Influence of self-management on patient-reported outcomes for individuals with chronic heart failure: a multilevel model approach from a longitudinal study

Purpose: Self-management is highly heterogenous in patient-reported outcomes in individuals with chronic heart failure and lacks a clinical definition. The aim of this study was to identify clinically meaningful strategies that improve patient-reported outcomes in those with chronic heart failure. Methods: A multicenter, prospective cohort study of 555 patients with heart failure were enrolled from May 2017 to May 2019. Self-management advice was provided in written form at discharge. Information regarding chronic heart failure in patient-reported outcomes and self-management was collected during follow-up. Multilevel models were applied to dynamically evaluate the effects of self-management strategies for patient-reported outcome of chronic heart failure (CHF-PRO) scores, as well as its physical and psychological domains. Minimal clinically important difference was introduced to further evaluate clinical significance. Results: Scores for CHF-PRO improved significantly after discharge. A regular schedule, avoidance of over-eating, and a low-sodium diet increased scores on patient-reported outcomes, including overall scores and physical and psychological scores. In addition, exercise improved patient-reported outcomes and its physical domain. The use of angiotensin-converting enzyme inhibitors also increased physical scores. Among these variables, a regular daily schedule and avoidance of over-eating almost every day reached clinical significance for CHF-PRO scores, as well as its physical and psychological domains. Conclusions: Self-management, especially the avoidance of over-eating and maintenance of a regular schedule, should be implemented to improve patient-reported outcomes in those with chronic heart failure.

scores and physical and psychological scores. In addition, exercise improved patient-reported outcomes and its physical domain. The use of angiotensin-converting enzyme inhibitors also increased physical scores. Among these variables, a regular daily schedule and avoidance of overeating almost every day reached clinical significance for CHF-PRO scores, as well as its physical and psychological domains. Conclusions: Self-management, especially the avoidance of over-eating and maintenance of a regular schedule, should be implemented to improve patient-reported outcomes in those with chronic heart failure.

Background
Chronic heart failure (CHF) is the terminal and most severe stage of heart disease, which affects 1.5-2% of the adult population in developed countries [1], and 0.9% of the population aged 35 to 74 years in China [2]. Patients with CHF suffer from poor quality of life (QoL) and prognosis. The 12-month mortality and re-hospitalization rates of CHF reach 17% and 44%, respectively [3]. Improving outcomes in patients with CHF is an important social problem that requires urgent attention. Selfmanagement is very important to CHF. The 2019 American College of Cardiology Expert Consensus highlighted that self-management strategies can improve outcomes in patients with heart failure (HF) and that the implementation of such strategies is encouraged [4]. Self-management has been proven to be effective in decreasing hospitalization and death rates in patients with CHF [5]. However, in terms of QoL, self-management is highly heterogeneous [6,7].
Self-management involves all aspects of a patient's activities of daily living, including medication adherence, a reasonable diet, limiting alcohol consumption, staying physically active, avoiding tobacco use, and maintenance of a regular daily routine, among others [3]. Self-management strategies have attracted significant attention from investigators. However, the most useful of all proposed strategies, and the extent that results in meaningful clinical changes, have not been identified in previous studies. Moreover, changes in strategies and patient conditions over time should not be ignored. All of these may play a role in the uncertainty of the effect of self-management on QoL [6,7]. Patient-reported outcome (PRO), recommended by the United States Food & Drug Administration to evaluate QoL, was adopted in the present study [8]. To better evaluate patients in China, we used a Chinese questionnaire known as the "CHF-PRO", which is specifically relevant to the population of mainland China [9]. Therefore, this study focused on self-management after discharge and applied multilevel models in an attempt to determine effective self-management strategies to improve CHF-PRO scores. Moreover, minimal clinically important difference (MCID) was applied to identify clinically meaningful strategies in this study [10].

Participants
Patients from three medical centers in the Shanxi province of China were enrolled according to predefined inclusion and exclusion criteria. The inclusion criteria were: age ≥18 years; diagnosed with HF according to current guidelines [3]; New York Heart Association (NYHA) functional class II-IV; and receipt of HF therapy in the past month. Patients who experienced acute cardiovascular events in the past 2 months, had a life expectancy of < 1 year, could not understand or complete the questionnaire 5 due to language barriers or intellectual disabilities, and those who refused to participate in this project were excluded.

Procedure and data collection
The present investigation was a multicenter, prospective cohort study performed from May 2017 to May 2019. Information regarding baseline data, self-administered questionnaire, and CHF-PRO scores were collected during hospitalization. Self-management advice, which included medication use, regular schedule, keeping warm, dietary instructions, health education, smoking cessation, temperance, and exercise, was provided in written form to the participants at discharge. Dietary instructions included a low-sodium diet (LSD), low-fat diet, and the avoidance of over-eating. Among these strategies, a regular schedule was defined as maintaining relatively fixed sleep and wake times, and LSD intake < 5 g of salt per day. All participants were followed-up at 1, 3, and 6 months after discharge in face-to-face consultations or telephone follow-up to obtain information regarding the selfadministered questionnaire and CHF-PRO scores [9]. To ensure quality, all questionnaires were administered by professionally trained individuals.
Baseline information included patient age, sex, height, weight, marital status, education, annual income, family history of cardiovascular disease, NYHA functional class, blood pressure, and complications. The Charlson comorbidity index was applied to assess complications.
The self-administered questionnaire was developed to assess self-management. The questionnaire contained all strategies provided at discharge as mentioned above, with responses scored on a 5point Likert, as follows: 0 (never happens); 1 (happens occasionally); 2 (happens half of the time); 3 (happens often); and 4 (happens every day).
The CHF-PRO was developed by the authors' research group and adopted in this study. This questionnaire contains 57 items, 12 subdomains, and 4 domains, which consisted of physical, psychological, social, and therapeutic domains [9]. Patients responded to each item on a 5-point Likert scale to reflect how often they had experienced each issue.

Statistical analysis
Continuous variables are expressed as mean ± standard deviation (SD) or median (interquartile 6 range). Univariate analysis of variables and calculation of MCID were performed using SPSS version 25.0 (IBM Corporation, Armonk, NY, USA). The backward method was used for statistically significant variables (P < 0.1). Further multilevel model assumptions were confirmed through analysis of residuals generated by MLwiN version 3.0 software (Centre for Multilevel Modelling, University of Bristol, Bristol, United Kingdom).

Multilevel model
The multilevel model, which can handle repeated measures data, was applied to assess the effect of self-management strategies to the overall summary (OS) of CHF-PRO. The main concept of this model is to estimate variance at each level and consider the effect of the explanatory variables on the variance to estimate the regression coefficient effectively [11]. The model was constructed as follows: Y ij represents OS of CHF-PRO taken from the ith person; e ij is the residual of the first level; β 0j is the coefficient variable, which could be formulated by equation 2; β 0 and β j stand for fixed parameters representing the average of the intercept and slope, respectively; and u 0j and u ij represent interindividual variability in intercepts and slopes via random effects. Maximum likelihood estimates can be computed from the covariance matrix.

Multivariate multilevel model
The multivariate multilevel model was fitted to assess self-management strategies on physical scores (PHYS), psychological scores (PSYS) [11]. The multivariate variance components model was constructed as follows: 7 In the equation above, Y itk represents the vector of two outcome measurements, taken from the i th person at time t; D k is a pseudo variable, with a unique pseudo variable for each outcome; the k response variable, β 0ik is the overall intercept for person i; β 1ik denotes a patient-specific slope; and e itk is residual error at time t for person i.
In the present study, model 1 was the null model. Time was added to model 1 as an explanatory variable to establish model 2, which was used to study the effect of time on variables. Model 3 was constructed when baseline information and self-management situation of participants were included in model 2.

MCID
Although P < 0.05 is often considered to be the criterion for evaluating the effectiveness of an intervention in PRO or QoL, the P value merely represents statistical significance. In our study, MCID was introduced to analyze its clinical significance to determine more effective self-management strategies. ES of the distribution method was applied to calculate MCID according to characteristics of the current CHF-PRO data [10,12]. ES was formulated as follows: In the equation above, x 0 represents baseline scores of patients.
represents the average baseline scores of individuals, and is the average follow-up scores of individuals. In our study, a moderate effect of 0.5 was used as the effect size statistics to estimate MCID.
Finally, β values of the multi-level model were compared with MCID. The first level of the variables was considered "0", and multiplied the β value by the grade of levels minus "1". The corresponding 8 grade of variables up to MCID was defined as reaching clinical significance.

Sample characteristics
Baseline characteristics of the patients are shown in Table 1 Table 2.

Multilevel model of self-management on CHF-PRO
Three model levels were applied to assess self-management strategies on OS of CHF-PRO; the results are summarized in distribution diagram is close to a straight line. Therefore, it indicated that the assumption of normal distribution of each level residuals was reasonable (Fig. 2).  [13][14][15]. We used multivariate statistical methods to avoid the influence of these covariates on the results; thus, we were able to obtain self-management strategies that improved CHF-PRO more accurately.

MCID and its interpretation to the multilevel model
Results of our study demonstrated that maintaining a regular schedule improved CHF-PRO. Over-eating often relies on patient perception and lacks objective indicators for evaluation. As such, few studies have extensively investigated this factor. Our study unexpectedly found that avoidance of over-eating dramatically decreased OS, as well as PHYS and PSYS in CHF-PRO. Research presented at the American Heart Association meeting in 2000 found that a single large meal led to a fourfold increase in heart attacks within 2 h of the meal [20]. A rich diet burdens the heart due to diversion of the circulation to the gastrointestinal tract following a meal. Such a diversion increases cardiac blood and causes further stress on the heart. Moreover, acute fluctuations in blood pressure and heart rate occur after a rich meal and lead to further damage to the heart [21]. If an individual with CHF consumed a large, high-salt meal, acute decompensation could even occur [22]. The avoidance of over-eating may improve CHF-PRO by decreasing the incidence of these types of adverse events. This result provides new evidence supporting the management of CHF and direction for future studies.
An LSD was recommended by the 2016 European Society of Cardiology Guidelines for CHF [3]. In the present study, we confirmed that an LSD increased OS, PHYS, and PSYS of CHF-PRO. Previous studies and the ongoing Geriatric Out-of-Hospital Randomized Meal Trial in Heart Failure (GOURMET-HF) study applied the KCCQ summary score as an indicator of QoL outcome and drew the same conclusion as that in our study [23][24][25]. Regarding PHYS, the reason for the increase may be that an LSD improved symptoms and signs of CHF [26, 27] and promoted exercise tolerance in patients [27]. However, few studies have focused on the relationship between LSD and psychological states. More studies are needed to confirm this and the mechanism also remains to be further elucidated. Adherence to an LSD has also been noted by researchers. Chung et al confirmed that patients who adhered to an LSD perceived more benefits than those who were non-adherent [28]. All of the research above focused exclusively on statistical significance and ignored clinical significance. When MCID was introduced, it did not reach clinical significance, regardless of a patient's adherence to an LSD in this study. This also may be because some patients did not accurately calculate the amount of salt they ate at home.
More stringent studies and investigations examining clinical significance are needed in the future.
Regular aerobic exercise is encouraged in patients with HF to improve functional capacity and symptoms, as per guideline recommendations [3]. Studies have shown that exercise can reduce allcause mortality and readmission for patients with CHF; however, the effects of exercise on QoL remain uncertain [29]. A recent meta-analysis confirmed that exercise improved both exercise capacity and QoL compared with the no-exercise control group at the 12-month follow-up, but with weaker evidence for a treatment effect at the 6-month follow-up [30]. Our study demonstrated that exercise improved PRO, especially physical condition. This is consistent with previous studies and provides the new evidence for the effect at the 6-month follow-up. However, this strategy did not reach MCID. It may be because we only defined the frequency and time of exercise, but not the intensity.
The findings of this study should be interpreted in light of its limitations. First, all advice adopted in this study was beneficial to strategies for patients with CHF. Based on ethical considerations, we provided all participants with advice when they were discharged; as such, there was no control group.
It revealed that the causal effect was not as strong as that from a randomized controlled trial. We will use randomized controlled trial design in future research to assess one of the meaningful strategies in this study. Second, although this was a multicenter study, all patients were from the Shanxi Province of China and, as such, the findings may be regionally biased. Larger-scale studies are needed in the future to confirm the findings in this regard. Finally, some of the self-management strategies used in this study were not precisely defined. For example, a regular schedule did not limit the sleep time per day or apply related scales to measure sleep quality, which may have led to some imprecision. In future studies, we will further quantify the strategies addressed in this study to obtain more effective self-management strategies for patients with CHF.

Conclusions
In summary, the present study analyzed the effect of various self-management strategies on the dynamics of PRO using multi-level models and further evaluated clinical significance with MCID. We Helsinki declaration and its later amendments or comparable ethical standards. Patients were informed verbally and in writing about the study and gave written informed consent.

Consent for publication
All authors have approved the manuscript for publication.

Availability of data and material
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests
The authors declare that they have no competing interests.

Authors' contributions
All authors participated in the study design. JT was responsible for collecting the data and drafting the article. QZ, JR and LH participated in the data collection and modified the article. JZ and JL participated in the data analysis and modified the article. QH and YZ proposed the original concept for this study, supervised the data analysis, and revised the paper. All authors read and approved the final manuscript.       Comparation of MCID to the cumulative β for variables. Each point represents the value that the correspond β of strategy multiplied by (grade-1). MCID is shown as a dotted black line.
The strategy is of the clinical significance when the its value is larger than MCID. Figure (a) represents the influence of management strategies on OS. Figure (b) and (c) represent the influence of management strategies on PHY and PSY, respectively.