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Background Pain has been frequently described as a clinical feature of COVID‐19, and the main pain syndromes that have been associated with the acute phase of this disease so far are headache, myalgia, arthralgia, and neuropathic pain. Understanding the characteristics of pain symptoms is crucial for a better clinical approach. Methods Patients who were diagnosed as having COVID‐19 using reverse transcription‐polymerase chain reaction were included in the study. Patients were asked to complete a 51‐item questionnaire via a phone interview, which included questions on demographics, acute COVID‐19 symptoms, the presence of pain symptoms, and their characteristics in the acute phase of COVID‐19. Results A total of 222 out of 266 patients with COVID‐19 participated in the study, yielding a response rate of 83.5%. A total of 159 patients reported at least one kind of pain syndrome with a prevalence of 71.6%. Myalgia was reported in 110 (49.6%) patients, headache in 109 (49.1%), neuropathic pain symptoms in 55 (24.8%), and polyarthralgia in 30 (13.5%) patients. A total of 66 patients reported only one type of pain, 46 reported two types, 42 reported three types, and five patients reported all four types of pain. Logistic regression analysis showed that there were significant associations between these pain syndromes and a strong association was found between neuropathic pain and headache. Conclusion Pain is a frequently observed symptom of mild‐to‐moderate COVID‐19. There are significant relationships between pain syndromes in COVID‐19, which may be due to a sequence of common etiologic factors. Significance This study described the main pain syndromes associated acute phase of mild‐to‐moderate COVID‐19 and its associated features. Headaches and pain of neuropathic characteristics were prevalent in this sample.

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BackgroundCompound muscle action potential (CMAP) scan and MScanFit have been used to understand the consequences of denervation and reinnervation. This study aimed to monitor these parameters during Wallerian degeneration (WD) after acute nerve transections (ANT).MethodsBeginning after urgent surgery, CMAP scans were recorded at 1–2 day intervals in 12 patients with ANT of the ulnar or median nerves, by stimulating the distal stump (DS). Stimulus intensities (SI), steps, returners, and MScanFit were calculated. Studies were grouped according to the examination time after ANT. Results were compared with those of 27 controls.ResultsCMAP amplitudes and MScanFit progressively declined, revealing a positive correlation with one another. SIs were higher in WD groups than controls. Steps appeared or disappeared in follow‐up scans. The late WD group had higher returner% than the early WD and control groups.ConclusionsMScanFit can monitor neuromuscular dysfunction during WD. SIs revealed excitability changes in DS.

ObjectiveTo investigate the possible subgroups of patients with Cluster Headache (CH) by using K-means cluster analysis.MethodsA total of 209 individuals (mean (SD) age: 39.8 (11.3) years), diagnosed with CH by headache experts, participated in this cross-sectional multi-center study. All patients completed a semi-structured survey either face to face, preferably, or through phone interviews with a physician. The survey was composed of questions that addressed sociodemographic characteristics as well as detailed clinical features and treatment experiences.ResultsCluster analysis revealed two subgroups. Cluster one patients (n = 81) had younger age at diagnosis (31.04 (9.68) vs. 35.05 (11.02) years; p = 0.009), a higher number of autonomic symptoms (3.28 (1.16) vs. 1.99(0.95); p < 0.001), and showed a better response to triptans (50.00% vs. 28.00; p < 0.001) during attacks, compared with the cluster two subgroup (n = 122). Cluster two patients had higher rates of current smoking (76.0 vs. 33.0%; p=0.002), higher rates of smoking at diagnosis (78.0 vs. 32.0%; p=0.006), higher rates of parental smoking/tobacco exposure during childhood (72.0 vs. 33.0%; p = 0.010), longer duration of attacks with (44.21 (34.44) min. vs. 34.51 (24.97) min; p=0.005) and without (97.50 (63.58) min. vs. (83.95 (49.07) min; p = 0.035) treatment and higher rates of emergency department visits in the last year (81.0 vs. 26.0%; p< 0.001).ConclusionsCluster one and cluster two patients had different phenotypic features, possibly indicating different underlying genetic mechanisms. The cluster 1 phenotype may suggest a genetic or biology-based etiology, whereas the cluster two phenotype may be related to epigenetic mechanisms. Toxic exposure to cigarettes, either personally or secondarily, seems to be an important factor in the cluster two subgroup, inducing drug resistance and longer attacks. We need more studies to elaborate the causal relationship and the missing links of neurobiological pathways of cigarette smoking regarding the identified distinct phenotypic classes of patients with CH.