Evidence of symptomatic treatment for fibromyalgia (FM) is very low. Whole body cryotherapy (WBC) modulates different neurotransmitters, which might have a role in pain alleviation and could exert an effect on FM. Our aim was to evaluate the efficacy of WBC for the control of pain and impact of disease in FM. For this we run an open, randomized, crossover trial of Cryosense TCT™ cabin vs rest. Patients with FM according to ACR criteria were recruited consecutively from general practices. Trial endpoints were change (∆) in pain after 2 and 4 weeks, measured by a visual analogue scale (VAS), ∆ burden of disease, evaluated by the Fibromyalgia Impact Questionnaire (FIQ), and severity of FM, measured by the Combined Index of Severity of Fibromyalgia (ICAF). Within group differences, sequence and period effects were tested with Student’s t or Mann–Whitney U tests. Multiple linear regression models were used to adjust effect by baseline differences between groups. Sixty patients were included in the trial. A period effect was noted, with residual effect of WBC; therefore, only results from the first sequence were analysed. ∆VAS pain, ∆FIQ and ∆ICAF scores were significantly larger in the WBC group after the first period (3.0 vs 0.3 in ∆VAS pain; 32.1 vs 0.4 in ∆FIQ; 13.7 vs 0.07 in ∆ICAF; all p < 0.001), and were confirmed after adjustment. In conclusion, WBC with a Cryosense TCT cabin may be a useful adjuvant therapy for FM; further studies on long-term effect and compared to other physical therapies are warranted.Trial registration NCT03425903.Electronic supplementary materialThe online version of this article (10.1007/s00296-018-4176-0) contains supplementary material, which is available to authorized users.
We use recent unconditional quantile regression methods (UQR) to study the distributive effects of education in Argentina. Standard methods usually focus on mean effects, or explore distributive effects by either making stringent modeling assumptions, and/or through counter-factual decompositions that require several temporal observations. An empirical case shows the flexibility and usefulness of UQR methods. Our application for the case of Argentina shows that education contributed positively to increased inequality in Argentina, mostly due to the effect of strongly heterogeneous effects of education on earnings.
We propose a new command, , for explaining nonnormalities in linear panel-data models. The command performs tests to explore skewness and excess kurtosis, allowing researchers to identify departures from Gaussianity in both error components of a standard panel regression, separately or jointly. The tests are based on recent results by Galvao et al. (2013, Journal of Multivariate Analysis 122: 35–52) and extend the classical Jarque–Bera normality test for the case of panel data.
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