scholarly journals Age dependent associations of risk factors with heart failure: pooled population based cohort study

BMJ ◽  
2021 ◽  
pp. n880
Keyword(s):  
Risk Factors ◽  
Heart Failure ◽  
Cohort Study ◽  
Population Based ◽  
Age Dependent

scholarly journals Heart Failure Is a Clinically and Densitometrically Independent Risk Factor for Osteoporotic Fractures: Population-Based Cohort Study of 45,509 Subjects

2012 ◽  
Vol 97 (4) ◽  
pp. 1179-1186 ◽  
Author(s):  
Sumit R. Majumdar ◽  
Justin A. Ezekowitz ◽  
Lisa M. Lix ◽  
William D. Leslie
Keyword(s):  
Risk Factors ◽  
Heart Failure ◽  
Cohort Study ◽  
Osteoporotic Fractures ◽  
Population Based ◽  
Recent Onset ◽  
Major Osteoporotic Fractures ◽  
Hip Bmd ◽  
Osteoporosis Risk Factors ◽  
Osteoporosis Risk

Objective: The aim of the study was to determine whether heart failure is associated with an increased risk of major osteoporotic fractures that is independent of bone mineral density (BMD). Methods: We conducted a population-based cohort study in Manitoba, Canada, by linking a clinical registry of all adults 50 yr of age and older who underwent initial BMD testing from 1998–2009 with administrative databases. We collected osteoporosis risk factors, comorbidities, medications, and BMD results. Validated algorithms identified recent-onset heart failure before the BMD test and new fractures after. The main outcome was time to major osteoporotic fractures (i.e. clinical vertebrae, distal forearm, humerus, and hip), and multivariable proportional hazards models were used for analyses. Results: The cohort consisted of 45,509 adults; 1,841 (4%) had recent-onset heart failure. Subjects with heart failure were significantly (P < 0.001) older (74 vs. 66 yr) and had more previous fractures (21 vs. 13%) and lower total hip BMD [T-score, −1.3 (sd 1.3) vs. −0.9 (sd 1.2)] than those without. There were 2703 incident fractures over the 5-yr observation. Overall, 10% of heart failure subjects had incident major fractures compared with 5% of those without [unadjusted hazard ratio (HR), 2.45; 95% confidence interval (CI), 2.11–2.85]. Adjustment for osteoporosis risk factors, comorbidities, and medications attenuated but did not eliminate this association (HR, 1.33; 95% CI, 1.11–1.60), nor did further adjustment for total hip BMD (HR, 1.28; 95% CI, 1.06–1.53). Conclusions: Heart failure is associated with a 30% increase in major fractures that is independent of traditional risk factors and BMD, and it also identifies a high-risk population that may benefit from increased screening and treatment for osteoporosis.

scholarly journals The Risk of Heart Failure and Other Cardiovascular Hospitalizations After Early Stage Breast Cancer: A Matched Cohort Study

2019 ◽  
Vol 111 (8) ◽  
pp. 854-862 ◽  
Author(s):  
Husam Abdel-Qadir ◽  
Paaladinesh Thavendiranathan ◽  
Peter C Austin ◽  
Douglas S Lee ◽  
Eitan Amir ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Heart Failure ◽  
Cohort Study ◽  
Early Stage ◽  
Statistical Tests ◽  
Population Based ◽  
Emergency Department Visits ◽  
Early Stage Breast Cancer ◽  
Control Subjects

AbstractBackgroundData are limited regarding the risk of heart failure (HF) requiring hospital-based care after early stage breast cancer (EBC) and its relationship to other types of cardiovascular disease (CVD).MethodsWe conducted a population-based, retrospective cohort study of EBC patients (diagnosed April 1, 2005–March 31, 2015) matched 1:3 on birth-year to cancer-free control subjects. We identified hospitalizations and emergency department visits for CVD through March 31, 2017. We used cumulative incidence function curves to estimate CVD incidence and cause-specific regression models to compare CVD rates between cohorts. All statistical tests were two-sided.ResultsWe identified 78 318 EBC patients and 234 954 control subjects. The 10-year incidence of CVD hospitalization was 10.8% (95% confidence interval [CI] = 10.5% to 11.1%) after EBC and 9.1% (95% CI = 8.9% to 9.2%) in control subjects. Ischemic heart disease was the most common reason for CVD hospitalization after EBC. After regression adjustment, the relative rates compared with control subjects remained statistically significantly elevated for HF (hazard ratio [HR] = 1.21, 95% CI = 1.14 to 1.29, P < .001), arrhythmias (HR = 1.31, 95% CI = 1.23 to 1.39, P < .001), and cerebrovascular disease (HR 1.10, 95% CI = 1.04 to 1.17, P = .002) hospitalizations. It was rare for HF hospital presentations (2.9% of cases) to occur in EBC patients without recognized risk factors (age >60 years, hypertension, diabetes, prior CVD). Anthracycline and/or trastuzumab were used in 28 950 EBC patients; they were younger than the overall cohort with lower absolute rates of CVD, hypertension, and diabetes. However, they had higher relative rates of CVD in comparison with age-matched control subjects.ConclusionsAtherosclerotic diagnoses, rather than HF, were the most common reasons for CVD hospitalization after EBC. HF hospital presentations were often preceded by risk factors other than chemotherapy, suggesting potential opportunities for prevention.

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

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.

scholarly journals Prevalence and determinants of the precursor stages of heart failure: results from the population-based STAAB cohort study

2020 ◽  
pp. 204748732092263
Author(s):  
Caroline Morbach ◽  
Götz Gelbrich ◽  
Theresa Tiffe ◽  
Felizitas A Eichner ◽  
Martin Christa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Heart Failure ◽  
Cohort Study ◽  
Cardiac Dysfunction ◽  
Age Groups ◽  
Heart Association ◽  
Population Based ◽  
Left Ventricular ◽  
Cross Sectional ◽  
Group B

Aims Prevention of heart failure relies on the early identification and control of risk factors. We aimed to identify the frequency and characteristics of individuals at risk of heart failure in the general population. Methods and Results We report cross-sectional data from the prospective Characteristics and Course of Heart Failure Stages A–B and Determinants of Progression (STAAB) cohort study investigating a representative sample of residents of Würzburg, Germany. Sampling was stratified 1:1 for sex and 10:27:27:27:10 for age groups of 30–39/40–49/50–59/60–69/70–79 years. Heart failure precursor stages were defined according to American College of Cardiology/American Heart Association: stage A (risk factors for heart failure), stage B (asymptomatic cardiac dysfunction). The main results were internally validated in the second half of the participants. The derivation sample comprised 2473 participants (51% women) with a distribution of 10%/28%/25%/27%/10% in respective age groups. Stages A and B were prevalent in 42% and 17% of subjects, respectively. Of stage B subjects, 31% had no risk factor qualifying for stage A (group ‘B-not-A’). Compared to individuals in stage B with A criteria, B-not-A were younger, more often women, and had left ventricular dilation as the predominant B qualifying criterion (all P < 0.001). These results were confirmed in the validation sample ( n = 2492). Conclusion We identified a hitherto undescribed group of asymptomatic individuals with cardiac dysfunction predisposing to heart failure, who lacked established heart failure risk factors and therefore would have been missed by conventional primary prevention. Further studies need to replicate this finding in independent cohorts and characterise their genetic and -omic profile and the inception of clinically overt heart failure in subjects of group B-not-A.

scholarly journals Age dependent associations of risk factors with heart failure: pooled population based cohort study

BMJ ◽  
2021 ◽  
pp. n461
Author(s):  
Jasper Tromp ◽  
Samantha M A Paniagua ◽  
Emily S Lau ◽  
Norrina B Allen ◽  
Michael J Blaha ◽  
...  
Keyword(s):  
Risk Factors ◽  
Heart Failure ◽  
Cohort Study ◽  
Absolute Risk ◽  
Population Based ◽  
Attributable Risk ◽  
Smoking History ◽  
Middle Aged ◽  
Current Smoking ◽  
Incident Heart Failure

Abstract Objective To assess age differences in risk factors for incident heart failure in the general population. Design Pooled population based cohort study. Setting Framingham Heart Study, Prevention of Renal and Vascular End-stage Disease Study, and Multi-Ethnic Study of Atherosclerosis. Participants 24 675 participants without a history of heart failure stratified by age into young (<55 years; n=11 599), middle aged (55-64 years; n=5587), old (65-74 years; n=5190), and elderly (≥75 years; n=2299) individuals. Main outcome measure Incident heart failure. Results Over a median follow-up of 12.7 years, 138/11 599 (1%), 293/5587 (5%), 538/5190 (10%), and 412/2299 (18%) of young, middle aged, old, and elderly participants, respectively, developed heart failure. In young participants, 32% (n=44) of heart failure cases were classified as heart failure with preserved ejection fraction compared with 43% (n=179) in elderly participants. Risk factors including hypertension, diabetes, current smoking history, and previous myocardial infarction conferred greater relative risk in younger compared with older participants (P for interaction <0.05 for all). For example, hypertension was associated with a threefold increase in risk of future heart failure in young participants (hazard ratio 3.02, 95% confidence interval 2.10 to 4.34; P<0.001) compared with a 1.4-fold risk in elderly participants (1.43, 1.13 to 1.81; P=0.003). The absolute risk for developing heart failure was lower in younger than in older participants with and without risk factors. Importantly, known risk factors explained a greater proportion of overall population attributable risk for heart failure in young participants (75% v 53% in elderly participants), with better model performance (C index 0.79 v 0.64). Similarly, the population attributable risks of obesity (21% v 13%), hypertension (35% v 23%), diabetes (14% v 7%), and current smoking (32% v 1%) were higher in young compared with elderly participants. Conclusions Despite a lower incidence and absolute risk of heart failure among younger compared with older people, the stronger association and greater attributable risk of modifiable risk factors among young participants highlight the importance of preventive efforts across the adult life course.

Incidence of and Risk Factors for Heart Failure in Patients with Psoriatic Disease – A Cohort Study

2021 ◽  
Author(s):  
Sahil Koppikar ◽  
Keith Colaco ◽  
Paula Harvey ◽  
Shadi Akhtari ◽  
Vinod Chandran ◽  
...  
Keyword(s):  
Risk Factors ◽  
Heart Failure ◽  
Cohort Study ◽  
Psoriatic Disease

scholarly journals Associations between pre-pregnancy psychosocial risk factors and infant outcomes: a population-based cohort study in England

2021 ◽  
Vol 6 (2) ◽  
pp. e97-e105
Author(s):  
Katie Harron ◽  
Ruth Gilbert ◽  
Jamie Fagg ◽  
Astrid Guttmann ◽  
Jan van der Meulen
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Population Based ◽  
Psychosocial Risk Factors ◽  
Psychosocial Risk ◽  
Infant Outcomes
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