Introduction
Chronic heart failure (CHF) is a global health challenge affecting approximately 26 million people worldwide, CHF remains a primary driver of hospital readmissions worldwide, placing an immense burden on vascular health systems. Despite advances in pharmacotherapy, the “revolving door” of hospitalizations persists due to suboptimal management of underlying risk factors. Without rigorous monitoring and individualized treatment, CHF often progresses to acute decompensation, leading to frequent hospitalizations, high mortality rates, and increased healthcare costs.1–4 Most recently in 2023, studies reported on the rehospitalization rate after one year of follow-up of a total of 1.036.771 patients; While global rehospitalization rates vary significantly ranging from 14.0% in Israel to 63.0% in the United States;4,5 There is a scarcity of data regarding the efficacy of decentralized, international-standard management models in Southeast Asia, particularly in Vietnam.6–9 This research addresses this gap by evaluating a structured intervention program focused on risk factor modification and individualized care in Vietnam.
We aim to investigate the specific clinical and lifestyle factors that drive readmission in the Vietnamese population to refine outpatient care pathways. Therefore, we report on a study on the investigation of the rate and some risk factors and contributing factors associated with rehospitalization in chronic heart failure patients within 6 months after being enrolled in an optimal management and treatment program at an international general hospital model in Vietnam to evaluate the effectiveness of the patient management and optimal treatment program.
Subjects and Methods
Study Design
We employed a prospective cross-sectional descriptive design with longitudinal follow-up.
Population
The study included 163 outpatients aged 18 and over diagnosed with CHF via Framingham criteria at Hai Phong International General Hospital, at Vinh Bao, Hai Phong City, Vietnam, between January 2022 and December 2023.1,10
Clinical Procedures
Diagnosis followed the Framingham criteria, requiring two major or one major and two minor criteria.1,10 Patients were staged according to the New York Heart Association (NYHA) classification.1,10,11 The primary endpoint was the number of rehospitalizations within 6 months of program enrollment.
Intervention
Patients were enrolled in an “Optimal Management Program” involving titrated medication, lifestyle counseling (smoking/alcohol cessation), and monitoring of heart rate and sleep patterns.
Data Analysis
Statistical processing was performed using IBM SPSS 25.0. Categorical variables were compared using Chi-square and Fisher’s exact tests (p < 0.05 considered significant).12
Research Results
General Characteristics of the Study population
The study of 163 patients diagnosed with chronic heart failure and followed up for management and treatment at the hospital showed an average age of 67.40 ± 12.33 [32–89], with most being elderly, accounting for 79.8%, while the young group accounted for 20.2%, with a statistically significant difference with p = 0.0001 (p < 0.001). The proportion of males (53.4%) was higher than females (46.6%), but the difference was not statistically significant with p = 0.391 (p> 0.05).
The educational level in the study group was mainly those who had not graduated from high school (70/163) or graduated from high school (64/163), accounting for 42.9% and 39.3%, respectively. The proportion of patients with a university degree (23/163) accounted for 14.1% and post-graduate (6/163) only accounted for 3.7% in the study group.
Assessment of nutritional status showed a mean Body Mass Index (BMI) value of 21.58 ± 2.43 [14.80–28.80]. The BMI classification showed that the BMI value within the normal range accounted for 133/163 (81.6%), overweight accounted for 22/163 (13.5%), obese 0/163 (0.0%), and underweight accounted for 8/163 (4.9%). No obese patients were encountered in the study.
Heart failure patients with alcohol and beer abuse accounted for 57/163 (35.0%), and tobacco accounted for 63/163 (38.7%).
The average heart rate before treatment was 92.37 ± 23.05 beats/minute, the lowest was 44 beats/minute, and the highest was 189 beats/minute. Systolic blood pressure had a higher average value than the normal threshold. Systolic blood pressure had an average value of 146.23 ± 28.08 mmHg [90–248], diastolic blood pressure had an average value of 77.65 ± 17.29 mmHg [40–130].
All 163 patients were diagnosed with heart failure with NYHA (New York Heart Association) functional classification with NYHA II accounting for 47/163 (28.8%), NYHA III accounting for 93/163 (57.1%), and NYHA IV accounting for 23/163 (14.1%).
The test results show that all average test indicators fall within normal limits. In some cases, in the context of anemia, thrombocytopenia, or acute exacerbation of COPD, decreased red blood cell, hemoglobin, and platelet counts or elevated white blood cell counts above normal levels may be observed. Some patients with kidney failure, lipid disorders, or accompanying elevated liver enzymes may have higher than normal levels of urea, creatinine, increased blood lipid test indicators, and some chronic heart failure cases presenting with shortness of breath show high Pro BNP levels.
Mild hypokalemia or mild hyperkalemia may also be encountered in certain cases. On routine chest X-rays, 17.8% of cases had an enlarged cardiac silhouette. Regarding treatment, all 163 patients were optimally and individually treated by specialist doctors according to updated cardiovascular guidelines.
After the treatment process, left ventricular systolic function assessed by Doppler echocardiography showed a significant improvement in the average ejection fraction (EF%) after 6 months of treatment, with the improvement being statistically significant (p < 0.01).
In 6 months of follow-up management and treatment, 16/163 patients were hospitalized for inpatient treatment (9.82%), of which 3/163 (1.84%) were hospitalized twice. Individualized analysis showed that among these, there was 1 case of heart failure on the background of mitral valve chord rupture requiring surgery but the patient and family did not agree, a case of hypertrophic cardiomyopathy due to myocarditis, or atrial fibrillation, arrhythmia on the background of persistent chronic atrial fibrillation requiring ablation with radiofrequency (RF) energy but the patient did not agree. Some cases were hospitalized for inpatient treatment due to other medical conditions such as pneumonia, acute exacerbation of chronic obstructive pulmonary disease, sleep disorders, psychological factors of anxiety and stress…
Relationship
Analysis of the relationship between heart rate and rehospitalization rate, it shows a correlation with statistical significance p = 0.0001 (<0.001). No correlation was found between the mean value of systolic blood pressure (p = 0.591) and diastolic blood pressure (p = 0.494) with the rehospitalization rate (p> 0.05). The rehospitalization rate has a correlation with the NYHA dyspnea level with statistical significance p = 0.01 (<0.05).
There was no significant difference in some risk factors such as age, education level, BMI with the rehospitalization rate in this study (p> 0.05); While there was a statistically significant difference between the rehospitalization rate and gender (male and female) with p< 0.01, the difference was statistically significant between rehospitalization and alcohol/beer abuse or no alcohol/beer abuse, smoking or no smoking with p <0.05.
Valvular heart disease (stenosis, insufficiency) was the most common disease, accounting for 89.6%. Hypertension was 63.2%, coronary artery disease was 50.3%, atrial fibrillation was 20.2%, coronary artery disease with stent was 13.5%, old myocardial infarction was 12.9%, valvular heart disease with surgery was 9.6%, some less common diseases were Basedow 3.7%, hypothyroidism 3.1%, and cardiomyopathy 1.2%. Among these underlying diseases, almost no underlying disease was found to be a statistically significant promoter of heart failure progression, except for coronary artery disease (p<0.01), arrhythmias such as atrial fibrillation, atrial flutter (p<0.01), and sinus tachycardia (p<0.001).
The most common underlying diseases were lipid metabolism disorder (68.7%), musculoskeletal disease (36.8%), gastroesophageal reflux disease (35.6%), sleep disorders (28.8%), diabetes mellitus (19.0%), renal failure (14.7%), chronic obstructive pulmonary disease (12.3%), cerebrovascular accident (11.0%), and adrenal insufficiency (3.1%).
Among these underlying diseases, no significant difference was found between the rehospitalization rate and diabetes mellitus, lipid metabolism disorder, cerebrovascular accident, renal failure, chronic obstructive pulmonary disease, musculoskeletal disease, adrenal insufficiency, gastroesophageal reflux disease, and the group with no underlying diseases (p>0.05). However, a significant difference was found between the sleep disorders and those without sleep disorders with rehospitalization rate (p<0.05).
Thus, the average age of the cohort was 67.40 ± 12.33 years, with 79.8% being elderly. Males accounted for 53.4%. The 6-month rehospitalization rate was 9.82% (16 patients), with 1.84% of patients requiring two admissions.
Clinical Predictors
Clinical Factor’s tachycardia (p > 90 bpm) was a major predictor (p < 0.001) mean that Baseline heart rate correlated strongly with readmission (p < 0.001). No significant correlation was found for systolic (p = 0.591) or diastolic blood pressure (p = 0.494). Readmission was significantly more frequent in males (p < 0.01).
Behavioral Factors
35.0% of the cohort abused alcohol and 38.7% were smokers; both factors significantly increased readmission risk (p < 0.05).
Comorbidities
Coronary artery disease (50.3%), sinus tachycardia (35.6%), and atrial fibrillation (20.2%) were major clinical promoters of readmission.
Sleep Disorders
28.8% of patients suffered from sleep disorders, which were significantly associated with increased rehospitalization (p < 0.05).
Discussion
General Characteristics of the Study Population
The study of 163 out patients diagnosed with chronic heart failure and followed up for management and treatment at Hospital, we obtained the following results (Table 1 and Table 2): The average age of the study group was indicating that the study population was mainly elderly, which is consistent with the age of the majority of elderly patients in other studies.4,5 In terms of gender, the proportion of males was higher than females, but the difference was not statistically significant with p>0.05. Other risk factors such as age between the elderly and young groups, education level, and BMI classification were not found to have a significant difference in the study population (p>0.05). However, in some studies such as Foroutan F (2023), the average age of patients rehospitalized after 30 days was reported to be 77.2 years, with the highest average age recorded in the United States and the lowest in Uganda.
The number of males and females was equal, with an average female proportion of 49.7%. The highest proportion of females was in Uganda, while the highest proportion of males was in Greece. Foroutan F found that the average age was associated with the 1-year mortality rate.5Table 1General Characteristics of the Study GroupGeneral CharacteristicsNumber (n)Percentage (%)GenderMale8753.4Female7646.6p = 0.391Age groupElder13079.8Young3320.2P = 0.0001Average valueLimit of valueAverage age67.40 ± 12.3332-89Systolic blood pressure146.23 ± 28.0890 – 248Diastolic blood pressure77.65 ± 17.2940 – 130Heart rate92.37 ± 23.0544 – 189Body Mass Index (BMI)21.58 ± 2.4314.8–28.8Heart failure Classification by New York Heart AssociationNumber (n)Percentage (%)Degree of dyspnea according to New York Heart Association (NYHA) classificationClass I00.0Class II4728.8Class III9357.1Class IV2314.1The number of rehospitalizations during the 6-month treatment period169.8Out of these 16 heart failure patients who were readmitted, 6 cases were due to direct cardiovascular causes, and the other 10 were caused by exacerbations of their underlying conditions1 time138.0≥ 2 times31.8Total (n):163100.0%Table 2Hematological and Biochemical Characteristics of the Study GroupLaboratory ParametersMeanRangeComplete Blood Count (CBC)Red Blood Cells (T/L)4.46 ± 0.633.06–7.20Hb (g/L)135.24 ± 18.5370.0–236.0White Blood Cells (G/L)7.85 ± 2.313.60–17.60Platelets (G/L)245.41 ± 71.81105.00–473.00Blood BiochemistryBlood Glucose7.08 ± 2.583.60–16.6Ure7.17 ± 3.382.77–25.50Creatinin94.29 ± 32.8627.20–250.60GOT36.45 ± 31.0512.1–274.6GPT28.22 ± 21.0110.00–162.00Cholesterol5.21 ± 1.692.20–19.80Triglycerid2.80 ± 5.370.50–67.10HDL – Cholesterol1.20 ± 0.310.43–1.97LDL – Cholesterol3.12 ± 1.470.53–15.20Pro BNP453.50 ± 158.0734.0–1753.0Na+134.58 ± 3.74120.80–144.30K+3.96 ± 0.422.90–5.70Cl−102.54 ± 6.2686.00–148.2Chest X-ray CharacteristicsQuantity (n)Percentage (%)Normal13482.2Cardiomegaly (Enlarged heart)2917.8Baseline heart failure classification by EF (%)Quantity (n)Percentage (%)EF ≥ 50%: Heart failure with preserved ejection fraction (HFpEF)11570.6%40 < EF < 49: Heart failure with mildly reduced ejection fraction (HFmrEF)3320.2%EF ≤ 40%: Heart failure with reduced ejection fraction (HFrEF)159.2%Comparison of ECG Heart RateBefore TreatmentAfter 6 Monthsof TreatmentMean Heart Rate (Cycles/minute)90.65 ± 22.6371.79 ± 10.88p-valueP = 0.0001 < 0.001Left Ventricular Ejection Fraction - LVEF (%)Before TreatmentAfter 6 Monthsof TreatmentLeft Ventricular Systolic Function55.62 ± 11.92[23.4–81.0]70.10 ± 9.00[49.0–89.0]p-valuep = 0.005 < 0.01
During the 6-month follow-up period, The remarkably low rehospitalization rate (9.82%) observed in this study suggests that bridging the gap between clinical guidelines and real-world practice is achievable through structured outpatient management, compared to the 25.0% reported in international studies like Riles EM (2014), suggests that our individualized management program effectively bridges the gap between clinical guidelines and real-world practice.10,13
Relationship
Heart failure patients often have risk factors such as alcohol and tobacco use, with prevalence rates of 35.0% and 38.7%, respectively. Numerous studies have identified these as risk factors for cardiovascular diseases. Analyzing the relationship between rehospitalization rate and these risk factors, we found that alcohol and tobacco use were significantly associated with a higher rehospitalization rate (p < 0.05).14,15 Gender also showed a significant association with rehospitalization rate (p < 0.01), possibly due to men having more risk factors and comorbidities than women (Table 3).16,17Table 3Relationship Between Rehospitalization Rate and Some Risk FactorsNoRisk FactorsRehospitalizationNumber (n)Percentage (%)P1AgeElder13079.80.774> 0.05Young3320.22GenderMale8753.40.006< 0.01Female7646.63Education levelUnder high school7042.90.513> 0.05High school6439.3Graduate2314.1Post-graduate63.74Body Mass Index (BMI)Normal13381.60.508> 0.05Overweight2213.5Thin84.95SmokingYes6338.70.015< 0.05None10061.36Alcohol and beerYes5735.00.019< 0.05None10665.07Hypertensive crisisYes106.10.291> 0.05None15393.98The number of rehospitalization169.8The number of Non-Rehospitalized14790.2Total (n)163100.0%
Systolic blood pressure had an average value higher than the normal range, as many patients in the study group were newly diagnosed with hypertension or were currently being treated for hypertension but had not yet achieved target blood pressure control.18 In this study, we did not find a significant association between systolic blood pressure and rehospitalization rate within 6 months. However, several studies have shown that uncontrolled or undetected hypertension can be a risk factor for heart failure, even leading to complex arrhythmias such as atrial fibrillation. In our study, 63.2% of patients had hypertension, and 6.1% were hospitalized for hypertensive crisis requiring emergency treatment.
All patients achieved target blood pressure control during the treatment of hypertensive crisis.
The average heart rate in our study was 92.37 ± 23.05 beats/minute. Additionally, there was a positive correlation between baseline heart rate and rehospitalization rate within 6 months (p < 0.01). Although the association was weak, it was statistically significant, indicating that uncontrolled heart rate and faster heart rate may predict a higher risk of hospitalization.
Heart rate optimization remains a critical therapeutic target, as elevated rates independently predict early readmission, likely due to increased myocardial oxygen demand and reduced filling time; Optimizing heart rate through treatment can help reduce rehospitalization rates and mortality in heart failure patients.
The results show that the majority of patients have NYHA II–III heart failure, accounting for 28.8% and 57.1%, respectively (Table 1). Even in the untreated state, a significant proportion of patients have NYHA IV heart failure, accounting for 14.1%. These results are consistent with other studies.5,11 The rehospitalization rate shows a correlation with the NYHA dyspnea severity with a statistically significant p-value of 0.01 (p <0.05); This is reasonable because patients with more severe heart failure have a higher risk of rehospitalization.
The underlying heart diseases were divided into two groups: the first group includes diseases that cause or contribute to the progression of heart failure (Table 4), and the second group includes underlying comorbidities (Table 5). Table 4Relationship Between Rehospitalization Rate and Diseases That Cause Heart Failure or Promote Disease ProgressionNoDiseases that Cause Heart Failure or Promote Disease Progression RehospitalizationNumber (n)Percentage (%)P1HypertensionYes10363.20.067> 0.05None6036.82Hypertensive crisisYes106.10.291> 0.05None15393.93Valvular heart diseaseYes14689.60.868> 0.05None1710.44Valvular heart disease with surgeryYes169.80.461> 0.05None14790.25Coronary artery disease with stentYes2213.50.689> 0.05None14186.56Coronary artery diseaseYes8250.30.001< 0.01None8149.77Old myocardial infarctionYes2112.90.923> 0.05None14287.18Some arrhythmiasSinus bradycardiaYes106.10.312> 0.05None15393.9Sinus tachycardiaYes5835.60.0001< 0.001None10564.4Atrial premature beatsYes2616.00.582> 0.05None13784.0Atrial fibrillation, atrial flutterYes3320.20.007< 0.01None13079.8Ventricular arrhythmiaYes2817.20.756> 0.05None13582.89CardiomyopathyYes21.20.166> 0.05None16198.810BasedowYes63.70.260> 0.05None15796.311HypothyroidismYes53.10.783> 0.05None15896.912The number of rehospitalization169.8The number of Non-Rehospitalized14790.2Total (n)163100.0%Table 5Relationship Between Rehospitalization Rate and Some Underlying DiseasesNoUnderlying DiseaseRehospitalizationNumber (n)Percentage (%)p1Diabetes mellitusYes3119.00.633> 0.05None13281.02Lipid metabolism disorderYes11268.70.111> 0.05None5131.33Cerebrovascular accidentYes1811.00.751> 0.05None14589.04Renal failureYes2414.70.181> 0.05None13985.35Chronic obstructive pulmonary diseaseYes2012.30.264> 0.05None14387.76Musculoskeletal diseaseYes6036.80.580> 0.05None10363.27Adrenal insufficiencyYes53.10.889> 0.05None15896.98Gastroesophageal reflux diseaseYes5835.60.135> 0.05None10564.49Sleep disordersYes4728.80.039< 0.05None11671.210The number of rehospitalization169.8The number of Non-Rehospitalized14790.2Total (n)163100.0%
The first group (Table 4) shows that valvular heart disease with various degrees of valvular lesions (stenosis, insufficiency) is the most common, accounting for 89.6%. Hypertension accounts for 63.2%, coronary artery disease for 50.3%, and atrial fibrillation for 20.2%. Hypertension, coronary artery disease, and valvular heart disease remain the main causes of heart failure.
Atrial fibrillation is also common, likely due to the presence of coronary artery disease and hypertension in many patients, which can trigger arrhythmias like atrial fibrillation. These results are consistent with previous studies that have shown valvular heart disease, hypertension, and coronary artery disease as the main causes of heart failure. Additionally, 6.1% of patients presented with hypertensive crisis upon examination.
A study by Gregg C. Fonarow et al (2008) showed that uncontrolled hypertension accounted for 10.7% and was a factor contributing to heart failure hospitalization.12
The study by Pfeffer MA and Braunwald E (1990) showed that in cases of acute myocardial infarction, especially extensive and transmural myocardial infarction, changes in the morphology of both the injured and non-injured areas of the ventricle can occur. The extension of the infarcted area in the early stages leads to the lengthening of the non-contractile area, causing ventricular hypertrophy. The non-infarcted area also undergoes a significant lengthening process, consistent with secondary volume hypertrophy, which may progress.
These changes can lead to structural changes that significantly affect ventricular function and patient prognosis.19
Research on heart failure associated with primary heart muscle disease is quite rare. In this study, only 1 case of dilated cardiomyopathy and 1 case of myocarditis were found, accounting for 1.2%, which is consistent with other studies, although our study is quite rare.5
Some comorbidities, such as coronary artery disease and atrial fibrillation, were significantly associated with the rehospitalization rate (p<0.01). Additionally, sinus rhythm was associated with a lower rehospitalization rate compared to the absence of sinus tachycardia, with a statistically significant difference (p<0.001).
Coronary artery disease accounted for 50.3%, coronary artery disease with stent placement for 13.5%, and previous myocardial infarction for 12.9%. Coronary artery disease is the most common cause of heart failure (HF) in developed countries and is a major therapeutic target for improving the incidence and mortality of heart failure-related diseases (Anuradha L et al)20 A study by Anuradha L et al (2014) showed that many patients with coronary artery disease, heart failure, and reduced ejection fraction experience angina-free disease. Medical treatment may be equivalent to revascularization surgery.20 The reason is that chronic myocardial ischemia leads to left ventricular dysfunction, especially after myocardial infarction, which leads to a series of changes in both the infarcted and non-infarcted tissue, known as adverse remodeling.
This remodeling leads to heart failure and its progression is related to the degree of adverse remodeling (Anuradha L et al).20
In our study, we found that atrial fibrillation was present in 20.2% of heart failure patients, which is quite similar but lower than the results of Torp Pedersen CT’s study of 1515 chronic heart failure patients, where the incidence of atrial fibrillation was 25.8%; The incidence of atrial fibrillation in chronic heart failure ranges from 10.0% to 50.0% depending on various factors such as age, cause of heart failure, and comorbidities.21 In terms of pathophysiology, the heart failure group is mainly elderly, as with increasing age, atrial degeneration and conduction system abnormalities increase. At an older age, people often have more comorbidities, which are risk factors for both atrial fibrillation and heart failure,21,22 such as hypertension,23 coronary artery disease,23,24 and diabetes.19,25,26
Some studies, such as that by Torp-Pedersen C (1999),8 have reported an increasing incidence of atrial fibrillation with increasing heart failure severity. Other authors such as Torp-Pedersen C (1999),21 and De Ferrari GM27 have noted that atrial fibrillation and hypertension are among the causes of heart failure. Zhang Z et al (2023) have used two-dimensional Mendelian randomization analysis through genetic instrumental variables to investigate the bidirectional causal effects between atrial fibrillation and heart failure, showing that heart failure (HF) increases the risk of atrial fibrillation (AF) by 44.0%.28 Heart failure remains a cause of death for patients with atrial fibrillation; The onset of atrial fibrillation in heart failure patients is a sign of cardiac overload and impaired compensatory capacity of the cardiovascular system to meet physiological demands.
Meanwhile, heart failure promotes atrial remodeling, with excessive left ventricular end-diastolic pressure transmitted to the atria through the mitral valve, leading to increased left atrial filling pressure. Conversely, this increases atrial wall pressure and alters the electrical properties of atrial tissue, which are factors in the onset and development of atrial fibrillation.28 Identifying early risk factors like atrial fibrillation is crucial for managing these risk factors to delay disease progression, prevent and reduce the burden of atrial fibrillation and heart failure-related healthcare, and potentially prevent and limit atrial fibrillation. Therefore, in the treatment of atrial fibrillation in patients with chronic heart failure, in addition to treatment with anticoagulants and rhythm conversion, regular periodic monitoring or when cardiac function is abnormal to detect and treat promptly, comprehensive management of comorbidities associated with atrial fibrillation such as hypertension, diabetes mellitus, and obesity is equally important.
In conclusion, atrial fibrillation is a common complication in heart failure patients, and the two conditions have a complex bidirectional relationship; Early identification and treatment of atrial fibrillation in heart failure patients can help improve prognosis and reduce the risk of complications such as stroke and heart failure progression.29–31
Thus, Clinical Comorbidities as above are Consistent with global literature, valvular heart disease, hypertension, and coronary artery disease were the primary drivers of HF. The bidirectional relationship between atrial fibrillation and HF further complicates prognosis; HF promotes atrial remodeling, while AF reduces cardiac output, creating a vicious cycle that necessitates aggressive rhythm and rate control.
The second group of comorbidities (Table 5) most commonly encountered are lipid metabolism disorders (68.7%), musculoskeletal disorders (36.8%), gastritis (35.6%), sleep disorders (28.8%), diabetes mellitus (19.0%), and chronic obstructive pulmonary disease (12.3%).32,33
Some associated symptoms are related to rehospitalization frequency, such as sleep disorders, with a statistically significant difference (p < 0.05). Heart failure causes shortness of breath when lying down in many patients, which is a feeling of difficulty breathing when lying down or even paroxysmal nocturnal dyspnea due to ventricular volume overload, leading to many cases of shortness of breath that wakes the patient after only one or two hours of sleep. These conditions improve when the patient changes their posture to sitting or standing.
These issues can disrupt the patient’s sleep and cause anxiety, fatigue, anxiety about medication use, or hospitalization. All of these factors affect the patient’s ability to maintain sleep. Thus, The Role of Sleep Disorders in Our findings highlight sleep disorders as a significant independent predictor of rehospitalization (p < 0.05).
This underscores the necessity of integrating psychological and sleep assessments into standard heart failure protocols; poor sleep quality often reflects underlying nocturnal dyspnea or heightened anxiety, both of which exacerbate heart failure progression.32,33
Some studies have shown that patients with diabetes mellitus have a 3–5 times higher risk of heart failure, with women being more affected than men. Hypertension, coronary artery disease, often combined with diabetes mellitus and/or metabolic syndrome, are leading causes of heart failure in developed countries.4,5
Observations by Foroutan F (2023) show that among patients at risk of rehospitalization after one year, the most common heart failure comorbidities are hypertension, followed by diabetes mellitus, atrial fibrillation, COPD, and kidney disease.23,24 However, Foroutan F’s (2023) observations also show that the prevalence of COPD and diabetes mellitus has explained some of the observed heterogeneity. Specifically, for every 1.0% increase in the prevalence of COPD or diabetes mellitus, the absolute risk of all-cause hospitalization within 30 days increases by 0.4% and 0.3%, respectively. Foroutan F also found that the prevalence of COPD was associated with a 1-year mortality rate, with a 0.2% increase in the absolute risk of all-cause mortality after 1 year for every 1.0% increase in COPD prevalence.
This suggests the combined disease burden of respiratory or diabetes comorbidities in patients with heart failure. It is necessary to control blood glucose levels, stabilize COPD treatment, avoid respiratory decompensation, and reduce the risk of hospitalization in these patients with heart failure.5
Elderly Patients with Heart Failure need a delicate balance. Elderly individuals with heart failure are particularly susceptible to acute decompensation, often triggered by conditions like pneumonia, acute exacerbations of COPD, infections, sepsis, myocardial infarction, or arrhythmias such as atrial fibrillation. Additionally, underlying health conditions like diabetes and anemia can contribute to the development of heart failure in older adults.
Therefore, to optimize heart failure management, it’s essential to concurrently manage risk factors, and it’s crucial to identify the underlying causes and factors that contribute to the progression of heart failure in each patient. This comprehensive assessment allows for tailored treatment plans that address specific needs and improve overall outcomes. This integrated approach can significantly enhance heart failure treatment and improve patient outcomes.
Conclusion
In this prospective observational cohort of chronic heart failure outpatients in Vietnam, a 6-month rehospitalization rate of 9.82% was observed. Readmission was associated with specific baseline risk factors, including male gender, smoking, alcohol consumption, higher baseline heart rate, NYHA functional class, and comorbidities such as coronary artery disease, atrial fibrillation, and sleep disorders. While these findings offer valuable baseline epidemiological insight into managed outpatient CHF cohorts in Southeast Asia, controlled comparative trials are required to establish the causal effectiveness of structured management interventions.
Limitations and Recommendations
Firstly, the study is limited by its single-center design, which may limit the generalizability of the findings to the broader Vietnamese as well as Southeast Asia population. Secondly, a relatively short 6-month follow-up period, while sufficient for assessing short-term outcomes, may not capture long-term sustainability. Future multi-center trials are needed to validate these findings across broader populations.