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Abstract Background There is no standardized EEG duration guideline for detecting epileptiform abnormalities in patients, and research on this topic is scarce. This study aims to determine an optimal EEG duration for efficient detection of epileptiform abnormalities across different patient groups. Methods Retrospective analysis was performed on EEG recordings and clinical data of patients with the first seizure and epilepsy. Patients were categorized based on various factors, including the interval time since the last seizure, use of anti-seizure medication (ASM), and seizure frequency. The detection ratio (DR) of epileptiform abnormalities and latency time for their discovery were calculated. Statistical analyses, including chi-square tests, logistic regression, and survival analysis were utilized to illustrate DR and latency times. Results In whole-night EEG recordings, the DR was 37.6% for the first seizure group and 57.4% for the epilepsy group. Although the maximum latency times were 720 min in both two groups, DR in the first seizure group was distinctly decreased beyond 300 min. Significant factors influencing the DR included the use of ASM in the first seizure group (P

Abstract Background Headache disorders are widely prevalent and pose a considerable economic burden on individuals and society. Globally, misdiagnosis and inadequate treatment of primary headache disorders remain significant challenges, impeding the effective management of such conditions. Despite advancements in headache management over the last decade, a need for comprehensive evaluations of the status of primary headache disorders in China regarding diagnosis and preventative treatments persists. Methods In the present study, we analyzed the established queries in the Survey of Fibromyalgia Comorbidity with Headache (SEARCH), focusing on previous diagnoses and preventative treatment regimens for primary headache disorders. This cross-sectional study encompassed adults diagnosed with primary headache disorders who sought treatment at 23 hospitals across China between September 2020 to May 2021. Results The study comprised 2,868 participants who were systematically examined. Migraine and tension-type headaches (TTH) constituted a majority of the primary headache disorders, accounting for 74.1% (2,124/2,868) and 23.3% (668/2,868) of the participants, respectively. Medication overuse headache (MOH) affected 8.1% (231/2,868) of individuals with primary headache disorders. Over half of the individuals with primary headache disorders (56.6%, 1,624/2,868) remained undiagnosed. The previously correct diagnosis rates for migraine, TTH, TACs, and MOH were 27.3% (580/2,124), 8.1% (54/668), 23.2% (13/56), and 3.5% (8/231), respectively. The misdiagnosis of “Nervous headache” was found to be the most prevalent among individuals with migraine (9.9%, 211/2,124), TTH (10.0%, 67/668), trigeminal autonomic cephalalgias (TACs) (17.9%, 10/56), and other primary headache disorders (10.0%, 2/20) respectively. Only a minor proportion of individuals with migraine (16.5%, 77/468) and TTH (4.7%, 2/43) had received preventive medication before participating in the study. Conclusions While there has been progress made in the rate of correct diagnosis of primary headache disorders in China compared to a decade ago, the prevalence of misdiagnosis and inadequate treatment of primary headaches remains a veritable issue. As such, focused efforts are essential to augment the diagnosis and preventive treatment measures related to primary headache disorders in the future.

Abstract Background To date, there have been very few studies that have explored the relationship between headaches and computer use. The chief aim of this study is to investigate the prevalence of primary headache disorders among informational technology staff and identify the potential factors contributing to it. Methods This is a cross-sectional study based on annual health checks of employees from the information technology industry. We identified 2216 information technology staff members from Beijing by stratified random sampling who met the inclusion criteria. All participants were initially required to have a physical examination, after which they complete a general situation questionnaire that included a headache screening question. Those who had suffered from headache within the previous year also completed the questionnaire developed by Lifting the Burden. The International Classification of Headache Disorders 3(ICHD-3) criteria was used for the diagnosis of headache. Results A total of 2012 valid questionnaires (males, 1544 [76.7%]; females, 468 [23.3%]) were obtained from 2216 participants for a response rate of 90.8%. A total of 619 participants were diagnosed with primary headache, the one-year prevalence of which was 30.8%. Regarding the classification of the primary headache, 152 participants suffered from migraine, with a one-year prevalence of 7.6%; 440 and 27 suffered from tension-type headache and unclassified headaches, with one-year prevalences of 21.9 and 1.3%, respectively. Multivariate regression analysis showed that female gender was a risk factor for migraine and tension-type headache (OR 3.21[95% CI 2.28–4.53] and 1.88[95% CI 1.47–2.40], respectively). Age was also related to migraine and tension-type headache. The 41–50 age group had 2.02 times the probability of migraine, and the 31–40 age group had 1.89 times the probability of tension-type headaches compared to the 18–30 age group. Obesity and excessive computer use (more than 12 h per day) were also factors contributing to tension-type headache (OR: 2.61[95% CI 1.91–3.56] and 1.63[95% CI 1.18–2.25], respectively). Conclusions The one-year prevalence of primary headache in this population was 30.8%. The prevalence of tension-type headache in this population was higher than that in the general Chinese population. The occurrence of primary headache is correlated with many factors, among which excessive computer use significantly contributed to the risk of tension-type headache.

Abstract Background Recently, numerous biological experiments have indicated that microRNAs (miRNAs) play critical roles in exploring the pathogenesis of various human diseases. Since traditional experimental methods for miRNA-disease associations detection are costly and time-consuming, it becomes urgent to design efficient and robust computational techniques for identifying undiscovered interactions. Methods In this paper, we proposed a computation framework named weighted bipartite network projection for miRNA-disease association prediction (WBNPMD). In this method, transfer weights were constructed by combining the known miRNA and disease similarities, and the initial information was properly configured. Then the two-step bipartite network algorithm was implemented to infer potential miRNA-disease associations. Results The proposed WBNPMD was applied to the known miRNA-disease association data, and leave-one-out cross-validation (LOOCV) and fivefold cross-validation were implemented to evaluate the performance of WBNPMD. As a result, our method achieved the AUCs of 0.9321 and $$0.9173 \pm 0.0005$$ 0.9173±0.0005 in LOOCV and fivefold cross-validation, and outperformed other four state-of-the-art methods. We also carried out two kinds of case studies on prostate neoplasm, colorectal neoplasm, and lung neoplasm, and most of the top 50 predicted miRNAs were confirmed to have an association with the corresponding diseases based on dbDeMC, miR2Disease, and HMDD V3.0 databases. Conclusions The experimental results demonstrate that WBNPMD can accurately infer potential miRNA-disease associations. We anticipated that the proposed WBNPMD could serve as a powerful tool for potential miRNA-disease associations excavation.

Abstract Background Cluster headache (CH), a rare primary headache disorder, is currently thought to be a genetic susceptibility which play a role in CH susceptibility. A large numbers of genetic association studies have confirmed that the HCRTR2 (Hypocretin Receptor 2) SNP rs2653349, and the ADH4 (Alcohol Dehydrogenase 4) SNP rs1126671 and rs1800759 polymorphisms are linked to CH. In addition, the CLOCK (Circadian Locomotor Output Cycles Kaput) gene is becoming a research hotspot for CH due to encoding a transcription factor that serves as a basic driving force for circadian rhythm in humans. The purpose of this study was to evaluate the association between CH and the HCRTR2, ADH4 and CLOCK genes in a Chinese CH case–control sample. Methods We genotyped polymorphisms of nine single nucleotide polymorphisms (SNPs) in the HCRTR2, ADH4 and CLOCK genes to perform an association study on a Chinese Han CH case-control sample (112 patients and 192 controls),using Sequenom MALDI-TOF mass spectrometry iPLEX platform. The frequencies and distributions of genotypes and haplotypes were statistically compared between the case and control groups to identify associations with CH. The effects of SNPs on CH were further investigated by multiple logistic regression. Results The frequency of the HCRTR2 SNP rs3800539 GA genotype was significantly higher in cases than in controls (48.2% vs.37.0%). The GA genotypes was associated with a higher CH risk (OR = 1.483, 95% CI: 0.564-3.387, p = 0.038), however, after Bonferroni correction, the association lost statistical significance. Haplotype analysis of the HCRTR2 SNPs showed that among eight haplotypes, only H1-GTGGGG was linked to a reduced CH risk (44.7% vs. 53.1%, OR = 0.689, 95% CI =0.491~0.966, p = 0.030). No significant association of ADH4, CLOCK SNPs with CH was statistically detected in the present study. Conclusions Association between HCRTR2, ADH4,CLOCK gene polymorphisms and CH was not significant in the present study, however, haplotype analysis indicated H1-GTGGGG was linked to a reduced CH risk.