Multimorbidity in patients with heart failure from 11 Asian regions: A prospective cohort study using the ASIAN-HF registry

A sex-disaggregated analysis of the prognostic value of lean type 2 diabetes mellitus in the adult population with acute myocardial infarction

BACKGROUND

Emerging evidence has demonstrated the unfavourable cardiovascular risk of individuals with lean type 2 diabetes mellitus (T2DM). Our study aims to investigate the prognostic value of lean T2DM in patients with acute myocardial infarction (AMI), stratified by sex.

METHODS

The study cohort examines the clinical characteristics and long-term outcomes of individuals with AMI, stratified by four phenotypes based on T2DM and lean body category-lean T2DM, non-lean T2DM, lean non-T2DM and non-lean non-T2DM. The primary outcome was long-term all-cause mortality. Cox regression model was constructed to investigate the associations of lean and non-lean T2DM phenotypes with mortality, adjusted for age, ethnicity, previous AMI, AMI type, chronic kidney disease, angiotensin converting enzyme inhibitor or angiotensin receptor blockers, beta-blockers, and smoking status.

RESULTS

A cohort of 9545 AMI patients was examined, with a mean follow-up duration of 3.4 ± 2.4 years. Majority had the non-lean T2DM phenotype (40.4%), followed by non-lean non-T2DM (29.8%), lean non-T2DM (15.9%), and lean T2DM (13.9%). In the T2DM group, one-quarter was lean (N = 1324), while the vast majority (74.5%) was non-lean. Individuals with lean T2DM tended to be female and older. Patients with lean T2DM had the highest rates of heart failure (23.3%, p < 0.001), cardiogenic shock (9.1%, p = 0.036), and long-term all-cause mortality (32.6%, p < 0.001). Cox regression demonstrated that lean T2DM was an independent predictor of mortality (adjusted hazard ratio [aHR] 1.171, 95% CI 1.040-1.319, p = 0.009) after adjustment. The presence of higher mortality risk following AMI was present in males (aHR 1.201, 95% CI 1.037-1.391, p = 0.015), but not in females (aHR 1.066, 95% CI 0.869-1.308, p = 0.538).

CONCLUSIONS

The lean T2DM phenotype was present in one-quarter of the AMI cohort with T2DM. The lean T2DM phenotype was an independent predictor of long-term mortality following AMI, although this association was stronger in males than in females.

Data Mining to Identify the Right Interventions for the Right Patient for Heart Failure: A Real-World Study

OBJECTIVES

To identify the right interventions for the right heart failure (HF) patients in the real-world setting using machine learning (ML) trained on individual-level clinical data linked with social determinants of health (SDOH) data.

METHODS

In this retrospective cohort study, point-of-care claims data from Komodo Health and SDOH data from the National Health and Wellness Survey (NHWS), from January 2014-December 2020, were linked. Data mining was conducted using K-means clustering, an ML tool. Komodo Health data were used to access longitudinal data for the selected patient cohorts and crosssectional data from NHWS for additional patient information. The primary outcome was HF-related hospitalizations; secondary outcomes, all-cause hospitalization and all-cause mortality. Use of digital healthcare (DHC)/non-DHC interventions and related outcomes were also assessed.

RESULTS

The study population included 353 HF patients (mean age, 63.5 years; 57.2% women). The use of non-DHC (75.9%-81.9%) and DHC (4.0%-9.1%) interventions increased from baseline to followup. Overall, 17.0% of patients had HF-related hospitalizations (DHC, 6.9%; non-DHC, 16.5%) and 45.0% had all-cause hospitalization (DHC, 75.0%; non-DHC, 50.9%). Two archetypes with distinct patient profiles were identified. Archetype 1 (vs. 2) characterised by older age, greater disease severity, more comorbidities, more medication use, took steps to prevent heart attack/problems, had better lifestyle, higher HF-related hospitalizations (18.3% vs. 16.3%) and lower all-cause hospitalizations (42.9% vs. 46.3%). The trends remained the same regardless of the intervention type.

CONCLUSIONS

Identification of patient archetypes with distinct profiles can be useful to understand underlying disease subtypes, identify specific interventions, predict clinical outcomes, and define the right intervention for the right patient.

Therapeutic Consequences and Prognostic Impact of Multimorbidity in Heart Failure: Time to Act

Background/Objectives: In heart failure (HF) with reduced ejection fraction (HFrEF), the early diagnosis and proper treatment of comorbidities (CMs) are of fundamental relevance. Our aim was to assess the prevalence of CMs among real-world patients requiring hospitalisation for HFrEF and to investigate the effect of CMs on the implementation of guideline-directed medical therapy (GDMT) and on all-cause mortality (ACM). Methods: The data of a consecutive HFrEF patient cohort hospitalised for HF between 2021 and 2024 were analysed retrospectively. Sixteen CMs (6 CV and 10 non-CV) were considered. Patients were divided into three categories: 0-3 vs. 4-6 vs. ≥7 CMs. GDMT at discharge and ACM were compared among CM categories. The predictors of 1-year ACM were also evaluated. Results: From the 388 patients (male: 76%, age: 61 [50-70] years; NT-proBNP: 5286 [2570-9923] pg/mL; ≥2 cardiovascular-kidney-metabolic disease overlap: 46%), a large proportion received GDMT (RASi: 91%; βB: 85%; MRA: 95%; SGLT2i: 59%; triple therapy [TT: RASi+βB+MRA]: 82%; quadruple therapy [QT: TT + SGLT2i]: 54%) at discharge. Multimorbidity was accompanied with a (p < 0.05) lower application ratio of RASi (96% vs. 92% vs. 85%; 0-3 vs. 4-6 vs. ≥7 CMs) and βB therapy (94% vs. 85% vs. 78%), while MRA (99% vs. 94% vs. 94%) and SGTL2i use (61% vs. 59% vs. 57%) did not differ (p > 0.05). Patients with multimorbidity were less likely to be treated with TT (93% vs. 82% vs. 73%, p = 0.001), while no difference was detected in the implementation of QT (56% vs. 54% vs. 50%, p = 0.685). The 1-year ACM of patients with an increased burden of CMs was higher (9% vs. 13% vs. 25%, p = 0.003). The risk of 1-year ACM was favourably affected by the use of TT/QT and less severe left ventricular systolic dysfunction, while having ≥5 CMs had an unfavourable impact on prognosis. Conclusions: According to our real-world analysis, HFrEF patients with an increased burden of CMs can expect a less favourable outcome. However, modern GDMT can even be applied in this patient population, resulting in a significantly improved prognosis. Thus, clinicians should insist on the early, conscious implementation of a prognosis-modifying drug regime in multimorbid HF patients as well.

Disease Network-Based Approaches to Study Comorbidity in Heart Failure: Current State and Future Perspectives

PURPOSE OF REVIEW

Heart failure (HF) is often accompanied by a constellation of comorbidities, leading to diverse patient presentations and clinical trajectories. While traditional methods have provided valuable insights into our understanding of HF, network medicine approaches seek to leverage these complex relationships by analyzing disease at a systems level. This review introduces the concepts of network medicine and explores the use of comorbidity networks to study HF and heart disease.

RECENT FINDINGS

Comorbidity networks are used to understand disease trajectories, predict outcomes, and uncover potential molecular mechanisms through identification of genes and pathways relevant to comorbidity. These networks have shown the importance of non-cardiovascular comorbidities to the clinical journey of patients with HF. However, the community should be aware of important limitations in developing and implementing these methods. Network approaches hold promise for unraveling the impact of comorbidities in the complex presentation and genetics of HF. Methods that consider comorbidity presence and timing have the potential to help optimize management strategies and identify pathophysiological mechanisms.

Even a Low Comorbidity Burden Predicts Poor Outcomes in Chronic Heart Failure

BACKGROUND

Patients with heart failure often have multiple cardiovascular risk factors (CVRFs) and comorbidities (CMBs). We evaluated the impact of additive CMB and CVRF on heart failure prognosis.

METHODS

We retrospectively analyzed ambulatory patients with systolic dysfunction between January 2012 and May 2018. Follow-up was until January 2021. The endpoint was all-cause death. CVRF analyzed arterial hypertension, diabetes mellitus, and smoking. CMB evaluated coronary artery disease, noncoronary atherosclerotic disease, respiratory disease, dementia, anemia, chronic kidney disease, inflammatory/autoimmune disease, active cancer, and atrial fibrillation. Classification according to the number of CVRFs and/or CMBs is <2 and ≥2. The independent prognostic impact of CVRF/CMB burden was assessed with multivariate Cox regression.

RESULTS

Most patients had ≥2 CMBs (67.9%). Regarding CVRF, 14.9% presented none, 40.2% had 1, and 32.1% had 2. During a median 49-month follow-up, 419 (49.1%) patients died. Mortality was higher among patients with ≥2 CVRFs (56.1 versus 43.4% in those with <2) and in those with ≥2 CMBs (57.7 versus 31.0%). While patients with 1 CMB had similar mortality than those with none. Patients with ≥2 CMBs had higher long-term mortality risk: hazard ratio (HR), 2.47 (95% CI, 1.95-3.14). In patients with ≥2CVRFs, the HR of dying is 1.39 (95% CI, 1.14-1.70). When taken together, there was a clear survival disadvantage for patients with ≥2 CVRFs/CMBs-adjusted HR, 2.20 (95% CI, 1.45-3.34).

CONCLUSIONS

The presence of only 2 CVRFs/CMBs more than doubles the patients´ risk of dying. CVRF and CMB should be assessed as part of routine patient management.

Embracing an era of targeted combination therapy for heart failure with preserved ejection fraction

The concept of quadruple therapy as a "one-size-fit-all" approach is effective among all eligible patients with heart failure with reduced ejection fraction, with consistent and significant clinical benefits including reduced mortality across various subgroups. However, with exception of sodium-glucose cotransporter 2 inhibitors, the consistency of benefit with therapies does not extend to patients with heart failure with preserved ejection fraction. The clinical benefits of other promising medical therapies, such as angiotensin receptor-neprilysin inhibitors, mineralocorticoid receptor antagonists, and glucagon-like peptide-1 receptor agonists, have been demonstrated only in certain phenotypes of the highly heterogenous heart failure with preserved ejection fraction population. This variability can confuse frontline practicing cardiologists, potentially leading to the under-implementation of these medications. Therefore, we propose a simple approach: "targeted" combination therapy. This strategy aims to optimize evidence-based medications in heart failure with preserved ejection fraction by tailoring treatments to specific subgroups within the heart failure with preserved ejection fraction population where significant benefits are most evident.

Regional Differences in the Epidemiology of Heart Failure

Heart failure (HF) epidemiology, patient characteristics, and clinical outcomes exhibit substantial regional variations, reflecting diverse etiologies and health system capacities. This review comprehensively analyses these variations, drawing on data from recent global registries and clinical trials. Our review indicates that ischemic and hypertensive heart diseases are prevalent globally but differ in dominance depending on the region. Notably, regions such as Africa and Latin America show higher instances of HF from hypertensive heart disease and Chagas cardiomyopathy, respectively. Moreover, disparities in age and comorbidity profiles across regions highlight younger populations with HF in lower-income countries compared to older populations in high-income regions. This review also highlights the global disparity in guideline-directed medical and device therapy, underscoring significant underuse in lower-income regions. These insights emphasize the need for targeted HF management strategies considering regional clinical and demographic characteristics to enhance global HF care and outcomes.

Current and Future of Heart Failure Care in Asia

Heart failure (HF) is a significant global health concern, particularly in Asia, where over half of the world's population resides. Despite advances in treatment, the burden of HF is expected to rise in the region due to the aging population and an increase in non-communicable diseases associated with HF risk. This narrative review examines the current state of HF in Asia, highlighting differences in treatment utilization, underrepresentation of Asian individuals in clinical trials, emerging therapies, and implementation strategies, including the potential use of polypills and the need for expanded HF training opportunities for healthcare providers.

Distinct Comorbidity Clusters in Patients With Acute Heart Failure: Data From RELAX-AHF-2

BACKGROUND

Multimorbidity frequently occurs in patients with acute heart failure (AHF). The co-occurrence of comorbidities often follows specific patterns.

OBJECTIVES

This study investigated multimorbidity subtypes and their associations with clinical outcomes.

METHODS

From the prospective RELAX-AHF-2 (Relaxin for the Treatment of Acute Heart Failure-2) trial, 6,545 patients (26% with HF with preserved ejection fraction, defined as LVEF ≥50%) were classified into multimorbidity groups using latent class analysis. The association between subgroups and clinical outcomes was examined. Validation of these findings was conducted in the RELAX-AHF trial, which comprised 1,161 patients.

RESULTS

Five distinct multimorbidity groups emerged: 1) diabetes and chronic kidney disease (CKD) (often male, high prevalence of CKD and diabetes mellitus); 2) ischemic (ischemic HF); 3) elderly/atrial fibrillation (AF) (oldest, high prevalence of AF); 4) metabolic (obese, hypertensive, more often HF with preserved ejection fraction); and 5) young (fewest comorbidities). After adjusting for confounders, patients in the diabetes and CKD (HR: 1.80; 95% CI: 1.50-2.20), elderly/AF (HR: 1.42; 95% CI: 1.20-1.70), and metabolic (HR: 1.40; 95% CI: 1.20-1.80) groups had higher rates of the composite outcome than patients in the young group, primarily driven by differences in rehospitalization. Treatment allocation (placebo or serelaxin) modified these associations (Pinteraction <0.001). Serelaxin-treated patients in the young group were associated with a lower risk for all-cause mortality (HR: 0.59; 95% CI: 0.40-0.90). Similarly, patients from the RELAX-AHF trial clustered in 5 multimorbidity groups. The clinical characteristics and associations with outcomes could also be validated.

CONCLUSIONS

Comorbidities naturally clustered into 5 mutually exclusive groups in RELAX-AHF-2, showing variations in clinical outcomes. These data emphasize that the specific combination of comorbidities can influence adverse outcomes and treatment responses in patients with AHF.

Heart failure with preserved ejection fraction

Heart failure with preserved ejection fraction (HFpEF) accounts for nearly half of all heart failure cases and has a prevalence that is expected to rise with the growing ageing population. HFpEF is associated with significant morbidity and mortality. Specific HFpEF risk factors include age, diabetes, hypertension, obesity and atrial fibrillation. Haemodynamic contributions to HFpEF include changes in left ventricular structure, diastolic and systolic dysfunction, left atrial myopathy, pulmonary hypertension, right ventricular dysfunction, chronotropic incompetence, and vascular dysfunction. Inflammation, fibrosis, impaired nitric oxide signalling, sarcomere dysfunction, and mitochondrial and metabolic defects contribute to the cellular and molecular changes observed in HFpEF. HFpEF impacts multiple organ systems beyond the heart, including the skeletal muscle, peripheral vasculature, lungs, kidneys and brain. The diagnosis of HFpEF can be made in individuals with signs and symptoms of heart failure with abnormality in natriuretic peptide levels or evidence of cardiopulmonary congestion, facilitated by the use of HFpEF risk scores and additional imaging and testing with the exclusion of HFpEF mimics. Management includes initiation of guideline-directed medical therapy and management of comorbidities. Given the significant impact of HFpEF on quality of life, future research efforts should include a particular focus on how patients can live better with this disease.

Relationship of interleukin-16 with different phenogroups in acute heart failure with preserved ejection fraction

AIMS

Interleukin-16 (IL-16) has been reported to mediate left ventricular myocardial fibrosis and stiffening in patients with heart failure with preserved ejection fraction (HFpEF). We sought to elucidate whether IL-16 has a distinct impact on pathophysiology and prognosis across different subphenotypes of acute HFpEF.

METHODS AND RESULTS

We analysed 211 patients enrolled in a prospective multicentre registry of acute decompensated HFpEF for whom serum IL-16 levels after stabilization were available (53% female, median age 81 [interquartile range 75-85] years). We divided this sub-cohort into four phenogroups using our established clustering algorithm. The study endpoint was all-cause death. Patients were subclassified into phenogroup 1 ('rhythm trouble' [n = 69]), phenogroup 2 ('ventricular-arterial uncoupling' [n = 49]), phenogroup 3 ('low output and systemic congestion' [n = 41]), and phenogroup 4 ('systemic failure' [n = 52]). After a median follow-up of 640 days, 38 patients had died. Among the four phenogroups, phenogroup 2 had the highest IL-16 level. The IL-16 level showed significant associations with indices of cardiac hypertrophy, diastolic dysfunction, and congestion only in phenogroup 2. Furthermore, the IL-16 level had a significant predictive value for all-cause death only in phenogroup 2 (C-statistic 0.750, 95% confidence interval 0.606-0.863, P = 0.017), while there was no association between the IL-16 level and the endpoint in the other phenogroups.

CONCLUSIONS

Our results indicated that the serum IL-16 level had a significant association with indices that reflect the pathophysiology and prognosis of HFpEF in a specific phenogroup in acute HFpEF.

Clinical characteristics and outcomes in Asian patients with heart failure with mildly reduced ejection fraction

INTRODUCTION

Data on heart failure (HF) with mildly reduced ejection fraction (HFmrEF) is still emerging, especially in Asian populations. This study aims to compare the clinical characteristics and outcomes of Asian HFmrEF patients with those of HF patients with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF).

METHODS

Patients admitted nationally for HF between 2008 and 2014 were included in the study. They were categorised according to ejection fraction (EF). Patients with EF <40%, EF 40%-49% and EF ≥50% were categorised into the following groups: HFrEF, HFmrEF and HFpEF, respectively. All patients were followed up till December 2016. Primary outcome was all-cause mortality. Secondary outcomes included cardiovascular death and/or HF rehospitalisations.

RESULTS

A total of 16,493 patients were included in the study - HFrEF, n = 7,341 (44.5%); HFmrEF, n = 2,272 (13.8%); and HFpEF n = 6,880 (41.7%). HFmrEF patients were more likely to be gender neutral, of mid-range age and have concomitant diabetes mellitus, hyperlipidaemia, peripheral vascular disease and coronary artery disease ( P < 0.001). The two-year overall mortality rates for HFrEF, HFmrEF and HFpEF were 32.9%, 31.8% and 29.1%, respectively. HFmrEF patients had a significantly lower overall mortality rate compared to HFrEF patients (adjusted hazard ratio [HR] 0.89, 95% confidence interval [CI] 0.83-0.95; P < 0.001) and a significantly higher overall mortality rate (adjusted HR 1.25, 95% CI 1.17-1.33; P < 0.001) compared to HFpEF patients. This was similarly seen with cardiovascular mortality and HF hospitalisations, with the exception of similar HF hospitalisations between HFmrEF and HFpEF patients.

CONCLUSION

HFmrEF patients account for a significant burden of patients with HF. HFmrEF represents a distinct HF phenotype with high atherosclerotic burden and clinical outcomes saddled in between those of HFrEF and HFpEF. Further therapeutic studies to guide management of this challenging group of patients are warranted.

Real-World Clinical Burden of Newly Diagnosed Heart failure in Thai Patients

INTRODUCTION

There are limited data on the burden of newly diagnosed patients with heart failure (HF) in Thailand. Thus, this study aimed to fully understand the hospitalization, rehospitalization, mortality rates, demographics and characteristics, and quality of care in these patients.

METHOD

A retrospective review of all eligible adult patients' medical records from 2018 and 2019 was conducted at five hospitals. The patients were newly diagnosed with HF, as indicated by the International Classification of Diseases (ICD)-10 code "I50." Descriptive statistics was used to investigate patients' hospital burden and clinical outcome data.

RESULTS

There were 1134 patients newly diagnosed with HF, classified as HF with reduced ejection fraction (HFrEF), HF with preserved ejection fraction (HFpEF), and HF with mildly reduced ejection fraction (HFmrEF) (44.0, 40.0, and 16.0%, respectively). The male-to-female ratios in HFmrEF and HFpEF were similar. In contrast, the proportion of men with HFrEF was greater. The mean age of all patients was 66.0 years. The hospitalization rate was 1.3. Rehospitalization rates for HF-related issues were 0.1, 0.2, 0.4, and 0.5 at 30 days, 60 days, 180 days, and 1 year, respectively. The percentage of deaths from all causes among these patients was 9.8%, while the percentage of deaths from cardiovascular-related causes was 8.5%. Only a small proportion of patients received a target dose of guideline-directed medical therapy (GDMT).

CONCLUSIONS

The study revealed that the characteristics, hospitalization rate for HF, and in-hospital mortality rate among newly diagnosed patients with HF were higher compared to similar studies conducted in Thailand and other countries. Moreover, a high quality of care is needed to improve the morbidity and mortality associated with HF in Thailand.

Heart failure, the global pandemic: A call to action consensus statement from the global presidential conclave at the platinum jubilee conference of cardiological society of India 2023

Heart failure (HF) is emerging as a major public health problem both in high- and low - income countries. The mortality and morbidity due to HF is substantially higher in low-middle income countries (LMICs). Accessibility, availability and affordability issues affect the guideline directed therapy implementation in HF care in those countries. This call to action urges all those concerned to initiate preventive strategies as early as possible, so that we can reduce HF-related morbidity and mortality. The most important step is to have better prevention and treatment strategies for diseases such as hypertension, ischemic heart disease (IHD), type-2 diabetes, and rheumatic heart disease (RHD) which predispose to the development of HF. Setting up dedicated HF-clinics manned by HF Nurses, can help in streamlining HF care. Subsidized in-patient care, financial assistance for device therapy, use of generic medicines (including polypill strategy) will be helpful, along with the use of digital technologies.

Heart failure with mildly reduced and preserved ejection fraction: A review of disease burden and remaining unmet medical needs within a new treatment landscape

This review provides a comprehensive overview of heart failure with mildly reduced and preserved ejection fraction (HFmrEF/HFpEF), including its definition, diagnosis, and epidemiology; clinical, humanistic, and economic burdens; current pharmacologic landscape in key pharmaceutical markets; and unmet needs to identify key knowledge gaps. We conducted a targeted literature review in electronic databases and prioritized articles with valuable insights into HFmrEF/HFpEF. Overall, 27 randomized controlled trials (RCTs), 66 real-world evidence studies, 18 clinical practice guidelines, and 25 additional publications were included. Although recent heart failure (HF) guidelines set left ventricular ejection fraction thresholds to differentiate categories, characterization and diagnosis criteria vary because of the incomplete disease understanding. Recent epidemiological data are limited and diverse. Approximately 50% of symptomatic HF patients have HFpEF, more common than HFmrEF. Prevalence varies with country because of differing definitions and study characteristics, making prevalence interpretation challenging. HFmrEF/HFpEF has considerable mortality risk, and the mortality rate varies with study and patient characteristics and treatments. HFmrEF/HFpEF is associated with considerable morbidity, poor patient outcomes, and common comorbidities. Patients require frequent hospitalizations; therefore, early intervention is crucial to prevent disease burden. Recent RCTs show promising results like risk reduction of composite cardiovascular death or HF hospitalization. Costs data are scarce, but the economic burden is increasing. Despite new drugs, unmet medical needs requiring new treatments remain. Thus, HFmrEF/HFpEF is a growing global healthcare concern. With improving yet incomplete understanding of this disease and its promising treatments, further research is required for better patient outcomes.

Comorbidity of patients with noncommunicable diseases in general practice. Eurasian guidelines

Создание руководства поддержано Советом по терапевтическим наукам отделения клинической медицины Российской академии наук.

Distinguishing heart failure with reduced ejection fraction from heart failure with preserved ejection fraction: A phenomics approach

AIM

Pathophysiological differences between patients with heart failure with preserved (HFpEF) and reduced (HFrEF) ejection fraction (EF) remain unclear. Therefore we used a phenomics approach, integrating selected proteomics data with patient characteristics and cardiac structural and functional parameters, to get insight into differential pathophysiological mechanisms and identify potential treatment targets.

METHODS AND RESULTS

We report data from a representative subcohort of the prospective Singapore Heart Failure Outcomes and Phenotypes (SHOP), including patients with HFrEF (EF <40%, n = 217), HFpEF (EF ≥50%, n = 213), and age- and sex-matched controls without HF (n = 216). We measured 92 biomarkers using a proximity extension assay and assessed cardiac structure and function in all participants using echocardiography. We used multi-block projection to latent structure analysis to integrate clinical, echocardiographic, and biomarker variables. Candidate biomarker targets were cross-referenced with small-molecule and drug databases. The total cohort had a median age of 65 years (interquartile range 60-71), and 50% were women. Protein profiles strongly discriminated patients with HFrEF (area under the curve [AUC] = 0.89) and HFpEF (AUC = 0.94) from controls. Phenomics analyses identified unique druggable inflammatory markers in HFpEF from the tumour necrosis factor receptor superfamily (TNFRSF), which were positively associated with hypertension, diabetes, and increased posterior and relative wall thickness. In HFrEF, interleukin (IL)-8 and IL-6 were possible targets related to lower EF and worsening renal function.

CONCLUSION

We identified pathophysiological mechanisms related to increased cardiac wall thickness parameters and potentially druggable inflammatory markers from the TNFRSF in HFpEF.

The role of multimorbidity in patients with heart failure across the left ventricular ejection fraction spectrum: Data from the Swedish Heart Failure Registry

AIMS

The aim of this analysis was to provide data on the overall comorbidity burden, both cardiovascular (CV) and non-CV, in a large real-world heart failure (HF) population across the ejection fraction (EF).

METHODS AND RESULTS

Patients with HF from the Swedish HF Registry between 2000 and 2021 were included. Of 91 463 patients (median age 76 years [interquartile range 67-82]), 98% had at least one among the 17 explored comorbidities (94% at least one CV and 85% at least one non-CV comorbidity). All comorbidities, except for coronary artery disease (CAD), were more frequent in HF with preserved EF (HFpEF). Patients with multiple comorbidities were older, more likely female, inpatients, with HFpEF, worse New York Heart Association class and higher N-terminal pro-B-type natriuretic peptide levels. In a multivariable Cox model, 12 comorbidities were independently associated with a higher risk of death from any cause. The highest risk was associated with dementia (hazard ratio [HR] 1.55, 95% confidence interval [CI] 1.45-1.65), chronic kidney disease (HR 1.37, 95% CI 1.34-1.41), chronic obstructive pulmonary disease (HR 1.32, 95% CI 1.28-1.35). Obesity was associated with a lower risk of all-cause death (HR 0.81, 95% CI 0.79-0.84). CAD and valvular heart disease were associated with a higher risk of all-cause and CV mortality, but not non-CV mortality, whereas cancer and musculo-skeletal disease increased the risk of non-CV mortality. A significant interaction with EF was observed for several comorbidities. Occurrence of CV and non-CV outcomes was related to the number of CV and non-CV comorbidities, respectively.

CONCLUSION

The burden of both CV and non-CV comorbidities was high in HF regardless of EF, but overall higher in HFpEF. Multimorbidity was associated with a high risk of death with a different burden on CV or non-CV outcomes.

Abdul Kader MA, Loch A, Mahendran K, Ramli AW, Ong TK, Mohd Amin NH, Lee CY, Che Hassan HH, Zainal Abidin SK, Liew HB, Ho WS, Mohd Ghazi A. Characteristics of patients admitted with heart failure: Insights from the first Malaysian Heart Failure Registry

AIMS

Heart failure (HF) is a growing health problem, yet there are limited data on patients with HF in Malaysia. The Malaysian Heart Failure (MY-HF) Registry aims to gain insights into the epidemiology, aetiology, management, and outcome of Malaysian patients with HF and identify areas for improvement within the national HF services.

METHODS AND RESULTS

The MY-HF Registry is a 3-year prospective, observational study comprising 2717 Malaysian patients admitted for acute HF. We report the description of baseline data at admission and outcomes of index hospitalization of these patients. The mean age was 60.2 ± 13.6 years, 66.8% were male, and 34.3% had de novo HF. Collectively, 55.7% of patients presented with New York Heart Association (NYHA) Class III or IV; ischaemic heart disease was the most frequent aetiology (63.2%). Most admissions (87.3%) occurred via the emergency department, with 13.7% of patients requiring intensive care, and of these, 21.8% needed intubation. The proportion of patients receiving guideline-directed medical therapy increased at discharge (84.2% vs. 93.6%). The median length of stay (LOS) was 5 days, and in-hospital mortality was 2.9%. Predictors of LOS and/or in-hospital mortality were age, NYHA class, estimated glomerular filtration rate, and comorbid anaemia. LOS and in-hospital mortality were similar regardless of ejection fraction.

CONCLUSIONS

The MY-HF Registry showed that the HF population in Malaysia is younger, predominantly male, and ischaemic-driven and has good prospects with hospitalization for optimization of treatment. These findings suggest a need to reassess current clinical practice and guide resource allocation to improve patient outcomes.

Learning prevalent patterns of co-morbidities in multichronic patients using population-based healthcare data

The prevalence of longstanding chronic diseases has increased worldwide, along with the average age of the population. As a result, an increasing number of people is affected by two or more chronic conditions simultaneously, and healthcare systems are facing the challenge of treating multimorbid patients effectively. Current therapeutic strategies are suited to manage each chronic condition separately, without considering the whole clinical condition of the patient. This approach may lead to suboptimal clinical outcomes and system inefficiencies (e.g. redundant diagnostic tests and inadequate drug prescriptions). We develop a novel methodology based on the joint implementation of data reduction and clustering algorithms to identify patterns of chronic diseases that are likely to co-occur in multichronic patients. We analyse data from a large adult population of multichronic patients living in Tuscany (Italy) in 2019 which was stratified by sex and age classes. Results demonstrate that (i) cardio-metabolic, endocrine, and neuro-degenerative diseases represent a stable pattern of multimorbidity, and (ii) disease prevalence and clustering vary across ages and between women and men. Identifying the most common multichronic profiles can help tailor medical protocols to patients' needs and reduce costs. Furthermore, analysing temporal patterns of disease can refine risk predictions for evolutive chronic conditions.

Effect of frailty on medication deviation during the hospital-family transition period in older patients with cardiovascular disease: An observational study

Studies have shown that frailty increases cardiovascular disease (CVD) incidence in older patients and is associated with poor patient prognosis. However, the relationship between medication deviation (MD) and frailty remains unclear. This study aimed to explore the influence of frailty on MD during the hospital-family transition period among older patients with CVD. Between February 2022 and February 2023, 231 older people CVD patients were selected from a class III hospital in Nantong City using a multi-stage sampling method. A general information questionnaire was used to collect the socio-demographic characteristics of the participants prior to discharge, the frailty assessment scale was used to assess the participants frailty, and a medication deviation instrument was used to assess the participants MD on the 10th day after discharge. Propensity score matching was used to examine the effect of frailty on MD in older patients with CVD during the hospital-family transition period. The incidences of frailty and MD were 32.9% (76/231) and 75.8% (175/231), respectively. After propensity score matching, the risk of MD in frail patients with CVD was 4.978 times higher than that in non-frail patients with CVD (95% CI: [1.616, 15.340]; P = .005). Incidences of frailty and MD during the hospital-family transition period are high in older patients with CVD, and frailty has an impact on MD. Medical staff in the ward should comprehensively examine older patients with CVD for frailty and actively promote quality medication management during the hospital-family transition period to reduce MD occurrence and delay disease progression.

Prevalence of cardiac abnormalities and heart failure in unselected out-patients with type 2 diabetes mellitus and associated clinical factors: Real-world evidence from an Indian registry

OBJECTIVE

Type 2 diabetes mellitus (T2DM) is known to be associated with development of left ventricular (LV) dysfunction and heart failure (HF). The study aimed to determine the prevalence of LV dysfunction and HF in unselected out-patients with T2DM with no previous cardiac history and to correlate LV dysfunction and HF with demographic and comorbid characteristics.

METHODS

This cross-sectional study conducted at 27 centers in India captured demographic and clinical data through electronic case record forms. B-type natriuretic peptide of >105 pg/mL was used to diagnose HF and two-dimensional echocardiography was used to assess LV dysfunction.

RESULTS

Of the 615 patients, 54.3 % (n = 334) were males; mean age was 57.4 ± 10.48 years. More than one-third of the patients had T2DM duration of >10 years (n = 238; 38.7 %), with hypertension as the most prevalent comorbidity (n = 372, 78.6 %). Approximately 61.3 % of the patients had LV hypertrophy. The mean LV mass was 135.0 ± 56.16 g (95 % CI 130.28, 139.70). The prevalence of any type of LV dysfunction, including systolic or diastolic dysfunction and HF was 55 % (95 % CI 51.0, 59.0) and 10 % (95 % CI 7.0, 12.0), respectively. A negligible but statistically significant correlation was observed between LV dysfunction and T2DM duration (p = 0.011), alongside HF and age (p < 0.0001).

CONCLUSION

Real-world data from this registry from India demonstrates a substantial burden of LV dysfunction and HF in individuals with T2DM in India. It is imperative to formulate strategies for early identification of LV dysfunction in individuals with T2DM for prevention and consequent management of HF.

Discovering Distinct Phenotypical Clusters in Heart Failure Across the Ejection Fraction Spectrum: a Systematic Review

REVIEW PURPOSE

This systematic review aims to summarise clustering studies in heart failure (HF) and guide future clinical trial design and implementation in routine clinical practice.

FINDINGS

34 studies were identified (n = 19 in HF with preserved ejection fraction (HFpEF)). There was significant heterogeneity invariables and techniques used. However, 149/165 described clusters could be assigned to one of nine phenotypes: 1) young, low comorbidity burden; 2) metabolic; 3) cardio-renal; 4) atrial fibrillation (AF); 5) elderly female AF; 6) hypertensive-comorbidity; 7) ischaemic-male; 8) valvular disease; and 9) devices. There was room for improvement on important methodological topics for all clustering studies such as external validation and transparency of the modelling process. The large overlap between the phenotypes of the clustering studies shows that clustering is a robust approach for discovering clinically distinct phenotypes. However, future studies should invest in a phenotype model that can be implemented in routine clinical practice and future clinical trial design. HF = heart failure, EF = ejection fraction, HFpEF = heart failure with preserved ejection fraction, HFrEF = heart failure with reduced ejection fraction, CKD = chronic kidney disease, AF = atrial fibrillation, IHD = ischaemic heart disease, CAD = coronary artery disease, ICD = implantable cardioverter-defibrillator, CRT = cardiac resynchronization therapy, NT-proBNP = N-terminal pro b-type natriuretic peptide, BMI = Body Mass Index, COPD = Chronic obstructive pulmonary disease.

Recent successes in heart failure treatment

Remarkable recent advances have revolutionized the field of heart failure. Survival has improved among individuals with heart failure and a reduced ejection fraction and for the first time, new therapies have been shown to improve outcomes across the entire ejection fraction spectrum of heart failure. Great strides have been taken in the treatment of specific cardiomyopathies such as cardiac amyloidosis and hypertrophic cardiomyopathy, whereby conditions once considered incurable can now be effectively managed with novel genetic and molecular approaches. Yet there remain substantial residual unmet needs in heart failure. The translation of successful clinical trials to improved patient outcomes is limited by large gaps in implementation of care, widespread lack of disease awareness and poor understanding of the socioeconomic determinants of outcomes and how to address disparities. Ongoing clinical trials, advances in phenotype segmentation for precision medicine and the rise in technology solutions all offer hope for the future.

Penalized Model-Based Unsupervised Phenomapping Unravels Distinctive HFrEF Phenotypes With Improved Outcomes Discrimination From Sacubitril/Valsartan Treatment Independent of MAGGIC Score

Background The angiotensin receptor-neprilysin inhibitor (LCZ696) has emerged as a promising pharmacological intervention against renin-angiotensin system inhibitor in reduced ejection fraction heart failure (HFrEF). Whether the therapeutic benefits may vary among heterogeneous HFrEF subgroups remains unknown. Methods and Results This study comprised a pooled 2-center analysis including 1103 patients with symptomatic HFrEF with LCZ696 use and another 1103 independent HFrEF control cohort (with renin-angiotensin system inhibitor use) matched for age, sex, left ventricular ejection fraction, and comorbidity conditions. Three main distinct phenogroup clusterings were identified from unsupervised machine learning using 29 clinical variables: phenogroup 1 (youngest, relatively lower diabetes prevalence, highest glomerular filtration rate with largest left ventricular size and left ventricular wall stress); phenogroup 2 (oldest, lean, highest diabetes and vascular diseases prevalence, lowest highest glomerular filtration rate with smallest left ventricular size and mass), and phenogroup 3 (lowest clinical comorbidity with largest left ventricular mass and highest hypertrophy prevalence). During the median 1.74-year follow-up, phenogroup assignment provided improved prognostic discrimination beyond Meta-Analysis Global Group in Chronic Heart Failure risk score risk score (all net reclassification index P<0.05) with overall good calibrations. While phenogroup 1 showed overall best clinical outcomes, phenogroup 2 demonstrated highest cardiovascular death and worst renal end point, with phenogroup 3 having the highest all-cause death rate and HF hospitalization among groups, respectively. These findings were broadly consistent when compared with the renin-angiotensin system inhibitor control as reference group. Conclusions Phenomapping provided novel insights on unique characteristics and cardiac features among patients with HFrEF with sacubitril/valsartan treatment. These findings further showed potentiality in identifying potential sacubitril/valsartan responders and nonresponders with improved outcome discrimination among patients with HFrEF beyond clinical scoring.

The Relationship between Nocturnal Dipping Status, Morning Blood Pressure Surge, and Hospital Admissions in Patients with Systolic Heart Failure

BACKGROUND

Hypertension is a known risk factor for developing heart failure. However, there is limited data to investigate the association between morning blood pressure surge (MBPS), dipping status, echocardiographic parameters, and hospital admissions in patients with systolic heart failure.

OBJECTIVES

To evaluate the relationship between morning blood pressure surge, non-dipper blood pressure pattern, echocardiographic parameters, and hospital admissions in patients with systolic heart failure.

METHODS

We retrospectively analyzed data from 206 consecutive patients with hypertension and a left ventricular ejection fraction below 40%. We divided the patients into two groups according to 24-hour ambulatory blood pressure monitoring (ABPM) results: dippers (n=110) and non-dippers (n=96). Morning blood pressure surge was calculated. Echocardiographic findings and hospital admissions during follow-up were noted. Statistical significance was defined as p < 0.05.

RESULTS

The study group comprised 206 patients with a male predominance and mean age of 63.5 ± 16.1 years. The non-dipper group had significantly more hospital admissions compared to dippers. There was a positive correlation between MBPS and left atrial volume index (r=0.331, p=0.001), the ratio between early mitral inflow velocity and flow propagation velocity (r= 0.326, p=0.001), and the ratio between early mitral inflow velocity and mitral annular early diastolic velocity (E/Em) (r= 0.314, p=0.001). Non-dipper BP, MBPS, and E/Em pattern were found to be independently associated with increased hospital admissions.

CONCLUSION

MBPS is associated with diastolic dysfunction and may be a sensitive predictor of hospital admission in patients with systolic heart failure.

Identifying high risk clinical phenogroups of pulmonary hypertension through a clustering analysis

INTRODUCTION

The classification and management of pulmonary hypertension (PH) is challenging due to clinical heterogeneity of patients. We sought to identify distinct multimorbid phenogroups of patients with PH that are at particularly high-risk for adverse events.

METHODS

A hospital-based cohort of patients referred for right heart catheterization between 2005-2016 with PH were included. Key exclusion criteria were shock, cardiac arrest, cardiac transplant, or valvular surgery. K-prototypes was used to cluster patients into phenogroups based on 12 clinical covariates.

RESULTS

Among 5208 patients with mean age 64±12 years, 39% women, we identified 5 distinct multimorbid PH phenogroups with similar hemodynamic measures yet differing clinical outcomes: (1) "young men with obesity", (2) "women with hypertension", (3) "men with overweight", (4) "men with cardiometabolic and cardiovascular disease", and (5) "men with structural heart disease and atrial fibrillation." Over a median follow-up of 6.3 years, we observed 2182 deaths and 2002 major cardiovascular events (MACE). In age- and sex-adjusted analyses, phenogroups 4 and 5 had higher risk of MACE (HR 1.68, 95% CI 1.41-2.00 and HR 1.52, 95% CI 1.24-1.87, respectively, compared to the lowest risk phenogroup 1). Phenogroup 4 had the highest risk of mortality (HR 1.26, 95% CI 1.04-1.52, relative to phenogroup 1).

CONCLUSIONS

Cluster-based analyses identify patients with PH and specific comorbid cardiometabolic and cardiovascular disease burden that are at highest risk for adverse clinical outcomes. Interestingly, cardiopulmonary hemodynamics were similar across phenogroups, highlighting the importance of multimorbidity on clinical trajectory. Further studies are needed to better understand comorbid heterogeneity among patients with PH.

Phenotype-Specific Outcome and Treatment Response in Heart Failure with Preserved Ejection Fraction with Comorbid Hypertension and Diabetes: A 12-Month Multicentered Prospective Cohort Study

Despite evidence of SGLT2 inhibitors in improving cardiovascular outcomes of heart failure with preserved ejection fraction (HFpEF), the heterogenous mechanism and characteristic multimorbidity of HFpEF require a phenotypic approach. Metabolic phenotype, one common HFpEF phenotype, has various presentations and prognoses worldwide. We aimed to identify different phenotypes of hypertensive-diabetic HFpEF, their phenotype-related outcomes, and treatment responses. The primary endpoint was time to the first event of all-cause mortality or hospitalization for heart failure (HHF). Among 233 recruited patients, 24.9% experienced primary outcomes within 12 months. A total of 3.9% was lost to follow-up. Three phenotypes were identified. Phenotype 1 (n = 126) consisted of lean, elderly females with chronic kidney disease, anemia, and concentric hypertrophy. Phenotype 2 (n = 62) included younger males with coronary artery disease. Phenotype 3 (n = 45) comprised of obese elderly with atrial fibrillation. Phenotype 1 and 2 reported higher primary outcomes than phenotype 3 (p = 0.002). Regarding treatment responses, SGLT2 inhibitor was associated with fewer primary endpoints in phenotype 1 (p = 0.003) and 2 (p = 0.001). RAAS inhibitor was associated with fewer all-cause mortality in phenotype 1 (p = 0.003). Beta blocker was associated with fewer all-cause mortality in phenotype 1 (p = 0.024) and fewer HHF in phenotype 2 (p = 0.011). Our pioneering study supports the personalized approach to optimize HFpEF management in hypertensive-diabetic patients.

Phenomics and Robust Multiomics Data for Cardiovascular Disease Subtyping

The complex landscape of cardiovascular diseases encompasses a wide range of related pathologies arising from diverse molecular mechanisms and exhibiting heterogeneous phenotypes. This variety of manifestations poses significant challenges in the development of treatment strategies. The increasing availability of precise phenotypic and multiomics data of cardiovascular disease patient populations has spurred the development of a variety of computational disease subtyping techniques to identify distinct subgroups with unique underlying pathogeneses. In this review, we outline the essential components of computational approaches to select, integrate, and cluster omics and clinical data in the context of cardiovascular disease research. We delve into the challenges faced during different stages of the analysis, including feature selection and extraction, data integration, and clustering algorithms. Next, we highlight representative applications of subtyping pipelines in heart failure and coronary artery disease. Finally, we discuss the current challenges and future directions in the development of robust subtyping approaches that can be implemented in clinical workflows, ultimately contributing to the ongoing evolution of precision medicine in health care.

Trajectories of renal biomarkers and new-onset heart failure in the general population: Findings from the PREVEND study

AIMS

Renal dysfunction is one of the most critical risk factors for developing heart failure (HF). However, the association between repeated measures of renal function and incident HF remains unclear. Therefore, this study investigated the longitudinal trajectories of urinary albumin excretion (UAE) and serum creatinine and their association with new-onset HF and all-cause mortality.

METHODS AND RESULTS

Using group-based trajectory analysis, we estimated trajectories of UAE and serum creatinine in 6881 participants from the Prevention of Renal and Vascular End-stage Disease (PREVEND) study and their association with new-onset HF and all-cause death during the 11-years of follow-up. Most participants had stable low UAE or serum creatinine. Participants with persistently higher UAE or serum creatinine were older, more often men, and more often had comorbidities, such as diabetes, a previous myocardial infarction or dyslipidaemia. Participants with persistently high UAE had a higher risk of new-onset HF or all-cause mortality, whereas stable serum creatinine trajectories showed a linear association for new-onset HF and no association with all-cause mortality.

CONCLUSION

Our population-based study identified different but often stable longitudinal patterns of UAE and serum creatinine. Patients with persistently worse renal function, such as higher UAE or serum creatinine, were at a higher risk of HF or mortality.

Fat Mass is Associated with Subclinical Left Ventricular Systolic Dysfunction in Patients with Type 2 Diabetes Mellitus Without Established Cardiovascular Diseases

INTRODUCTION

Left ventricular global longitudinal strain (GLS) is considered to be the first marker of diabetes mellitus-related subclinical cardiac dysfunction, but whether it is attributable to fat mass and distribution remains uncertain. In this study, we explored whether fat mass, especially fat mass in the android area, is associated with subclinical systolic dysfunction before the onset of cardiac disease.

METHODS

We conducted a single-center prospective cross-sectional study between November 2021 and August 2022 on inpatients of the Department of Endocrinology, Nanjing Drum Tower Hospital. We included 150 patients aged 18-70 years with no signs, symptoms, or history of clinical cardiac disease. Patients were evaluated with speckle tracking echocardiography and dual energy X-ray absorptiometry. The cutoff values for subclinical systolic dysfunction were set at a global longitudinal strain (GLS) < 18%.

RESULTS

After adjusting for sex and age, patients with GLS < 18% had a higher mean (± standard deviation) fat mass index (8.06 ± 2.39 vs. 7.10 ± 2.09 kg/m², p = 0.02), higher mean trunk fat mass (14.9 ± 4.9 vs. 12.8 ± 4.3 kg, p = 0.01), and higher android fat mass (2.57 ± 1.02 vs. 2.18 ± 0.86 kg, p = 0.02) than those in the GLS ≥ 18%. Partial correlation analysis showed that the fat mass index, truck fat mass, and android fat mass were negatively correlated with GLS after adjusting for sex and age (all p < 0.05). Adjusted for traditional cardiovascular metabolic factors, fat mass index (odds ratio [OR] 1.27, 95% confidence interval [CI] 1.05-1.55, p = 0.02), trunk fat mass (OR 1.13, 95% CI 1.03-1.24, p = 0.01), and android fat mass (OR 1.77, 95% CI 1.16-2.82, p = 0.01) were independent risk factors for GLS < 18%.

CONCLUSION

Among patients with type 2 diabetes mellitus without established clinical cardiac disease, fat mass, especially android fat mass, was associated with subclinical systolic dysfunction independently of age and sex.

Impact of multimorbidity on mortality in heart failure with reduced ejection fraction: which comorbidities matter most? An analysis of PARADIGM-HF and ATMOSPHERE

AIMS

Multimorbidity, the coexistence of two or more chronic conditions, is synonymous with heart failure (HF). How risk related to comorbidities compares at individual and population levels is unknown. The aim of this study is to examine the risk related to comorbidities, alone and in combination, both at individual and population levels.

METHODS AND RESULTS

Using two clinical trials in HF - the Prospective comparison of ARNI (Angiotensin Receptor-Neprilysin Inhibitor) with ACEI (Angiotensin-Converting Enzyme Inhibitor) to Determine Impact on Global Mortality and morbidity in HF trial (PARADIGM-HF) and the Aliskiren Trial to Minimize Outcomes in Patients with Heart Failure trials (ATMOSPHERE) - we identified the 10 most common comorbidities and examined 45 possible pairs. We calculated population attributable fractions (PAF) for all-cause death and relative excess risk due to interaction with Cox proportional hazard models. Of 15 066 patients in the study, 14 133 (93.7%) had at least one and 11 867 (78.8%) had at least two of the 10 most prevalent comorbidities. The greatest individual risk among pairs was associated with peripheral artery disease (PAD) in combination with stroke (hazard ratio [HR] 1.73; 95% confidence interval [CI] 1.28-2.33) and anaemia (HR 1.71; 95% CI 1.39-2.11). The combination of chronic kidney disease (CKD) and hypertension had the highest PAF (5.65%; 95% CI 3.66-7.61). Two pairs demonstrated significant synergistic interaction (atrial fibrillation with CKD and coronary artery disease, respectively) and one an antagonistic interaction (anaemia and obesity).

CONCLUSIONS

In HF, the impact of multimorbidity differed at the individual patient and population level, depending on the prevalence of and the risk related to each comorbidity, and the interaction between individual comorbidities. Patients with coexistent PAD and stroke were at greatest individual risk whereas, from a population perspective, coexistent CKD and hypertension mattered most.

Phenotyping of Elderly Patients With Heart Failure Focused on Noncardiac Conditions: A Latent Class Analysis From a Multicenter Registry of Patients Hospitalized With Heart Failure

Background The burden of noncardiovascular conditions is becoming increasingly prevalent in patients with heart failure (HF). We aimed to identify novel phenogroups incorporating noncardiovascular conditions to facilitate understanding and risk stratification in elderly patients with HF. Methods and Results Data from a total of 1881 (61.2%) patients aged ≥65 years were extracted from a prospective multicenter registry of patients hospitalized for acute HF (N=3072). We constructed subgroups of patients with HF with preserved ejection fraction (HFpEF; N=826, 43.9%) and those with non-HFpEF (N=1055, 56.1%). Latent class analysis was performed in each subgroup using 17 variables focused on noncardiovascular conditions (including comorbidities, Clinical Frailty Scale, and Geriatric Nutritional Risk Index). The latent class analysis revealed 3 distinct clinical phenogroups in both HFpEF and non-HFpEF subgroups: (1) robust physical and nutritional status (Group 1: HFpEF, 41.2%; non-HFpEF, 46.0%); (2) multimorbid patients with renal impairment (Group 2: HFpEF, 40.8%; non-HFpEF, 41.9%); and (3) malnourished patients (Group 3: HFpEF, 18.0%; non-HFpEF, 12.1%). After multivariable adjustment, compared with Group 1, patients in Groups 2 and 3 had a higher risk for all-cause death over the 1-year postdischarge period (hazard ratio [HR], 2.79 [95% CI, 1.64-4.81] and HR, 2.73 [95% CI, 1.39-5.35] in HFpEF; HR, 1.96 [95% CI, 1.22-3.14] and HR, 2.97 [95% CI, 1.64-5.38] in non-HFpEF; respectively). Conclusions In elderly patients with HF, the phenomapping focused on incorporating noncardiovascular conditions identified 3 phenogroups, each representing distinct clinical outcomes, and the discrimination pattern was similar for both patients with HFpEF and non-HFpEF. This classification provides novel risk stratification and may aid in clinical decision making.

Heart Failure and Multimorbidity in Asia

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 patients with HF are almost a decade younger than Western Europe and North American patients. However, over two in three patients have multimorbidity. Comorbidities usually cluster due to the close and complex links between chronic medical conditions. Elucidating these links may guide public health policies to address risk factors. In Asia, barriers in treating comorbidities at the patient, healthcare system and national level hamper preventative efforts. Asian patients with HF are younger yet have a higher burden of comorbidities than Western patients. A better understanding of the unique co-occurrence of medical conditions in Asia can improve the prevention and treatment of HF.

Management, clinical outcomes, and its predictors among heart failure patients admitted to tertiary care hospitals in Ethiopia: prospective observational study

BACKGROUND

Heart failure is a global pandemic, as it affects approximately 64.34 million people worldwide with a $346.17 billion global economic burden. The prevalence of heart failure has increased from 43.4 to 46.5% in the last 10 years in lower and middle-income countries. Most of the studies conducted in Ethiopia were retrospective cross-sectional, with limited study participants, and conducted in a single setting that commonly addresses the prevalence and pattern of heart failure rather than clinical outcome, associated factors, and specific management in different areas. Hence, this study aimed to assess management, clinical outcomes and their predictors among heart failure patients admitted to tertiary care hospitals in Ethiopia.

METHODS

A prospective observational study design was conducted on heart failure patients admitted at two tertiary care hospitals in Ethiopia from September 2020 to May 2021. Using semi-structured questionnaires relevant data were collected from patients' medical records and face-to-face interviewing. Data were analyzed using SPSS version 23.0. A multivariate Cox regression model was performed to identify independent predictors of 90-day all-cause mortality. Variables with P values < 0.05 were considered statistically significant.

RESULTS

Out of 283 patients enrolled in this study, 52.3% were male and the mean (± SD) age was 52.4 ± 17.9 years. The most common medications prescribed during hospitalization and discharge were diuretics (98.9% vs 95.6%), angiotensin I converting enzyme inhibitors/angiotensin II receptor blockers (48.8% vs 67.3%), and beta-blockers (46.6% vs 64.7%), respectively. In the present study, the 90-day all-cause mortality was 10.2%. Hypertension (HR = 3.7, 95% CI 1.2-11.6), cardiogenic shock (HR = 8.7, 95% CI 3.2-20.8), alcohol drinking (HR = 2.8, 95% CI 1.1-7.8), absence of angiotensin I converting enzyme inhibitors/angiotensin II receptor blockers (HR = 0.02, 95% CI 0.0-0.2), and reduced ejection fraction (HR = 1.5, 95% CI 1.1-3.8) were predictors of 90-day all-cause mortality.

CONCLUSION

High 90-day all-cause mortality was observed among heart failure patients in the present study. In the current study, the majority of heart failure patients were treated with diuretics. Alcohol drinking, hypertension, cardiogenic shock, reduced ejection fraction, and absence of angiotensin I converting enzyme inhibitors/angiotensin II receptor blockers drugs were predictors of poor treatment outcomes for whom restriction of alcohol consumption, early management of hypertension, reduced ejection fraction, cardiogenic shock, and providing angiotensin I converting enzyme inhibitors/angiotensin II receptor blockers drugs for all heart failure patients would be recommended to improve these poor treatment outcomes.

Comorbidities complicating heart failure: changes over the last 15 years

AIMS

Management of comorbidities represents a critical step in optimal treatment of heart failure (HF) patients. However, minimal attention has been paid whether comorbidity burden and their prognostic value changes over time. Therefore, we examined the association between comorbidities and clinical outcomes in HF patients between 2002 and 2017.

METHODS AND RESULTS

The 2002-HF cohort consisted of patients from The Coordinating Study Evaluating Outcomes of Advising and Counseling in Heart Failure (COACH) trial (n = 1,032). The 2017-HF cohort were outpatient HF patients enrolled after hospitalization for HF in a tertiary referral academic hospital (n = 382). Kaplan meier and cox regression analyses were used to assess the association of comorbidities with HF hospitalization and all-cause mortality. Patients from the 2017-cohort were more likely to be classified as HF with preserved ejection fraction (24 vs 15%, p < 0.001), compared to patients from the 2002-cohort. Comorbidity burden was comparable between both cohorts (mean of 3.9 comorbidities per patient) and substantially increased with age. Higher comorbidity burden was significantly associated with a comparable increased risk for HF hospitalization and all-cause mortality (HR 1.12 [1.02-1.22] and HR 1.18 [1.05-1.32]), in the 2002- and 2017-cohort respectively. When assessing individual comorbidities, obesity yielded a statistically higher prognostic effect on outcome in the 2017-cohort compared to the 2002-HF cohort (p for interaction 0.026).

CONCLUSION

Despite major advances in HF treatment over the past decades, comorbidity burden remains high in HF and influences outcome to a large extent. Obesity emerges as a prominent comorbidity, and efforts should be made for prevention and treatment. Created with BioRender.com.

Sodium-Glucose Cotransporter 2 Inhibitors and the Risk of Pneumonia and Septic Shock

CONTEXT

Individuals with type 2 diabetes mellitus (DM) have an increased risk of pneumonia and septic shock. Traditional glucose-lowering drugs have recently been found to be associated with a higher risk of infections. It remains unclear whether sodium-glucose cotransporter 2 inhibitors (SGLT2is), which have pleiotropic/anti-inflammatory effects, may reduce the risk of pneumonia and septic shock in DM.

METHODS

MEDLINE, Embase, and ClinicalTrials.gov were searched from inception up to May 19, 2022, for randomized, placebo-controlled trials of SGLT2i that included patients with DM and reported outcomes of interest (pneumonia and/or septic shock). Study selection, data extraction, and quality assessment (using the Cochrane Risk of Bias Assessment Tool) were conducted by independent authors. A fixed-effects model was used to pool the relative risk (RRs) and 95% CI across trials.

RESULTS

Out of 4568 citations, 26 trials with a total of 59 264 patients (1.9% developed pneumonia and 0.2% developed septic shock) were included. Compared with placebo, SGLT2is significantly reduced the risk of pneumonia (pooled RR 0.87, 95% CI 0.78-0.98) and septic shock (pooled RR 0.65, 95% CI 0.44-0.95). There was no significant heterogeneity of effect size among trials. Subgroup analyses according to the type of SGLT2i used, baseline comorbidities, glycemic control, duration of DM, and trial follow-up showed consistent results without evidence of significant treatment-by-subgroup heterogeneity (all Pheterogeneity > .10).

CONCLUSION

Among DM patients, SGLT2is reduced the risk of pneumonia and septic shock compared with placebo. Our findings should be viewed as hypothesis generating, with concepts requiring validation in future studies.

Worsening of Renal Function Among Hospitalized Patients With Acute Heart Failure: Phenotyping, Outcomes, and Predictors

OBJECTIVE

To define clinical phenotyping and its associated outcome of worsening of renal function (WRF) in hospitalized acute heart failure (AHF) patients.

PATIENTS AND METHODS

Latent class analysis was performed in 113 AHF patients who developed WRF within 72 hours in the DOSE (Diuretic Optimization Strategies Evaluation) trial (from March 2008 to November 2009) and ROSE-AHF (Renal Optimization Strategies Evaluation in Acute Heart Failure) trial (from September 2010 to March 2013) to identify potential WRF phenotypes. Clinical characteristics and outcome (in-hospital and post-discharge) were compared between different phenotypes.

RESULTS

Two WRF phenotypes were identified by latent class analysis, which we named WRF minimally responsive to diuretics (WRF-MRD) and WRF responsive to diuretics (WRF-RD). Among the population, 58 (9.5%) developed WRF-MRD and 55 (9.0%) developed WRF-RD. Patients with WRF-MRD had more comorbidities than WRF-RD. In WRF-MRD, there were an early increase in serum creatinine, a smaller amount of net fluid loss and weight loss, and a higher rate of worsening or persistent heart failure over 72 hours. In contrast, for those with WRF-RD, they had faster in-hospital net fluid loss and weight loss and a better 60-day survival after discharge even compared with patients without WRF (P=.004). Furthermore, baseline chronic obstructive pulmonary disease, diabetes, and cystatin C were independent predictors of WRF-MRD, whereas serum hemoglobin and sodium predicted WRF-RD.

CONCLUSIONS

Among hospitalized AHF patients, we identified two phenotypes of WRF with distinct response to heart failure treatment, predictors, and short-term prognosis after discharge. The results could help early differentiation of WRF phenotypes in clinical practice.

Impact of Non-cardiac Comorbidities on Long-Term Clinical Outcomes and Health Status After Acute Heart Failure in China

Background

Individual non-cardiac comorbidities are prevalent in HF; however, few studies reported how the aggregate burden of non-cardiac comorbidities affects long-term outcomes, and it is unknown whether this burden is associated with changes in health status.

Aims

To assess the association of the overall burden of non-cardiac comorbidities with clinical outcomes and quality of life (QoL) in patients hospitalized for heart failure (HF).

Methods

We prospectively enrolled patients hospitalized for HF from 52 hospitals in China. Eight key non-cardiac comorbidities [diabetes, chronic renal disease, chronic obstructive pulmonary disease (COPD), anemia, stroke, cancer, peripheral arterial disease (PAD), and liver cirrhosis] were included, and patients were categorized into four groups: none, one, two, and three or more comorbidities. We fitted Cox proportional hazards models to assess the burden of comorbidities on 1-year death and rehospitalization.

Results

Of the 4,866 patients, 25.3% had no non-cardiac comorbidity, 32.2% had one, 22.9% had two, and 19.6% had three or more in China. Compared with those without non-cardiac comorbidities, patients with three or more comorbidities had higher risks of 1-year all-cause death [heart rate, HR 1.89; 95% confidence interval (CI) 1.48–2.39] and all-rehospitalization (HR 1.35; 95%CI 1.15–1.58) after adjustment. Although all patients with HF experienced a longitudinal improvement in QoL in the 180 days after discharge, those with three or more non-cardiac comorbidities had an unadjusted 11.4 (95%CI −13.4 to −9.4) lower Kansas City Cardiomyopathy Questionnaire (KCCQ) scores than patients without comorbidities. This difference decreased to −6.4 (95%CI −8.6 to −4.2) after adjustment for covariates.

Conclusion

Among patients hospitalized with HF in this study, a higher burden of non-cardiac comorbidities was significantly associated with worse health-related QoL (HRQoL), increased risks of death, and rehospitalization post-discharge. The findings highlight the need to address the management of comorbidities effectively in standardized HF care.

Heart Failure: An Underappreciated Complication of Diabetes. A Consensus Report of the American Diabetes Association

Heart failure (HF) has been recognized as a common complication of diabetes, with a prevalence of up to 22% in individuals with diabetes and increasing incidence rates. Data also suggest that HF may develop in individuals with diabetes even in the absence of hypertension, coronary heart disease, or valvular heart disease and, as such, represents a major cardiovascular complication in this vulnerable population; HF may also be the first presentation of cardiovascular disease in many individuals with diabetes. Given that during the past decade, the prevalence of diabetes (particularly type 2 diabetes) has risen by 30% globally (with prevalence expected to increase further), the burden of HF on the health care system will continue to rise. The scope of this American Diabetes Association consensus report with designated representation from the American College of Cardiology is to provide clear guidance to practitioners on the best approaches for screening and diagnosing HF in individuals with diabetes or prediabetes, with the goal to ensure access to optimal, evidence-based management for all and to mitigate the risks of serious complications, leveraging prior policy statements by the American College of Cardiology and American Heart Association.

Phenotypes of heart failure with preserved ejection fraction and effect of spironolactone treatment

Aims

The aims of this study were to explore phenotypes of heart failure with preserved ejection fraction (HFpEF) and evaluate differential effects of spironolactone treatment.

Methods and results

A swap‐stepwise algorithm was used for variable selection. Latent class analysis based on 10 selected variables was employed in a derivative set of 1540 patients from the TOPCAT trial. Cox proportional hazard models were used to evaluate the prognoses and effects of spironolactone treatment. Three phenotypes of HFpEF were identified. Phenotype 1 was the youngest with low burden of co‐morbidities. Phenotype 2 was the oldest with high prevalence of atrial fibrillation, pacemaker implantation, and hypothyroidism. Phenotype 3 was mostly obese and diabetic with high burden of other co‐morbidities. Compared with phenotype 1, phenotypes 2 (hazard ratio [HR]: 1.46; 95% confidence interval [CI]: 1.14–1.89; P = 0.003) and 3 (HR: 2.35; 95% CI: 1.80–3.07; P < 0.001) were associated with higher risks of the primary composite outcome. Spironolactone treatment was associated with a reduced risk of the primary outcome only in phenotype 1 (HR: 0.63; 95% CI: 0.40–0.98; P = 0.042).

Conclusions

Three distinct HFpEF phenotypes were identified. Spironolactone treatment could improve clinical outcome in a phenotype of relatively young patients with low burden of co‐morbidities.

National trend in heart failure hospitalization and outcome under public health insurance system in Thailand 2008-2013

Background

There are limited data on the burden, characteristics, and outcomes of hospitalized heart failure (HF) patients in Thailand. The aim of this study was to investigate national trend in HF hospitalization rate, in-hospital and 1-year mortality rate, and rehospitalization rate in Thailand.

Methods

We analyzed the claims data of hospitalized patients obtained from the three major Thailand public health reimbursement systems between 2008 and 2013. Patients aged ≥ 18 years with a principal diagnosis of HF by the International Classification of Diseases, Tenth Revision, Thai modification were included. Comorbidities were identified by secondary diagnosis codes. The annual rate of HF hospitalization was calculated per 100,000 beneficiaries. Records of subsequent hospitalization of discharged patients were retrieved. For 1-year mortality rate, vital status of each patient was obtained from Thai Civil Registration of Death database. All outcomes were tested for linear trends across calendar years.

Results

Between 2008 and 2013, 434,933 HF hospitalizations were identified. The mean age was 65.3 years (SD 14.6), and 58.1% were female. The HF hospitalization rate increased from 138 in 2008 to 168 per 100,000 beneficiaries in 2013 (P for trend < 0.001). Nearly half (47.4%) had had a prior HF admission within 1 year. A small proportion of patients (7.4%) received echocardiography during hospitalization. The median length of hospital stay was 3 days. In-hospital mortality declined from 4.4 to 3.8% (P for trend < 0.001). The overall 30-day and 1-year rehospitalization rates were 34 and 73%, respectively, without significant trends over the study period. Most common cause of 30-day rehospitalization was HF (42%). One-year mortality decreased from 31.8% in 2008 to 28.5% in 2012 (P for trend < 0.001).

Conclusion

Between 2008 and 2013, HF hospitalization rate in Thailand increased. The in-hospital and 1-year mortality rates decreased slightly. However, the rehospitalization rate remained high mainly due to recurrent HF hospitalization.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02629-2.

Magnitude, pattern and correlates of multimorbidity among patients attending chronic outpatient medical care in Bahir Dar, northwest Ethiopia: The application of latent class analysis model

OBJECTIVE

This study aimed to investigate the magnitude, pattern and associated factors of multimorbidity in Bahir Dar, northwest Ethiopia.

METHODS

A multi-centered facility-based study was conducted among 1440 participants aged 40+ years attending chronic outpatient medical care. Two complementary methods (interview and review of medical records) were employed to collect data on socio-demographic, behavioral and disease related characteristics. The data were analyzed by STATA V.16 and R Software V.4.1.0. We fitted logistic regression and latent class analyses (LCA) models to identify the factors associated with multimorbidity and determine patterns of disease clustering, respectively. Statistical significance was considered at P-value <0.05.

RESULTS

The magnitude of individual chronic conditions ranged from 1.4% (cancer) to 37.9% (hypertension), and multimorbidity was identified in 54.8% (95% CI = 52.2%-57.4%) of the sample. The likelihood of having multimorbidity was higher among participants aged 45-54 years (AOR: 1.6, 95%CI = 1.1, 2.2), 55-64 years (AOR: 2.6, 95%CI = 1.9, 3.6) and 65+ years (AOR: 2.6, 95%CI = 1.9, 3.6) compared to those aged 40-44 years. The odds of multimorbidity was also higher among individuals classified as overweight (AOR: 1.6, 95%CI = 1.2, 2.1) or obese (AOR: 1.9, 95%CI = 1.3, 3.0) than the normal weight category. Four patterns of multimorbidity were identified; the cardiovascular category being the largest class (50.2%) followed by the cardio-mental, (32.6%), metabolic (11.5%) and respiratory (5.7%) groups. Advanced age, being overweight and obesity predicted latent class membership, adjusting for relevant confounding factors.

CONCLUSIONS

The magnitude of multimorbidity in this study was high, and the most prevalent conditions shaped the patterns of multimorbidity. Advanced age, being overweight and obesity were the factors correlated with multimorbidity. Further research is required to better understand the burden of multimorbidity and related factors in the population, and to determine the impact of multimorbidity on individuals' well-being and functioning.

Multi-Biomarker Points and Outcomes in Patients Hospitalized for Heart Failure: Insights From the China PEACE Prospective Heart Failure Study

Objective

To quantitatively characterize the pattern of systemic impairment reflected by conventional biomarkers and assess how it relates to clinical outcomes and quality of life among patients hospitalized for heart failure (HF).

Methods

Patients hospitalized for HF from 52 hospitals in China were enrolled between 2016 and 2018. They were divided into developing and validating cohorts; the developing cohort was used for calculating the weights of biomarkers and constructing the multi-biomarker panel, while the validating one was used for evaluating the relationship between multi-biomarker points and outcomes. In total, five conventional biomarkers reflecting various pathophysiological processes were included in the panel: N-terminal pro-B type natriuretic peptide, high-sensitivity troponin T, hemoglobin, albumin, and creatinine. The weights of the biomarkers were defined based on their relationship with cardiovascular death, and each patient had a multi-biomarker point ranging from 0 to 12. The primary clinical outcome was cardiovascular death, and the other clinical outcomes included rehospitalization for HF, all-cause death, and all-cause rehospitalization in 1-year. The quality of life was measured using Kansas City Cardiovascular Questionnaire. Multi-variable Cox proportional hazard models were used to assess the risks of clinical outcomes, and generalized linear models were used to evaluate the quality of life.

Results

In total, 4,693 patients hospitalized for HF were included in this analysis; the median (interquartile range, IQR) age was 67 (57-75) years old and 1,763 (37.6%) were female. The median multi-biomarker point was 5 (IQR, 2-6). There were 18.0% of patients in the low point group (<2), 29.4% in the mid-low point group (2-4), 27.8% in the mid-high point group (5-6), and 24.7% in the high point group (>6). Compared with those in the low point group, the patients in the high point group had a significantly excess risk of cardiovascular death (adjusted hazard ratio: 5.69, 95% CI, 3.33-9.70). Furthermore, patients with higher points were also more prone to worse quality of life.

Conclusion

Systemic impairment reflected by abnormal conventional biomarker values was common amongst patients hospitalized for HF and had substantially cumulative adverse influence on clinical outcomes and quality of life.

Effects of Dapagliflozin in Asian Patients With Heart Failure and Reduced Ejection Fraction in DAPA-HF

Background

Patients with heart failure with reduced ejection fraction (HFrEF) in Asia exhibit many differences from those in other parts of the world.

Objectives

This study sought to investigate the efficacy and safety of dapagliflozin, compared with placebo, in HFrEF patients in Asia, compared with those elsewhere, enrolled in the DAPA-HF (Dapagliflozin and Prevention of Adverse-outcomes in Heart Failure) trial.

Methods

Patients in New York Heart Association functional class II to IV with a left ventricular ejection fraction ≤40% and elevated N-terminal pro–B-type natriuretic peptide were eligible for the DAPA-HF trial. The primary outcome in the DAPA-HF trial was the composite of an episode of worsening HF (HF hospitalization or urgent HF visit requiring intravenous therapy) or cardiovascular death.

Results

Of the 4,744 patients in the DAPA-HF trial, 1,096 (23.1%) were enrolled in Asia; 721 (15.2% overall, 65.8% of patients in Asia) were enrolled in East Asia (237 in China, 343 in Japan, and 141 in Taiwan), 138 (2.9% overall, 12.6% in Asia) in South-East Asia (Vietnam), and 237 (5.0% overall, 21.6% in Asia) in South Asia (India). Patients from Asia had similar rates of worsening HF events and mortality compared with patients elsewhere. Compared with placebo, dapagliflozin reduced the risk of the primary endpoint to the same extent in patients from Asia (HR: 0.65; 95% CI: 0.49 to 0.87) as elsewhere (HR: 0.77; 95% CI: 0.66 to 0.89) (P for interaction = 0.32). Consistent benefits were observed for the other prespecified outcomes and among the regions of Asia. Study drug discontinuation and prespecified adverse events did not differ between regions.

Conclusions

Dapagliflozin, compared with placebo, reduced the risk of worsening HF events and cardiovascular death to the same extent in Asian patients as elsewhere. (Study to Evaluate the Effect of Dapagliflozin on the Incidence of Worsening Heart Failure or Cardiovascular Death in Patients With Chronic Heart Failure [DAPA-HF]; NCT03036124)

Evaluating the adverse outcome of subtypes of heart failure with preserved ejection fraction defined by machine learning: A systematic review focused on defining high risk phenogroups

The ability to distinguish clinically meaningful subtypes of heart failure with preserved ejection fraction (HFpEF) has recently been examined by machine learning techniques but studies appear to have produced discordant results. The objective of this study is to synthesize the types of HFpEF by examining their features and relating them to phenotypes with adverse prognosis. A systematic search was conducted using the search terms "Diastolic Heart Failure" OR "heart failure with preserved ejection fraction" OR "heart failure with normal ejection fraction" OR "HFpEF" AND "machine learning" OR "artificial intelligence" OR 'computational biology'. Ten studies were identified and they varied in their prevalence of ten clinical variables: age, sex, body mass index (BMI) or obesity, hypertension, diabetes mellitus, coronary artery disease, atrial fibrillation, chronic kidney disease, chronic obstructive pulmonary disease or symptom severity (NYHA class or BNP). The clinical findings associated with the different phenotypes in > 85 % of studies were age, hypertension, atrial fibrillation, chronic kidney disease and worse symptoms severity; an adverse outcome was in 65 % to 85 % of studies identified diabetes mellitus and female sex and in less than 65 % of studies was body mass index or obesity, and coronary artery disease. COPD was a relevant factor in only 33 % of studies. Adverse clinical outcome - death or admission to hospital (for heart failure) defined phenogroups with the worst outcome. Combining the 4 studies that calculated the MAGGIC score showed a significant (p<0.05) linear relationship between MAGGIC score and outcome, using the one-year event rate. A new score based on strength of the evidence of the HFpEF studies analyzed here, using 9 variables (eliminating COPD), showed a significant (p<0.009) linear relationship with one-year event rate. Three studies examined biomarkers in detail and the ones most prominently related to outcome or consistently found in the studies were GDF15, FABP4, FGF23, sST2, renin and TNF. The dominant factors that identified phenotypes of HFpEF with adverse outcome were hypertension, atrial fibrillation, chronic kidney disease and worse symptoms severity. A new simplified score, based on clinical factors, was proposed to assess prognosis in HFpEF. Several biomarkers were consistently elevated in phenogroups with adverse outcomes and may indicate the underlying mechanism or pathophysiology specific for phenotypes with an adverse prognosis.

Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults

Background

Multimorbidity presents an enormous problem to societal and healthcare utilization under the context of aging population in low- and middle-income countries (LMICs). Currently, systematic studies on the profile of multimorbidity and its characteristics among Chinese elderly are lacking. We described the temporal and spatial trends in the prevalence of multimorbidity and explored chronological changes of comorbidity patterns in a large elderly population survey.

Methods

Data were extracted from the Chinese Longitudinal Healthy Longevity Study (CLHLS) conducted between 1998 and 2018 in a random selection of half of the counties and city districts. All the elderly aged 65 and older were included in the survey of eight waves. We used 13 investigated chronic diseases to measure the prevalence of multimorbidity by means of geography, subpopulation, and chronological changes. The patterns of multimorbidity were assessed by computing the value of relative risk (RR indicates the likelihood of certain diseases to be associated with multimorbidity) and the observed-to-expected ratio (O/E indicates the likelihood of the coexistence of a multimorbidity combination).

Results

From 1998 to 2018, the prevalence of multimorbidity went from 15.60 to 30.76%, increasing in the fluctuation across the survey of eight waves (p_{for trend} = 0.020). Increasing trends were observed similarly in a different gender group (p_male = 0.009; p_female = 0.004) and age groups among female participants (p_~80 = 0.009; p₈₁₋₉₀ = 0.004; p₉₁₋₁₀₀ = 0.035; p_101~ = 0.018). The gap in the prevalence of multimorbidity between the north and the south was getting narrow across the survey of eight waves. Hypertension was the highest prevalent chronic condition while diabetes was most likely to coexist with other chronic conditions in the CLHLS survey. The most frequently occurring clusters were hypertension and heart disease, hypertension and cataract, and hypertension and chronic lung disease. And, the cancer, TB, and Parkinson's disease cluster took the domination of O/E rankings over time, which had a higher probability of coexistence in all the multimorbidity combinations.

Conclusions

The prevalence of multimorbidity has been increasing nationwide, and more attention should be paid to a rapid growth in the southern part of China. It demands the effective diagnosis and treatment adopted to the highly prevalent comorbidities, and strategies and measures were adjusted to strongly relevant clusters.

Diabetes and prediabetes in patients with heart failure and preserved ejection fraction

Aim

There is an association between heart failure with preserved ejection fraction (HFpEF) and insulin resistance, but less is known about the diabetic continuum, and in particular about pre‐diabetes, in HFpEF. We examined characteristics and outcomes of participants with diabetes or pre‐diabetes in PARAGON‐HF.

Methods and results

Patients aged ≥50 years with left ventricular ejection fraction ≥45%, structural heart disease and elevated N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) were eligible. Patients were classified according to glycated haemoglobin (HbA1c): (i) normal HbA1c, <6.0%; (ii) pre‐diabetes, 6.0%–6.4%; (iii) diabetes, ≥6.5% or history of diabetes. The primary outcome was a composite of cardiovascular (CV) death and total heart failure hospitalizations (HFH). Of 4796 patients, 50% had diabetes and 18% had pre‐diabetes. Compared to patients with normal HbA1c, patients with pre‐diabetes and diabetes more often were obese, had a history of myocardial infarction and had lower Kansas City Cardiomyopathy Questionnaire scores, while patients with diabetes had more clinical evidence of congestion, but similar NT‐proBNP concentrations. The risks of the primary composite outcome (rate ratio [RR] 1.59, 95% confidence interval [CI] 1.35–1.88), total HFH (RR 1.67, 95% CI 1.39–2.02) and CV death (hazard ratio [HR] 1.35, 95% CI 1.07–1.71) were higher among patients with diabetes, compared to those with normal HbA1c. Patients with pre‐diabetes had a higher risk (which was intermediate between that of patients with diabetes and those with normal HbA1c) of the primary outcome (HR 1.27, 95% CI 1.00–1.60) and HFH (HR 1.35, 95% CI 1.03–1.77), but not of CV death (HR 1.02, 95% CI 0.75–1.40). Patients with diabetes treated with insulin had worse outcomes than those not, and those with ‘lean diabetes’ had similar mortality rates to those with a higher body mass index, but lower rates of HFH.

Conclusion

Pre‐diabetes is common in patients with HFpEF and is associated with worse clinical status and greater risk of HFH. Clinical Trial Registration: ClinicalTrials.gov Identifier NCT01920711.