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  • 1. Mork, P.J.
    et al.
    Nilsson, Johan
    Stockholm University, Faculty of Social Sciences, Stress Research Institute.
    Lorås, H.W.
    Riva, Roberto
    Stockholm University, Faculty of Social Sciences, Department of Psychology.
    Lundberg, Ulf
    Stockholm University, Faculty of Social Sciences, Centre for Health Equity Studies (CHESS). Stockholm University, Faculty of Social Sciences, Department of Psychology.
    Westgaard, R.H.
    Heart rate variability in fibromyalgia patients and healthy controls during non-REM and REM sleep: a case–control study2013In: Scandinavian Journal of Rheumatology, ISSN 0300-9742, E-ISSN 1502-7732, Vol. 42, no 6, p. 505-508Article in journal (Refereed)
    Abstract [en]

    Objectives: To investigate heart rate variability (HRV) in fibromyalgia (FM) patients and healthy controls (HCs) during different sleep stages, and to examine the association of HRV with pain and sleep quality.

    Method: Polysomnography was recorded from 23 female FM patients and 22 age- and sex-matched HCs. HRV was recorded from bedtime until awakening including the standard deviation of normal-to-normal intervals (SDNN), the root mean square successive difference (RMSSD), and the low (LF; 0.04–0.15 Hz) and high (HF; 0.15–0.4 Hz) frequency power. Subjective scores of neck/shoulder pain and sleep quality were obtained at bedtime and awakening.

    Results: Both patients and HCs showed high incidence of arousals per hour (FM: 16 ± 9.7; HCs: 17 ± 11). RMSSD was lower in patients than HCs during non-rapid eye movement (non-REM) stage 2 (N2) sleep (mean ± SD; 30 ± 12 ms vs. 42 ± 13 ms, p < 0.002) and during REM sleep (23 ± 11 ms vs. 37 ± 16 ms, p < 0.003). HRV did not differ between groups during N3 sleep (p > 0.19 for all comparisons). In patients, SDNN, RMSSD, and HF power showed modest positive correlations with sleep quality (HF power during N3 sleep showed the highest correlation; Spearman’s ρ = 0.54) and modest negative correlations with neck/shoulder pain (RMSSD during N3 sleep showed the highest correlation with pain at bedtime; Spearman’s ρ = –0.51).

    Conclusions: RMSSD, indicative of parasympathetic predominance, is attenuated in FM patients compared to HCs during N2 sleep and REM sleep. This difference was not present for the HF component. HRV during sleep in FM patients is moderately and positively associated with sleep quality and moderately and negatively associated with neck/shoulder pain

  • 2. Wändell, P.
    et al.
    Andreasson, Anna
    Stockholm University, Faculty of Social Sciences, Stress Research Institute. Karolinska Institutet, Sweden.
    Hagström, H.
    Kapetanovic, M. C.
    Carlsson, A. C.
    The use of anthropometric measures in the prediction of incident gout: results from a Swedish community-based cohort study2019In: Scandinavian Journal of Rheumatology, ISSN 0300-9742, E-ISSN 1502-7732, Vol. 48, no 4, p. 294-299Article in journal (Refereed)
    Abstract [en]

    Objectives: To study associations between different anthropometric measures and incident gout, and to find the best predictive measure.

    Method: We used the baseline investigation from the Malmo Diet and Cancer study, excluding cases of prevalent gout (n = 28 081). Cox regression for each anthropometric measurement was calculated per standard deviation increment for men and women, with hazard ratios (HRs) and 95% confidence intervals (CIs), using a hospital diagnosis of incident gout (M10) during follow-up as the outcome. Incremental C-statistics for each anthropometric measure were used to determine the measure with the best predictive capacity, in models adjusted for age, socio-economic data, lifestyle factors, comorbidities, and antihypertensive medications.

    Results: The study population included 11 049 men and 17 032 women, with 633 incident gout cases, 393 in men (3.6%) and 240 in women (1.4%). For both men and women, the five anthropometric measurements with highest C-statistics were weight, body mass index (BMI), waist circumference (WC), hip circumference, and waist-to-height ratio; in men, the measurement with the highest C-statistic was BMI (0.7361; fully adjusted HR 1.52, 95% CI 1.39-1.68), and in women WC (0.8085; fully adjusted HR 1.62, 95% CI 1.46-1.81). The increment in C-statistic with anthropometric measures was good, around 0.035. Waist-to-hip ratio, waist-to-hip-to-height ratio, body fat percentages, and especially A Body Shape Index had lower C-statistics.

    Conclusions: Both BMI and WC showed good predictive ability for incident gout. The clinically used cut-offs for BMI and WC appeared to be relevant in the assessment of increased risk of gout.

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