Clinical Importance of Protein Intake in Hospitalized Elderly Patients With Heart Failure

Abstract

Background: The relationship between protein intake and the long-term prognosis of elderly patients with heart failure remains poorly understood. We investigated the association between predischarge protein intake and long-term prognosis in hospitalized elderly patients with heart failure.

Methods and Results: A single-center, retrospective analysis of hospitalized patients aged ≥65 years with heart failure and reduced ejection fraction was conducted. Protein intake was evaluated by nutritionists based on visual measurements of the percentage of dietary intake obtained for 7 days before discharge by a nurse. A cutoff of 1.2 g/kg/day protein intake was used to compare the incidence of a composite endpoint, including all-cause mortality and heart failure rehospitalization within 1 year. Among the 100 patients (median age 79 years; 47% male), 56% had low protein intake (<1.2 g/kg/day). Patients with low protein intake had a significantly higher rate of composite endpoints than those with high protein intake (50% vs. 20%; log-rank test P=0.03). Multivariable Cox proportional hazards model revealed that low protein intake was independently associated with long-term prognosis with a hazard ratio of 2.73 and a 95% confidence interval of 1.10–6.80 (P=0.03).

Conclusions: Low protein intake in the predischarge phase was associated with long-term prognosis in hospitalized elderly patients with heart failure and reduced ejection fraction.

With the increasing aging population in developed countries, the incidence of cardiovascular diseases, especially congestive heart failure, in the elderly has surged markedly, representing a major public health issue.¹ Despite significant advances in medication and interventional therapies, long-term outcomes, including death and heart failure rehospitalization, remain unsatisfactory for elderly patients with heart failure.² Geriatric factors, including frailty, malnutrition, cognitive function, social support, and cardiopulmonary function, are considered to have a multifaceted effect on the prognosis of elderly patients with heart failure.^3,4

Low protein intake is often present in elderly patients with chronic heart failure.³ Several factors associated with heart failure, such as anorexia, altered olfactory function, mastication disorders and social isolation, are known to cause reduced protein intake.⁵ Low protein intake contributes to an imbalance between catabolism and anabolism, which with time promotes geriatric conditions such as frailty and cardiac cachexia. Protein intake must be increased to correct protein deficiency and prevent the progression of frailty and sarcopenia.³ Previous studies have demonstrated that the supplementation of protein foods, such as essential amino acids, creatine, and L-arginine, improves the prognosis of cardiovascular patients.⁶ Despite the important clinical consequences of protein deficiencies and treatment for them, protein deficiencies are still substantially underestimated, inaccurately assessed, and not counteracted.⁷ Nutritional management targeted at preventing the progression of malnutrition and abnormal body composition during hospitalization is important from the perspective of patient prognosis. The American Society for Parenteral and Enteral Nutrition (ASPEN) and the European Society for Clinical Nutrition and Metabolism (ESPEN) recommend a protein intake of at least 1.2 g/kg/day for elderly patients with acute or chronic disease.^8,9 However, the recommended daily protein intake in elderly patients with heart failure has not been established, and the effect of protein intake >1.2 g/kg/day on long-term prognosis is poorly understood.^10,11 In the present study, we investigated the association between low protein intake and long-term prognosis in hospitalized elderly patients with heart failure.

Methods

Study Population

This was a single-center, retrospective, observational study. Consecutive patients aged ≥65 years who were admitted to the Kindai University Hospital between April 2018 and March 2021 with a diagnosis of acute decompensated heart failure and who had a left ventricular ejection fraction of <40% before discharge (n=222) were included. Among these patients, those who died in hospital (n=25), were discharged <7 days after admission (n=34), had end-stage renal disease requiring dialysis (n=13), were provided a protein-restricted diet due to chronic kidney disease (n=21), had no oral intake before discharge (n=3), or were lost to follow up within 1 year (n=26) were excluded. The patients in the study were classified into 2 groups based on protein intake: low (<1.2 g/kg/day), and high (≥1.2 g/kg/day) protein intake. Acute decompensated heart failure was diagnosed according to the Framingham criteria.¹²

The study protocol was approved by the Kindai University Ethics Committee (R05-203), and patients were recruited using an opt-out approach. This study conformed to the principles outlined in the 1975 Declaration of Helsinki. All patients received guideline-directed acute treatment by the attending physician and were prescribed standard therapeutic agents such as loop diuretics, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, β-blockers, and mineralocorticoid receptor antagonists.¹³

Data Collection

Age, sex, New York Heart Association (NYHA) class, vital signs, and medical history of the patients at admission were obtained from hospital medical records. Body mass index (BMI), vital signs, blood test data, and medication data were extracted from the hospital medical records at discharge. The prognostic nutritional index (PNI) before discharge was calculated using the following formula: 10 × serum albumin level at discharge (g/dL) + 0.005 × total lymphocyte count at discharge (mm³). Echocardiography was performed by a cardiologist before discharge, and left ventricular ejection fraction was measured using the Simpson method.

Dietary Management and Assessment

The patient’s nutritional strategy was planned by the attending physician and nutritionist and was determined based on the patient’s current symptoms. Target energy and protein levels were calculated using a simple formula based on the standard body weight. Based on the ESPEN guidelines, 30 kcal/kg/day of energy and 1.2 g/kg/day of protein were used as standards and adjusted according to the individual patient’s condition.⁹ Oral intake was assessed visually by a nurse after each meal on a 10-point scale of percentage intake.¹⁴ The main meals and dishes were estimated separately. This is standard practice in most hospitals in Japan. Based on the calculated daily oral intake for 7 days before discharge, the nutritionist calculated the actual nutritional intake, including daily energy and protein intake.

Outcome

The primary endpoint was a comparison of the incidence of composite endpoint within 1 year between patients with low protein intake and those with high protein intake. The composite endpoint was all-cause mortality and rehospitalization for heart failure. The incidence of these events was obtained from medical records or questionnaires mailed to hospitals where the patients had follow-up appointments. The secondary endpoint was a comparison of the incidences of composite endpoints within 1 year between patients with an energy intake ≥30 kcal/kg/day and those with an energy intake <30 kcal/kg/day.

Statistical Analysis

Continuous variables are expressed as medians between interquartile ranges and compared using the Wilcoxon test. Categorical variables are expressed as percentages and compared using the χ² test. The Kaplan-Meier survival analysis revealed event-free rates, and log-rank tests were used to compare the primary and secondary endpoints for subgroup analyses. Univariate and multivariate analyses were performed using a Cox proportional hazards model. Adjusted models were selected based on risk factors related to long-term prognosis and the nutritional assessment index, including age, sex, BMI and PNI ≤38. Subgroup analyses were conducted according to sex, NYHA class, and BMI.

Propensity score matching was performed to minimize bias between the 2 groups. The following 3 items showed significant differences between the 2 groups in patient background and were selected as factors for the propensity score: age (<79 vs. ≥79 years), BMI (<19.8 vs. ≥19.8 kg/m²), and serum creatinine (<1.10 vs. ≥1.10 mg/dL). A close correlation was found between energy and protein intake (Pearson’s rank correlation coefficient r=0.71). Energy intake was excluded from the propensity score matching due to multicollinearity considerations. All statistical analyses were performed using SPSS 23.0 J (IBM Corporation, Armonk, NY, USA), with P<0.05 considered significant.

Results

Patient Characteristics

Among the 100 patients (mean age 79 years; 47% male), 56% had low protein intake (Table 1). Forty-three percent had a history of hospitalization for heart failure, and 34% had a history of myocardial infarction. Patients with low protein intake were younger than those with high protein intake. In the admission data, NYHA classification, blood pressure, heart rate, comorbidities, and history of hospitalization for heart failure were comparable between the 2 groups.

Table 1.

Patient Characteristics at Admission in the Full Analysis Set

	All patients (n=100)	Low protein intake (n=56)	High protein intake (n=44)	P value
Age (years)	79 (73–85)	78 (72–82)	82 (78–88)	0.03
Male	47 (47)	22 (39)	25 (57)	0.08
NYHA class III/IV	75 (75)	43 (77)	32 (73)	0.64
SBP (mmHg)	133 (111–150)	132 (114–146)	136 (107–160)	0.97
DBP (mmHg)	85 (67–100)	83 (69–99)	87 (66–106)	0.67
Heart rate (beats/min)	93 (80–112)	91 (77–111)	100 (85–113)	0.40
Comorbidity
Hypertension	74 (74)	40 (71)	34 (77)	0.51
Dyslipidemia	50 (50)	30 (54)	20 (46)	0.42
Diabetes	40 (40)	24 (43)	16 (36)	0.51
Atrial fibrillation	39 (39)	23 (41)	16 (36)	0.63
COPD	8 (8)	3 (5)	5 (11)	0.23
Prior HF hospitalization	43 (43)	26 (46)	17 (39)	0.44
Prior MI	34 (34)	22 (39)	12 (27)	0.21

Data are presented as median (25th to 75th percentiles), or n (%). COPD, chronic obstructive pulmonary disease; DBP, diastolic blood pressure; HF, heart failure; MI, myocardial infarction; NYHA, New York Heart Association; SBP, systolic blood pressure.

The discharge data revealed that patients with low protein intake had significantly higher BMI and serum creatinine levels than those with high protein intake (Table 2). Blood pressure, heart rate, and PNI were comparable between the 2 groups. Although a sodium glucose cotransporter 2 inhibitor was administered at a lower rate, the administered rate was higher in patients with low protein intake than in those with high protein intake. There were no significant differences in the use of other medications between the 2 groups. Daily energy intake per kilogram of body weight was significantly lower in patients with low protein intake than in those with high protein intake.

Table 2.

Patient Characteristics at Discharge in the Full Analysis Set

	All patients (n=100)	Low protein intake (n=56)	High protein intake (n=44)	P value
BMI (kg/m2)	19.8 (17.8–22.1)	21.5 (19.3–24.5)	17.9 (16.7–19.7)	<0.01
SBP (mmHg)	102 (93–118)	99 (93–119)	103 (99–118)	0.53
DBP (mmHg)	61 (55–68)	59 (55–70)	64 (55–68)	0.65
Heart rate (beats/min)	70 (63–79)	72 (63–78)	69 (62–79)	0.46
Laboratory parameters
Hemoglobin (g/dL)	12.1 (10.5–14.0)	11.9 (10.7–14.2)	12.4 (10.0–13.9)	0.99
Serum creatinine (mg/dL)	1.10 (0.84–1.59)	1.34 (0.90–1.76)	0.94 (0.79–1.30)	<0.01
Serum albumin (g/dL)	3.3 (3.0–3.7)	3.3 (3.0–3.7)	3.5 (3.1–3.8)	0.46
High-sensitive CRP (mg/dL)	0.30 (0.11–0.96)	0.39 (0.15–1.31)	0.22 (0.06–0.79)	0.05
BNP (pg/mL)	361 (242–719)	357 (225–717)	377 (239–735)	0.97
PNI	41 (37–45)	40 (37–45)	42 (38–45)	0.51
PNI ≤38	34 (34)	21 (38)	13 (30)	0.37
LVEF (%)	30 (24–33)	30 (24–33)	30 (26–33)	0.85
Prescription
Loop diuretics	90 (90)	49 (88)	41 (93)	0.28
ACEI/ARB	87 (87)	49 (88)	38 (87)	0.87
β-blocker	78 (78)	41 (73)	37 (84)	0.19
MRA	56 (56)	31 (55)	25 (57)	0.88
SGLT2-I	15 (15)	12 (21)	3 (7)	0.04
Energy intake
kcal/day	1,390 (1,250–1,540)	1,350 (1,150–1,530)	1,410 (1,280–1,530)	0.11
kcal/kg/day	27.4 (23.2–31.6)	23.7 (19.3–25.1)	31.7 (29.8–34.7)	<0.01
Protein intake
g/day	56 (51–63)	56 (47–61)	58 (53–65)	0.02
g/kg/day	1.1 (0.9–1.3)	0.9 (0.8–1.1)	1.3 (1.2–1.4)	<0.01

Data are presented as median (25th to 75th percentiles), or n (%). ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; BMI, body mass index; BNP, B-type natriuretic peptide; CRP, C-reactive protein; DBP, diastolic blood pressure; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonist; PNI, prognostic nutritional index; SBP, systolic blood pressure; SGLT2-I, sodium glucose cotransporter 2 inhibitor.

Outcome

The overall incidence of the composite endpoint at 1 year was 37% (37 of 100 patients). The Kaplan-Meier analysis revealed that patients with low protein intake had a significantly higher incidence of the composite endpoint within 1 year than those with high protein intake (50% [28 of 56 patients] vs. 20% [9 of 44 patients]; log-rank test P=0.03; Figure 1). The Cox proportional hazards model analysis demonstrated that lower protein intake was associated with a hazard ratio (HR) of 2.34 (95% confidence interval [CI] 1.08–5.05) for the composite endpoint in univariable analysis (Table 3). Multivariable analysis revealed an independent association with an HR of 2.73 (95% CI 1.10–6.80).

Figure 1.

Kaplan-Meier analysis of patients who were free of the composite endpoint, including all-cause death and heart failure rehospitalization classified by protein intake.

Table 3.

Cox Regression Hazard Model for the Composite Endpoint

	Unadjusted HR (95% CI)	P value	Adjusted HR* (95% CI)	P value
Protein intake <1.2 g/kg/day	2.34 (1.08–5.05)	0.03	2.73 (1.10–6.80)	0.03

*Data on age, sex, body mass index, and PNI ≤38 were collected. CI, confidence interval; HR, hazard ratio; PNI, prognostic nutritional index.

When study patients were classified by an energy intake of 30 kcal/kg/day, the incidences of composite endpoints within 1 year were comparable between the 2 groups (patients with energy intake ≥30 kcal/kg/day 24% [8 of 33 patients] vs. patients with energy intake <30 kcal/kg/day 36% [24 of 67 patients]; log-rank test P=0.23; Supplementary Figure 1). The Cox proportional hazards model analysis for composite endpoints demonstrated that energy intake <30 kcal/kg/day resulted in a HR of 1.63 (95% CI 0.73–3.63), P=0.23 in a univariable analysis, and a HR of 1.51 (95% CI 0.60–3.83), P=0.38 in multivariable analysis (Supplementary Table).

Subgroup Analyses

Patients were stratified into subgroups based on sex, NYHA classification, and BMI (Supplementary Figure 2A–F). In the subgroup analysis (Supplementary Figure 2A,B), male patients with low protein intake had a significantly higher incidence of the composite endpoint than those with high protein intake (55% [12 of 22 patients] vs. 16% [4 of 25 patients]; log-rank test P<0.01). However, there was no significant difference between low and high protein intake in male patients (those with low protein intake 32% [11 of 34 patients] vs. those with high protein intake 26% [5 of 19 patients]; log-rank test P=0.61).

In the NYHA classification I or II subgroup, no significant difference was observed in the composite endpoint (patients with low protein intake 23% [3 of 13 patients] vs. patients with high protein intake 17% [2 of 12 patients]; log-rank test P=0.64; Supplementary Figure 2C). In contrast, in the subgroup with NYHA classification III or IV, patients with low protein intake had a significantly higher incidence of the composite endpoint than those with high protein intake (47% [20 of 43 patients] vs. 22% [7 of 32 patients]; log-rank test P=0.03; Supplementary Figure 2D).

In the subgroup with BMI <18.5 kg/m² (Supplementary Figure 2E), there was no significant difference between the 2 groups (patients with low protein intake 38% [3 of 8 patients] vs. patients with high protein intake 28% [7 of 25 patients]; log-rank test P=0.50). In contrast, in the subgroup with BMI ≥18.5 kg/m² (Supplementary Figure 2F), there was a significant difference in the composite endpoint between the 2 groups (patients with low protein intake 42% [20 of 48 patients] vs. patients with high protein intake: 11% [2 of 19 patients]; log-rank test P=0.02).

Propensity Score Matching

Propensity score matching was performed to adjust for differences in patient backgrounds between the 2 groups, and 22 patients with low protein intake and 22 with high protein intake were matched in a 1 : 1 ratio. The patient background at admission after propensity score matching showed no significant differences between the 2 groups in terms of age, sex, NYHA classification, vital signs, or comorbidities (Table 4). Regarding patient background at discharge, the BMI and vital signs were not significantly different between the 2 groups (Table 5). Blood tests showed no significant differences between the 2 groups except for high-sensitivity C-reactive protein levels. The PNI was significantly lower in patients with low protein intake than in those with high protein intake. After propensity score matching, the incidence of the composite endpoint was compared between the 2 groups (Figure 2). Patients with low protein intake had a significantly higher incidence of the composite endpoint within 1 year than those with high protein intake (41% [9 of 22 patients] vs. 9% [2 of 22 patients]; log-rank test P=0.02).

Table 4.

Patient Characteristics at Admission After Propensity Score Matching

	All patients (n=44)	Low protein intake (n=22)	High protein intake (n=22)	P value
Age (years)	80 (76–86)	80 (76–85)	80 (78–86)	0.94
Male	23 (52)	11 (50)	12 (55)	0.76
NYHA class III/IV	33 (75)	18 (82)	15 (69)	0.30
SBP (mmHg)	134 (110–153)	130 (95–152)	139 (112–159)	0.31
DBP (mmHg)	83 (64–98)	88 (65–97)	85 (65–106)	0.60
Heart rate (beats/min)	94 (81–112)	88 (79–114)	100 (85–107)	0.43
Comorbidity
Hypertension	37 (84)	17 (77)	20 (91)	0.21
Dyslipidemia	21 (48)	13 (59)	8 (36)	0.13
Diabetes	17 (39)	9 (41)	8 (36)	0.76
Atrial fibrillation	15 (34)	9 (41)	6 (27)	0.34
COPD	1 (2)	0 (0)	1 (5)	0.50
Prior HF hospitalization	13 (30)	8 (36)	5 (23)	0.32
Prior MI	14 (32)	9 (41)	5 (23)	0.20

Data are presented as median (25th–75th percentiles), or n (%). Abbreviations as in Table 1.

Table 5.

Patient Characteristics at Discharge After Propensity Score Matching

	All patients (n=44)	Low protein intake (n=22)	High protein intake (n=22)	P value
BMI (kg/m2)	19.5 (17.2–21.2)	20.0 (18.0–25.2)	19.1 (16.9–20.7)	0.16
SBP (mmHg)	101 (95–113)	102 (94–112)	102 (98–117)	0.62
DBP (mmHg)	62 (56–68)	59 (57–66)	64 (56–70)	0.79
Heart rate (beats/min)	70 (62–78)	72 (64–81)	67 (63–76)	0.17
Laboratory parameters
Hemoglobin (g/dL)	12.0 (10.4–13.6)	11.3 (10.5–12.9)	12.3 (10.0–14.6)	0.21
Serum creatinine (mg/dL)	0.98 (0.83–1.87)	1.00 (0.84–2.22)	0.96 (0.78–1.40)	0.33
Serum albumin (g/dL)	3.3 (2.9–3.7)	3.1 (2.7–3.5)	3.5 (3.1–3.8)	0.06
High-sensitive CRP (mg/dL)	0.34 (0.14–1.45)	0.65 (0.22–2.06)	0.21 (0.06–1.03)	0.02
BNP (pg/mL)	337 (145–724)	369 (283–799)	292 (125–750)	0.26
PNI	41 (36–46)	38 (33–45)	42 (38–48)	<0.05
PNI ≤38	17 (39)	12 (55)	5 (23)	0.03
LVEF (%)	30 (27–34)	30 (24–34)	30 (29–34)	0.66
Prescription
Loop diuretics	41 (93)	19 (86)	22 (100)	0.12
ACEI/ARB	39 (89)	19 (86)	20 (91)	0.50
β-blocker	37 (84)	17 (77)	20 (91)	0.21
MRA	26 (59)	13 (59)	13 (59)	1.00
SGLT2-I	7 (16)	6 (27)	1 (5)	<0.05
Energy intake
kcal/day	1,390 (1,240–1,510)	1,280 (1,020–1,430)	1,440 (1,340–1,560)	<0.01
kcal/kg/day	27.8 (24.0–31.1)	23.9 (19.1–24.9)	30.6 (28.7–34.3)	<0.01
Protein intake
g/day	56 (50–62)	51 (42–56)	60 (55–65)	<0.01
g/kg/day	1.1 (0.9–1.3)	0.9 (0.8–1.0)	1.3 (1.2–1.4)	<0.01

Data are presented as median (25th–75th percentiles), or n (%). Abbreviations as in Table 2.

Figure 2.

Kaplan-Meier analysis of patients who were free of composite endpoint after propensity score matching.

Discussion

In the present study, nurses visually checked the percentage of dietary intake of hospitalized elderly patients with heart failure for 7 days before discharge, and protein intake was assessed by a nutritionist. The results demonstrated that 56% of the patients did not achieve a protein intake of at least 1.2 g/kg/day. Compared with patients with high protein intake, those with low protein intake were younger, had worse renal function at discharge, and had significantly lower daily energy intake per body weight. Furthermore, patients with low protein intake had a poorer long-term prognosis than those with high protein intake. In hospitalized elderly patients with heart failure, low protein intake was independently associated with long-term prognosis. Subgroup analyses revealed that among male patients, NYHA III/IV patients, and patients with a BMI of 18.5 kg/cm², patients with a low protein intake had a worse long-term prognosis than those with a high protein intake. After propensity score matching, patients with low protein intake had a significantly higher incidence of composite endpoints than those with high protein intake.

Malnutrition is highly prevalent in patients with heart failure and has the potential to affect the trajectory of the disease.¹⁵ Nevertheless, major heart failure guidelines recommend a limited consensus on malnutrition because of the lack of effective treatment strategies.^16,17 Guidelines for nutritional therapy recommend a protein intake of at least 1.2 g/kg/day for elderly patients with acute or chronic diseases; however, it is unclear whether this recommendation extends to patients with heart failure.⁹ Treatment strategies for appropriate nutritional interventions need to be established for elderly patients with heart failure.

A previous study has reported on the estimation of protein intake from urinalysis and its association with prognosis in elderly patients with heart failure.¹⁰ The researchers used the large observational study (BIOSTAT-CHF) database to calculate the estimated protein intake based on urinary urea nitrogen obtained from spot urine at the time of admission and BMI. When patients were stratified into quartiles based on estimated protein intake, a significant increase in all-cause mortality in the group with the lowest estimated protein intake was observed compared with those with the highest. In their study, patients with a low estimated protein intake had more signs of fluid overload, such as peripheral edema, rales, and hepatomegaly, than those with a high estimated protein intake. This finding suggests that protein intake during the acute phase of heart failure is affected by the severity of heart failure. Protein intake before discharge is considered to reflect chronic geriatric conditions rather than the severity of heart failure including cardiac function and hemodynamics. Thus, patients with low protein intake before hospital discharge should be managed by a multidisciplinary team for chronic geriatric conditions and heart failure.¹⁸

A single-center, retrospective study investigated the association between protein intake and heart failure rehospitalization within 1 year in elderly patients with heart failure and moderate or higher malnutrition.¹¹ They also examined the cutoff value of daily protein intake associated with prognosis. No significant difference was observed in the rate of heart failure rehospitalization between patients with low and high protein intake when protein intake <1.3 g/kg/day and <1.4 g/kg/day were used as cutoff values, and protein intake <1.2 g/kg/day was associated with heart failure rehospitalization. In the present study, a protein intake cutoff of <1.2 g/kg/day was associated with worse long-term prognosis in hospitalized elderly patients with heart failure, suggesting 1.2 g/kg/day could be a relatively reasonable cutoff point for assessing long-term prognosis in elderly patients with heart failure.

Another single-center, retrospective study explored the association between dietary intake and a composite endpoint in hospitalized patients with heart failure, including younger patients.¹⁹ The dietary intake was checked by a nurse for 3 meals a day before discharge, and patients were classified into 2 groups according to whether they consumed 100% of their meals. Patients with incomplete intake had an increased composite endpoint compared with those with complete intake. They suggested that whole food intake was associated with prognosis. Because their study was not specific to elderly patients with heart failure, it is unclear whether there are equivalent clinical implications for complete dietary intake in elderly patients with heart failure.

In the present study, patients with low protein intake tended to have a higher BMI. This inverse association between low protein intake and high BMI has been previously reported in elderly hospitalized patients.^20–22 To correct for the impact of BMI differences on long-term prognosis, we performed a multivariate analysis including BMI and found that low protein intake was independently associated with the development of the composite endpoint. In addition, after adjusting for patient background by propensity score matching, including BMI, patients with low protein intake had a significantly higher incidence of the composite endpoint than those with high protein intake. Although the prognostic impact of BMI and undernutrition in patients with heart failure has not been investigated well, a retrospective study reported the impact of BMI and undernutrition on in-hospital mortality by sex.²³ In male patients, low BMI and undernutrition were associated with worse in-hospital prognosis; however, neither was associated with in-hospital prognosis in female patients. The effect of BMI and protein intake on the long-term prognosis of elderly patients with heart failure remains unclear and warrants further investigation.

Strengths

Muscle wasting is known to be associated with increased mortality in patients with heart failure.^24,25 In addition to high protein intake, it may help maintain muscle mass and is important for reducing the progression to frailty and cardiac cachexia.²⁶ Active nutritional support has been found to be associated with reduced mortality in older populations as well as in patients with heart failure.^27,28 In our study, the average protein intake 1 week before hospital discharge was examined, indicating protein intake during the stabilization phase of heart failure. Therefore, a low protein intake reflects not only the severity of heart failure, including cardiac function and dynamics, but also chronic geriatric conditions. Therefore, patients with low protein intake during hospitalization are likely to have low protein intake after discharge. Cardiologists should consider protein intake in elderly patients with heart failure not only during hospitalization but also after discharge. Continuous nutritional intervention during hospitalization and after discharge, as well as adequate protein intake, can prevent physical inactivity and muscle wasting, and consequently avoid worse long-term prognosis.²⁸ Furthermore, visually confirming the percentage of dietary intake and calculating protein intake during hospitalization is clinically significant because it is a simple and accurate method to assess protein intake.

Study Limitations

The present study has several limitations. First, the study population was relatively small, and the study was conducted at a single institution. Second, although we demonstrated an association between protein intake and mortality, we did not establish a causal relationship, which warrants further studies in the form of randomised controlled trials. Third, we did not evaluate protein intake after discharge; therefore, the association between long-term protein intake after discharge and patient prognosis remains unclear. Fourth, the treatment strategy selected and used during hospitalization was at the discretion of the attending physician, which could have led to patient treatment bias. However, the severity of heart failure, such as the percentage of NYHA class III/IV at admission, BNP levels at discharge and vital signs at admission and discharge were not significantly different between the 2 groups. Last, in Japan, dapagliflozin and empagliflozin were approved for heart failure in October 2020 and November 2021, respectively, therefore, the proportion of patients treated with sodium glucose cotransporter 2 inhibitors in this study was low. Whether sodium glucose cotransporter 2 inhibitor affected energy intake, protein intake, and long-term prognosis was not elucidated in this study.

Conclusions

In hospitalized elderly patients with heart failure and reduced ejection fraction, low protein intake before discharge was associated with a prognosis within 1 year. Invasive nutritional support and careful post-discharge follow up of patients with low protein intake are important.

Acknowledgments

The authors thank Editage (www.editage.com) for English language editing.

Sources of Funding

This research received no grant from any funding agency in the public, commercial, or not-for-profit sectors.

Disclosures

The authors declare that they have no conflicts of interest.

IRB Information

The study protocol was approved by the Kindai University Ethics Committee (R05-203).

Data Availability

Data are available on reasonable request.

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circrep.CR-24-0067

References

• 1.   Kanaoka K, Iwanaga Y, Sumita Y, Nakai M, Miyamoto Y. Management and outcomes of acute heart failure hospitalizations in Japan. Circ J 2024; 88: 1265–1273.
• 2.   Relevance of nutritional assessment and treatment to counteract cardiac cachexia and sarcopenia in chronic heart failure. Clin Nutr 2021; 40: 5141–5155.
• 3.   von Haehling S, Ebner N, Dos Santos MR, Springer J, Anker SD. Muscle wasting and cachexia in heart failure: Mechanisms and therapies. Nat Rev Cardiol 2017; 14: 323–341.
• 4.   Sato Y, Kuragaichi T, Nakayama H, Hotta K, Nishimoto Y, Kato T, et al. Developing multidisciplinary management of heart failure in the super-aging society of Japan. Circ J 2023; 88: 2–9.
• 5.   O’Keeffe M, Kelly M, O’Herlihy E, O’Toole PW, Kearney PM, Timmons S, et al. Potentially modifiable determinants of malnutrition in older adults: A systematic review. Clin Nutr 2019; 38: 2477–2498.
• 6.   An P, Wan S, Luo Y, Luo J, Zhang X, Zhou S, et al. Micronutrient supplementation to reduce cardiovascular risk. J Am Coll Cardiol 2022; 80: 2269–2285.
• 7.   Pasini E, Corsetti G, Dioguardi FS. Nutritional supplementation and exercise as essential allies in the treatment of chronic heart failure: The metabolic and molecular bases. Nutrients 2023; 15: 2337.
• 8.   McClave SA, Taylor BE, Martindale RG, Warren MM, Johnson DR, Braunschweig C, et al. Guidelines for the provision and assessment of nutrition support therapy in the adult critically ill patient: Society of Critical Care Medicine (SCCM) and American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.). JPEN J Parenter Enteral Nutr 2016; 40: 159–211.
• 9.   Volkert D, Beck AM, Cederholm T, Cruz-Jentoft A, Hooper L, Kiesswetter E, et al. ESPEN practical guideline: Clinical nutrition and hydration in geriatrics. Clin Nutr 2022; 41: 958–989.
• 10.   Streng KW, Hillege HL, Ter Maaten JM, van Veldhuisen DJ, Dickstein K, Ng LL, et al. Clinical implications of low estimated protein intake in patients with heart failure. J Cachexia Sarcopenia Muscle 2022; 13: 1762–1770.
• 11.   Saijo T, Yasumoto K, Ryomoto K, Momoki C, Habu D. Association of protein intake during hospitalization with readmission in older adult patients with heart failure at risk of malnutrition. Nutr Clin Pract 2023; 38: 686–697.
• 12.   Ho KK, Pinsky JL, Kannel WB, Levy D. The epidemiology of heart failure: The Framingham Study. J Am Coll Cardiol 1993; 22: 6A–13A.
• 13.   Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: The task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016; 37: 2129–2200.
• 14.   Kawasaki Y, Sakai M, Nishimura K, Fujiwara K, Fujisaki K, Shimpo M, et al. Criterion validity of the visual estimation method for determining patients’ meal intake in a community hospital. Clin Nutr 2016; 35: 1543–1549.
• 15.   Billingsley HE, Hummel SL, Carbone S. The role of diet and nutrition in heart failure: A state-of-the-art narrative review. Prog Cardiovasc Dis 2020; 63: 538–551.
• 16.   Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE Jr, Drazner MH, et al. 2013 ACCF/AHA guideline for the management of heart failure: A report of the American College of Cardiology Foundation/American Heart Association task force on practice guidelines. J Am Coll Cardiol 2013; 62: e147–e239.
• 17.   McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, et al. 2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J 2021; 42: 3599–3726.
• 18.   Olson M, Thompson Z, Xie L, Nair A. Broadening heart failure care beyond cardiology: Challenges and successes within the landscape of multidisciplinary heart failure care. Curr Cardiol Rep 2023; 25: 851–861.
• 19.   Yoshida T, Shoji S, Shiraishi Y, Kawana M, Kohno T, Inoue K, et al. Hospital meal intake in acute heart failure patients and its association with long-term outcomes. Open Heart 2020; 7: e001248.
• 20.   Tsai JR, Chang WT, Sheu CC, Wu YJ, Chen MA, Hsu YH, et al. Adequacy of prescribed caloric and protein intake and reduction of mortality in critically ill patients with body mass indices <30 kg/m². Nutrition 2022; 94: 111529.
• 21.   Katano S, Yano T, Kouzu H, Ohori K, Shimomura K, Honma S, et al. Energy intake during hospital stay predicts all-cause mortality after discharge independently of nutritional status in elderly heart failure patients. Clin Res Cardiol 2021; 110: 1202–1220.
• 22.   Matsuo H, Yoshimura Y, Fujita S, Maeno Y, Tanaka S. Association of resting energy expenditure-based energy intake sufficiency with functional recovery, dysphagia, and 1-year mortality following heart failure: A prospective observational study. Clin Nutr ESPEN 2023; 55: 364–372.
• 23.   Kwaśny A, Uchmanowicz I, Juárez-Vela R, Młynarska A, Łokieć K, Czapla M. Sex-related differences in the impact of nutritional status on in-hospital mortality in heart failure: A retrospective cohort study. Eur J Cardiovasc Nurs 2024; 23: 176–187.
• 24.   Anker SD, Morley JE. Cachexia: A nutritional syndrome? J Cachexia Sarcopenia Muscle 2015; 6: 269–271.
• 25.   Izumiya Y. Heart failure medication and muscle wasting. Circ J 2023; 88: 20–21.
• 26.   Sato Y, Kuragaichi T, Nakayama H, Hotta K, Nishimoto Y, Kato T, et al. Developing multidisciplinary management of heart failure in the super-aging society of Japan. Circ J 2023; 88: 2–9.
• 27.   Bauer J, Biolo G, Cederholm T, Cesari M, Cruz-Jentoft AJ, Morley JE, et al. Evidence-based recommendations for optimal dietary protein intake in older people: A position paper from the PROT-AGE Study Group. J Am Med Dir Assoc 2013; 14: 542–559.
• 28.   Hersberger L, Dietz A, Bürgler H, Bargetzi A, Bargetzi L, Kägi-Braun N, et al. Individualized nutritional support for hospitalized patients with chronic heart failure. J Am Coll Cardiol 2021; 77: 2307–2319.