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A map of Asia showing Asian countries coloured according to geographical regions with a non-exhaustive list of registries
Source publication
Purpose of the Review
Multimorbidity, the presence of two or more comorbidities, is common in patients with heart failure (HF) and worsens clinical outcomes. In Asia, multimorbidity has become the norm rather than the exception. Therefore, we evaluated the burden and unique patterns of comorbidities in Asian patients with HF.
Recent Findings
Asian...
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Multimorbidity is associated with increased out-of-pocket healthcare costs, making people with multimorbidity more vulnerable to cost-related non-adherence to recommended treatment. This study aimed to understand how people with multimorbidity would prioritise different healthcare services and chronic conditions when faced with potential budget con...
Citations
... The Asian continent has the highest prevalence of heart failure (HF) cases globally [1]. Diabetes is especially common in South East Asian HF populations, where a unique 'lean-diabetic' phenotype with worse outcomes has been identified [2]. The Asian Sudden Cardiac Death in Heart Failure (ASIAN-HF) registry (across 11 Asian countries) reported a 42.5% prevalence of diabetes among HF patients, specifically in higher-income countries such as Singapore, Hong Kong, and Thailand [3]. ...
Background
Heart failure (HF) and diabetes are associated with increased incidence and worse prognosis of each other. The prognostic value of global longitudinal strain (GLS) measured by cardiovascular magnetic resonance (CMR) has not been established in HF patients with diabetes.
Methods
In this prospective, observational study, consecutive patients (n = 315) with HF underwent CMR at 3T, including GLS, late gadolinium enhancement (LGE), native T1, and extracellular volume fraction (ECV) mapping. Plasma biomarker concentrations were measured including: N-terminal pro B-type natriuretic peptide(NT-proBNP), high-sensitivity troponin T(hs-TnT), growth differentiation factor 15(GDF-15), soluble ST2(sST2), and galectin 3(Gal-3). The primary outcome was a composite of all-cause mortality or HF hospitalisation.
Results
Compared to those without diabetes (n = 156), the diabetes group (n = 159) had a higher LGE prevalence (76 vs. 60%, p < 0.05), higher T1 (1285±42 vs. 1269±42ms, p < 0.001), and higher ECV (30.5±3.5 vs. 28.8±4.1%, p < 0.001). The diabetes group had higher NT-pro-BNP, hs-TnT, GDF-15, sST2, and Gal-3. Diabetes conferred worse prognosis (hazard ratio (HR) 2.33 [95% confidence interval (CI) 1.43–3.79], p < 0.001). In multivariable Cox regression analysis including clinical markers and plasma biomarkers, sST2 alone remained independently associated with the primary outcome (HR per 1 ng/mL 1.04 [95% CI 1.02–1.07], p = 0.001). In multivariable Cox regression models in the diabetes group, both GLS and sST2 remained prognostic (GLS: HR 1.12 [95% CI 1.03–1.21], p = 0.01; sST2: HR per 1 ng/mL 1.03 [95% CI 1.00-1.06], p = 0.02).
Conclusions
Compared to HF patients without diabetes, those with diabetes have worse plasma and CMR markers of fibrosis and a more adverse prognosis. GLS by CMR is a powerful and independent prognostic marker in HF patients with diabetes.
... Hospitalization for heart failure comes with a high risk of both short-term and long-term mortality (8). The HF's prognosis remains grim and the 5year mortality risk after the diagnosis is 50%, which is worse than many types of cancer (9). ...
... Data on patients with prevalent HF showed that approximately two in three Asian patients have at least two comorbidities apart from HF. The multi-morbidity patterns in patients with HF are associated with worse outcomes (9). ...
... This might be due to the negative effects of drug therapy problems on the optimizing the heart failure management. 9 Reduced ejection fraction was not a predictors of heart failure mortality in our study. However, lower left ventricular ejection fraction (LVEF) predicts the poor treatment outcome of heart failure in Angola (29). ...
Background Heart failure is a major cause of morbidity and mortality worldwide. Patients with HF often have multiple factors that accelerate disease progression and worsen the response to treatment. Therefore, the study was aims to assess the pooled magnitude and associated factors of poor heart failure treatment outcome in Ethiopia Methods Five databases, including PubMed, Science Direct, Scopus, HINARI and Google Scholar, were used. Finally, 12 studies that satisfied the eligibility criteria were included in the systematic review and meta-analysis. The protocol of PRISMA 2020 was used to undertake this systematic review and meta-analysis. The data were extracted by using a Microsoft Excel sheet, and STATA 14 was utilized for the analysis. The Joanna Briggs institute meta-analysis of statistics assessment and review instrument (JBI-MAStARI) was used for quality assessment. The Cochrane Q test statistic and I2 tests were used to assess heterogeneity. A funnel plot, Egger's weighted regression, and Begg's test were used to investigate publication bias. Result The pooled magnitude of poor heart failure treatment outcome was 16.67% (95%CI: 10.67-22.67). Heterogeneity was not observed across the included studies (I2 = 0.0%, p = 0.962). The predictors of poor heart failure treatment outcome were smoking a cigarettes (AOR= 10.74; 95% CI, 3.239-35.631), the medication related problems (AOR=3.99; 95% CI, 1.90-8.37). Conclusion The magnitude of poor heat failure treatment outcome was found to be high. Smoking a cigarette and the presence of medication related problems were the predictors of heart failure treatment outcome. Therefore, a proper health education and clinical pharmacy service should be implemented.
... years). 19,20 This finding could be caused by the rapid "westernization" of diets in the population that had low health literacy, leading to multimorbidity (as shown in this study, almost 70% of patients had coronary arterial disease (CAD), more than 70% had hypertension, and almost 50% had a history of smoking) in younger population, leading to "premature" HF. 21 Our registry shares the same gender predisposition with that in 9 Asian countries, Europe, and the USA, ranging from 45% up to 75%. 3 Moreover, our registry had a slightly lower AFib proportion than the ASIAN-HF registry (10.2% vs. 13.2%). 19 The management of HFrEF, according to the latest guidelines 1,8 was the four pillars consisting of RAAS blocker, beta-receptor blocker, MRA, and sodium-glucose co-transporter-2 inhibitor (SGLT2i). ...
Background : As the prevalence of heart failure (HF) kept rising each year, the burden caused by it also escalating, especially in terms of economic burden. This is urging the physician to quickly tackle the problem. Although HFrEF medications were developing vastly, the outcome of HF in real world still varies. This indicates another approach is still needed to manage HFrEF/HFmrEF comprehensively. This paper is aimed to give an overview of HFrEF and HFmrEF epidemiological data, based on CORE-HF real world data. Methods : The CORE-HF is a single-center, prospective-cohort registry, which enrolls all patients with chronic HF, that were recruited consecutively from the outpatient Sebelas Maret HF Clinic. Both enrollment and follow-up have been performed since January 2018 until December 2022. Variables recorded consists of baseline characteristics, risk factors, subjective indicators, objective diagnostic assessments, therapies, and outcomes (readmission and mortality). Results : The population of this registry was younger (58.7 ± 12.14) compared to other HF registries, with more multi comorbidities. The number of HFrEF patient was higher than HFmrEF (77.7% vs 22.3%), with clinically higher mortality rate (7.2% in the 1st year and 18.2% in the next year). Although triple therapy initiation and uptitration were excellent in number, the mortality rate during second year of follow-up was higher than other registries. We found non-compliant behavior to be responsible for those results. Conclusion : Based on CORE-HF sub-analysis of the HFrEF and HFmrEF groups, adherence to HF guidelines is the main but not the only key leading to lower mortality and rehospitalization. Our data provide satisfying low hard outcomes, but solving the non-compliance behavior and optimizing the non-pharmacological approach should be done comprehensively by the HF team.
... 3 Asian patients with HF also demonstrate a different epidemiology, whereby they tend to get the disease younger and experience a higher burden of comorbidities, relative to their White counterparts. 4 Cardiomyopathies, a group of diseases of the heart muscle rendering the thickening, stiffening, or stretching (dilation) of the walls of heart chambers, are the leading nonischemic cause of HF globally. 3 HF has an important genetic component, and studies on nonischemic cardiomyopathies have been especially valuable for interrogating the genetics underlying HF. ...
Previous studies on cardiomyopathies have been particularly valuable for clarifying pathological mechanisms in heart failure, an etiologically heterogeneous disease. In this review, we specifically focus on cardiomyopathies in Asia, where heart failure is particularly pertinent. There has been an increase in prevalence of cardiomyopathies in Asia, in sharp contrast with the decline observed in Western countries. Indeed, important disparities in cardiomyopathy incidence, clinical characteristics, and prognosis have been reported in Asian versus White cohorts. These have been accompanied by emerging descriptions of a distinct rare and common genetic basis for disease among Asian cardiomyopathy patients marked by an increased burden of variants with uncertain significance, reclassification of variants deemed pathogenic based on evidence from predominantly White cohorts, and the discovery of Asian-specific cardiomyopathy-associated loci with underappreciated pathogenicity under conventional classification criteria. Findings from epigenetic studies of heart failure, particularly DNA methylation studies, have complemented genetic findings in accounting for the phenotypic variability in cardiomyopathy. Though extremely limited, findings from Asian ancestry-focused DNA methylation studies of cardiomyopathy have shown potential to contribute to general understanding of cardiomyopathy pathophysiology by proposing disease and cause-relevant pathophysiological mechanisms. We discuss the value of multiomics study designs incorporating genetic, methylation, and transcriptomic information for future DNA methylation studies in Asian cardiomyopathy cohorts to yield Asian ancestry-specific insights that will improve risk stratification in the Asian population.
Aim
To explore the cognitive representations and emotional responses to living with chronic heart failure of people receiving limited community disease management.
Background
Individuals living with heart failure face self‐care and emotional challenges due to the overwhelming nature of adapting to lifestyle changes, particularly in subtropical areas.
Design
Qualitative descriptive. We applied Leventhal's Common Sense Model of Self‐Regulation as the framework for interviews and analyses.
Methods
Twenty patients with chronic heart failure were interviewed during a hospital admission for exacerbation of their condition in a tertiary hospital in Thailand.
Results
Analysis of the components of Leventhal's model of cognitive representations of illness revealed two themes relating to Illness Identity : (1) lack of knowledge of the diagnosis and how to recognise symptoms of the disease, and (2) recognition of symptoms of an exacerbation of CHF was based on past experience rather than education. These resulted in delays responding to cardiac instability and confusion about the intent of treatment. Participants recognised the chronicity of their disease but experienced it as an unrelenting cycle of relative stability and hospitalisations. Perceived Controllability was low. Two themes were: (1) Low perceived trust in the efficacy of medical treatment and lifestyle changes, and (2) Low perceived trust in their ability to comply with recommended lifestyle changes. The Consequences were significant emotional distress and high burden of disease. The two themes of emotional responses were (1) Frustration and hopelessness with the uncertainty and unpredictability of the disease, and (2) Sense of loss of independence, functional capacity and participation in life's activities.
Conclusion
Chronically ill patients need support to understand their illness and make better treatment and lifestyle decisions. Improving patients' self‐efficacy to manage treatment and symptom fluctuations has the potential to improve their mental well‐being and minimise the impact of their condition on suffering and participation in employment and community.
Implications for the Profession and/or Patient Care
Leventhal's Common Sense Model of Self‐Regulation can be used to examine cognitive and emotional elements of illness perceptions, which link to individuals' ability to make informed decisions about disease management and influence health behaviours. Understanding illness perceptions underpins strategies for enhancing and sustaining self‐management behaviours.
Impact
The study findings accentuate the need to establish long‐term condition support programs in low‐middle income countries where the burden of heart failure is increasing exponentially.
Reporting Method
The Consolidated Criteria for Reporting Qualitative Research (COREQ) guideline was used to explicitly and comprehensively report our qualitative research.
Patient or Public Contribution
Patients contributed to the conduct of the study by participating in the data collection via face‐to‐face interviews.
Aims:
Heart failure (HF) is one of the most frequent diagnoses for 30-day readmission after hospital discharge. Nurses have role in reducing unplanned readmission and providing quality of care during HF trajectories. This systematic review assessed the quality and significant factors of machine learning (ML)-based 30-day HF readmission prediction models.
Methods and results:
Eight academic and electronic databases were searched to identify all relevant articles published between 2013 and 2023. Thirteen studies met our inclusion criteria. The sample sizes of the selected studies ranged from 1,778 to 272,778 patients, and patients' average age ranged from 70 to 81 years. Quality appraisal was performed.
Conclusion:
The most commonly used ML approaches were Random Forest and XGBoost. The 30-day HF readmission rates ranged from 1.2% to 39.4%. The area under the receiver operating characteristic curve for models predicting 30-day HF readmission were between 0.51 and 0.93. Significant predictors included sixty variables with nine categories (socio-demographics, vital signs, medical history, therapy, echocardiographic findings, prescribed medications, laboratory results, comorbidities, and hospital performance index). Future studies using ML algorithms should evaluate the predictive quality of the factors associated with 30-day HF readmission presented in this review, considering different healthcare systems and type of HF. More prospective cohort studies with combining structured and unstructured data are required to improve the quality of ML based prediction model, which may help nurses and other healthcare professionals assess early and accurate 30-day HF readmission predictions and plan individualized care after hospital discharge.
Registration:
This study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD 42023455584).
