Fractal analysis and recurrence quantification analysis of heart rate and pulse transit time for diagnosing chronic fatigue syndrome

2002 ◽  
Vol 12 (4) ◽  
pp. 264-272 ◽  
Author(s):  
Jochanan E. Naschitz ◽  
Edmond Sabo ◽  
Shaul Naschitz ◽  
Itzhak Rosner ◽  
Michael Rozenbaum ◽  
...  
Keyword(s):  
Heart Rate ◽  
Chronic Fatigue Syndrome ◽  
Transit Time ◽  
Fractal Analysis ◽  
Pulse Transit Time ◽  
Chronic Fatigue ◽  
Recurrence Quantification Analysis ◽  
Fatigue Syndrome ◽  
Recurrence Quantification ◽  
Quantification Analysis

Search for disease-specific cardiovascular reactivity patterns: developing the methodology

2004 ◽  
Vol 108 (1) ◽  
pp. 37-46 ◽  
Author(s):  
Jochanan E. NASCHITZ ◽  
Michael ROZENBAUM ◽  
Madeline FIELDS ◽  
Hillel ISSEROFF ◽  
Sean ENIS ◽  
...  
Keyword(s):  
Heart Rate ◽  
Transit Time ◽  
Cardiovascular Reactivity ◽  
Pulse Transit Time ◽  
Chronic Fatigue ◽  
Tilt Test ◽  
Discriminant Score ◽  
Mixed Control ◽  
Fatigue Syndrome ◽  
Disease Specific

Aberrations of CVR (cardiovascular reactivity), an expression of autonomic function, lack specificity for a particular disorder. Recently, a CVR pattern particular to chronic fatigue syndrome has been observed. In the present study, we aimed to develop methodologies for assessing disease-specific CVR patterns. As a prototype, a population of 50 consecutive patients with FMF (familial Mediterranean fever) was studied and compared with control populations. A 10 min supine/30 min head-up tilt test with recording of the heart rate and blood pressure or the pulse transit time was performed. Five studies were conducted applying different methods. In each study, statistical analysis identified independent predictors of CVR in FMF. Based on regression coefficients of these predictors, a linear DS (discriminant score) was computed for every subject. Each study established an equation to assess CVR, calculate DS for FMF and determine the sensitivity and specificity of the DS cut-off. In each of the five studies, abnormal CVR was observed in FMF patients. The best accuracy (88% sensitivity and 90.1% specificity for FMF) was obtained by a method based on beat-to-beat heart rate and pulse transit time recordings. Data was processed by fractal and recurrence quantitative analysis with recordings in FMF patients compared with a mixed control population. Identification of disease-specific CVR patterns was possible with the methodologies described in the present study. In FMF, disease-specific CVR may be explained by the interplay between neuroendocrine loops specific to FMF with cardiovascular homoeostatic mechanisms. Recognition of disease-specific CVR patterns may advance the understanding of homoeostatic mechanisms and have implications in clinical practice.

scholarly journals Reduced heart rate variability predicts fatigue severity in individuals with chronic fatigue syndrome/myalgic encephalomyelitis

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Rosa María Escorihuela ◽  
Lluís Capdevila ◽  
Juan Ramos Castro ◽  
María Cleofé Zaragozà ◽  
Sara Maurel ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Chronic Fatigue Syndrome ◽  
Frequency Domain ◽  
Chronic Fatigue ◽  
Myalgic Encephalomyelitis ◽  
Healthy Controls ◽  
Fatigue Syndrome ◽  
Potential Biomarker ◽  
Fatigue Severity

Abstract Background Heart rate variability (HRV) is an objective, non-invasive tool to assessing autonomic dysfunction in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME). People with CFS/ME tend to have lower HRV; however, in the literature there are only a few previous studies (most of them inconclusive) on their association with illness-related complaints. To address this issue, we assessed the value of different diurnal HRV parameters as potential biomarker in CFS/ME and also investigated the relationship between these HRV indices and self-reported symptoms in individuals with CFS/ME. Methods In this case–control study, 45 female patients who met the 1994 CDC/Fukuda definition for CFS/ME and 25 age- and gender-matched healthy controls underwent HRV recording-resting state tests. The intervals between consecutive heartbeats (RR) were continuously recorded over three 5-min periods. Time- and frequency-domain analyses were applied to estimate HRV variables. Demographic and clinical features, and self-reported symptom measures were also recorded. Results CFS/ME patients showed significantly higher scores in all symptom questionnaires (p < 0.001), decreased RR intervals (p < 0.01), and decreased HRV time- and frequency-domain parameters (p < 0.005), except for the LF/HF ratio than in the healthy controls. Overall, the correlation analysis reached significant associations between the questionnaires scores and HRV time- and frequency-domain measurements (p < 0.05). Furthermore, separate linear regression analyses showed significant relationships between self-reported fatigue symptoms and mean RR (p = 0.005), RMSSD (p = 0.0268) and HFnu indices (p = 0.0067) in CFS/ME patients, but not in healthy controls. Conclusions Our findings suggest that ANS dysfunction presenting as increased sympathetic hyperactivity may contribute to fatigue severity in individuals with ME/CFS. Further studies comparing short- and long-term HRV recording and self-reported outcome measures with previous studies in larger CFS/ME cohorts are urgently warranted.

Is physical deconditioning a perpetuating factor in chronic fatigue syndrome? A controlled study on maximal exercise performance and relations with fatigue, impairment and physical activity

2001 ◽  
Vol 31 (1) ◽  
pp. 107-114 ◽  
Author(s):  
E. BAZELMANS ◽  
G. BLEIJENBERG ◽  
J. W. M. VAN DER MEER ◽  
H. FOLGERING
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Chronic Fatigue Syndrome ◽  
Physical Fitness ◽  
Maximal Exercise ◽  
Negative Relationship ◽  
Chronic Fatigue ◽  
Controlled Study ◽  
Fatigue Syndrome ◽  
Physical Deconditioning

Background. Chronic fatigue syndrome (CFS) patients often complain that physical exertion produces an increase of complaints, leading to a greater need for rest and more time spent in bed. It has been suggested that this is due to a bad physical fitness and that physical deconditioning is a perpetuating factor in CFS. Until now, studies on physical deconditioning in CFS have shown inconsistent results.Methods. Twenty CFS patients and 20 matched neighbourhood controls performed a maximal exercise test with incremental load. Heart rate, blood pressure, respiratory tidal volume, O2 saturation, O2 consumption, CO2 production, and blood-gas values of arterialized capillary blood were measured. Physical fitness was quantified as the difference between the actual and predicted ratios of maximal workload versus increase of heart rate. Fatigue, impairment and physical activity were assessed to study its relationship with physical fitness.Results. There were no statistically significant differences in physical fitness between CFS patients and their controls. Nine CFS patients had a better fitness than their control. A negative relationship between physical fitness and fatigue was found in both groups. For CFS patients a negative correlation between fitness and impairment and a positive correlation between fitness and physical activity was found as well. Finally, it was found that more CFS patients than controls did not achieve a physiological limitation at maximal exercise.Conclusions. Physical deconditioning does not seem a perpetuating factor in CFS.

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