Cognitive effort decreases beta,alpha, and theta coherence and ends afterdischarges in human brain

ObjectiveMental activation has been reported to modify the occurrence of epileptiform activity. We studied its effect on afterdischarges.MethodIn 15 patients with implanted electrodes we presented cognitive tasks when afterdischarges occurred. We developed a wavelet cross-coherence function to analyze the electrocorticography before and after the tasks and compared findings when cognitive tasks did or did not result in afterdischarge termination. Six patients returned for functional MRI (fMRI) testing, using similar tasks.ResultsCognitive tasks often could terminate afterdischarges when direct abortive stimulation could not. Wavelet cross-coherence analysis showed that, when afterdischarges stopped, there was decreased coherence throughout the brain in the 7.13–22.53 Hz frequency ranges (p values 0.008–0.034). This occurred a) regardless of whether an area activated on fMRI and b) regardless of whether there were afterdischarges in the area.ConclusionsIt is known that cognitive tasks can alter localized or network synchronization. Our results show that they can change activity throughout the brain. These changes in turn can terminate localized epileptiform activity.SignificanceCognitive tasks result in diffuse brain changes that can modify focal brain activity. Combined with a seizure detection device, cognitive activation might provide a non-invasive method of terminating or modifying seizures.     

利用数据挖掘对某医院零加成后慢病门诊费用分析

目的： 通过分析该院药品零加成后慢病门诊费用变化，为后续医保费用管控及合理用药提供参考意见。方法： 使用数据挖掘方法，分别利用费用消耗占比、月度次均费用变化情况以及皮尔逊相关系数（Pearson Correlation Coefficient）分析各类费用变化情况及药品费用对其他费用的影响。结果： 次均总费用、次均西成药费用、次均中草药费用整体呈现下降的趋势，次均检查费用、次均检验费用、次均挂号费用、次均手术费用、次均麻醉费用、次均治疗费用呈现上升趋势。结论： 次均总费用下降主要是由于次均西成药费的下降所产生的，但是次均西成药费下降与次均麻醉费用、次均检验费用、次均检查费用上升是呈现相关性的，这也揭示了次均总费用下降速度慢于次均西成药费下降速度的原因。     

Data mining and analysis of scientific research data records on Covid-19 mortality,immunity, and vaccine development - In the first wave of the Covid-19 pandemic

Background and aimsCovid-19 is a global pandemic that requires a global and integrated response of all national medical and healthcare systems. Covid-19 exposed the need for timely response and data sharing on fast spreading global pandemics. In this study, we investigate the scientific research response from the early stages of the pandemic, and we review key findings on how the early warning systems developed in previous epidemics responded to contain the virus.MethodsWe conducted data mining of scientific literature records from the Web of Science Core Collection, using the topics Covid-19, mortality, immunity, and vaccine. The individual records are analysed in isolation, and the analysis is compared with records on all Covid-19 research topics combined. The data records are analysed with commutable statistical methods, including R Studio’s Bibliometrix package, and the Web of Science data mining tool.ResultsFrom historical analysis of scientific data records on viruses, pandemics and mortality, we identified that Chinese universities have not been leading on these topics historically. However, during the early stages of the Covid-19 pandemic, the Chinese universities are strongly dominating the research on these topics. Despite the current political and trade disputes, we found strong collaboration in Covid-19 research between the US and China. From the analysis on Covid-19 and immunity, we wanted to identify the relationship between different risk factors discussed in the news media. We identified a few clusters, containing references to exercise, inflammation, smoking, obesity and many additional factors. From the analysis on Covid-19 and vaccine, we discovered that although the USA is leading in volume of scientific research on Covid-19 vaccine, the leading 3 research institutions (Fudan, Melbourne, Oxford) are not based in the USA. Hence, it is difficult to predict which country would be first to produce a Covid-19 vaccine.ConclusionsWe analysed the conceptual structure maps with factorial analysis and multiple correspondence analysis (MCA), and identified multiple relationships between keywords, synonyms and concepts, related to Covid-19 mortality, immunity, and vaccine development. We present integrated and corelated knowledge from 276 records on Covid-19 and mortality, 71 records on Covid-19 and immunity, and 189 records on Covid-19 vaccine.     

Risk factors for complications and in-hospital mortality: An analysis of 19,834 open pelvic ring fractures

BackgroundOpen pelvic fractures are rare injuries, associated with high patient morbidity and mortality. Few studies have investigated the impact of patient demographics, comorbidities, and injury related factors on complication and mortality rates. The purpose of this study was to: (1) identify the overall incidence of complications and mortality after open pelvic fractures, (2) compare patient factors between those who did and did not develop complications, (3) identify perioperative independent risk factors for complications and mortality.MethodsA query was performed for patients with open pelvic fractures between 2007 and 2017 using the American College of Surgeons National Trauma Data Bank. Patient and injury specific variables were collected and complications were identified using International Classification of Disease Ninth and Tenth edition Codes. Patient demographic and perioperative data was compared using Fisher’s exact test and chi-square test for categorical variables, and Welch’s t-test for continuous variables. Using pooled data from multiple imputations, logistic regressions were used to calculate odds ratios and confidence intervals of independent risk factors for complications.ResultsA total of 19,834 open pelvic fracture cases were identified, with 9622 patients (48.5%) developing at least one complication. Patients who developed complications were older (35.0 vs 38.1 years), and had higher Injury Severity Scores (17.7 vs 26.5), lower Glasgow Coma Scores (14.2 vs 11.7), and a larger proportion presenting with hypotension (21% vs 6.9%). After pooled regression involving 19 factors, these were the strongest independent predictors of inpatient complication and mortality.ConclusionWe report a mortality rate of 14%, with an inclusive complication rate of 48.5%. Evaluating risk factors for morbidity and mortality for this devastating orthopaedic injury provides knowledge of an inherently sparse population.Level of EvidenceLevel II, Retrospective study.     

Examining the evolution and classification of player position using performance indicators in the National Rugby League during the 2015–2019 seasons

ObjectivesThis study aimed to: 1) examine recent seasonal changes in performance indicators for different National Rugby League (NRL) playing positions; and 2) determine the accuracy of performance indicators to classify and discriminate positional groups in the NRL.DesignRetrospective, longitudinal analysis of individual performance metrics.Methods48 performance indicators (e.g. passes, tackles) from all NRL games during the 2015–2019 seasons were collated for each player´s match-related performance. The following analyses were conducted with all data: (i) one-way ANOVA to identify seasonal changes in performance indicators; (ii) principal component analysis (PCA) to group performance indicators into factors; (iii) two-step cluster analysis to classify playing positions using the identified factors; and (iv) discriminant analysis to discriminate the identified playing positions.ResultsANOVA showed significant differences in performance indicators across seasons (F = 2.3–687.7; p = 0–0.05; partial η² = 0.00–0.075). PCA pooled all performance indicators and identified 14 factors that were included in the two-step cluster analysis (average silhouette = 0.5) that identified six positional groups: forwards, 26.7%, adjustables, 17.2%, interchange, 23.2%, backs, 20.9%, interchange forwards, 5.5% and utility backs, 6.5%. Lastly, discriminant analysis revealed five discriminant functions that differentiated playing positions.ConclusionsResults indicated that player’s performance demands across different playing positions did significantly change over recent seasons (2015–2019). Cluster analysis yielded a high-level of accuracy relative to playing position, identifying six clusters that best discriminated positional groups. Unsupervised analytical approaches may provide sports scientists and coaches with meaningful tools to evaluate player performance and future positional suitability in RL.     

医院共享数据库建设

在分析医院信息化建设存在问题的基础上，提出利用共享数据库来实现各个业务管理部门数据共享。重点介绍共享数据库及其功能模块、客户展示模块，引入共享数据库有利于实现全院数据的统一管理，为今后进行数据挖掘奠定基础。     

基于超效率DEA的天津市基本公共卫生配置资源效率研究

评价天津市各辖区基本公共卫生服务的资源配置效率,寻求有效的资源配置措施和方法,为进一步优化卫生资源配置提供参考依据。方法利用数据包络分析,对天津市16辖区的基本公共卫生服务进行效率评价。结果天津市基本公共卫生服务的资源配置效率整体不高,仅有5辖区达到了规模最优,多数区非DEA有效,且投入过剩与产出不足并存。结论为了达到最优的基本公共卫生服务效率,政府及各级基本公共卫生服务机构必须有效地完善、落实相关政策,优化资源投入结构,统筹地区差异,加强资源供给管理,提高资源利用效率。     

基于数据挖掘探索中医治疗新型冠状病毒肺炎的组方规律并验案分析一则＊

目的 总结中医治疗新冠肺炎处方的用药特点及组方规律，以期为临床遣方用药提供理论参考，更好地发挥中医药的防治优势。方法 基于中医传承辅助平台（V2.5），运用关联规则算法、复杂系统熵聚类等高级数据挖掘方法统计中医治疗新冠肺炎处方中的药物基本信息，并对其核心药物组合及组方规律进行分析。结果 共收集到中医治疗新冠肺炎的处方159首，涉及中药168味；高频药物有杏仁、半夏、甘草、茯苓、藿香等；核心药对有石膏-杏仁、半夏-茯苓、麻黄-杏仁等；潜在常用药对有附子-石膏、藿香-麻黄、连翘-蝉蜕等；基于无监督熵层次聚类分析得到新方4首。结论 中医治疗新冠肺炎的核心药物组合为麻杏石甘汤和藿朴夏苓汤，治则上以宣肺调气、分消祛湿、健脾益气、化痰开郁、清热解毒等法同用，扶正祛邪，肺脾胃同调；但临床还需兼顾其可能伤阴、结瘀、旁及肝肾的病机特点，中后期适当佐以养阴润燥、活血通络及调肝补肾之品，以防伤阴损阳、疫毒入血的重症转变。