scholarly journals Anthropometric measures in relation to risk of heart failure hospitalization: a Swedish population-based cohort study

2012 ◽  
Vol 24 (2) ◽  
pp. 215-220 ◽  
Author(s):  
Yan Borné ◽  
Bo Hedblad ◽  
Birgitta Essén ◽  
Gunnar Engström
Keyword(s):  
Heart Failure ◽  
Cohort Study ◽  
Population Based ◽  
Heart Failure Hospitalization ◽  
Anthropometric Measures ◽  
Swedish Population

scholarly journals Multiple anthropometric measures in relation to incidence of diabetes: a Swedish population-based cohort study

2015 ◽  
Vol 25 (6) ◽  
pp. 1100-1105 ◽  
Author(s):  
Yan Borné ◽  
Peter M. Nilsson ◽  
Olle Melander ◽  
Bo Hedblad ◽  
Gunnar Engström
Keyword(s):  
Cohort Study ◽  
Population Based ◽  
Anthropometric Measures ◽  
Swedish Population

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 The prediction of colorectal cancer using anthropometric measures: A Swedish population‐based cohort study with 22 years of follow‐up

2019 ◽  
Vol 7 (9) ◽  
pp. 1250-1260 ◽  
Author(s):  
Anna Andreasson ◽  
Hannes Hagström ◽  
Filip Sköldberg ◽  
Kristina Önnerhag ◽  
Axel C Carlsson ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cohort Study ◽  
Population Based ◽  
Anthropometric Measures ◽  
Swedish Population

scholarly journals Country of birth and risk of hospitalization due to heart failure: a Swedish population-based cohort study

2010 ◽  
Vol 26 (4) ◽  
pp. 275-283 ◽  
Author(s):  
Yan Borné ◽  
Gunnar Engström ◽  
Birgitta Essén ◽  
Jan Sundquist ◽  
Bo Hedblad
Keyword(s):  
Heart Failure ◽  
Cohort Study ◽  
Population Based ◽  
Country Of Birth ◽  
Swedish Population

scholarly journals S134. THE INCIDENCE OF PSYCHOSIS IN OLDER PEOPLE: A SWEDISH POPULATION-BASED COHORT STUDY

2018 ◽  
Vol 44 (suppl_1) ◽  
pp. S377-S378 ◽  
Author(s):  
Jean Stafford ◽  
Robert Howard ◽  
Christina Dalman ◽  
James Kirkbride
Keyword(s):  
Cohort Study ◽  
Older People ◽  
Population Based ◽  
Swedish Population

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.

Sign in / Sign up

Export Citation Format

Share Document