基于数据挖掘的舒鹏教授治疗胃癌临床病案的回顾性研究
发布时间：2018-01-01 14:32
本文关键词：基于数据挖掘的舒鹏教授治疗胃癌临床病案的回顾性研究 出处：《南京中医药大学》2016年硕士论文 论文类型：学位论文
【摘要】：研究目的以江苏省中医院舒鹏教授临床治疗胃癌的实践经验为基础,以数据挖掘技术为手段,对舒鹏教授近年来辨治胃癌的临床经验及学术思想进行归纳、探讨和分析,并进一步总结舒鹏教授治疗胃癌的经验及学术思想,以供同道借鉴,为提高中医药在胃癌治疗中的疗效做出努力。研究方法对舒鹏教授2012年1月至2015年1月门诊诊治的胃癌病案进行整理和收集,严格按照纳入标准和排除标准进行筛选,将符合标准的162例胃癌病案资料建立临床病案数据库,运用频数分布、聚类分析等方法着重挖掘病案中症状、辨证分型、方药之间的规律,结合舒鹏教授的临证经验及学术思想,对挖掘结果进行总结、归纳和分析。研究结果在舒鹏教授诊治的这162例胃癌患者中,男性107例,女性55例,年龄在25-85岁之间,平均年龄60±1.09岁。所有诊次症状中,频数芝10的有13种,分别为乏力(59例,36.42%)、纳差(54例,33.33%)、嗳气(31例,19.14%)、便溏(28例,17.28%)、泛酸(24例,14.81%)、畏寒(23例,14.20%)、便秘(12例,7.41%)、胃胀(16例,9.88%)、进食梗阻(13例,8.02%)、嘈杂(13例,8.02%)、呕吐(12例,7.41%)、失眠(11例,6.79%)、胃痛(10例,6.17%)。采用将中医证型规范成单证的方式,将单证按照虚证和实证进行分类,结果表明虚证中常见证型为脾胃气虚(54.32%)、脾胃虚寒(26.54%)及气阴两虚(19.14%)、胃阴虚(17.28%),而癌毒内聚(27.16%)、胃气郁滞(24.07%)及寒湿困脾(18.52%)、肝脾不调(12.35%)是主要的实证。舒鹏教授选用的中药共18类,其中频数在100次以上,频率在3%上的药物仅8类,累计频率占88.43%,分别为消食药、补虚药、化痰止咳平喘药、活血化瘀药、行气药、清热药、收涩药及温里药。舒鹏教授治疗胃癌使用药比较广泛,共使用中药152种,总计3354昧次,频率70%也仅有13味中药：炙甘草(98.15%)、炒稻芽(93.83%)、炒麦芽(93.83%)、黄芪(90.74%)、山楂(90.74%)、神曲(90.12%)、鸡内金(87.04%)、白术(82.72%)、陈皮(77.16%)、法半夏(76.54%)、党参(72.22%)、浙贝母(70.37%)。研究结论通过研究发现,胃癌的临床常见症状：为乏力、纳差、便溏、便秘、胃胀、失眠、畏寒、进食梗阻、嗳气、泛酸、嘈杂、胃痛及呕吐。常见证型以脾胃气虚、癌毒内聚、脾胃虚寒、胃气郁滞及气阴两虚、寒湿困脾、胃阴虚、肝脾不调为主。舒鹏教授治疗胃癌常用药物补虚药、消食药、化痰止咳平喘药、行气药、活血化瘀药、清热药、收涩药及温里药,如炙甘草、炒稻芽、炒麦芽、黄芪、山楂、神曲、鸡内金、白术、陈皮、法半夏、党参、浙贝母等。总体治法为健脾养胃,扶正固本为主,祛邪为辅。
[Abstract]:The purpose of the study is based on the practical experience of Jiangsu Province Traditional Chinese Medicine Hospital professor Shu Peng treatment of gastric cancer, according to data mining technology as a means of Professor Shu Peng's academic thought and clinical experience in treating gastric cancer were summarized, discussion and analysis, and further summarizes the experience and academic thoughts of professor Shu Peng in treatment of gastric cancer, for the colleagues to make efforts for reference. To improve the efficacy of traditional Chinese medicine in the treatment of gastric cancer. The research methods of Professor Shu Peng in January 2012 to January 2015 outpatient treatment of gastric cancer cases were collected and collected, in strict accordance with the inclusion criteria and exclusion criteria were selected to establish the clinical medical record database of medical records of 162 cases of gastric cancer will meet the standard, the use of frequency distribution, cluster analysis methods focus on the mining of medical records in the symptoms, syndromes, prescriptions between law, combined with Professor Shu Peng's academic thought and clinical experience, the results of data mining 杩涜鎬荤粨,褰掔撼鍜屽垎鏋，
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