Effectiveness of Guideline-Directed Medical Therapy for Acute Heart Failure With Reduced Ejection Fraction in Frail Elderly Patients With Malnutrition

Abstract

Background: The appropriateness of guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) in malnourished elderly patients is unclear. This study aims to assess the effects of GDMT on acute heart failure (AHF) with reduced ejection fraction in this specific population using the Geriatric Nutritional Risk Index (GNRI).

Methods and Results: We retrospectively collected data of patients aged >75 years who were admitted to St. Luke’s International Hospital for AHF with reduced ejection fraction from 2011 to 2022. Malnutrition was defined as a GNRI score <92. GDMT was defined as the prescription of 3 or more of the medications for HFrEF at the time of discharge. Among 467 patients, 345 (73.9%) had malnutrition. In the low GNRI group, GDMT was associated with a lower all-cause mortality at 1 year (HR 0.46; 95% CI 0.24–0.89; P=0.021), but not in heart failure (HF) readmission (HR 0.83; 95% CI 0.55–1.25; P=0.364) at 1 year after discharge. In the high GNRI group, GDMT was not significantly associated with these outcomes (all-cause mortality: HR 0.59; 95% CI 0.12–3.06; P=0.534; HF readmission: HR 0.55; 95% CI 0.29–1.05; P=0.069).

Conclusions: Implementation of GDMT in AHF with reduced ejection fraction may enhance prognosis, even among elderly patients with malnutrition.

Heart failure (HF) is a public health problem with a high mortality rate, despite technological advancements in treatment.¹ Moreover, the incidence of HF increases with age, and as the population ages, the number of HF patients is expected to rise.^2,3 In this context, several pieces of evidence have emerged regarding drug therapy that improve prognosis and are recommended in guidelines for the treatment of HF with reduced ejection fraction (HFrEF).⁴ Beta-blockers, angiotensin-converting enzyme inhibitors (ACE-Is)/angiotensin receptor blockers (ARBs)/angiotensin receptor-neprilysin inhibitor (ARNI), mineralocorticoid receptor antagonists (MRAs), and sodium-glucose cotransporter 2 inhibitors (SGLT2-Is) are among the specific drugs recommended. The early introduction of guideline-directed medical therapy (GDMT) using these agents has been shown to improve the prognosis of HFrEF.⁵

In contrast, the appropriateness of GDMT in the elderly needs to be carefully considered. This is because HF in the elderly is characterized by several comorbidities, frailty, and cognitive dysfunction, and is affected by adverse drug reactions and polypharmacy.^6–8 In particular, elderly patients with malnutrition may be at high risk for these GDMT-related adverse effects, although this is not yet known.

This study aimed to examine the impact of GDMT on HF in frail elderly patients with malnutrition using the Geriatric Nutritional Risk Index (GNRI), a nutritional index related to the prognosis of HFrEF.^9,10

Methods

Study Design and Patient Population

This study was a retrospective, single-center cohort study. Patients aged >75 years, who were admitted to St. Luke’s International Hospital for AHF with reduced ejection fraction from January 2011 to May 2022, were enrolled. AHF was diagnosed according to the Framingham criteria.¹¹ Those with missing variables needed to calculate the GNRI or those with no information after discharge from the study were excluded. This study was conducted in accordance with the Declaration of Helsinki and the Japanese Ministry of Health, Labor and Welfare’s Ethical Guidelines for Medical and Health Research Involving Human Subjects. The study protocol was approved by the Ethics Committee of St. Luke’s International Hospital.

Data Collection and Definition

Patients’ sociodemographic characteristics, laboratory data, and information on survival and hospitalization were extracted from St. Luke’s International Hospital’s electronic medical records. HFrEF was defined as a left ventricular ejection fraction <40% based on recent guidelines, and patients meeting that criterion on echocardiography at admission were included in this study. Nutritional status was evaluated using the GNRI, an index of nutritional assessment, and calculated using the following formula: 14.89 × serum albumin (g/dL) + 41.7 × body mass index (BMI) / 22. To assess nutritional status, the GNRI was calculated using the serum albumin and BMI measured at the time of discharge. A low GNRI was defined as <92, based on previous studies.^9,10 GDMT was defined as the inclusion of at least 3 of the following drugs in the discharge prescription: β-blockers, ACE-Is/ARBs/ARNI, MRAs and SGLT2-Is. Additionally, we defined hospitalizations for AHF from April 2020 onwards as occurring during the pandemic period to account for the influence of the Coronavirus disease 2019 (COVID-19) pandemic on our study.

Outcome

In this study, the association between GNRI and GDMT was examined first. Then, the association between GDMT and all-cause mortality or first HF readmission at 1 year after discharge was examined in patients with low and high GNRI scores, respectively.

Statistical Analysis

Patient baseline characteristics were presented as percentages for categorical variables, and means with standard deviations or medians with interquartile ranges for continuous variables. Patient characteristics between the 2 GNRI groups were analyzed using the Mann-Whitney U test, the χ² test, or the Fisher’s exact test as appropriate. The event-free period was plotted using the Kaplan-Meier method and analyzed with the log-rank test. In addition, association between GDMT and all-cause mortality and first HF readmission at 1 year after discharge were examined using separate Cox proportional hazards model. The first model was univariable. Second, a multivariable model examining all-cause mortality was applied to both the entire cohort and the low GNRI group, with adjustments made for age, sex, systolic blood pressure (BP) at admission, history of HF admission, estimated glomerular filtration rate (eGFR), and GNRI. HF readmission was analyzed using a model adjusted for age, sex, systolic BP at admission, history of HF admission, eGFR, hemoglobin, serum sodium, serum potassium, and GNRI. Last, a multivariable model for the high GNRI group, adjusted for age and sex only due to the limited number of outcomes, was examined.

In a sensitivity analysis, the relationship between GDMT and cardiac death within 1 year following discharge was evaluated using the Cox proportional hazards model across the entire cohort as well as the low GNRI group. These analyses were adjusted for age, sex, and systolic BP at admission. Due to the small number of events in the high GNRI group, this analysis was not performed. The Cox proportional hazards model was also applied to the low GNRI group, targeting the cohort from the pre-pandemic period to eliminate the potential influence of COVID-19. Additionally, the analysis was conducted on the cohort excluding individuals who were not prescribed ARNI or SGLT2-Is at discharge. Since the population during the pandemic period and the cohort with prescriptions that included ARNI and SGLT2-Is were limited in number, we did not conduct an analysis on these groups. All analyses were conducted using R (version 4.4.1), and a P value <0.05 was considered statistically significant.

Results

Baseline Characteristics

A flowchart for patient selection into the study is shown in Figure 1. A total of 578 patients were admitted to hospital for AHF with reduced ejection fraction. Among these patients, 111 were excluded from the study due to missing variables that were required for GNRI calculation or missing information after discharge. Therefore, a total of 467 patients were included in the final analysis. Of these, 345 (73.9%) were in the low GNRI group. The baseline characteristics of the patients by GNRI status (low and high GNRI groups) are shown in Table 1. The overall mean age was 84 years, and the low GNRI group was significantly older than the high GNRI group. Left ventricular ejection fraction and frequency of comorbidity did not differ between the 2 groups except for dementia, which was higher in the low GNRI group. Regarding laboratory data, distribution of the renal function test was similar, but N-terminal pro B-type natriuretic peptide (NT-proBNP) was significantly higher in the low GNRI group than in the high GNRI group. Overall, HF medication prescription rates at discharge were 84.8% for β-blockers, 68.5% for ACE-Is/ARBs/ARNI, 52.9% for MRAs, and 7.3% for SGLT2-Is. The overall GDMT achievement rate at discharge was 38.8%. Medication prescription for HF and GDMT at discharge did not differ significantly between the 2 groups except for SGLT2-Is, which was higher in the high GNRI group. The number of medication prescriptions for HF by GNRI is shown in Figure 2. The proportion of patients in the low GNRI group who received quadruple therapy was significantly lower than that of the high GNRI group (P=0.002). Meanwhile, there were no significant differences between the 2 groups in the number of other combination therapies.

Figure 1.

Flowchart of patient selection into the study cohort. GNRI, geriatric nutritional risk index.

Table 1.

Patient Characteristics by GNRI Status

	Total (n=467)	Low GNRI group (n=345)	High GNRI group (n=122)	P value
Age (years)	84±6	85±6	82±5	<0.001
Sex, male, n (%)	257 (55.0)	183 (53.0)	74 (60.7)	0.178
Body weight at discharge (kg)	49.6±11.1	46.2±9.6	59.0±9.6	<0.001
Pandemic period	81 (17.3)	54 (15.7)	27 (22.1)	0.137
Clinical parameters at admission
Systolic BP (mmHg)	133±27	133±28	133±25	0.806
Diastolic BP (mmHg)	73±19	71±18	76±19	0.027
Heart rate (beats/min)	94±22	94±22	94±23	0.859
GNRI at discharge	85.1±10.4	80.6±7.8	97.8±5.1	<0.001
LVEF (%)	29±7	29±8	29±7	0.637
Medical history
Hypertension	409 (87.6)	297 (86.1)	112 (91.8)	0.137
Diabetes	242 (51.8)	170 (49.3)	72 (59.0)	0.081
Dyslipidemia	266 (57.0)	192 (55.7)	74 (60.7)	0.394
Atrial fibrillation	190 (40.7)	133 (38.6)	57 (46.7)	0.141
COPD	21 (4.5)	13 (3.8)	8 (6.6)	0.306
Cerebral infarction	144 (30.8)	105 (30.4)	39 (32.0)	0.841
Prior HF admission	196 (42.0)	148 (42.9)	48 (39.3)	0.564
Dementia	52 (11.1)	49 (14.2)	3 (2.5)	<0.001
Laboratory data at admission
Creatinine level (mg/dL), median (quartile 1–3)	1.22 (0.87–1.84)	1.22 (0.85–1.89)	1.20 (0.89–1.82)	0.952
eGFR (mL/min/1.73 m2)	41±23	42±24	41±20	0.673
Albumin at discharge (g/dL)	3.2±0.5	3.0±0.4	3.6±0.3	<0.001
Serum sodium (mEq/L)	140±4	139±5	140±4	0.018
Serum potassium (mEq/L)	4.1±0.6	4.1±0.7	4.1±0.5	0.778
NT-proBNP (pg/mL), median (quartile 1–3)	8,072 (3,816–22,859)	10,414 (4,081–27,068)	5,749 (3,088–10,664)	<0.001
Haemoglobin (g/dL)	10.8±2.1	10.6±2.1	11.4±1.8	<0.001
Medication at discharge
β-blockers	396 (84.8)	288 (83.5)	108 (88.5)	0.235
ACE-Is/ARBs/ARNI	320 (68.5)	233 (67.5)	87 (71.3)	0.510
MRAs	247 (52.9)	182 (52.8)	65 (53.3)	1.000
SGLT2-Is	34 (7.3)	16 (4.6)	18 (14.8)	<0.001
Loop diuretics	331 (70.9)	241 (69.9)	90 (73.8)	0.483
GDMT	181 (38.8)	129 (37.4)	52 (42.6)	0.362

Unless indicated otherwise, data are presented as n (%), or mean±SD. ACE-Is, angiotensin-converting enzyme inhibitors; ARBs, angiotensin receptor blockers; ARNI, angiotensin receptor-neprilysin inhibitor; BP, blood pressure; COPD, chronic obstructive pulmonary disease; eGFR, estimated glomerular filtration rate; GDMT, guideline-directed medical therapy; GNRI, Geriatric Nutritional Risk Index; HF, heart failure; MRAs, mineralocorticoid receptor antagonists; NT-proBNP, N-terminal pro-B type natriuretic peptide; SD, standard deviation; SGLT2-Is, sodium-glucose cotransporter 2 inhibitors.

Figure 2.

Number of medication prescriptions for heart failure by the Geriatric Nutritional Risk Index (GNRI).

The baseline characteristics of the low GNRI group by GDMT status (GDMT and no GDMT groups) are shown in Table 2. Clinical parameters and frequency of comorbidity did not differ between the 2 groups. Regarding the laboratory data, renal function was significantly worse in the no GDMT group than in the GDMT group, and serum potassium and NT-proBNP were significantly higher in the no GDMT group than in the GDMT group. For medications at discharge, the prescription rate of loop diuretics was significantly higher in the GDMT group than in the no GDMT group.

Table 2.

Patient Characteristics in the Low GNRI Group by GDMT Status

	GDMT group (n=129)	No GDMT group (n=216)	P value
Age (years)	84±6	85±6	0.102
Sex, male	59 (45.7)	124 (57.4)	0.047
Body weight at discharge (kg)	45.6±9.6	46.6±9.7	0.356
Pandemic period	32 (24.8)	22 (10.2)	<0.001
Clinical parameters at admission
Systolic BP (mmHg)	135±27	132±28	0.331
Diastolic BP (mmHg)	74±18	70±18	0.070
Heart rate (beats/min)	97±20	93±23	0.081
GNRI at discharge	81.0±7.3	80.4±8.1	0.639
LVEF (%)	29±7	29±8	0.270
Medical history
Hypertension	107 (82.9)	190 (88.0)	0.253
Diabetes	55 (42.6)	115 (53.2)	0.073
Dyslipidemia	68 (52.7)	124 (57.4)	0.461
Atrial fibrillation	46 (35.7)	87 (40.3)	0.460
COPD	8 (6.2)	5 (2.3)	0.082
Cerebral infarction	33 (25.6)	72 (33.3)	0.164
Prior HF admission	50 (38.8)	98 (45.4)	0.277
Dementia	15 (11.6)	34 (15.7)	0.368
Laboratory data at admission
Creatinine level (mg/dL), median (quartile 1–3)	1.01 (0.80–1.34)	1.43 (0.92–2.41)	<0.001
eGFR (mL/min/1.73 m2)	49±22	37±24	<0.001
Albumin at discharge (g/dL)	3.1±0.4	3.0±0.4	0.046
Serum sodium (mEq/L)	140±5	139±4	0.007
Serum potassium (mEq/L)	3.9±0.6	4.2±0.7	<0.001
NT-proBNP (pg/mL), median (quartile 1–3)	6,613 (3,826–16,381)	13,420 (4,768–30,616)	0.003
Haemoglobin (g/dL)	10.9±2.1	10.4±2.0	0.020
Medication at discharge
β-blockers	129 (100.0)	159 (73.6)	<0.001
ACE-Is/ARBs/ARNI	127 (98.4)	106 (49.1)	<0.001
MRAs	128 (99.2)	54 (25.0)	<0.001
SGLT2-Is	15 (11.6)	1 (0.5)	<0.001
Loop diuretics	104 (80.6)	137 (63.4)	0.001

Unless indicated otherwise, data are presented as n (%), or mean±SD. Abbreviations as in Table 1.

All-Cause Mortality and First HF Readmission

Sixty-seven patients died within 1 year; 60 in the low GNRI group and 7 in the high GNRI group. 133 patients were readmitted due to HF within 1 year after discharge, with 96 in the low GNRI group and 37 in the high GNRI group. Kaplan-Meier curves for all-cause mortality and HF readmission are shown in Figure 3. In the entire group and the low GNRI group, patients who received GDMT had significantly lower all-cause mortality. In the entire group, patients who received GDMT had significantly lower HF admission, while there was no significant association in the low GNRI group. In the high GNRI group, there was no significant difference in all-cause mortality or HF readmission rate between patients who received GDMT and those who did not receive GDMT. The results based on Cox regression analysis are shown in Table 3. In the entire group, GDMT was significantly associated with a lower all-cause mortality (HR 0.47; 95% CI 0.26–0.87; P=0.016), but not with HF readmission (HR 0.78; 95% CI 0.54–1.12; P=0.170) in the adjusted analysis. In the low GNRI group, GDMT was significantly associated with a lower all-cause mortality (HR 0.46; 95% CI 0.24–0.89; P=0.021), but not with HF readmission (HR 0.83; 95% CI 0.55–1.25; P=0.364) in the adjusted analysis. In the high GNRI group, GDMT was not significantly associated with either all-cause mortality (HR 0.59; 95% CI 0.12–3.06; P=0.534) or HF readmission (HR 0.55; 95% CI 0.29–1.05; P=0.069) in the adjusted analysis.

Figure 3.

Kaplan-Meier analysis for all-cause mortality and heart failure (HF) readmission by guideline-directed medical therapy (GDMT) use. (A,B) Kaplan-Meier curves of the entire group. (C,D) Kaplan-Meier curves of the low Geriatric Nutritional Risk Index (GNRI) group. (E,F) Kaplan-Meier curves of the high GNRI group.

Table 3.

Results of Cox Regression Analysis Based on GDMT Use and All-Cause Mortality or First HF Readmission

	All-cause mortality			First HF readmission
	HR	95% CI	P value	HR	95% CI	P value
Entire group
Unadjusted	0.43	0.24–0.78	0.005	0.65	0.45–0.94	0.022
Adjusted	0.47	0.26–0.87	0.016	0.78	0.54–1.12	0.170
Low GNRI group
Unadjusted	0.41	0.22–0.78	0.006	0.70	0.46–1.07	0.100
Adjusted	0.46	0.24–0.89	0.021	0.83	0.55–1.25	0.364
High GNRI group
Unadjusted	0.59	0.11–3.08	0.536	0.54	0.28–1.03	0.061
Adjusted	0.59	0.12–3.06	0.534	0.55	0.29–1.05	0.069

All-cause mortality in the entire group and the low GNRI group: adjusted by age, sex, systolic BP at admission, prior HF admission, eGFR, and GNRI. HF readmission in the entire group and the low GNRI group: adjusted by age, sex, systolic BP at admission, prior HF admission, eGFR, hemoglobin, serum sodium, serum potassium, and GNRI. All-cause mortality and HF readmission in high GNRI group: adjusted by age, sex. CI, confidence interval; HR, hazard ratio. Other abbreviations as in Table 1.

Sensitivity Analysis

The total number of cardiac deaths within 1 year was 32. The sensitivity analysis revealed no significant differences in cardiac mortality between patients receiving GDMT and those who did not, both in the entire cohort (HR 0.44; 95% CI 0.18–1.07; P=0.071) and within the low GNRI group (HR 0.47; 95% CI 0.19–1.15; P=0.099).

Among individuals with a low GNRI before the pandemic period, GDMT was associated with reduced all-cause mortality (HR 0.36; 95% CI 0.17–0.80; P=0.013), but not associated with reduced HF readmission (HR 0.89; 95% CI 0.57–1.39; P=0.613). Among patients whose discharge prescriptions did not include ARNI or SGLT2-Is, the use of GDMT was associated with a significant reduction in all-cause mortality (HR 0.46; 95% CI 0.23–0.92; P=0.028). However, it was not associated with a significant reduction in HF readmissions (HR 0.84; 95% CI 0.54–1.30; P=0.445).

Discussion

This study examined the effect of discharge GDMT in elderly malnourished patients hospitalized for AHF with reduced ejection fraction, as measured using the GNRI. The results showed that, in malnourished patients with low GNRI, GDMT was significantly associated with a lower incidence of all-cause mortality after 1 year of discharge. In contrast, GDMT was not associated with prognosis in patients who were not malnourished.

There is evidence that GDMT improves the prognosis in many patients with HFrEF.^12,13 However, observational studies are important to confirm the efficacy of GDMT in the elderly population only, as evidence-generating randomized controlled trials (RCTs) involve people of different ages, including young people. Previous observational studies have shown that the combination of ACE-Is/ARBs and β-blockers was associated with a favorable prognosis in elderly patients hospitalized for AHF.^14,15 Other observational studies have shown that the triple combination of ACE-Is/ARBs, β-blockers and MRA was also associated with a better prognosis in elderly and frail patients.^16,17 In contrast, 1 study reported that the triple combination therapy did not reduce mortality or readmission and increased the risk of fall-related adverse events.¹⁸ Together, these studies imply that the use of 3 or more HF medications in combination in the elderly is controversial. In this study, we included the relatively new HF drugs ARNI and SGLT2-Is to examine the effects of 3 and 4 HF drugs in combination therapy.

The GNRI was also used to focus on malnourished patients, who may be more susceptible to adverse events. Previous studies have shown that HF patients with a low GNRI, indicating malnutrition, have a poorer prognosis.¹⁹ To the best of our knowledge, this is the first observational study that has examined GDMT efficacy on an elderly population at high risk of malnutrition. GDMT may be effective in frail elderly patients with HFrEF, but the GDMT achievement rate in this study was low at approximately 40%, regardless of nutritional status. The low prescription rate of SGLT2-Is may be due to the fact that it is a new induction agent, whereas the low prescription rates of ACE-Is/ARBs/ARNI and MRAs may reflect actual clinical practice. Previous studies have reported that frail and elderly patients with HFrEF had a lower number of HF medications.^15,20 Possible reasons for this include an assumption by the healthcare provider that older adults are less tolerant of HF medications, there is a lack of knowledge about managing medication side-effects, and clinical inertia.¹⁹ Addressing these issues on the healthcare provider side requires thorough HF education for healthcare providers and clinical decision support based on electronic health records.²¹

In the high GNRI group, no significant association was identified between GDMT and all-cause mortality, most likely due to the baseline characteristics of this group. Compared with the low GNRI group, individuals in the high GNRI group were younger, had a higher body weight, and demonstrated elevated albumin levels, indicating that this group comprised a relatively healthier patient population. Furthermore, the lower NT-proBNP levels observed in the high GNRI group suggest that the severity of HF was likely less severe than in the low GNRI group. These characteristics, and the smaller sample size of the high GNRI group, are thought to have contributed to the absence of significant effects of GDMT. With respect to HF readmission outcomes using the Cox proportional hazards model, no significant association with GDMT were observed across any group. These findings may be attributable to the multifactorial nature of HF readmissions, as previously reported in the literature. These involve not only biological factors but also behavioral risk issues such as poor adherence to therapy and socioeconomic determinants like social status.²² Furthermore, the decision to admit patients with HF often relies on the clinical judgment of physicians, leading to variability in the severity of HF among cases. This variability might also have contributed to the absence of statistically significant differences observed in our study.

Regarding the results in the sensitivity analysis, there were no significant relationships between cardiac death and GDMT in the entire cohort and the low GNRI group. As the number of cardiac death events was limited, careful consideration is necessary when interpreting these findings. Furthermore, we conducted a subgroup analysis of the cohort from the pre-pandemic period, specifically examining patients in the low GNRI group. GDMT was linked to a reduction in all-cause mortality when the pandemic period was excluded, with a lower hazard ratio (HR) observed compared with analyses that included the pandemic period. These findings suggest that the pandemic’s impact may have slightly diminished the effectiveness of GDMT by the disruptions to the healthcare system and the effects of COVID-19 infections during the pandemic. However, even in analyses including the pandemic period, a notable reduction in mortality associated with GDMT was observed, implying that GDMT likely remained effective in reducing mortality even under pandemic conditions. Conversely, in the subgroup excluding ARNI and SGLT2-Is, HR for all-cause mortality did not exhibit significant differences when compared with the original low GNRI group. These findings indicate that combination therapy incorporating conventional HF medications, such as β-blockers and ACE-Is, may provide adequate efficacy even in elderly patients with malnutrition.

Study Limitations

This study had several limitations. First, this constituted a single-center investigation involving a limited patient cohort. Specifically, the restricted number of patients within the high GNRI group potentially hindered the detection of statistically significant differences in the endpoints for this group. Second, given the observational nature of the study, covariate adjustments were made. However, unmeasured or unknown confounders may have influenced the results. Some of the variables that differed in patients’ background (e.g., NT-proBNP) could also not be adjusted for due to the limited number of endpoints. Third, due to an absence of data on indicators such as the frailty index, a comprehensive assessment of frailty could not be conducted.²³ Fourth, patients may have died or were admitted for HF in other healthcare institutions. Fifth, consideration of patients’ pre-admission use of HF medications was omitted. Additionally, an evaluation of the patients’ ability to adhere to prescribed HF medications post-discharge during the follow-up period was not conducted. Last, the dosage of HF medications was not taken into account in the analysis.

In this study, we were able to provide evidence that can be used as a reference for appropriate treatment of HF in vulnerable elderly patients. In a practical setting, there are many situations in which providers hesitate to prescribe HF medications to elderly HF patients. Based on the results of this study, physicians may consider using a combination of multiple HF medications aggressively in this population. As a result, this study may provide an opportunity to improve the quality of HF care in the elderly in the future.

Conclusions

GDMT was associated with a lower incidence of all-cause mortality among malnourished elderly patients hospitalized with AHF with reduced ejection fraction. These results may provide a basis for recommending GDMT to frail elderly HF patients. However, there was no significant association between GDMT and reduced HF rehospitalization in this population. The findings of this study were derived from a small-scale observational investigation, warranting cautious interpretation. To develop effective treatment strategies for elderly and frail patients with HF, the implementation of interventional studies is essential.

Acknowledgments

During the preparation of this manuscript, the authors used ChatGPT (GPT-4o, by OpenAI), and DeepL (by DeepL GmbH) in order to proofread the English text and enhance readability. After using these tools, the authors reviewed and edited the content as needed, and take full responsibility for the content of the published article.

Sources of Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Disclosures

The authors declare that they have no competing interests.

Author Contributions

The authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.

IRB Information

The present study was approved by the Ethics Committee of St. Luke’s International Hospital (Reference no. 23-R003).

References

• 1.   Tsao CW, Lyass A, Enserro D, Larson MG, Ho JE, Kizer JR, et al. Temporal trends in the incidence of and mortality associated with heart failure with preserved and reduced ejection fraction. JACC Heart Fail 2018; 6: 678–685, doi:10.1016/j.jchf.2018.03.006.
• 2.   Conrad N, Judge A, Tran J, Mohseni H, Hedgecott D, Crespillo AP, et al. Temporal trends and patterns in heart failure incidence: A population-based study of 4 million individuals. Lancet 2018; 391: 572–580, doi:10.1016/S0140-6736(17)32520-5.
• 3.   Kuwayama T, Okumura T, Kondo T, Oishi H, Kimura Y, Kazama S, et al. Characteristics, treatment, and prognosis in octogenarian and older patients with acute heart failure in Japan: Prospective observational study on acute pharmacotherapy and prognosis in management of acute heart failure (POPEYE-AHF Registry). Circ J 2024, 89: 83–92, doi:10.1253/circj.CJ-24-0299.
• 4.   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, doi:10.1093/eurheartj/ehab368.
• 5.   Mebazaa A, Davison B, Chioncel O, Cohen-Solal A, Diaz R, Filippatos G, et al. Safety, tolerability and efficacy of up-titration of guideline-directed medical therapies for acute heart failure (STRONG-HF): A multinational, open-label, randomised, trial. Lancet 2022; 400: 1938–1952, doi:10.1016/S0140-6736(22)02076-1.
• 6.   Murad K, Goff DC, Morgan TM, Burke GL, Bartz TM, Kizer JR, et al. Burden of comorbidities and functional and cognitive impairments in elderly patients at the initial diagnosis of heart failure and their impact on total mortality: The cardiovascular health study. JACC Heart Fail 2015; 3: 542–550, doi:10.1016/j.jchf.2015.03.004.
• 7.   Chang TI, Park H, Kim DW, Jeon EK, Rhee CM, Kalantar-Zadeh K, et al. Polypharmacy, hospitalization, and mortality risk: A nationwide cohort study. Sci Rep 2020; 10: 18964, doi:10.1038/s41598-020-75888-8.
• 8.   Kanai M, Minamisawa M, Motoki H, Seko Y, Kimura K, Okano T, et al. Prognostic impact of hyperpolypharmacy due to noncardiovascular medications in patients after acute decompensated heart failure: Insights from the clue of risk stratification in the elderly patients with heart failure (CURE-HF) registry. Circ J 2023; 88: 33–42, doi:10.1253/circj.CJ-22-0712.
• 9.   Kitamura M, Izawa KP, Yaekura M, Mimura Y, Nagashima H, Oka K. Differences in nutritional status and activities of daily living and mobility in elderly hospitalized patients with heart failure. ESC Heart Fail 2019; 6: 344–350, doi:10.1002/ehf2.12393.
• 10.   Matsumura K, Teranaka W, Taniichi M, Otagaki M, Takahashi H, Fujii K, et al. Differential effect of malnutrition between patients hospitalized with new-onset heart failure and worsening of chronic heart failure. ESC Heart Fail 2021; 8: 1819–1826, doi:10.1002/ehf2.13279.
• 11.   McKee PA, Castelli WP, McNamara PM, Kannel WB. The natural history of congestive heart failure: The Framingham study. N Engl J Med 1971; 285: 1441–1446, doi:10.1056/NEJM197112232852601.
• 12.   McMurray JJV, Packer M, Desai AS, Gong J, Lefkowitz MP, Rizkala AR, et al. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N Engl J Med 2014; 371: 993–1004, doi:10.1056/NEJMoa1409077.
• 13.   McMurray JJV, Solomon SD, Inzucchi SE, Køber L, Kosiborod MN, Martinez FA, et al. Dapagliflozin in patients with heart failure and reduced ejection fraction. N Engl J Med 2019; 381: 1995–2008, doi:10.1056/NEJMoa1911303.
• 14.   Yamaguchi T, Kitai T, Miyamoto T, Kagiyama N, Okumura T, Kida K, et al. Effect of optimizing guideline-directed medical therapy before discharge on mortality and heart failure readmission in patients hospitalized with heart failure with reduced ejection fraction. Am J Cardiol 2018; 121: 969–974, doi:10.1016/j.amjcard.2018.01.006.
• 15.   Seo WW, Park JJ, Park HA, Cho HJ, Lee HY, Kim KH, et al. Guideline-directed medical therapy in elderly patients with heart failure with reduced ejection fraction: A cohort study. BMJ Open 2020; 10: e030514, doi:10.1136/bmjopen-2019-030514.
• 16.   Abe T, Jujo K, Kametani M, Minami Y, Fukushima N, Saito K, et al. Prognostic impact of additional mineralocorticoid receptor antagonists in octogenarian heart failure patients. ESC Heart Fail 2020; 7: 2711–2724, doi:10.1002/ehf2.12862.
• 17.   Kondo T, Adachi T, Kobayashi K, Okumura T, Izawa H, Murohara T, et al. Physical frailty and use of guideline-recommended drugs in patients with heart failure and reduced ejection fraction. J Am Heart Assoc 2023; 12: e026844, doi:10.1161/JAHA.122.026844.
• 18.   Goyal P, Zullo AR, Gladders B, Onyebeke C, Kwak MJ, Allen LA, et al. Real-world safety of neurohormonal antagonist initiation among older adults following a heart failure hospitalization. ESC Heart Fail 2023; 10: 1623–1634, doi:10.1002/ehf2.14317.
• 19.   Honda Y, Nagai T, Iwakami N, Sugano Y, Honda S, Okada A, et al. Usefulness of geriatric nutritional risk index for assessing nutritional status and its prognostic impact in patients aged ≥65 years with acute heart failure. Am J Cardiol 2016; 118: 550–555, doi:10.1016/j.amjcard.2016.05.045.
• 20.   Stolfo D, Lund LH, Becher PM, Orsini N, Thorvaldsen T, Benson L, et al. Use of evidence-based therapy in heart failure with reduced ejection fraction across age strata. Eur J Heart Fail 2022; 24: 1047–1062, doi:10.1002/ejhf.2483.
• 21.   Ghazi L, Yamamoto Y, Riello RJ, Coronel-Moreno C, Martin M, O’Connor KD, et al. Electronic alerts to improve heart failure therapy in outpatient practice: A cluster randomized trial. J Am Coll Cardiol 2022; 79: 2203–2213, doi:10.1016/j.jacc.2022.03.338.
• 22.   Malhotra C, Chaudhry I, Keong YK, Sim KLD. Multifactorial risk factors for hospital readmissions among patients with symptoms of advanced heart failure. ESC Heart Failure 2024; 11: 1144–1152, doi:10.1002/ehf2.14670.
• 23.   Searle SD, Mitnitski A, Gahbauer EA, Gill TM, Rockwood K. A standard procedure for creating a frailty index. BMC Geriatr 2008; 8: 24, doi:10.1186/1471-2318-8-24.