Factors influencing heart rate variability power spectral analysis during controlled breathing in patients with chronic heart failure or hypertension and in healthy normotensive subjects

2004 ◽  
Vol 107 (2) ◽  
pp. 183-190 ◽  
Author(s):  
Gianfranco PICCIRILLO ◽  
Damiano MAGRÌ ◽  
Camilla NASO ◽  
Silvia di CARLO ◽  
Antonio MOISÈ ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Sudden Death ◽  
Ejection Fraction ◽  
Nyha Class ◽  
Power Spectral ◽  
Normotensive Subjects ◽  
Controlled Breathing ◽  
Frequency Power

A decreased LFP (low-frequency power) spectral component of HRV [HR (heart rate) variability] is a risk factor for sudden death in patients with CHF (chronic heart failure). In the present study, we evaluated factors (age, arterial pressures and HR) influencing LFP and HFP (high-frequency power) components in short-term recordings during controlled breathing in patients with CHF or hypertension, and healthy normotensive subjects. In patients with CHF, we also compared LFP values with known markers of sudden death [NYHA (New York Heart Association) class, HR and ejection fraction]. All HRV measures were significantly lower in patients with CHF than in hypertensive and normotensive subjects (P<0.001), and in hypertensive than in normotensive subjects (P<0.05). Stepwise multiple regression analysis showed that, in patients with CHF, LFP was inversely associated with NYHA class (β=−0.5, P<0.0001) and HR (β=−0.2, P=0.001) and was positively associated with ejection fraction (β=0.28, P<0.0001). In patients with CHF, LFP remained unchanged with age. In normotensive and hypertensive subjects, HFP decreased with age, but in patients with CHF it did not. In the ≥60<70 and ≥70 years of age subgroups, we found no difference between HFP in the three groups studied. Hence, in normotensives and hypertensives, LFP tended to diminish with age (β=−0.4, P<0.0001 in normotensives; β=−0.4, P<0.001 in hypertensives) and was inversely associated with HR (β=−0.2, P=0.002 in normotensives; β=−0.3, P=0.002 in hypertensives). Conversely, in patients with CHF, LFP is predominantly influenced by NYHA class, HR and ejection fraction, but not by age. LFP might therefore increase the sensitivity of factors already used in stratifying the risk of sudden death in patients with CHF.

scholarly journals Developing and validating models to predict sudden death and pump failure death in patients with heart failure and preserved ejection fraction

2020 ◽  
Author(s):  
Li Shen ◽  
Pardeep S. Jhund ◽  
Inder S. Anand ◽  
Peter E. Carson ◽  
Akshay S. Desai ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Sudden Death ◽  
Ejection Fraction ◽  
External Validation ◽  
Model Performance ◽  
Preserved Ejection Fraction ◽  
Clinical Model ◽  
Pump Failure ◽  
History Of

Abstract Background Sudden death (SD) and pump failure death (PFD) are leading modes of death in heart failure and preserved ejection fraction (HFpEF). Risk stratification for mode-specific death may aid in patient enrichment for new device trials in HFpEF. Methods Models were derived in 4116 patients in the Irbesartan in Heart Failure with Preserved Ejection Fraction trial (I-Preserve), using competing risks regression analysis. A series of models were built in a stepwise manner, and were validated in the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM)-Preserved and Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) trials. Results The clinical model for SD included older age, men, lower LVEF, higher heart rate, history of diabetes or myocardial infarction, and HF hospitalization within previous 6 months, all of which were associated with a higher SD risk. The clinical model predicting PFD included older age, men, lower LVEF or diastolic blood pressure, higher heart rate, and history of diabetes or atrial fibrillation, all for a higher PFD risk, and dyslipidaemia for a lower risk of PFD. In each model, the observed and predicted incidences were similar in each risk subgroup, suggesting good calibration. Model discrimination was good for SD and excellent for PFD with Harrell’s C of 0.71 (95% CI 0.68–0.75) and 0.78 (95% CI 0.75–0.82), respectively. Both models were robust in external validation. Adding ECG and biochemical parameters, model performance improved little in the derivation cohort but decreased in validation. Including NT-proBNP substantially increased discrimination of the SD model, and simplified the PFD model with marginal increase in discrimination. Conclusions The clinical models can predict risks for SD and PFD separately with good discrimination and calibration in HFpEF and are robust in external validation. Adding NT-proBNP further improved model performance. These models may help to identify high-risk individuals for device intervention in future trials. Clinical trial registration I-Preserve: ClinicalTrials.gov NCT00095238; TOPCAT: ClinicalTrials.gov NCT00094302; CHARM-Preserved: ClinicalTrials.gov NCT00634712. Graphic abstract

scholarly journals Influence of heart failure severity on heart rate variability

2005 ◽  
Vol 133 (11-12) ◽  
pp. 484-491 ◽  
Author(s):  
Danijela Zamaklar-Trifunovic ◽  
Petar Seferovic ◽  
Mirjana Zivkovic ◽  
Vera Jelic ◽  
Goran Vukomanovic ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Nyha Class ◽  
Low Frequency ◽  
Total Power ◽  
Pump Failure ◽  
Spectral Components ◽  
Failure Severity ◽  
Heart Failure Severity

Introduction. Autonomic regulation of cardiovascular functions in congestive heart failure is characterised by enhanced sympathetic and diminished parasympathetic activity. The long term predominance of sympathetic tone is a significant factor in arrhythmogenesis, sudden cardiac death, and progressive pump failure. Heart rate variability (HRV) is a noninvasive method for estimating the sympatho vagal balance in cardiovascular control. Aim. The aim of this study was to analyse the influence of heart failure severity on HRV. Method. HRV was estimated through the spectral analysis of short term ECG (Cardiovit AT 60, Schiller, CH) in 63 patients (78% male, mean age 56.9?10.9 years) and 14 healthy volunteers (57.1% male, mean age 53.1?8.2 years). The following spectral components were measured: VLF (very low frequency), LF (low frequency), HF (high frequency), and total power (Tot Power). Results. All spectral components were statistically, significantly lower in patients with heart failure in comparison to healthy controls (VLF: 159.89?147.02 vs. 285.50?202.77 ms2; p=0.023, LF: 161.48?204.01 vs. 474.57?362.93 ms2; p<0.001, HF: 88.58?102.47 vs. 362.71?318.28 ms2; p<0.001), as well as total power (Tot Power: 723.39?644.52 vs. 1807.29?1204.74 ms2; p<0.001). A significant, negative correlation between HRV parameters and NYHA class was detected in heart failure patients (VLF: r=-0.391; p=0.002, LF: r=-0.401; p=0.001, and Tot Power r=-0.372; p=0.003). Ejection fraction proved to be in significant, positive correlation to VLF (r=0.541; p=0.002), LF (r=0.531; p=0.003), HF (r=0.418; p=0.020), and Tot Power (r=0.457; p=0.013). Conclusion. Significant HRV reduction is a precursor to incipient heart failure (NYHA I). In heart failure progression, total power as well as the power of all spectral components is progressively reduced. LF and Tot Power are the most prominent parameters for discriminating between the different stages of heart failure. These results could promote HRV as an important decision-making tool in heart failure treatment as well as in monitoring the results of that treatment.

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