Arthritis & Rheumatism, Volume 62,
November 2010 Abstract Supplement

Abstracts of the American College of
Rheumatology/Association of Rheumatology Health Professionals
Annual Scientific Meeting
Atlanta, Georgia November 6-11, 2010.


Nocturnal Heart Rate Variability Parameters. A Potential Fibromyalgia Biomarker.

Lerma,  Claudia, Martinez,  Aline, Ruiz,  Natllely, Vargas,  Angelica, Infante,  Oscar, Martinez-Lavin,  Manuel

Background:

Researchers strive to identify biomarkers for fibromyalgia (FM). Heart rate variability (HRV) analyses provide a quantitative marker of autonomic nervous system activity. Several HRV studies in FM have described changes consistent with relentless sympathetic hyperactivity. Sleep is modulated by autonomic activity. Sleeping problems are prominent in FM.

Objective:

To explore different HRV parameters measured during sleeping hours as potential FM biomarkers.

Patients and Methods:

We studied 21 women with FM according to the 1990 ACR criteria and 21 age-matched healthy women. None of the participants was on any medication that could affect autonomic activity. All participants used a Holter monitor while sleeping at home. Calculations were done from 00.00 to 06.00 hours. The following time-domain HRV parameters were studied: mean NN interval (mean NN), standard deviation of the NN intervals (SDNN), mean standard deviation of the average NN intervals calculated over 5 minutes (SDANN), and finally a HRV parameter developed by one of the authors (CL); transient heart rate acceleration episodes (THRAE).

Statistical analysis:

Student T test compared parameters from both groups. The best cut-off point for each parameter was determined from ROC curves. Sensitivity, specificity, positive predictive value, negative predictive value and odds ratio were estimated for each parameter.

Results:

Are shown in tables 1 and 2. Both groups have similar demographic characteristics. HRV values clearly differentiated patients from controls. Nocturnal SDNN had the greatest odds ratio (12, with confidence intervals 95%= 3.2–44.9) followed by SDANN (8.5, CI 95%, 2.2–31.8)

Table 1. Demographic data and HRV analyses from 00.00 to 06.00 hr.

 FM n = 21Controls n = 21p
Age (years) ± SD32.7 ± 8.030.5 ± 7.60.37
Body mass index24.5 ± 4.625.2 ± 3.20.56
NN mean (ms)857 ± 92937 ± 1320.02
SDNN (ms)91 ± 22122 ± 33< 0.01
SDANN (ms)58 ± 2278 ± 280.03
THRAE23 ± 1441 ± 310.01

Table 2. Predictive values of the potential HRV biomarkers.

 Cutoff pointAUCSensitivity (%)Specificity (%)PPV (%)NPV (%)OR (CI 95%)
NN mean at night (ms)888.10.67716768705 (1.3–18.7)
SDNN (ms)113.10.798667728212 3.2–44.9)
SDANN (ms)68.80.71816771788.5 (2.2–31.8)
THRAE28.50.65765262693.5 (0.9–13.1)
AUC = area under ROC curve, PPV = positive predictive value, NPV = negative predictive value, OR = odds ratio.    

Conclusions:

We identify 4 nocturnal HRV parameters that differentiate FM patients from healthy individuals. Multivariate analysis of these values could possibly yield more discriminative information. The specificity of these findings for FM when compared to other painful rheumatic syndromes remains to be established.

To cite this abstract, please use the following information:
Lerma, Claudia, Martinez, Aline, Ruiz, Natllely, Vargas, Angelica, Infante, Oscar, Martinez-Lavin, Manuel; Nocturnal Heart Rate Variability Parameters. A Potential Fibromyalgia Biomarker. [abstract]. Arthritis Rheum 2010;62 Suppl 10 :808
DOI: 10.1002/art.28576

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