Non-Apnea Sleep Disorder associates with increased risk of incident heart failure—A nationwide population-based cohort study

BackgroundMetabolically healthy obese (MHO) individuals and their association with cardiometabolic diseases have remained controversial. We aimed to explore the risk of incident heart failure (HF) based on the baseline metabolic health and obesity status as well as their transition over 2 years.MethodsThe Korean National Health Insurance Service-National Health Screening Cohort data of 514,886 participants were analyzed. Obesity was defined as BMI ≥25 kg/m2 according to the Korean Centers for Disease Control and Prevention. The metabolic health and obesity status were evaluated at baseline and after two years. Study participants were followed to either the date of newly diagnosed HF or the last follow-up visit, whichever occurred first.ResultsThe MHO group comprised 9.1% of the entire population and presented a better baseline metabolic profile than the metabolically unhealthy non-obese (MUNO) and metabolicavlly unhealthy obese (MUO) groups. During the median 71.3 months of follow-up, HF developed in 5,406 (1.5%) participants. The adjusted hazard ratios [HRs (95% CI)] of HF at baseline compared with the metabolically healthy non-obese (MHNO) group were 1.29 [1.20–1.39], 1.37 [1.22–1.53], and 1.63 [1.50–1.76] for MUNO, MHO, and MUO groups, respectively. With the stable MHNO group as reference, transition into metabolically unhealthy status (MUNO and MUO) increased the risk of HF, regardless of the baseline status. Subjects who were obese at both baseline and follow-up showed an increased risk of HF, regardless of their metabolic health status.ConclusionsMetabolic health and obesity status and their transition can predict the risk of incident HF. Losing metabolic health in baseline non-obese and obese individuals and remaining obese in baseline obese individuals showed a significantly increased risk of incident HF. Maintaining good metabolic health and a lean body may prevent the development of HF.

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P5004Peripheral neuropathy and increased risk of heart failure: a population-based longitudinal cohort study

European Heart Journal ◽

10.1093/eurheartj/ehz746.0182 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

Y Sun ◽

J Oxnard ◽

B J New ◽

I R Mordi ◽

W Meng ◽

...

Keyword(s):

Heart Failure ◽

Cohort Study ◽

Peripheral Neuropathy ◽

Diabetic Neuropathy ◽

Population Based ◽

Longitudinal Cohort Study ◽

Smoking History ◽

Longitudinal Cohort ◽

Clinical Variables ◽

Increased Risk

Abstract Background One of the main pathophysiological processes thought to be implicated in the development of diabetic cardiomyopathy is a microvascular disease (MiVD) that is prevalent in type 2 diabetes (T2D). However, the role of MiVD in the development of heart failure (HF) is not known. T2D screening programmes identify three types of MiVD – retinopathy, nephropathy and neuropathy. Both retinopathy and nephropathy have been independently associated with the development of incident HF in observational cohort studies. There is less data on peripheral neuropathy and HF outcomes. This study aimed to determine the independent association of diabetic neuropathy with incident HF events in a large longitudinal population cohort of T2D patients with a detailed clinical follow-up that includes available echocardiographic data. Design This was a population-based longitudinal cohort study from the Genetics of Diabetes Audit and Research in Tayside Scotland study (GoDARTS) from 1996 to 2016. A total of 9,598 patients with T2D were included with data available on hospital admissions, prescribing and other clinical variables including age, gender, smoking history, duration of T2D, body mass index, systolic blood pressure, glycosylated haemoglobin (HbA1c), triglyceride, total LDL and HDL cholesterol levels. Neuropathy cases were identified using a well-validated record linkage method utilising neuropathic drug prescription records to identify cases of neuropathic pain and to monofilament testing that is used to diagnose neuropathy. Results There were 805 HF events. After adjustment for clinical variables, the presence of painful neuropathy related to a 57% increased risk of incident HF (HR 1.57, 95% CI = 1.32–1.89, p<0.001). A similar risk was also observed with diabetic neuropathy identified by monofilament testing with a 52% (HR 1.52, CI = 1.013–1.225, P<0.05) increased risk of incident HF. Conclusions and relevance Peripheral neuropathy, a feature of MiVD, may be pathophysiologically associated with the development of HF in patients with T2D and may be a therapeutic target.

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Fasting Plasma Glucose and Incident Heart Failure Risk: A Population-Based Cohort Study and New Meta-analysis

Journal of Cardiac Failure ◽

10.1016/j.cardfail.2014.05.011 ◽

2014 ◽

Vol 20 (8) ◽

pp. 584-592 ◽

Cited By ~ 11

Author(s):

Hassan Khan ◽

Setor K. Kunutsor ◽

Jussi Kauhanen ◽

Sudhir Kurl ◽

Eiran Z. Gorodeski ◽

...

Keyword(s):

Heart Failure ◽

Cohort Study ◽

Plasma Glucose ◽

Fasting Plasma Glucose ◽

Meta Analysis ◽

Population Based ◽

Failure Risk ◽

Fasting Plasma ◽

Incident Heart Failure

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Bioimpedance and new onset heart failure: A longitudinal study of ~500,000 individuals from the general population

10.1101/183483 ◽

2017 ◽

Author(s):

Daniel Lindholm ◽

Eri Fukaya ◽

Nicholas J. Leeper ◽

Erik Ingelsson

Keyword(s):

Machine Learning ◽

Risk Factors ◽

Myocardial Infarction ◽

Heart Failure ◽

Cohort Study ◽

Population Based ◽

Heart Failure Hospitalization ◽

Predictive Capacity ◽

History Of ◽

Incident Heart Failure

AbstractImportanceHeart failure constitutes a high burden on patients and society, but although lifetime risk is high, it is difficult to predict without costly or invasive testing. Knowledge about novel risk factors could enable early diagnosis and possibly preemptive treatment.ObjectiveTo establish new risk factors for heart failure.DesignWe applied supervised machine learning in UK Biobank in an agnostic search of risk factors for heart failure. Novel predictors were then subjected to several in-depth analyses, including multivariable Cox models of incident heart failure, and assessment of discrimination and calibration.SettingPopulation-based cohort study.Participants500,451 individuals who volunteered to participate in the UK Biobank cohort study, excluding those with prevalent heart failure.Exposure3646 variables reflecting different aspects of lifestyle, health and disease-related factors.Main OutcomeIncident heart failure hospitalization.ResultsMachine learning confirmed many known and putative risk factors for heart failure, and identified several novel candidates. Mean reticulocyte volume appeared as one novel factor, and leg bioimpedance another; the latter appearing as the most important new factor. Leg bioimpedance was significantly lower in those who developed heart failure (p=1.1x10-72) during up to 9.8-year follow-up. When adjusting for known heart failure risk factors, leg bioimpedance was inversely related to heart failure (hazard ratio [95%CI], 0.60 [0.48–0.73]) and 0.75 [0.59–0.94], in age- and sex-adjusted and fully adjusted models, respectively, comparing the upper vs. lower quartile). A model including leg bioimpedance, age, sex, and self-reported history of myocardial infarction showed good predictive capacity of future heart failure hospitalization (C-index=0.82) and good calibration.Conclusions and RelevanceLeg bioimpedance is inversely associated with heart failure incidence in the general population. A simple model of exclusively non-invasive measures, combining leg bioimpedance with history of myocardial infarction, age, and sex provides accurate predictive capacity.Key pointsQuestionWhich are the most important risk factors for incident heart failure?FindingsIn this population-based cohort study of ~500,000 individuals, machine learning identified well-established risk factors, but also several novel factors. Among the most important were leg bioimpedance and mean reticulocyte volume. There was a strong inverse relationship between leg bioimpedance and incident heart failure, also in adjusted analyses. A model entailing leg bioimpedance, age, sex, and self-reported history of myocardial infarction showed good predictive capacity of heart failure hospitalization and good calibration.MeaningLeg bioimpedance appears to be an important new factor associated with incident heart failure.

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Social relationships and the risk of incident heart failure: Results from a prospective population-based study of older men

European Heart Journal Open ◽

10.1093/ehjopen/oeab045 ◽

2021 ◽

Author(s):

Aishah Coyte ◽

Rachel Perry ◽

A O Papacosta ◽

L T Lennon ◽

P H Whincup ◽

...

Keyword(s):

Heart Failure ◽

Marital Status ◽

Social Relationships ◽

Social Relationship ◽

Population Based ◽

Developing Heart ◽

Frequency Of Contact ◽

Increased Risk ◽

Contact Frequency ◽

Incident Heart Failure

Abstract Background Limited social relationships, particularly in older adults, has been implicated as a risk factor for cardiovascular disease. However, little is known about the associations between poor social relationships and heart failure incidence. Methods Prospective study of socially representative men aged 60-79 years drawn from general practices in 24 British towns and followed up for a maximum of 18 years. 3698 participants with no previous diagnosis of heart failure were included. Information on social relationships was based on a combination of marital status, living circumstances, and social contacts with friends and family. These provided information on contact frequency, contact satisfaction, and a social relationship score (low to high) combining frequency and satisfaction with contact. Heart failure included both incident non-fatal heart failure and death from heart failure. Results Among 3698 participants, 330 developed heart failure. Men with low compared to high frequency of contact with family and friends had an increased risk of incident heart failure (hazard ratio (HR) 1.59, 95%CI 1.15-2.18); this remained statistically significant after adjustment for social class, behavioural and biological risk factors. Low compared to high scores for satisfaction with contacts was associated with increased risk of heart failure (adjusted HR = 1.54; 95%CI 1.14-2.07). Lower social relationship scores (combining frequency and satisfaction with contact) were associated with greater risk of incident heart failure (adjusted HR = 1.38, 95%CI 1.02-1.87). Marital status and living alone were not significantly associated with heart failure. Conclusion Weaker social relationships appear to increase the risk of developing heart failure in older age. Further research is needed to investigate pathways underlying these associations and to test whether interventions to strengthen social relationships can reduce the risk of heart failure.

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