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Query: UMLS:C0015674 (chronic fatigue syndrome)
 2,978 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

It is now the most common vector-borne disease in the United States. But because of misdiagnosis, the spread of this disease may also be more apparent than real. Lack of standardized serologic tests and varying clinical presentations do create confusion. Nevertheless, it is possible to distinguish Lyme disease from look-alike disorders, such as chronic fatigue syndrome and fibromyalgia.
Hosp Pract (Off Ed) 1993 Apr 15
PMID:Current understanding of Lyme disease. 846 65

This study aimed to develop a method to distinguish between the cardiovascular reactivity in chronic fatigue syndrome (CFS) and other patient populations. Patients with CFS (n = 23), familial Mediterranean fever (n = 15), psoriatic arthritis (n = 10), generalized anxiety disorder (n = 12), neurally mediated syncope (n = 20), and healthy subjects (n = 20) were evaluated with a shortened head-up tilt test (HUTT). A 10-minute supine phase of the HUTT was followed by recording 600 cardiac cycles on tilt, i. e., 5 to 10 minutes. Beat-to-beat heart rate (HR) and pulse transit time (PTT) were acquisitioned. Data were processed by recurrence plot and fractal analysis. Fifty-two variables were calculated in each subject. On multivariate analysis, the best predictors of CFS were HR-tilt-R/L, PTT-tilt-R/L, HR-supine-DET, PTT-tilt-WAVE, and HR-tilt-SD. Based on these predictors, the 'Fractal & Recurrence Analysis-based Score' (FRAS) was calculated: FRAS = 76.2 + 0.04*HR-supine-DET - 12.9*HR-tilt-R/L - 0.31*HR-tilt-SD - 19.27*PTT-tilt-R/L - 9.42* PTT-tilt-WAVE. The best cut-off differentiating CFS from the control population was FRAS = + 0.22. FRAS > + 0.22 was associated with CFS (sensitivity 70 % and specificity 88 %). The cardiovascular reactivity received mathematical expression with the aid of the FRAS. The shortened HUTT was well tolerated. The FRAS provides objective criteria which could become valuable in the assessment of CFS.
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PMID:Fractal analysis and recurrence quantification analysis of heart rate and pulse transit time for diagnosing chronic fatigue syndrome. 1235 73

Methods used for the assessment of cardiovascular reactivity are flawed by nonlinear dynamics of the cardiovascular responses to stimuli. In an attempt to address this issue, we utilized a short postural challenge, recorded beat-to-beat heart rate (HR) and pulse transit time (PTT), assessed the data by fractal and recurrence quantification analysis, and processed the obtained variables by multivariate statistics. A 10-min supine phase of the head-up tilt test was followed by recording 600 cardiac cycles on tilt, that is, 5-10 min. Three groups of patients were studied, each including 20 subjects matched for age and gender--healthy subjects, patients with essential hypertension (HT), and patients with chronic fatigue syndrome (CFS). The latter group was studied on account of the well-known dysautonomia of CFS patients, which served as contrast against the cardiovascular reactivity of the healthy population. A total of 52 variables of the HR and PTT were determined in each subject. The multivariate model identified the best predictors for the assessment of reactivity of healthy subjects vs CFS. Based on these predictors, the "Fractal & Recurrence Analysis-based Score" (FRAS) was calculated: FRAS=76.2+0.04*HR-supine-DET -12.9*HR-tilt-R/L -0.31*HR-tilt-s.d. -19.27*PTT-tilt-R/L -9.42*PTT-tilt-WAVE. The median values and IQR of FRAS in the groups were: healthy=-1.85 (IQR 1.89), hypertensives=+0.52 (IQR 5.78), and CFS=-24.2 (5.34) (HT vs healthy subjects: P=0.0036; HT vs CFS: P<0.0001). Since the FRAS differed significantly between the three groups, it appears likely that the FRAS may recognize phenotypes of cardiovascular reactivity.
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PMID:Assessment of cardiovascular reactivity by fractal and recurrence quantification analysis of heart rate and pulse transit time. 1257 89