期刊文献+

SCL-90量表评分与冠状动脉粥样硬化的相关性分析

Correlation Analysis between SCL-90 Scale Scores and Coronary Atherosclerosis
在线阅读 下载PDF
导出
摘要 目的:通过分析SCL-90量表评分与冠状动脉粥样硬化程度的相关性,探讨心理因素与冠心病的关系,并揭示其可能机制。方法:纳入50例2017年1月至2022年1月于镇江市第一人民医院心内科因疑诊冠心病而接受冠脉造影检查的住院患者,填写90项症状自评量表(SCL-90),最终30例患者满足入选条件,以量表得分评估10项心理因子分与冠状动脉粥样硬化程度之间的相关性。分组分析时选取22例术中诊断为冠脉粥样硬化或冠心病者为研究组,8例术中诊断为心肌桥或冠脉造影正常者为对照组。比较组间患者的一般临床资料和10项心理因子分结果。对Gensini评分与SCL-90量表因子分进行二变量Spearman相关分析,并将Gensini评分与SCL-90因子分在控制年龄性别的条件下进行偏相关分析。在控制性别的条件下将多项与冠心病存在关联的指标纳入偏相关分析矩阵,探索与SCL-90量表因子分存在相关性的指标。运用多元线性回归分析冠脉粥样硬化或冠心病的独立危险因素。结果:分组分析结果表明,冠脉明显病变组精神病因子分显著高于轻度病变组和对照组。抑郁因子分(r = 0.363, P = 0.048)、精神病因子分(r = 0.439, P = 0.015)与Gensini评分存在正相关性。且控制年龄和性别后抑郁因子分(r = 0.513, P = 0.005)、精神病因子分(r = 0.465, P = 0.013)与Gensini评分呈现出更强的相关性。多元回归分析表明,对于冠状动脉粥样硬化严重程度最具有预测价值的心理因素是抑郁(β = 0.512, T = 3.583, P = 0.001)。在控制了性别的情况下,精神病因子(r = 0.493, P = 0.007)和抑郁因子(r = 0.398, P = 0.033)与血清碱性磷酸酶水平也存在正相关性。结论:精神病因子、抑郁因子与冠状动脉粥样硬化程度正相关,其中抑郁为冠状动脉粥样硬化独立危险因素,具有一定预测价值。心理因素可能通过改变血清碱性磷酸酶水平间接促进冠脉粥样硬化进展。 Objective: To explore the relationship between psychological factors and coronary heart disease by analyzing the correlation between SCL-90 scores and the severity of coronary atherosclerosis, and to reveal the possible mechanisms. Methods: Fifty inpatients who underwent coronary angiography due to suspected coronary heart disease at the First People’s Hospital of Zhenjiang from January 2017 to January 2022 were enrolled. They completed the 90-item Symptom Checklist-90 (SCL-90). Finally, 30 patients met the inclusion criteria, and the correlation between the scores of 10 psycho-logical factors and the severity of coronary atherosclerosis was evaluated. Twenty-two patients with a diagnosis of coronary atherosclerosis or coronary heart disease during the operation were select-ed as the study group, and eight patients with a diagnosis of myocardial bridge or normal coronary angiography were selected as the control group. The general clinical data and the results of the 10 psychological factors were compared between the two groups. The bivariate Spearman correlation analysis was used to analyze the correlation between Gensini’s score and SCL-90 factor score, and the partial correlation analysis was performed to control for age and gender. Under the condition of controlling for gender, multiple variables associated with coronary heart disease were included in the partial correlation analysis matrix to explore the indicators that are correlated with SCL-90 fac-tor score. Multiple linear regression analysis was used to analyze the independent risk factors for coronary atherosclerosis or coronary heart disease. Results: The results of the grouping analysis showed that the scores of the psychotic factor in the severe coronary artery disease group were sig-nificantly higher than those in the mild coronary artery disease group and the control group. The depression factor score (r = 0.363, P = 0.048) and psychotic factor score (r = 0.439, P = 0.015) were positively correlated with the Gensini’s score. After controlling for age and gender, the factor scores for depression (r = 0.513, P = 0.005) and psychosis (r = 0.465, P = 0.013) showed a stronger correla-tion with Gensini’s score. The multiple regression analysis showed that depression (β = 0.512, T = 3.583, P = 0.001) was the psychological factor with the highest predictive value for the severity of coronary atherosclerosis. Under the condition of controlling for gender, the psychotic factor (r = 0.493, P = 0.007) and the depression factor (r = 0.398, P = 0.033) were positively correlated with the level of serum alkaline phosphatase. Conclusion: The psychotic factor and depression factor are positively correlated with the severity of coronary atherosclerosis, and depression is an independ-ent risk factor for coronary atherosclerosis with certain predictive value. Psychological factors may indirectly promote the progression of coronary atherosclerosis by altering the level of serum alka-line phosphatase.
出处 《临床医学进展》 2023年第6期10505-10514,共10页 Advances in Clinical Medicine
  • 相关文献

参考文献2

二级参考文献27

  • 1卢东裕,康瑶,白琳,刘芳,王小慧,张道杰.高效液相串联质谱仪氨基酸及酰基肉碱检测结果可比性分析[J].中国优生与遗传杂志,2020(8):924-926. 被引量:3
  • 2Brook RD, Yalavarthi S, Myles JD, et al. Determinants of vascular function in patinents with chronic gout. J Clin Hypertens (Green-wieh) ,2011,13:178-188.
  • 3Gertlcr MM, Garn SM, Levinc SA. Serum uric acid in relation to age and physique in health and in coronary heart disease. Ann Intern Med, 1951,34 : 1421-1431.
  • 4Kang DH. Potential role of uric acid at a risk factor for cardiovascular disease. Korean J Intern Med ,2010,25 : 18-20.
  • 5Kim SY, Guevara JP, Kim KM, et al. Hyperuricemia and coronary heart disease: a systematic review and meta-analysis. Arthritis Care Res( Hoboken), 2010,62 : 170-180.
  • 6De Luca G, Secco GG, Santagostino M, et al. Uric acid dose not affect the prevalence and extent of coronary artery disease. Results from a prospective study. Nutr Metab cardiovasc Dis, 2010,22:426-433.
  • 7Gensini GG. A more meaningful scoring system for determiuating the severity of coronary heart disease. Am J Cardiol, 1983, 51 : 606.
  • 8Skak-Nielsen H,Torp-Pedersen C, Finer N, et al. Uric acid as a risk factor for cardiovascular disease and mortality in overweight/ obese individuals. PLoS One, 2013, 8 :e59121.
  • 9Skinner KA,White CR, Patel D. et al. Nitrosation of uric acid by peroxynit_rite. Formation of vasoactive nitric oxide donor. J Biol Chem, 1998,273:24491-24497.
  • 10Jacob G, Elaine C, Justine D, et al. High-dose allopurinol improves endothelial function by profoundly reducing vascular oxidative stress and not by lowering uric acid. Circulation, 2006, 114:2508-2516.

共引文献27

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部