to 3 (\u0026quot;nearly every day\u0026quot;). A PHQ-2 score of 3 points was identified as the optimal cut point for screening purposes [9].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePROMIS physical function-4a\u003c/strong\u003e. This questionnaire\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003emeasures disease-specific physical health based on a four-point Likert scale from 1 (\u0026ldquo;without any difficulty\u0026rdquo;) to 4 (\u0026ldquo;with great difficulty\u0026rdquo;) [10]. Items were added up to a sum scale.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEQ5D.\u0026nbsp;\u003c/strong\u003eThe generic health status was examined using the second part of the EuroQol questionnaire (EQ-5D). The second part consists of a visual analogue scale (EQ VAS) with the endpoints labelled \u0026lsquo;best imaginable health state\u0026rsquo; at the top and \u0026lsquo;worst imaginable health state\u0026rsquo; at the bottom having numerical values of 100 and 0, respectively [11]. For analysis, we used the EQ VAS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size and statistical analysis\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe primary aim was to investigate the feasibility and implementation of the collection of PROMs in routine clinical practice. The sample size of these pilot studies was calculated according to Vietbauer et al [7]. For all variables, descriptive statistics were computed. Depending on the variables\u0026apos; scale levels, N and % or median and interquartile range are reported. Correlation analysis was performed with Spearman\u0026rsquo;s rank test. Two-tailed tests of significance were considered to be significant at a p-value \u0026lt;0.05 and highly significant at p \u0026lt;0.01. Group and interaction effects of selected factors on PROMs over time were measured by mixed models. Data were analyzed with IBM SPSS version 24 for Microsoft Windows.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatients and Follow-up\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 144 patients were screened for enrollment, and n = 99 were included into the study during treatment at the Heart Failure Unit. The most frequently reported heart failure symptoms were dyspnea NYHA III or IV (90%) and peripheral edema (79%). The follow-up rate after one month, six months and one year was 80%, 72% and 65% respectively. Within one year, 19 patients (19%) died (\u003cem\u003eFigure 1, Supplementary Table 1\u003c/em\u003e).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic data, severity of disease and therapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample consisted of n = 33 (33%) women. The mean age was 64 years (range\u0026nbsp;19‑87). Nearly all patients (96%) were German. The majority (59%) were married or lived in a solid partnership. Only 20% were employed. A large majority of 88 patients (89%) had been hospitalized for heart failure within 12 months prior to the current inpatient stay. Of these, 83 patients (84%) had been admitted to the hospital at least once as an emergency or had consulted the emergency department themselves. For 14% of patients it was somewhat difficult to pay their living costs, for 9% very difficult. Comorbidities such as arterial hypertension (74%) diabetes mellitus (42%), chronic lung diseases (21%) and chronic kidney disease (41%) were common. 31% of the patients were overweight and 32% were obese (\u003cem\u003eTable 1\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eHF with reduced ejection fraction (HFrEF, LVEF \u0026le; 40%) was most common (66%) while 24% suffered from HF with preserved ejection fraction (HFpEF, LVEF \u0026ge; 50%). HF with mildly reduced ejection fraction (HFmrEF, LVEF 40-49%) was less frequent (10%). Reduced right ventricular function was present in half of the patients (53%). The most common high-grade valve disease was mitral valve regurgitation (23%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe use of heart failure medication was widespread. 88% of patients were taking beta-blockers, 46% SGLT-2 inhibitors, and 62% mineral corticoid receptor antagonists. Sacubitril/Valsartan was prescribed to 52%, ACE inhibitors to 20% and angiotensin II receptor antagonists to 14% (86% took one of the three drugs). Severe side-effects of heart failure medication were reported by 14% of patients. At the time of study enrollment, 15% of patients were receiving positive inotropic therapy. The median duration of hospitalization was 13 days (range 2-257 days). Twenty-three patients (23%) underwent cardiac resynchronization therapy (CRT) and 6% had a Left ventricular assist device.\u003c/p\u003e\n\u003cp\u003eDuring the inpatient stay, 30% of patients were admitted to the intensive care unit, including five patients (5%) with unplanned admissions. Five patients (5%) received short-term mechanical circulatory support.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHF therapy during follow-up\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe proportion of patients with NYHA class III and IV decreases from 78% to 29% between inclusion and follow-up date (\u003cem\u003eTable 2\u003c/em\u003e). Changes in heart failure medication (preparations and dosages of the four most beneficial drugs) were very frequent during follow-up. 20% of patients reported adjustments within the first 30 days, 21% within 6 months of inclusion \u0026nbsp; and 25% within 12 months (\u003cem\u003eTable 3\u003c/em\u003e). During follow-up, 3 patients underwent CRT implantation. Five patients underwent LVAD implantation. Within one year, 5 patients underwent heart transplantation and 6 patients underwent valve surgery (\u003cem\u003eFigure 1\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults of PROMS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients reported a mean \u003cstrong\u003eKCCQ-12\u003c/strong\u003e overall score of 55.2 points (\u0026plusmn;28.3 points SD) one month after discharge. In the further follow-ups revealed KCCQ-12 overall score raised to 57.2 points (\u0026plusmn;26.4 points SD) after six months and 62.0 points (\u0026plusmn;28.5 points SD) after one year. \u003cstrong\u003ePHQ-2\u003c/strong\u003e score \u0026ge;3 points was found in 20 patients (25%) after one month, and in 14 patients (18%) after six months. In the last follow-up assessment after 12 months, 13 patients (17%) achieved a PHQ \u0026ge;3 points. Mean\u003cstrong\u003e\u0026nbsp;PROMIS Physical Function Shortform 4a\u003c/strong\u003e sum score was 12.6 (\u0026plusmn;4.8 SD) one month after discharge. In the further follow-ups mean sum scores of 13.0 (\u0026plusmn;4.9 SD) and 13.9 (\u0026plusmn;4.9 SD) were measured. \u003cstrong\u003eEQ-5D-VAS\u003c/strong\u003e showed a mean of 59.2 (\u0026plusmn;19.6 SD) one month after discharge and 59.1 (\u0026plusmn;21.7 SD) after six months as well as 62.8 (\u0026plusmn;21.5 SD) after one year of follow-up (\u003cem\u003eFigure 2\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eTo illustrate longitudinal trajectories, Sankey plots were created for NYHA class, KCCQ-12, PROMIS-4a, and EQ-5D-VAS (\u003cem\u003eFigure 3\u003c/em\u003e). These visualizations highlight that most patients showed either relative stability or moderate improvement over 12 months, while a relevant proportion remained in lower categories of function and quality of life. In particular, the KCCQ‑12 and PROMIS-4a plots demonstrated shifts from lower to moderate or higher functional levels, confirming the mean improvements observed in these scores. In contrast, most patients in the EQ-5D-VAS remained in moderate categories, with only a subset reporting higher perceived quality of life over time. Interestingly. Regarding NYHA classification, a marked proportion of patients improved from NYHA III/IV to better classes, whereas only a minority worsened during follow-up.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient opinion on PROMs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne and six months after enrollment, patients were asked for their opinion on the assessment of PROMs. 81% and 87% respectively agreed or strongly agreed that their answers gave a good insight into how they assess various health conditions and limitations caused by their illness. 79% and 81% respectively stated that the questionnaire can help physicians to understand whether the current treatment for heart failure is successful. At both points in the survey, 76% of patients said they would like their heart failure treatment to be adjusted based on their responses. 91% and 96% of patients respectively felt they were adequately informed about the purpose of the questionnaire. Further, only 14% at both follow-up points stated that the questionnaire was too long (\u003cem\u003eFigure 4\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnscheduled visits\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn unscheduled visit was conducted for n = 9 patients. The most common reasons for unscheduled visits were progressive dyspnea, increasing edema and weakness (n=6 each, 67%). Three patients (33%) reported renal failure and cardiac arrhythmia. Patients with unscheduled visits had significantly lower KCCQ-12 sum scores (p = 0.028). In particular, the subscales \u0026apos;symptom frequency\u0026apos; (p = 0.014) and \u0026apos;social limitation\u0026apos; (p = 0.011) showed lower values than in the respective previous measurement. PROMIS Physical Function Shortform 4a sum score showed a similar pattern with significantly lower scors (p = 0.028) whereas the PHQ-2 score and the EQ5D-VAS did not differ significantly.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation between PROMs and NYHA class as well as generic PROMs and disease‑specific PROMS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe found significant correlation (r = 0.572 to 0.806, p \u0026lt;0.001 each) between the measured values of the sum scores of all four PRO instruments at all measurement times. Interestingly, there was no significant correlation between PROMs and clinical NYHA class. One month after inclusion, there was still a trend towards a correlation of NYHA class with KCCQ-12 overall score (r = -0.217, p = 0.057) and PROMIS Physical Function Shortform 4a sum score (r = ‑0.221, p = 0.053). In contrast, there were strong correlations between the results of the disease-specific and generic PROMs (r = 0.606 to 0.765, p\u0026lt;0.001 each, \u003cem\u003eSupplementary Table\u0026nbsp;2\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReliability of PROMs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigh parallel test reliabilities were found between the PROMs (standardized Cronbach\u0026apos;s alpha 0.75-0.90). The internal consistency was comparable for all measurement times, indicating good retest reliability. A direct measurement of retest reliability using bivariate correlations is not possible due to the longitudinal design of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInfluence of selected factors on PROMs over time\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients who were hospitalized again due to heart failure within one month of discharge (n\u0026nbsp;=\u0026nbsp;17, 21%) had a significantly lower PROMIS Physical Function Shortform 4a sum score (p\u0026nbsp;= 0.029) and tended to have lower KCCQ-12 sum score (p = 0.057) and EQ5D-VAS (p\u0026nbsp;=\u0026nbsp;0.077). Emergency outpatient presentations due to heart failure within 12 months of study entry had no consistent impact on PROMs. Patients who met the composite endpoint of re-hospitalization due to heart failure or death within 12 months of study entry had lower PHQ-2 scores (p = 0.036) and EQ5D-VAS (p = 0.042) and showed a tendency towards lower KCCQ-12 sum score (p = 0.054) at the last study visit. Side effects of heart failure medication perceived as limiting by the patients themselves as well as the etiology of heart failure did not have a significant influence on the PROMs at any time. The patient age showed a general effect on the KCCQ-12 sum score (p = 0.038), which, however, remained constant over the trial visits (p=.884). No effect of patient age was seen in the three other PROMs. Men generally showed higher PROMIS Physical Function Shortform 4a sum scores (p = 0.044), with the effect remaining constant over time. Furthermore, men tended to have higher PHQ-2 scores (p = 0.082), while no influence of sex was found for KCCQ-12 and EQ5D-VAS (\u003cem\u003eTable 4\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eMixed linear models were used to assess the effect of heart failure therapies \u0026ndash; pharmacological treatment, cardiac surgery, and heart transplantation \u0026ndash; on patient-reported outcome measures, adjusted for age and sex. No significant associations were found between therapy type and any PROM, nor were there significant time or interaction effects (all p \u0026gt; 0.05, Supplementary Table 3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003eMain findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis feasibility study has three main findings.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eRepeated collection of patient-reported outcome measures is feasible in patients with severe heart failure during and after an acute decompensation.\u003c/li\u003e\n \u003cli\u003eThe instruments evaluated here (PROMIS-4a, KCCQ-12, PHQ-2, EQ-5D) capture collinear information. Depending on the purpose, collection of 1-2 measures may suffice.\u003c/li\u003e\n \u003cli\u003eChanges in patient-reported outcome measures are not highly influenced by heart failure events or heart failure therapies, suggesting that patient-reported outcome measures capture important additional information in patients with severe heart failure.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eIn this study, we longitudinally evaluated the feasibility and results of the ICHOM standard set of PROMs in patients with acute heart failure or decompensated chronic heart failure. A 12‑month follow-up was performed in 65% of patients, 19% of patients had died after 12\u0026nbsp;months and 16% were lost to follow-up. Over 80% of patients agreed or strongly agreed that their answers gave a good insight into how they assess various health conditions and limitations caused by their illness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFeasibility of repeated PROM collection in patients with severe heart failure\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRepeated PROM collection was positively perceived by patients. In our study, three quarters of the patients (76%) stated that they would be glad to have their heart failure treatment adapted based on their answers. PROs can facilitate discussions of patient preferences and help engage patients in shared decision-making. Use of PROs to measure values, preferences, or changes in PROs can facilitate provider and patient engagement in timely discussions regarding goals of care. Examples include patient-centered palliative care discussions or, alternatively, discussions regarding interventions such as LVAD or implantable cardioverter-defibrillator therapy. In both cases, understanding the patient\u0026apos;s perspective on current HRQOL and perceptions of treatment burden is critical to ensuring shared decision‑making. The results indicate that the promotion of shared decision-making by use of PROs would be mutually beneficial for patients and healthcare providers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHow many PROMs are needed?\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn our study, we used a combination of four PROMs\u0026mdash;KCCQ-12, PROMIS Physical Function Shortform 4a, PHQ-2, and EQ-5D\u0026mdash;to assess various dimensions of health in patients with acute heart failure or decompensated chronic heart failure. The selection of these instruments reflects the need for a comprehensive yet practical approach to capture the multifaceted nature of the patient experience.\u003c/p\u003e\n\u003cp\u003eGiven the complexity of heart failure, which affects physical, emotional, and social well-being, using multiple PROMs allowed us to assess both disease-specific and generic aspects of health. The KCCQ-12 focused on cardiovascular symptoms and limitations, while PROMIS Physical Function assessed physical capacity. The PHQ-2 provided insights into depressive symptoms, and EQ-5D captured overall quality of life. Together, these tools ensured a broad understanding of how heart failure impacts patients across different domains.\u003c/p\u003e\n\u003cp\u003eWhile these PROMs provided valuable data, we also considered patient burden and feasibility. Despite using four instruments, our study demonstrated that repeated PROM assessments at multiple time points (30 days, 6 months, and 12 months) were well-tolerated by patients, with high levels of engagement. However, it is worth considering that a smaller set of 2-3 PROMs could suffice in future studies without compromising the quality of the data, especially if the focus is on streamlining the assessment process.\u003c/p\u003e\n\u003cp\u003eIn conclusion, the combination of these four PROMs allowed us to capture a comprehensive view of health-related quality of life and functional status in heart failure patients. While our findings support the use of multiple PROMs, the number of instruments should be carefully considered based on the study\u0026rsquo;s goals and the practical considerations of patient burden. A balanced approach, combining disease-specific and generic PROMs, offers an effective way to assess the most relevant aspects of the patient experience.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdded information from PROMs in patients with severe heart failure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults of PROMs may support the results of traditional endpoints, but can also weaken them. For instance, in the COAPT trial, transcatheter mitral valve repair determined a one-month mean between-group difference of 16 points in KCCQ overall summary score which was sustained over time [12]. In most pharmacological trials, including the more recent trials on sodium-glucose cotransporter 2 inhibitors, the average treatment effect on KCCQ was \u0026lt;5 points [13].\u003c/p\u003e\n\u003cp\u003eA notable result was the weak correlation between PROMs and clinical NYHA classification, echoing prior studies that highlight discrepancies between clinician-assigned functional status and patient-reported health status [14]. Further, a recently published study reported worse in-hospital and post-discharge patient-reported health status, but these measures were similar to HFrEF after adjustment for other clinical factors\u0026nbsp;[15].\u003c/p\u003e\n\u003cp\u003eFurther, no significant associations were found between therapy type (heart failure medication, cardiac surgery and interventions as well as heart transplantation). This suggests that therapy modality does not substantially influence patient-reported quality of life or psychological well-being. Variability in PROMs appears to be driven mainly by individual patient characteristics, underscoring the importance of personalized and psychosocially oriented care in heart failure management.\u003c/p\u003e\n\u003cp\u003eHeart failure outcomes and survival have long been advocated as the source of medical truth. Based on our preliminary analyses, clinical outcomes and PROs reflect different aspects of a well‑being in patients with severe heart failure, and therefore both can provide important data to guide treatment decisions, such as treatment selection and evaluation of treatment efficacy. In parallel to minimizing disease progression, improving patient well-being, social functioning and quality of life is an important therapeutic goal. Measuring effects in these domains is the purpose of PROMs. Our feasibility study shows that validated PROMs can be repeatedly collected in patients with severe heart failure. By asking the same questions systematically and reproducibly over time, the PROs can validly and sensitively capture the impact of heart failure on patients\u0026apos; lives. Declines in KCCQ-12 or PROMIS-4a scores, for instance, could signal the need for timely therapeutic adjustments, such as modifying medication regimens or initiating palliative care. Such actionable insights underscore the importance of integrating PROMs into routine workflows, ensuring they directly inform care decisions.\u003c/p\u003e\n\u003cp\u003eThe use of PROMs has several limitations. Common comorbidities in patients with HF, such as obesity and lung disease, and psycho-social factors will influence quality of life and therefore affect PROMs independent of heart failure status and therapy. The use of PROMs depends on the patient\u0026apos;s willingness and ability to participate. In our study, about a fifth of the patients who underwent screening were excluded because they were unable or unwilling to participate. Most PROMs report continuous outcomes on scales that do not always reflect linear changes. The large number of PRO instruments means that the comparability of results is more limited than for well-defined outcomes such as mortality. The observed collinearity in several validated PROMs suggests that selected PROMs may suffice for assessment of patient well-being over time. In addition, PROs cover many dimensions: symptoms, physical limitations, social limitations and quality of life. The standardization of PROM tools, as exemplified by the ICHOM set, could support cross‑institutional comparisons and improve the consistency of outcome measurement.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis feasibility study demonstrates that repeated assessment of patient-reported outcomes using validated instruments is possible in patients with severe heart failure. Collinearity of the readouts suggest that careful selection of a limited number of PROMs may allow meaningful and simplified assessment of patient well-being. Changes in PROMs were not related to heart failure therapies or events, highlighting that PROMs measure domains of well-being that are not directly linked to outcome-modifying therapies. These preliminary results underpin the value of PROMs for assessment of the quality of care in patients with heart failure.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eNone.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTW and HG conceived the study. LZ collected the data. TW analyzed and evaluated the data. TW and HG wrote the manuscript. HR, CM, and PK supplemented and edited the manuscript. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSavarese G, Becher PM, Lund LH, Seferovic P, Rosano GMC, Coats A. Global burden of heart failure: a comprehensive and updated review of epidemiology. \u003cem\u003eCardiovasc Res.\u003c/em\u003e 2023;118:3272\u0026ndash;87\u003c/li\u003e\n \u003cli\u003eMcDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, B\u0026ouml;hm M, Burri HB, Butler J, Čelutkienė J, Chioncel O, Cleland JGF, Coats AJS, Crespo-Leiro MG, Farmakis D, Gilard M, Heymans S, Hoes AW, Jaarsma T, Jankowska EA, Lainscak M, Lam CSP, Lyon AR, McMurray JJV, Mebazaa A, Mindham R, CMuneretto C, Piepoli MF, Price S, Rosano GMC, Ruschitzka F, Skibelund AK, ESC Scientific Document Group. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). With the special contribution of the Heart Failure Association (HFA) of the ESC. \u003cem\u003eEur J Heart Fail.\u0026nbsp;\u003c/em\u003e2022;24:4\u0026ndash;131\u003c/li\u003e\n \u003cli\u003eHeidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, Deswal A, Drazner MH, Dunlay SM, Evers LR, Fang JC, Fedson SE, Fonarow GC, Hayek SS, Hernandez AF, Khazanie P, Kittleson MM, Lee CS, Link MS, Milano CA, Nnacheta LC, Sandhu AT, Stevenson LW, Vardeny O, Vest AR, Yancy CW. 2022 AHA/ACC/HFSA Guideline for the management of heart failure: executive summary: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. \u003cem\u003eJ Am Coll Cardiol.\u003c/em\u003e 2022;79:1757\u0026ndash;80\u003c/li\u003e\n \u003cli\u003eCalvert M, Kyte D, Price G, Valderas JM, Hjollund NH. Maximising the impact of patient reported outcome assessment for patients and society. \u003cem\u003eBMJ.\u003c/em\u003e 2019;364:k52675\u003c/li\u003e\n \u003cli\u003eAnker SD, Agewall S, Borggrefe M, Calvert M, Jaime Caro J, Cowie MR, Ford I, Paty JA, Riley JP, Swedberg K, Tavazzi L, Wiklund I, Kirchhof P. The importance of patient-reported outcomes: a call for their comprehensive integration in cardiovascular clinical trials. Eur Heart J.2014;35:2001-9.\u003c/li\u003e\n \u003cli\u003eBurns DJP, Arora J, Okunade O, Beltrame JF, Bernardez-Pereira S, Crespo-Leiro MG, Filippatos GS, Hardman S, Hoes AW, Hutchison S, Jessup M, Kinsella T, Knapton M, Lam CSP, Masoudi FA, McIntyre H, Mindham R, Morgan L, Otterspoor L, Parker V, Persson HE, Pinnock C, Reid CM, Riley J, Stevenson LW, and McDonagh TA. International Consortium for Health Outcomes Measurement (ICHOM): Standardized Patient-Centered Outcomes Measurement Set for Heart Failure Patients. \u003cem\u003eAm Coll Cardiol HF.\u003c/em\u003e 2020;8:212\u0026ndash;22\u003c/li\u003e\n \u003cli\u003eViechtbauer W, Smits L, Kotz D, Duce L, Spigt M, Serroyen J and Crutzen R. A simple formula for the calculation of sample size in pilot studies. \u003cem\u003eJ Clin Epidemiol.\u003c/em\u003e 2015;68:1375\u0026ndash;1379\u003c/li\u003e\n \u003cli\u003eGreen CP, Porter CB, Bresnahan DR, Spertus JA. Development and evaluation of the Kansas City Cardiomyopathy Questionnaire: a new health status measure for heart failure. \u003cem\u003eJ Am Coll Cardiol.\u003c/em\u003e 2000;35:1245\u0026ndash;1255\u003c/li\u003e\n \u003cli\u003eKroenke K, Spitzer Robert L, Williams JBW. The patient health questionnaire-2: Validity of a two-item depression screener. \u003cem\u003eMedical Care.\u003c/em\u003e 2003;41:1284\u0026ndash;1292\u003c/li\u003e\n \u003cli\u003ehttps://www.healthmeasures.net/explore-measurement-systems/promis/intro-to-promis/list-of-adult-measures\u003c/li\u003e\n \u003cli\u003eGroup EuroQol. EuroQol\u0026ndash;a new facility for the measurement of health related quality of life. \u003cem\u003eHealth Policy.\u003c/em\u003e 1990;16:199\u0026ndash;208\u003c/li\u003e\n \u003cli\u003eArnold SV, Chinnakondepalli KM, Spertus JA, Magnuson EA, Baron SJ, Kar S, Lim DS, Mishell JM, Abraham WT, Lindenfeld JA, Mack MJ, Stone GW, Cohen DJ. Health status after transcatheter mitral-valve repair in heart failure and secondary mitral regurgitation: COAPT trial. \u003cem\u003eJ Am Coll Cardiol.\u003c/em\u003e 2019;73:2123\u0026ndash;32\u003c/li\u003e\n \u003cli\u003eGuo Z, Wang L, Yu J, Wang Y, Yang Z, Zhou C. The role of SGLT-2 inhibitors on health-related quality of life, exercise capacity, and volume depletion in patients with chronic heart failure: a meta-analysis of randomized controlled trials. \u003cem\u003eInt J Clin Pharm.\u003c/em\u003e 2023;45:547\u0026ndash;555\u003c/li\u003e\n \u003cli\u003eTran AT, Chan PS, Jones PG, Spertus JA. Comparison of patient self-reported health status with clinician-assigned New York Heart Association Classification. \u003cem\u003eJAMA Network Open.\u003c/em\u003e 2020;3:e20141319.\u003c/li\u003e\n \u003cli\u003ePeters AE, Mentz RJ, Sun J-L, Harrington JL, Fudim M, Alhanti B, Hernandez AF, Butler J, Starling RC, Greene SJ. Patient-reported and Clinical Outcomes Among Patients Hospitalized for Heart Failure With Reduced Versus Preserved Ejection Fraction. \u003cem\u003eJ Cardiac Fail.\u0026nbsp;\u003c/em\u003e2022;28:1652\u0026ndash;1660\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Baseline\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003echaracteristics\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e (n=99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;N (\u003cem\u003e%\u003c/em\u003e) or Median (\u003cem\u003eIQR\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic data\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66 (\u003cem\u003e47 \u0026ndash; 85\u003c/em\u003e)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33 (\u003cem\u003e33)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBody mass index [kg m\u003csup\u003e-2\u003c/sup\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (\u003cem\u003e7\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCurrent smoker\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 \u003cem\u003e(6)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFormer smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62 \u003cem\u003e(63)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDuration of hospital stay [days]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13 \u003cem\u003e(1 \u0026ndash; 29)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeft ventricular function \u0026ndash; LVEF\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;50% (HFpEF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24 (\u003cem\u003e24\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40-50% (HFmrEF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (\u003cem\u003e10\u003c/em\u003e)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;40% (HFrEF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65 (\u003cem\u003e66\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRight ventricular function \u0026ndash; TAPSE\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNormal (TAPSE \u0026ge;16 mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33 (\u003cem\u003e39\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReduced (TAPSE \u0026lt;16 mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (\u003cem\u003e61)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere valve disorders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere mitral regurgitation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 (\u003cem\u003e23\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere mitral stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (\u003cem\u003e2\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere tricuspid regurgitation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (\u003cem\u003e14\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere aortic valve regurgitation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (\u003cem\u003e2\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere aortic valve stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (\u003cem\u003e3\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart failure medication\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eACE inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20 \u003cem\u003e(20)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAngiotensin II receptor antagonist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 \u003cem\u003e(14)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBeta blockers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e87 \u003cem\u003e(88)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMineral corticoid receptor antagonists\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61 \u003cem\u003e(62)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSacubitril/Valsartan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51 \u003cem\u003e(52)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLoop diuretics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88\u003cem\u003e\u0026nbsp;(89)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSGLT-2 inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45 \u003cem\u003e(46)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms at inclusion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDyspnoe NYHA III/IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e91 (\u003cem\u003e92\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOrthopnoe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45 (\u003cem\u003e45\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81 (\u003cem\u003e82\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePulmonary congestion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54 (\u003cem\u003e54\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePeripheral edema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80 (\u003cem\u003e81\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCervical venous congestion, ascites or intestinal congestion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45 (\u003cem\u003e45\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMorbidity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHistory of Atrial fibrillation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54 (\u003cem\u003e55\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCurrent treatment because of Myocardial infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (\u003cem\u003e6\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHistory of Myocardial infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25 (\u003cem\u003e25\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eArterial hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73 (\u003cem\u003e74\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42 (\u003cem\u003e42\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChronic lung disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21 (\u003cem\u003e21\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRenal failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51 (\u003cem\u003e51\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;not requiring dialysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36 (\u003cem\u003e36\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;requiring dialysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15 (\u003cem\u003e15\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDevices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eICD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19 \u003cem\u003e(19)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCRT-P or CRT-D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 \u003cem\u003e(23)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLVAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 \u003cem\u003e(6)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDetails of index hospital stay\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCardiac surgery during hospital stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18 \u003cem\u003e(18)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnplanned ICU stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 \u003cem\u003e(5)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMechanical circulatory support (Impella, ECMO, ECMella)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 \u003cem\u003e(5)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: NYHA class\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eNYHA class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e30 days\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eN\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eN\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNYHA I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNYHA II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNYHA III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNYHA IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Clinical Follow-up data\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical follow-up data\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e30 days\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRehospitalization due to heart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConsultation of the emergency unit due to heart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSevere side effects due to heart failure medication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChanges in heart failure medication* - therein\u0026hellip;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;Additional drug(s)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2.5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e8.5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e6.3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;Medication(s) discontinued\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e3.8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e4.2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e7.8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;Dose increased\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e9\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e11.4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e5.6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e4.7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eDose reduced\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2.5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2.8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e6.3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChanges in diuretic medication - therein\u0026hellip;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;Additional drug(s)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1.3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1.4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e3.1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;Medication(s) discontinued\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e6.3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1.4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e0\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e0.0\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;Dose increased\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1.3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e2.8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1.6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eDose reduced\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e0\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e0.0\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e5.6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e1.6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u0026rdquo;Magic 4\u0026rdquo; and Vericiguat\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Influence of selected factors on PROMs over time (mixed models\u003c/strong\u003e)\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eEQ-5D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003ePROMIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003ePHQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eKCCQ-12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGroup\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInteraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInteraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInteraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eInteraction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eℇ\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eℇ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eℇ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eℇ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eℇ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eℇ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eℇ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eℇ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHF medication Side effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePatient\u0026apos;s age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePatient\u0026apos;s sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.06\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRehospitalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRehospitalization or death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEmergency treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\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":"Acute heart failure, decompensation, patient-reported outcomes, KCCQ-12, PHQ-2, quality of life, longitudinal study","lastPublishedDoi":"10.21203/rs.3.rs-8722112/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8722112/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims\u003c/h2\u003e \u003cp\u003eAcute decompensation of heart failure (HF) is a major cause of hospital admissions and adverse outcomes. Patient-reported outcome measures (PROMs) offer valuable insights into patient experience and may support treatment decisions. This study aimed to assess PROMs in patients hospitalized for acute decompensated HF at multiple time points after discharge to evaluate the feasibility of repeated PROM assessments and to capture changes in health status, medication management, and quality of life.\u003c/p\u003e\u003ch2\u003eMethods and Results\u003c/h2\u003e \u003cp\u003eConsecutive patients hospitalized for decompensated HF completed PROMs at 30 days, 6 months, and 12 months post-discharge. Collected data included demographics, comorbidities, hospitalizations, medication use, and PROMs using the KCCQ-12, PROMIS Physical Function Shortform 4a (PROMIS-4a), and PHQ-2. Generic quality of life was assessed with the EQ-5D. Among 99 patients (median age 66 years, 33% women, 90% NYHA III/IV on admission, 89% rehospitalized for HF within 12 months), all PROM instruments indicated substantial disease burden. Strong parallel reliabilities were observed (Cronbach\u0026rsquo;s alpha 0.75\u0026ndash;0.90). PROMIS-4a was associated with age (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and sex (p\u0026thinsp;=\u0026thinsp;0.04), while KCCQ-12 was associated with age (p\u0026thinsp;=\u0026thinsp;0.04). All PROM scores improved during follow-up. Cardiovascular events\u0026mdash;including transplantation, rehospitalization, emergency treatment, and therapy failure\u0026mdash;did not significantly affect PROM trajectories.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eRepeated assessment of patient-reported outcomes after HF decompensation is feasible. Using one or two PROM instruments may be sufficient, as the measures showed parallel development. Preliminary findings indicate that PROMs capture aspects of patient health not fully explained by HF severity or treatment modalities.\u003c/p\u003e","manuscriptTitle":"Assessing proper patient-reported outcomes after recent discharge in acute heart failure – A Longitudinal Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-10 00:35:37","doi":"10.21203/rs.3.rs-8722112/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":"86dd88c8-10b9-42ab-b3bd-c203496d3ac9","owner":[],"postedDate":"February 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-10T00:35:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-10 00:35:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8722112","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8722112","identity":"rs-8722112","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}