Abstract
IntroductionAt present, there is neither a laboratory test nor an imaging technique able to differentiate people with fibromyalgia (FM) from healthy controls. This lack of an objective biomarker has hampered FM recognition and research. Heart rate variability (HRV) analyses provide a quantitative marker of autonomic nervous system activity. Nighttime is a stable period in which most people are resting. Sleep is modulated by autonomic activity. Sleeping problems are prominent in FM. The objectives of this study are: 1) to explore different nocturnal HRV parameters as potential FM biomarkers and 2) to seek correlation between such HRV parameters and diverse FM symptoms.MethodsWe studied 22 women suffering from FM and 22 age-matched controls. All participants filled out several questionnaires related to FM symptoms. All participants used a Holter monitor over 24 hours while undertaking their routine activities during the day and while sleeping at their homes at night. Time-domain HRV parameters analyzed from 0000 to 0600 hours included, among others: mean normal-normal interbeat intervals (mean NN), standard deviation of the NN intervals (SDNN), and standard deviation of the successive NN differences (SDSD).ResultsNocturnal SDNN of less than 114 ms had the greatest predictive value to set apart patients from controls with an odds ratio of 13.6 (95% confidence interval: 3.9 to 47.8). In patients, decreased nighttime HRV markers indicative of sympathetic predominance had significant correlations with several FM symptoms: SDSD was associated with pain intensity (r = - 0.65, P = 0.001). SDNN correlated with constipation (r = - 0.53, P = 0.001), and mean NN with depression (r = - 0.53, P = 0.001). Controls displayed an opposite behavior. For them, increased nighttime SDNN correlated with Fibromyalgia Impact Questionnaire scores (r = 0.69, P = 0.001) and with other FM symptoms.ConclusionsNocturnal HRV indices indicative of sympathetic predominance are significantly different in FM women when compared to healthy individuals. In FM patients, these HRV parameters correlated with several symptoms including pain severity. Opposite associations were seen in controls. FM may not be just one end of a continuous spectrum of common symptoms. Nocturnal HRV analyses are potential FM biomarkers.
Highlights
At present, there is neither a laboratory test nor an imaging technique able to differentiate people with fibromyalgia (FM) from healthy controls
FM patients have less variability of heart rate than healthy controls, as evidenced by diminished standard deviation of the NN intervals (SDNN) pNN50 RMSSD and standard deviation of the successive NN differences (SDSD) parameters evaluated from the entire recording, as well as decreased SDNN (91.2 ms ± 21.5 versus 122.2 ms ± 32.0, P = 0.001), and SDANN (57.8 ms ± 19.2 versus 83.2 ms ± 35.9, P = 0.006) assessed during sleeping hours
Mean NN, mean normal-normal interbeat intervals (mean NN) interval; ms, milliseconds; pNN50, percentage of adjacent pairs of R-R intervals that differ by more than 50 ms from each other in a given time period; RMSSD, Square root of the mean of the squares of differences between adjacent NN intervals; SDANN, mean standard deviation of the average NN intervals calculated over 5 minutes; SDNN, standard deviation of the NN intervals; SDSD, standard deviation of the successive NN differences; Table 3 Receiver-operator characteristic curve analysis of heart rate variability indexes
Summary
There is neither a laboratory test nor an imaging technique able to differentiate people with fibromyalgia (FM) from healthy controls. This lack of an objective biomarker has hampered FM recognition and research. Heart rate variability (HRV) analyses provide a quantitative marker of autonomic nervous system activity. Patients who suffer from FM often have multiple complaints related to pain, sleep, fatigue, anxiety, and depression [1]. Most studies looking for autonomic performance in FM have used heart rate variability (HRV) analysis as a probing instrument. Almost all of these HRV studies were done during daytime. Due to the rapid advances of computer-based science, HRV analysis is becoming a useful non-invasive clinical tool to study autonomic nervous system performance
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