Heart rate recovery after the 6 min walk test rather than distance ambulated is a powerful prognostic indicator in heart failure with reduced and preserved ejection fraction: A comparison with cardiopulmonary exercise testing
Heart rate recovery (HRR) appears to be a robust prognostic marker in heart failure (HF). When using the 6 min walk test (6MWT) in HF, distance ambulated is generally the reference prognostic variable. We hypothesized that HRR after the 6MWT would be a better prognostic measure than distance ambulated.
Methods and results:
A 6MWT and cardiopulmonary exercise testing (CPX) were randomly performed in 258 HF patients [216 HF with reduced EF (HFrEF) and 42 HF preserved EF (HFpEF)], after which HRR was measured. HRR was defined as the difference between heart rate at peak exercise and 1 min following test termination. Patients were assessed for major cardiac events during a mean follow-up period of 22.8 ± 22.1 months. There were 50 major cardiac events during the tracking period. Univariate Cox regression analysis results identified HRR after both the 6MWT and CPX as a significant (P < 0.001) predictor of adverse events. Multivariate Cox regression analysis revealed that dichotomized HRR after the 6MWT and CPX was the strongest predictor of survival (χ(2) 61.1 and 53.8, respectively; P < 0.001), with LVEF (residual χ(2) 6.1, P < 0.05) adding significant prognostic value to the 6MWT model and ventilatory efficiency (the VE/VCO2 slope) (residual χ(2) 6.6, P < 0 .05) adding significant prognostic value to the CPX model.
HRR after the 6MWT is a powerful prognosticator that performs similarly to HRR after maximal exercise. If confirmed in subsequent studies, 6MWT HRR should replace 6MWT distance as the reference criterion 6MWT measure to consider when grading cardiovascular risk in HF patients.
" Combinations of the above stated definitions ≥3 regular oscillatory fluctuations in VE, with minimal average amplitude of ≥5 l/min persisting for ≥60% of the entire exercise time.    N60% duration; amplitude of N30% of the mean VE.   Oscillations ≥60% of entire exercise data at an amplitude N15%; amplitude of VE ≥5 l/min; a regular oscillation as defined by a SD of 3 consecutive cycle lengths within 20% of the average.    Cyclic fluctuation of VE at rest and during exercise with amplitude swings N30% of the mean VE, N15% for ≥60% of incremental exercise duration. "
"Finally, the model of parasympathetic nervous system (PNS) can be of independent interest in assessing the fitness of individuals. Recovery from physical activity (i.e., the health of PNS) is traditionally used for estimating cardiovascular health in clinical settings , . The ANS model developed in this work can be used to obtain stable estimates of PNS recovery in the natural environment. "
[Show abstract][Hide abstract] ABSTRACT: A variety of health and behavioral states can potentially be inferred from physiological measurements that can now be collected in the natural free-living environment. The major challenge, however, is to develop computational models for automated detection of health events that can work reliably in the natural field environment. In this paper, we develop a physiologically-informed model to automatically detect drug (cocaine) use events in the free-living environment of participants from their electrocardiogram (ECG) measurements. The key to reliably detecting drug use events in the field is to incorporate the knowledge of autonomic nervous system (ANS) behavior in the model development so as to decompose the activation effect of cocaine from the natural recovery behavior of the parasympathetic nervous system (after an episode of physical activity). We collect 89 days of data from 9 active drug users in two residential lab environments and 922 days of data from 42 active drug users in the field environment, for a total of 11,283 hours. We develop a model that tracks the natural recovery by the parasympathetic nervous system and then estimates the dampening caused to the recovery by the activation of the sympathetic nervous system due to cocaine. We develop efficient methods to screen and clean the ECG time series data and extract candidate windows to assess for potential drug use. We then apply our model on the recovery segments from these windows. Our model achieves 100% true positive rate while keeping the false positive rate to 0.87/day over (9+ hours/day of) lab data and to 1.13/day over (11+ hours/day of) field data.
Proceedings of the 13th international symposium on Information processing in sensor networks; 04/2014
[Show abstract][Hide abstract] ABSTRACT: Recently, it has become increasingly recognized that pulmonary hypertension (PH) is a particularly ominous consequence of left-sided heart failure (HF). The primary aim of this investigation was to assess the ability of key cardiopulmonary exercise testing (CPX) variables to detect elevated pulmonary pressures in a HF cohort.
This was a retrospective analysis of a prospectively collected database. Two hundred ninety-three subjects with HF (63 ± 10 years old, 79% male) underwent Doppler echocardiography to estimate resting pulmonary artery systolic pressure (PASP). Peak oxygen consumption (VO2), the minute ventilation/carbon dioxide production (VE/VCO2) slope, peak partial pressure of end-tidal CO2 (PETCO2) and exercise oscillatory ventilation (EOV) were determined.
Forty-six percent (n = 134) of the subjects presented with a PASP ≥40 mm Hg. A VE/VCO2 slope </≥36.0 was the best predictor of a PASP ≥40 mm Hg (odds ratio [OR] 12.1, 95% confidence interval [CI] 6.8-21.4; P < .001). Peak PETCO2 ≤34 mm Hg (OR 3.8, 95% CI 1.3-11.2; P < .001) and the presence of EOV (OR 3.2, 95% CI 1.8-5.8; P < .001) added significant diagnostic value.
Although CPX is an established prognostic assessment in the HF population, the results of the present investigation indicate that it may also have important diagnostic utility for PH.
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