Comprehensive Individualized nursing intervention enhances health outcomes and quality of life in patients with heart failure

Abstract

Background

Heart failure (HF) is associated with high morbidity, readmissions, and impaired quality of life. Because patient responses vary, tailored, nurse-led strategies, particularly in nutrition, activity, and psychosocial support, may address needs that routine care does not fully meet.

Objective

To assess the effectiveness of an individualized, nurse-led intervention integrating nutrition, graded exercise, and psychosocial support in patients with HF.

Methods

This prospective, single-center, parallel-group study involved adults with HF (n = 110 per group), who were assigned to groups using an odd-even allocation method. The control group (CG) received routine nursing care. The observation group (OG) received the same routine care plus a 3-month individualized program comprising customized nutritional counseling, staged exercise guidance, and structured psychosocial support with follow-up. Baseline and follow-up assessments consisted of measuring time to symptom resolution, cardiac function, arterial blood gases, nutritional status, psychological status, quality of life, and adverse events between the two groups.

Results

Compared with routine nursing care (CG), individualized nurse-led care (OG) had shortened time to symptom improvement (dyspnea 2.05 ± 0.61 vs. 2.57 ± 0.76 days; p < 0.001), improved cardiac function (LVEF, CO ↑; LVEDD, LVESD ↓; 6MWT ↑; all p < 0.05), enhanced gas exchange (PaCO₂ ↓, PaO₂ ↑; both p < 0.05), and better nutritional status (p < 0.05). Additionally, the OG had improved psychological status (p < 0.05), enhanced quality of life (SF-36 75.43 ± 9.03 vs. 66.43 ± 9.09; p < 0.05), and fewer adverse events (6.36% vs. 20.0%; χ²=7.462; p = 0.006).

Conclusion

An individualized nurse-led intervention is associated with multidomain benefits in patients with HF, supporting the integration of personalized nursing strategies into routine HF care pathways.

Introduction

Heart failure (HF) is a prevalent clinical syndrome characterized by structural or functional impairment of ventricular filling or ejection of blood [1]. It manifests with congestion and reduced cardiac output, typically presenting with dyspnea, fatigue, peripheral edema, and limited exercise tolerance, and affects 1–3% of the global population (over 56 million people), with sharply increasing prevalence in older adults [2, 3]. Despite advances in pharmacological and device-based therapies, HF remains a leading cause of hospitalization and death in those aged ≥ 75 years; one-year mortality approaches 45% and five-year mortality can reach 75%, imposing a substantial burden on patients and health care systems [4–6].

Comorbid conditions such as hypertension, diabetes mellitus, and obesity, alongside tobacco exposure, accelerate HF progression and worsen outcomes [7]. Importantly, malnutrition is reported in more than half of patients, further compromises prognosis through loss of skeletal muscle, impaired cardiac and peripheral function, and increased susceptibility to complications [8–10]. Psychological distress and functional decline are also common, undermining adherence and increasing readmissions [11].

In routine inpatient care, nursing focuses on medication administration, observation of vital signs, fluid balance, and discharge education [12]. However, these routine practices often underemphasize individualized nutritional counseling, structured exercise, and psychosocial support, which are essential for long-term outcomes [13, 14]. Evidence from other chronic conditions such as diabetes mellitus, chronic kidney disease, and chronic obstructive pulmonary disease (COPD) suggests that nurse-led individualized interventions can improve clinical stability, adherence, and quality of life [15–18].

For the assessment of quality of life (QOL) in patients with HF, both disease-specific and generic instruments are commonly used. Disease-specific tools such as the Kansas City Cardiomyopathy Questionnaire (KCCQ) and the Minnesota Living with Heart Failure Questionnaire (MLHFQ) are considered more sensitive to HF-related symptoms and functional changes [19, 20]. However, given that HF is a systemic condition frequently accompanied by comorbidities such as malnutrition, psychological distress, and reduced physical capacity, broader health-related QOL measures may provide complementary insights [21]. The 36-Item Short Form Health Survey (SF-36), as a generic instrument, captures multidimensional aspects of physical and mental health and allows for a more comprehensive evaluation of overall well-being [22]. In the present study, SF-36 was selected to reflect the global impact of the multidisciplinary nursing intervention on patients’ general health status.

In HF specifically, the effectiveness of comprehensive, nurse-delivered programs that integrate nutrition, exercise, and psychological support remains insufficiently studied. Accordingly, this study aimed to evaluate whether a nurse-led individualized intervention, combining personalized nutrition management, graded exercise, and structured psychosocial support is associated with improvements in clinical and patient-reported outcomes in patients with HF compared with routine care.

Materials and methods

Study design and participants

This prospective, single-center, parallel-group, quasi-experimental study was conducted at our hospital between May 2021 and May 2024. Patients were enrolled according to the 2021 ESC guidelines for the diagnosis and treatment of acute and chronic HF and the 2022 AHA/ACC/HFSA guideline for the management of HF [23, 24]. Patients were sequentially enrolled and assigned to the control group (CG, n = 110) or observation group (OG, n = 110) using an odd-even allocation method based on the order of admission (odd-numbered patients to CG and even-numbered patients to OG). The rationale for using this method was its feasibility and practicality in a real-world clinical setting, where strict randomization procedures were not implemented [25]. To minimize selection bias, all eligible patients were consecutively recruited according to predefined inclusion and exclusion criteria, and group assignment was determined prior to intervention without investigator discretion. Additional baseline clinical variables, including NYHA functional class, LVEF, HF phenotype, comorbidities, and medication use, were collected to further characterize the study population. Importantly, baseline characteristics were comparable between the two groups (p > 0.05) (Table 1).

Table 1.

Baseline demographic and clinical characteristics of patients with HF

Items	CG (n = 110)	OG (n = 110)	p-value
Gender (male/female)	56/54	53/57	> 0.05
Average BMI (kg/m²)	21.64 ± 1.75	21.59 ± 1.67	> 0.05
Average age (years)	61.73 ± 7.26	62.54 ± 7.54	> 0.05
Hypertensive, n (%)	40 (36.36%)	37 (33.64%)	> 0.05
Diabetes mellitus, n (%)	28 (25.45%)	31 (28.18%)	> 0.05
Coronary artery disease, n (%)	35 (31.82%)	33 (30.00%)	> 0.05
Average disease course (years)	2.78 ± 0.56	2.75 ± 0.52	> 0.05
NYHA class (II/III/IV)	38/52/20	41/49/20	> 0.05
LVEF (%)	41.26 ± 6.84	40.89 ± 7.02	> 0.05
HF phenotype (HFrEF/HFpEF)	72/38	69/41	> 0.05
ACEI/ARB use, n (%)	67 (60.91%)	70 (63.64%)	> 0.05
β-blocker use, n (%)	74 (67.27%)	76 (69.09%)	> 0.05
Diuretic use, n (%)	81 (73.64%)	79 (71.82%)	> 0.05

Inclusion criteria were: (1) age ≥ 20 years; (2) diagnosis of HF based on symptoms/signs plus objective evidence of structural or functional cardiac abnormality and/or elevated natriuretic peptide levels per guideline criteria [23, 24]; (3) stable clinical condition at enrollment (no acute myocardial infarction or stroke within the previous 3 months); and (4) adequate cognitive function and ability to communicate and participate in nursing interventions.

Exclusion criteria were: (1) concurrent malignant tumors or autoimmune disease; (2) severe hepatic or renal dysfunction (ALT/AST > 3× upper limit of normal; eGFR < 30 ml/min/1.73 m²); (3) severe valvular or congenital heart disease requiring surgical intervention; (4) participation in another interventional clinical trial within the previous 30 days; or (5) incomplete clinical data or refusal to provide informed consent.

Sample size calculation

The sample size was calculated a priori based on the primary outcome, namely the post-intervention SF-36 quality-of-life score. Based on the expected between-group difference in SF-36 score, we assumed a clinically meaningful mean difference of 8 points between the observation group and control group, with a pooled standard deviation of 15 points. Using a two-sided significance level of α = 0.05 and 80% power, the independent-samples t-test calculation indicated that at least 56 patients were required in each group. After allowing for an anticipated 15–20% dropout or incomplete-data rate, the minimum required sample size was approximately 67–70 patients per group. During the study period, 220 eligible patients with complete follow-up data were enrolled, with 110 patients assigned to each group, which exceeded the minimum required sample size and provided adequate power for detecting the prespecified difference in the primary outcome. The calculation was performed using PASS 15.0 software (NCSS, LLC, Kaysville, UT, USA).

Interventions

Control group (CG)

Patients received routine nursing care according to hospital standards, including close monitoring of vital signs, symptoms, and fluid balance, administration of prescribed medications with observation for adverse reactions, and guidance on self-care measures such as rest, gradual activity, and adherence to fluid and sodium restrictions. Patients were also provided with brief discharge education on medication use, diet, and warning signs requiring medical attention, and maintenance of a clean, quiet ward environment with general emotional support.

Observation group (OG)

Patients received the same routine nursing care as the CG, plus a three-month individualized nursing program with structured post-discharge follow-up. Additionally, nurses performed a baseline assessment of nutritional, functional, and psychological status and developed individualized care plans in consultation with patients and families. Ongoing communication and follow-up visits were used to reinforce self-management, monitor progress, and to allow timely plan adjustments. The program consisted of three components, as described below.

1.  Nutritional intervention: Dietary adherence was monitored through regular follow-up consultations, and adjustments were made based on patient condition and nutritional status. Detailed dietary histories were obtained, and factors influencing nutritional status were evaluated. Daily energy requirements were estimated by age and body mass index (BMI), with macronutrient distribution was set at protein: carbohydrate: fat = 3:4:3. Dietary prescriptions included sodium restriction (≤ 2 g/day), fluid restriction (0.6–2.0 L/day depending on severity), reduced dietary fat, and increased intake of vegetables (≥ 400 g/day) and fruits (≥ 375 g/day).

2. Exercise intervention: The exercise program was tailored to each patient’s clinical status and tolerance and implemented in four stages: (1) rest during dyspnea episodes with appropriate ward temperature and humidity; (2) range of motion (ROM) exercises (10 min per session, three times daily); (3) bedside stepping (15 min per session, twice daily); and (4) walking and stair training sessions (15–20 min per session, twice daily). Exercise intensity was maintained at a low-to-moderate level, corresponding to a Borg Rating of Perceived Exertion (RPE) score of 9–13 [26], and was adjusted according to patient tolerance. Vital signs, including heart rate, blood pressure, and oxygen saturation, were monitored before and after each session. All exercise sessions during hospitalization were supervised by trained nursing staff. Progression between stages was based on clinical improvement, including relief of symptoms (e.g., dyspnea and fatigue), stable vital signs, and the patient’s ability to complete the current stage without discomfort. If patients experienced adverse symptoms, the intensity or stage was reduced accordingly.

3. Psychological intervention: Bedside counseling was provided to reduce anxiety, explain disease management, and enhance treatment adherence. After discharge, structured follow-up was conducted for 3 months, including weekly telephone consultations and monthly outpatient visits. Follow-up focused on monitoring symptoms, reinforcing adherence to dietary and exercise plans, and providing ongoing psychological support. Family members were encouraged to participate in follow-up to enhance compliance and emotional support.

Outcomes and measurements

Outcomes were assessed during hospitalization and over the three-month follow-up, as applicable. The primary outcome of this study was overall QOL improvement, assessed using the SF-36 score after intervention. Secondary outcomes included time to symptom improvement, cardiac function parameters, arterial blood gases, nutritional status, psychological status, and adverse events.

Quality of life (QOL)

The 36-Item Short Form Health Survey (SF-36) was used to assess eight domains of physical and mental health [22]. Each domain was scored 0-100 with higher scores indicating better health status. For analysis, an overall SF-36 score (0-100) was also calculated and reported as mean ± SD.

Time to symptom improvement

Time (days) from admission to physician-confirmed resolution of dyspnea, edema, fatigue, and correction of anemia was recorded as a secondary outcome. Symptom resolution was determined based on clinical examination findings combined with patient-reported improvement. Correction of anemia was defined as the return of hemoglobin levels to the normal reference range (≥ 120 g/L for males and ≥ 110 g/L for females), based on laboratory measurements. Anemia management followed routine clinical practice and was applied consistently across both groups.

Cardiac function

Echocardiography was performed to measure left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), and left ventricular ejection fraction (LVEF) in accordance with the American Society of Echocardiography recommendations [27]. Cardiac output (CO) was derived from Doppler parameters. Functional capacity was assessed by the six-minute walk test (6MWT) following American Thoracic Society guidelines [28]; distance was recorded in meters.

Arterial blood gases

Partial pressure of carbon dioxide (PaCO₂), partial pressure of oxygen (PaO₂), and pH were measured using a blood gas analyzer at rest on room air. Reference ranges were PaCO₂ 35–45 mmHg, PaO₂ 75–100 mmHg, and pH 7.35–7.45.

Nutritional status

BMI was calculated as weight (kg)/height (m²). Nutritional risk was evaluated using the Subjective Global Assessment (SGA), which classifies patients as A (well nourished), B (mild to moderate malnutrition), or C (severe malnutrition) [29]. Blood samples were analyzed for serum albumin (ALB), total protein (TP), hemoglobin (Hb), and transferrin (TF). Reference ranges were ALB 35–50 g/L, TP 60–80 g/L, Hb 120–160 g/L (male) and 110–150 g/L (female), and TF 2.0–3.6 g/L.

Psychological status

Anxiety and depression were assessed using the Self-Rating Anxiety Scale (SAS) [30] and the Self-Rating Depression Scale (SDS) [31]. Both are validated 20-item instruments scored on a 4-point Likert scale. Raw scores (20–80) were multiplied by 1.25 to yield a standard score (25–100), with higher scores indicating greater severity. Thresholds were: SAS < 50 = normal, 50–59 = mild, 60–69 = moderate, ≥ 70 = severe anxiety; SDS < 53 = normal, 53–62 = mild, 63–72 = moderate, ≥ 73 = severe.

Adverse events

Gastrointestinal and cardiac adverse events, including abdominal distension, diarrhea, constipation, worsening of HF, and arrhythmia were systematically monitored throughout hospitalization and follow-up. Events were captured via (i) daily patient self-reports of new or worsening symptoms, (ii) routine clinical examinations by nurses/physicians, and (iii) review of medical records, including progress notes and discharge summaries. Each suspected event was reviewed and confirmed by the attending physician. Patients were classified as ≥ 1 event or none, and incidence was expressed as a group proportion.

Statistical analysis

Statistical analysis was performed using SPSS version 20.0 (IBM Corp., Armonk, NY, USA), and figures were generated using GraphPad Prism version 8.0 (GraphPad Software, San Diego, CA, USA). Continuous variables were expressed as mean ± standard deviation (SD). Between-group comparisons were performed using independent samples t-tests, while within-group (pre-post) comparisons were conducted using paired t-tests. Categorical variables were presented as frequencies and percentages and analyzed using the chi-square (χ²) test. Normality of continuous variables was assessed using the Shapiro-Wilk test, and homogeneity of variance was evaluated using Levene’s test. To provide estimates of the magnitude and precision of treatment effects, between-groups mean differences (OG versus CG) with corresponding 95% confidence intervals (CIs) were calculated for continuous outcomes. Standardized effect sizes were quantified using Cohen’s d. For categorical outcomes, risk differences with 95% CIs were calculated. Because multiple secondary outcomes were evaluated, no formal adjustment for multiple comparisons was applied. Therefore, analyses of secondary outcomes should be considered exploratory, and the findings should be interpreted with appropriate caution. All statistical tests were two-sided, and a p-value < 0.05 was considered statistically significant.

Results

Baseline characteristics and clinical symptom improvement

There was no significant difference in the baseline clinical characteristics of the patients between the two groups (Table 1). Compared with the CG, patients in the OG experienced significantly faster resolution of all assessed clinical symptoms (Table 2). The time to relief of dyspnea was shorter in the OG than in the CG (2.05 ± 0.61 vs. 2.57 ± 0.76 days), corresponding to a mean difference of -0.52 days (95% CI: -0.71 to -0.33; Cohen’s d = 0.75; p < 0.001). Similarly, the time required for correction of anemia was reduced in the OG (4.88 ± 1.52 vs. 6.19 ± 1.86 days; mean difference: -1.31 days, 95% CI: -1.76 to -0.86; Cohen’s d = 0.77; p < 0.001). Patients in the OG also demonstrated faster resolution of edema (6.19 ± 1.64 vs. 7.93 ± 2.03 days; mean difference: -1.74 days, 95% CI: -2.23 to -1.25; Cohen’s d = 0.94; p < 0.001) and fatigue (5.84 ± 1.62 vs. 7.33 ± 1.66 days; mean difference: -1.49 days, 95% CI: -1.93 to -1.05; Cohen’s d = 0.90; p < 0.001).

Table 2.

Time to clinical symptom improvement in patients with heart failure

Groups	Dyspnea (days)	Correction of Anemia (days)	Edema (days)	Fatigue (days)
CG (n = 110)	2.57 ± 0.76	6.19 ± 1.86	7.93 ± 2.03	7.33 ± 1.66
OG (n = 110)	2.05 ± 0.61	4.88 ± 1.52	6.19 ± 1.64	5.84 ± 1.62
t value	5.596	5.720	6.993	6.737
Mean difference (95% CI)	-0.52 (-0.71, -0.33)	-1.31 (-1.76, -0.86)	-1.74 (-2.23, -1.25)	-1.49 (-1.93, -1.05)
Cohen’s d	-0.75	-0.77	-0.94	-0.90
P value	< 0.001	< 0.001	< 0.001	< 0.001

Cardiac function

As shown in Fig. 1, cardiac function improved in both groups following the intervention, with significantly greater improvements observed in the OG than in the CG. After intervention, LVEDD was significantly lower in the OG than in the CG (53.03 ± 6.57 vs. 57.01 ± 6.71 mm), corresponding to a mean difference of -3.98 mm (95% CI: -5.76 to -2.20; Cohen’s d = 0.71; p < 0.001). Similarly, LVESD was reduced in the OG compared with the CG (43.77 ± 6.25 vs. 47.83 ± 6.43 mm), with a mean difference of -4.06 mm (95% CI: -5.73 to -2.39; Cohen’s d = 0.74; p < 0.001). In contrast, measures of cardiac performance were significantly improved in the OG. LVEF was higher in the OG than in the CG (42.60 ± 2.54% vs. 38.03 ± 2.66%), yielding a mean difference of 4.57% (95% CI: 3.85–5.29; Cohen’s d = 1.49; p < 0.001). Cardiac output was also greater in the OG (4.57 ± 0.90 vs. 3.93 ± 0.83 L/min), with a mean difference of 0.64 L/min (95% CI: 0.41–0.87; Cohen’s d = 0.74; p < 0.001). Functional exercise capacity, assessed by 6MWT, was significantly improved in the OG, with patients achieving a greater walking distance than those in the CG (394.57 ± 55.90 vs. 333.93 ± 57.83 m). The between-group mean difference was 60.64 m (95% CI: 45.65–75.63; Cohen’s d = 1.07; p < 0.001). Within-group analyses further demonstrated significant improvements in all cardiac function parameters from baseline to post-intervention in both groups (all p < 0.05), with greater overall benefits observed in the OG.

Fig. 1.

Changes in cardiac function parameters before and after intervention in patients with HF

Arterial blood gases

As shown in Fig. 2, arterial blood gas parameters improved in both groups following the intervention, with greater improvements observed in the OG than in the CG. Post-intervention PaCO₂ was significantly lower in the OG than in the CG (41.11 ± 4.10 vs. 46.14 ± 4.22 mmHg), corresponding to a mean difference of -5.03 mmHg (95% CI: -6.11 to -3.95; Cohen’s d = 1.20; p < 0.001). In contrast, PaO₂ was significantly higher in the OG (81.47 ± 5.47 vs. 70.55 ± 5.32 mmHg), with a mean difference of 10.92 mmHg (95% CI: 9.46–12.38; Cohen’s d = 1.46; p < 0.001). Arterial pH remained within the normal physiological range (7.35–7.45) in both groups throughout the study. The baseline pH values were comparable between the two groups (CG: 7.42 ± 0.04; OG: 7.41 ± 0.05). Following intervention, pH decreased slightly in both groups but remained within the normal range, with a lower value observed in the OG than in the CG (7.37 ± 0.04 vs. 7.40 ± 0.04; mean difference: -0.03, 95% CI: -0.04 to -0.02; Cohen’s d = 0.75; p < 0.001). Although this difference reached statistical significance, both values remained within the normal physiological range, suggesting limited clinical relevance. Within-group analyses demonstrated significant improvements in arterial blood gas parameters following intervention in both groups (all p < 0.05), with greater overall improvements observed in the OG.

Fig. 2.

Arterial blood gases parameters before and after intervention in patients with HF

Nutritional status

As shown in Fig. 3, nutritional status improved in both groups following the intervention, with significantly greater improvements observed in the OG than in the CG. After intervention, BMI was significantly higher in the OG than in the CG (23.57 ± 1.75 vs. 22.65 ± 1.69 kg/m²), corresponding to a mean difference of 0.92 kg/m² (95% CI: 0.47–1.37; Cohen’s d = 0.53; p < 0.001). Similarly, serum ALB levels were higher in the OG (37.56 ± 5.56 vs. 35.63 ± 5.34 g/L), with a mean difference of 1.93 g/L (95% CI: 0.47–3.38; Cohen’s d = 0.54; p = 0.009). TP was also significantly increased in the OG compared with the CG (66.25 ± 5.87 vs. 63.88 ± 6.03 g/L), yielding a mean difference of 2.37 g/L (95% CI: 0.80–3.94; Cohen’s d = 0.40; p = 0.003). Markers associated with hematologic and nutritional status also favored the OG. Hb levels were higher in the OG than in the CG (97.79 ± 6.89 vs. 90.36 ± 6.83 g/L), corresponding to a mean difference of 7.43 g/L (95% CI: 5.63–9.23; Cohen’s d = 1.09; p < 0.001). Likewise, TF concentrations were significantly greater in the OG (3.28 ± 1.05 vs. 2.76 ± 1.03 g/L), with a mean difference of 0.52 g/L (95% CI: 0.27–0.77; Cohen’s d = 0.52; p < 0.001). Nutritional risk, assessed using the SGA, was significantly lower in the OG than in the CG (6.18 ± 1.82 vs. 7.21 ± 1.96), corresponding to a mean difference of -1.03 points (95% CI: -1.54 to -0.52; Cohen’s d = 0.55; p < 0.001).

Fig. 3.

Nutritional status before and after intervention in patients with HF

Adverse events

As indicated in Table 3, the overall incidence of gastrointestinal and cardiac adverse events was significantly lower in the OG than in the CG (6.36% vs. 20.00%). The absolute risk difference was − 13.64% (95% CI: -21.92% to -5.36%), indicating a significantly lower risk of adverse events among patients receiving the individualized nursing intervention (χ² = 7.462, p = 0.006). The most frequently reported adverse events were arrhythmia and diarrhea. Specifically, event rates in the CG and OG were 6.36% versus 1.82% for arrhythmia, 5.45% versus 1.82% for diarrhea, 2.73% versus 0.91% for abdominal distension, 2.73% versus 0.91% for constipation, and 2.73% versus 0.91% for worsening heart failure. Although the incidence of each individual event was numerically lower in the OG, the study was not specifically powered to detect differences in individual adverse-event categories because of the small number of events observed.

Table 3.

Incidence of adverse events in patients with HF

Groups	Abdominal distension n (%)	Diarrhea n (%)	Constipation n (%)	HF Worsening n (%)	Arrhythmia n (%)	Total incidence n (%)
CG (n = 110)	3 (2.73)	6 (5.45)	3 (2.73)	3 (2.73)	7 (6.36)	22 (20.0)
OG (n = 110)	1 (0.91)	2 (1.82)	1 (0.91)	1 (0.91)	2 (1.82)	7 (6.36)
Risk difference (95% CI)						-13.64% (-21.92, -5.36)
χ²						7.462
P value						0.006

Psychological status

As shown in Fig. 4, psychological status improved in both groups following the intervention, with significantly greater reductions in anxiety and depression symptoms observed in the OG than in the CG. Post-intervention SAS scores were significantly lower in the OG than in the CG (36.73 ± 4.22 vs. 43.63 ± 4.59), corresponding to a mean difference of -6.90 points (95% CI: -8.06 to -5.74; Cohen’s d = 1.55; p < 0.001). Similarly, post-intervention SDS scores were significantly lower in the OG (31.47 ± 4.32) than in the CG (38.24 ± 4.68), with a mean difference of -6.77 points (95% CI: -7.97 to -5.57; Cohen’s d = 1.51; p < 0.001).

Fig. 4.

Self-rating anxiety scale (SAS) and self-rating depression scale (SDS) scores before and after intervention in patients with HF

Quality of life

Quality of life, assessed by the SF-36 (the primary outcome), improved in both groups following the intervention, with significantly greater improvement observed in the OG than in the CG (Fig. 5). Post-intervention SF-36 scores were significantly higher in the OG than in the CG (75.43 ± 9.03 vs. 66.43 ± 9.09), corresponding to a mean difference of 9.00 points (95% CI: 6.63–11.37; Cohen’s d = 0.99; p < 0.001).

Fig. 5.

SF-36 quality of life scores before and after intervention in patients with HF

Discussion

HF is a progressive syndrome associated with high morbidity, frequent readmissions, and poor survival despite advances in pharmacological and device-based therapies [32]. Beyond impaired cardiac function, malnutrition, exercise intolerance, and psychological distress are common and further degrade outcomes and quality of life [33]. Addressing these multidimensional needs is integral to contemporary HF care, and nurse-led, individualized interventions are increasingly recognized as key components of comprehensive management [14].

In this study, a nurse-led program integrating nutritional counseling, graded exercise, and psychosocial support was associated with broad improvements compared with routine nursing. Relative to the CG, patients in the OG showed faster symptom resolution, greater improvements in echocardiographic indices and 6MWT, more favorable arterial blood gases, improved nutritional status, lower anxiety and depression scores, higher SF-36 scores, and fewer adverse events. The observed improvements across multiple domains may be explained by the integrated nature of the intervention. Nutritional support may improve metabolic status, structured exercise may enhance functional capacity, and psychological support may improve adherence and reduce stress-related burden [34–36]. However, it should be noted that some physiological outcomes, such as echocardiographic parameters and arterial blood gases, may also be influenced by concurrent medical treatment and individual patient variability. Therefore, the observed effects are likely multifactorial, and the contribution of nursing interventions should be interpreted with appropriate caution. Our results align with prior work underscoring the importance of nutritional support in HF. Malnutrition is prevalent and predicts adverse outcomes [8]. Meta-analyses estimate a pooled malnutrition prevalence of approximately 45–46% in HF and link malnutrition with higher mortality and hospitalizations [37, 38]. Randomized or structured in-hospital nutrition programs have also shown benefit: among patients at high nutritional risk, individualized nutritional support reduced short-term mortality and major cardiovascular events with effects persisting to 180 days [39]. Tailored dietary counseling and nutrient optimization can improve ALB, Hb, and TF while helping to control congestion and fatigue [40]. Consistent with this evidence, the OG showed favorable changes in BMI, SGA category, and biochemical markers, which may reflect correction of nutritional deficits and improved functional reserve.

Structured, nurse-supervised exercise has been associated with enhanced functional capacity, improved cardiac performance, and lower readmissions in HF [41]. The staged program used here (ROM to ambulation/stairs) was associated with higher 6MWT and concurrent improvements in systolic function with reductions in ventricular dimensions, alongside decreases in PaCO₂ and increases in PaO₂. These patterns are consistent with better ventilatory efficiency and activity tolerance.

Psychological interventions were another important element of the program. Anxiety and depression are frequent in HF and can undermine adherence and prognosis [42]. Trial and review evidence shows that cognitive-behavioral therapy (CBT) in HF reduces depressive and anxiety symptoms and improves quality of life and self-care, which aligns with the lower SAS/SDS observed in the OG [43]. While our psychological support did not follow a formal CBT protocol, the direction of effect is consistent with benefits reported for structured psychological care [43]. Broader cardiovascular meta-analyses similarly report improvements in psychological symptoms and reductions in cardiac morbidity with structured psychological interventions, supporting integration within cardiac rehabilitation and multidisciplinary care [44]. Family involvement is also associated with better self-care and outcomes in HF dyads, consistent with our family-supported approach [45]. Although self-care behaviors were not directly measured using standardized instruments, the intervention included components targeting patient education, behavioral guidance, and adherence, which may have indirectly contributed to the observed improvements.

Notably, the incidence of adverse events was lower in the OG, paralleling reports that comprehensive, nurse-supported models improve stability. Although our intervention did not include telemonitoring, the lower adverse-event rate may reflect improved clinical stability associated with enhanced surveillance and patient engagement. Cochrane reviews show that structured telephone support and home telemonitoring in HF reduce all-cause mortality and HF hospitalizations, consistent with better clinical surveillance, education, and engagement [46]. Multidisciplinary HF services similarly improve care processes and outcomes, supporting the plausibility of the safety signal observed here [47]. In practice, closer monitoring, medication and dietary guidance, and improved engagement may mitigate preventable complications and stabilize clinical status.

This study has several limitations. First, it was a prospective, single-center, parallel-group, quasi-experimental study with a relatively small sample size, which may limit generalizability. Second, the follow-up period was short, and long-term outcomes such as readmission rates and mortality were not assessed. Third, because the intervention included nutritional, exercise, and psychological components, the independent effects of each component could not be distinguished. In addition, the use of an odd-even allocation method rather than true randomization may introduce potential selection bias, although baseline characteristics were comparable between groups. Furthermore, some heart failure-specific baseline variables were not comprehensively collected, which may limit the completeness of patient characterization. Additionally, the study was not prospectively registered in a public clinical trial registry. Although the study protocol, eligibility criteria, intervention procedures, and outcome measures were predefined and conducted under ethics committee approval, the lack of prospective registration may reduce transparency and increase the possibility of perceived selective outcome reporting. Finally, the use of the SF-36 as a generic quality-of-life instrument, rather than disease-specific tools such as the KCCQ or the MLHFQ, may reduce sensitivity to heart failure-specific changes. Future multicenter prospective studies with larger cohorts, longer follow-up, and more comprehensive outcome measures are needed to validate these findings.

Conclusion

Individualized, nurse-led care integrating nutrition, graded exercise, and psychosocial support is associated with multidomain improvements in patients with HF compared with routine care. Embedding such programs into standard care pathways may enhance patients’ recovery and quality of life outcomes.

Authors' contributions

FL conceived and designed the study. FL, JZ, and ZL contributed significantly to the experiments, arranging data, and performing data analyses. FL wrote and revised the manuscript. All authors read and approved the final manuscript.

Funding

This study received no external funding support.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

All patients provided their written, voluntarily informed consent. All procedures were carried out in accordance with the guidelines outlined in the Helsinki Declaration, and this study was approved by the Ethics Committee of Xuanwu Hospital, Capital Medical University (approval number: 21242KPRP-326).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.