ArticleFrontiers in physiology2013
Association of cardiovascular risk using non-linear heart rate variability measures with the framingham risk score in a rural population.
Article in Frontiers in physiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of the prevalence of fatigue in common mental disorders (mood disorders, anxiety disorders, personality disorders, and trauma and stressor related disorders).BMC psychiatry · 2026Pooled it
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- Mood regulation in euthymic patients with a history of antidepressant-induced mania.Bipolar disorders · 2024Article
- Assessment of autonomic dysfunction with the COMPASS-31 and its relationship with disease activity and cardiovascular risks in patients with psoriatic arthritis.Rheumatology international · 2022Observational
- The futility of long-term predictions in bipolar disorder: mood fluctuations are the result of deterministic chaotic processes.International journal of bipolar disorders · 2021Article
- The perils of being too stable: mood regulation in bipolar disorderJournal of psychiatry & neuroscience : JPN · 2018Article
- Heart Rate Variability in Coexisting Diabetes and Hypertension.Arquivos brasileiros de cardiologia · 2018Article
- DSM-5 Criteria and Depression Severity: Implications for Clinical Practice.Frontiers in psychiatry · 2018Article
- Association between Carotid Intima Media Thickness and Heart Rate Variability in Adults at Increased Cardiovascular Risk.Frontiers in physiology · 2017Article
- Association of Diabetes Related Complications with Heart Rate Variability among a Diabetic Population in the UAE.PloS one · 2017Article
- Complexity Change in Cardiovascular Disease.International journal of biological sciences · 2017Review
- Regulatory Roles of Fluctuation-Driven Mechanotransduction in Cell Function.Physiology (Bethesda, Md.) · 2016Review
- Article
- Identifying Common Genetic Risk Factors of Diabetic Neuropathies.Frontiers in endocrinology · 2015Review
- Article
- A community study of the effect of polycyclic aromatic hydrocarbon metabolites on heart rate variability based on the Framingham risk score.Occupational and environmental medicine · 2014Article
- Impaired signaling intrinsic to sinoatrial node pacemaker cells affects heart rate variability during cardiac disease.Journal of clinical trials · 2014Article
- How to Calculate Renyi Entropy from Heart Rate Variability, and Why it Matters for Detecting Cardiac Autonomic Neuropathy.Frontiers in bioengineering and biotechnology · 2014Article
- Cardiac autonomic dysfunction in type 2 diabetes - effect of hyperglycemia and disease duration.Frontiers in endocrinology · 2014Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular risk can be calculated using the Framingham cardiovascular disease (CVD) risk score and provides a risk stratification from mild to very high CVD risk percentage over 10 years. This equation represents a complex interaction between age, gender, cholesterol status, blood pressure, diabetes status, and smoking. Heart rate variability (HRV) is a measure of how the autonomic nervous system (ANS) modulates the heart rate. HRV measures are sensitive to age, gender, disease status such as diabetes and hypertension and processes leading to atherosclerosis. We investigated whether HRV measures are a suitable, simple, noninvasive alternative to differentiate between the four main Framingham associated CVD risk categories. In this study we applied the tone-entropy (T-E) algorithm and complex correlation measure (CCM) for analysis of HRV obtained from 20 min. ECG recordings and correlated the HRV score with the stratification results using the Framingham risk equation. Both entropy and CCM had significant analysis of variance (ANOVA) results [F (172, 3) = 9.51; <0.0001]. Bonferroni post hoc analysis indicated a significant difference between mild, high and very high cardiac risk groups applying tone-entropy (p < 0.01). CCM detected a difference in temporal dynamics of the RR intervals between the mild and very high CVD risk groups (p < 0.01). Our results indicate a good agreement between the T-E and CCM algorithm and the Framingham CVD risk score, suggesting that this algorithm may be of use for initial screening of cardiovascular risk as it is noninvasive, economical and easy to use in clinical practice.
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