首次中风患者预后生活能力与临床中医症状的关系

Relationship between prognostic viability and clinical TCM symptoms in patients with first stroke

目的探讨首次中风患者预后生活能力与临床中医症状的关系。方法以2019年2月至2020年6月收治的196例首发中风患者作为研究对象,根据出院后1年改良Rankin量表(modified Rankin scale,mRS)评分进行分组,回顾性分析入院时中医症状发生情况,对中医症状与出院1年后mRS评分关系进行回归分析。结果196例患者入院时均出现半身不遂,发生率为100%,而其他中医症状在不同mRS评分中表现差异均具有统计学意义(P<0.05)。多元线性回归分析显示,恶心呕吐、半身麻木、头痛、痰多、烦躁以及气短与mRS评分有关(P均<0.05);进一步逐步回归分析显示,在排除干扰症状后,恶心呕吐、半身麻木、头痛、痰多、烦躁以及气短构成回归模型,该回归模型残差分布符合正态分布,对于预测mRS评分具有显著作用(F=20.338,P<0.001)。结论首次中风患者中医症状发生情况与1年后运动功能水平有关,这可能是预测患者预后的有效指标,可通过多中心大样本量分析获取有效预测模型。

Objective To explore the relationship between prognostic viability and clinical TCM symptoms in patients with first stroke.Methods 196 patients with first stroke admitted from February 2019 to June 2020 were divided into groups according to the modified Rankin scale(mRS)score one year after discharge.The occurrence of TCM symptoms at admission was retrospectively analyzed,and the relationship between TCM symptoms and mRS score one year after discharge was regressed.Results All 196 patients had hemiplegia at admission,and the incidence was 100%.There were significant differences in other TCM symptoms in different mRS scores(P<0.05).Multiple linear regression analysis showed that nausea and vomiting,half body numbness,headache,excessive phlegm,irritability and shortness of breath were related to mRS score(all P<0.05);Further stepwise regression analysis showed that after excluding interference symptoms,nausea and vomiting,half body numbness,headache,excessive phlegm,irritability and shortness of breath constituted the regression model.The residual distribution of the regression model accorded with the normal distribution and played a significant role in predicting mRS score(F=20.338,P<0.001).Conclusion The occurrence of TCM symptoms in patients with first stroke is related to the level of motor function after 1 year,which may be an effective index to predict the prognosis of patients.An effective prediction model can be obtained through multi center large sample size analysis.