A Novel Data Mining Approach to the Identification of Effective Drugs or Combinations for Targeted Endpoints—Application to Chronic Heart Failure as a New Form of Evidence-based Medicine

Summary Background: Data mining is a technique for discovering useful information hidden in a database, which has recently been used by the chemical, financial, pharmaceutical, and insurance industries. It may enable us to detect the interesting and hidden data on useful drugs especially in the field of cardiovascular disease.Methods: & Results: We evaluated the current treatments for chronic heart failure (CHF) in our institute using a decision tree method of data mining and compared the results with those of large-scale clinical trials. We enrolled 1,100 patients with CHF (NYHA classes II–IV and EF < 40%) who were hospitalized at the National Cardiovascular Center during the past 31 months. Drugs prescribed at discharge were extracted from the clinical database. Both echocardiograms and plasma BNP level at 6–12 months after discharge were determined prospectively. It was found that beta-blockers, angiotensin converting enzyme inhibitors, and angiotensin II receptor antagonists independently improve both the plasma BNP level and %fractional shortening (FS), while oral inotropic agents increased the plasma BNP level and decreased %FS. These findings agree with evidence accumulated from several large-scale trials. Interestingly, statins, histamine receptor blockers, and alpha-glucosidase inhibitors also attenuated the severity of CHF, suggesting the possibility of new treatment of CHF.Conclusion: Clinical data mining using Japanese CHF patients yielded almost identical data to the results of large-scale trials, and also suggested novel and unexpected candidates for CHF therapy. Further validation of the data mining approved in the cardiovascular field is warranted.     

How cognitive reserve influences older adults’ cognitive state,executive functions and language comprehension: A structural equation model

Cognitive reserve has been defined as the individuals’ ability to tolerate age-related and neurodegenerative changes in the brain without developing clinical symptoms or signs of disease. Formal education, occupational attainment, and knowledge of other languages have been assessed as the most relevant factors determining cognitive reserve. The main objective of this study was to develop a structural equation model that reflects the direct influence of cognitive reserve on old adults’ general cognitive status and executive functioning, and indirectly on sentence comprehension performance through executive functions mediation. One hundred and fifty eight Spanish-speaking older adults, cognitively intact, were assessed to obtain cognitive reserve data, general cognitive status, executive functioning (inhibitory control, working memory and cognitive flexibility), and sentence comprehension measures. High indicators of adjustment of the proposed model were obtained. The most related factors to cognitive reserve were education and occupational attainment. As we hypothesize, cognitive reserve had a higher direct significant relation to cognitive status and, in a lesser extent, to executive functioning. Participants’ general cognitive status and executive function were high and directly related. Furthermore, cognitive reserve has an indirect positive relation to sentence comprehension via executive functions’ mediation.     

数据挖掘在艾滋病病人CD_~4+T淋巴细胞与机会性感染关系的应用研究

目的利用数据挖掘技术分析艾滋病(AIDS)病人CD4+T淋巴细胞与机会性感染的关系,以期对合并机会性感染的AIDS病人的早期预防性用药提供决策支持。方法使用数据挖掘中的C4.5决策树算法,分析重庆市公共卫生医疗救治中心2003-2008年的207例AIDS病人的相关数据。结果 AIDS病人的CD4+T淋巴细胞值在A(0-50)区间,合并感染卡氏肺孢子虫肺炎(PCP)机会很大(概率为82.35%)。如果没有感染PCP,但是感染了隐球性脑膜炎(NMY),其CD4+T淋巴细胞值在A(0-50)区间;既没有感染PCP,也没有感染NMY,但合并感染丙型肝炎(丙肝)及乙型肝炎(乙肝)者,其CD4+T淋巴细胞值在D(201-300)区间;没有感染PCP,也没有感染NMY,但合并感染丙肝未感染乙肝,其CD4+T淋巴细胞值在C(101-200)区间。结论通过使用数据挖掘技术中的决策树算法,得出AIDS病人CD4+T淋巴细胞值在某一个区间,更容易合并某一种机会性感染,CD4+T淋巴细胞值与机会性感染有着重要的关系。     

Coal mine dust lung disease in the modern era

Coal workers’ pneumoconiosis (CWP), as part of the spectrum of coal mine dust lung disease (CMDLD), is a preventable but incurable lung disease that can be complicated by respiratory failure and death. Recent increases in coal production from the financial incentive of economic growth lead to higher respirable coal and quartz dust levels, often associated with mechanization of longwall coal mining. In Australia, the observed increase in the number of new CWP diagnoses since the year 2000 has necessitated a review of recommended respirable dust exposure limits, where exposure limits and monitoring protocols should ideally be standardized. Evidence that considers the regulation of engineering dust controls in the mines is lacking even in high‐income countries, despite this being the primary preventative measure. Also, it is a global public health priority for at‐risk miners to be systemically screened to detect early changes of CWP and to include confirmed patients within a central registry; a task limited by financial constraints in less developed countries. Characteristic X‐ray changes are usually categorized using the International Labour Office classification, although future evaluation by low‐dose HRCT) chest scanning may allow for CWP detection and thus avoidance of further exposure, at an earlier stage. Preclinical animal and human organoid‐based models are required to explore potential re‐purposing of anti‐fibrotic and related agents with potential efficacy. Epidemiological patterns and the assessment of molecular and genetic biomarkers may further enhance our capacity to identify susceptible individuals to the inhalation of coal dust in the modern era.     

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.     

Effects of mining-derived metals on riffle-dwelling benthic fishes in Southeast Missouri, USA

We studied the ecological effects of mining-derived metals on riffle-dwelling benthic fishes at 16 sites in the Viburnum Trend lead–zinc mining district of southeast Missouri. Fish community attributes were compared to watershed features and to physical and chemical variables including metal concentrations in sediment pore water and fish. Ozark sculpin (Cottus hypselurus), rainbow darter (Etheostoma caeruleum), Ozark madtom (Noturus albater), and banded sculpin (Cottus carolinae) were the most abundant fishes collected. Species richness and density of riffle-dwelling benthic fishes were negatively correlated with metal concentrations in pore water and in fish. Sculpin densities were also negatively correlated with metal concentrations in pore water and in fish, but positively correlated with distance from mines and upstream watershed area. These findings indicate that metals associated with active lead–zinc mining adversely affect riffle-dwelling benthic fishes downstream of mining areas in the Viburnum Trend. Sculpins may be useful as a sentinel species for assessing mining-related impacts on fish communities.     

数据挖掘技术及其在医院管理里中的应用

随着中国加入WTO后,医院面临日趋激烈的竞争,医疗服务的激烈竞争迫使医院管理层寻找更有效的辅助决策技术来处理复杂的医疗事务,如何解决数据多到没时间去看的问题,数据挖掘技术就是医院管理者最好的选择。     

数据挖掘技术在中医医案的应用研究

医案是历代医家临床实践经验及学术思想的载体,伴随大数据时代的到来及数据挖掘技术的兴起,数据挖掘被广泛地应用于中医药领域,成为发掘与整理中医医案的实用工具。本文从中医药领域常用的数据挖掘技术、存在问题及对策3个方面进行综述,以期为中医医案的研究提供新的思路。     

中药酊剂临床外用技术规范(草案)

基于对中药酊剂外用技术的数据挖掘,结合临床实际应用研究,经外治学会专家多次论证,形成中药酊剂临床外用技术规范(草案),包括临床适用范围、操作步骤以及外用酊剂的方法、剂量、频率、时间、注意事项、不良反应及护理要点。以期规范中药外用酊剂的临床应用,提高其疗效并减少不良反应。     

基于数据挖掘的国医大师治疗心悸用药规律探讨

目的:基于中医传承软件系统探讨国医大师治疗心悸的用药规律。方法:收集整理《国医大师验案良方·心脑卷》中治疗心悸的病案并录入中医传承辅助平台,采用规则分析、改进互信息法、复杂系统熵聚类等数据挖掘方法,统计分析其中的用药规律。结果:分析纳入的83个病案得出149味中药,所用中药性味多为甘温,主要归心、肺、脾三经,包括丹参、黄芪、炙甘草、麦冬等高频次中药。提取置信度为1的丹参,五味子→麦冬组合,可窥见生脉饮的雏形并衍生出10个新方,新方可分为五类,分别为行气化痰类、滋阴养血类、温通心阳类、益气活血类和化痰祛瘀类。结论:国医大师治疗心悸有规律可循,主要以“益气通阳”“养阴补血”“化痰祛瘀”为组方规律,标本并治。