摘要
目的:通过对2008—2012年辽宁省中医院重症医学科(Intensive Care Unit,ICU)收治的急性呼吸窘迫综合征(acute respiratory distress syndrome,ARDS)患者进行聚类分析,确定ARDS患者的中医证候规律。方法:根据本研究的病例纳入及排除标准,按照统一制定的调查表录入辽宁中医药大学附属医院2008—2012年ICU收治ARDS患者,通过聚类分析,明确患者转入、1周、2周时的证型分布情况。结果:转入时聚成6类、1周后聚成7类、2周时聚成5类。结论:①ARDS病位在肺,但其病理变化涉及多个脏腑,气、血、阴、阳均受累积;②随着ARDS发病时间的变化,证型也有明显的变化;③疾病初起,病机关键不外乎虚实两端:肺脏受邪,真元损伤,或阴阳不相维系,元气外脱;④疾病中期,正气损耗,气机郁滞,水饮、淤血病理产物积聚,邪气留恋而呈现虚实夹杂为主的病机特点;⑤疾病后期,病理产物积聚和气机郁滞日久,正气亏衰,阴液耗伤。
Objective : Based on the cluster analysis of acute respiratory distress syndrome (ARDS) patients in 2008 to 2012 in Liaoning Province Hospital of Traditional Chinese Medicine in intensive care medicine (ICU), the characteristics of TCM syndrome in ARDS patients was determined. Methods:According to the case criteria and exclusion criteria, ICU ARDS patients we~ enrolled in the unified questionnaire in Affiliated Hospital of Liaoning University of Traditional Chinese Medicine from 2008 to 2012, through cluster analysis, syndrome type distributions of patients entering ICU, 1 week, 2 weeks. Results : There were 6 clusters when entering ICU, 7 clusters 1 week later and 5 clusters 2 weeks liner. Conclusion : ①ARDS locates in the lung, but its pathological changes involves multiple organs, Qi, blood, Yin, Yang;②as ARDS onset time changes, the syndrome types also have obvious ehanges;③at the beginning of the disease, the key pathogenesis is deficiency and excess. Attacked by evils, lung was damaged and real vital Qi was damaged or Yin and Yang failed to control each other, leading to vital Qi depletion ; ④ in the metaphase, vital Qi was exhausted, resulting in Qi stagation, fluid retention and blood stasis accumulation. The pathogenesis characteristics was mix of deficiency and excess; ⑤in the late period of the disease, pathological product accumulation and Qi stagnation for a long time, the vital Qi was deficiency and Yin fluid was damaged.
出处
《辽宁中医药大学学报》
CAS
2013年第11期13-14,共2页
Journal of Liaoning University of Traditional Chinese Medicine
基金
辽宁省科技厅社发处资助项目(2011225016)
关键词
ARDS
证候规律
聚类分析
ARDS
syndromes distribution
cluster analysis