目的:探讨中性粒细胞与高密度脂蛋白胆固醇比值(NHR)对冠心病(CHD)的预测价值。方法:研究940名研究对象,包括548例冠心病组以及392例对照组。相关性分析计算CHD与NHR的相关系数。最小绝对收缩和选择算子(LASSO)回归分析筛选潜在影响。...目的:探讨中性粒细胞与高密度脂蛋白胆固醇比值(NHR)对冠心病(CHD)的预测价值。方法:研究940名研究对象,包括548例冠心病组以及392例对照组。相关性分析计算CHD与NHR的相关系数。最小绝对收缩和选择算子(LASSO)回归分析筛选潜在影响。构建机器学习模型进行评估变量在诊断的重要性。采用ROC曲线分析危险因素对冠心病的预测能力。使用Spearman相关性分析来评估NHR与Gensini评分之间的关系。结果:相关性分析显示冠心病与NHR的相关系数为0.25,呈正相关(P Objective: To investigate the predictive value of the neutrophil-to-high-density lipoprotein cholesterol ratio (NHR) for coronary heart disease (CHD). Methods: A total of 940 subjects were studied, including 548 in the CHD group and 392 in the control group. Correlation analysis was conducted to calculate the correlation coefficient between CHD and NHR. LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis was performed to identify potential influencing factors. A machine learning model was constructed to evaluate the importance of variables in diagnosis. ROC (Receiver Operating Characteristic) curve analysis was used to assess the predictive ability of risk factors for CHD. Spearman correlation analysis was employed to evaluate the relationship between NHR and Gensini score. Results: Correlation analysis showed a positive correlation between CHD and NHR, with a correlation coefficient of 0.25 (P < 0.001). LASSO regression analysis revealed a significant association between NHR and CHD risk. Further analysis using machine learning algorithms demonstrated that NHR has good predictive value for CHD diagnosis. ROC curve analysis indicated that the combination of the top 7 most important risk factors improved the predictive value for CHD (AUC: 0.738, P < 0.001). Additionally, Spearman correlation analysis found that as NHR levels increased, the Gensini score also increased (r = 0.32, P < 0.001). Conclusion: NHR is an independent risk factor for CHD and is closely associated with both the prediction and SEVERITY of CHD. The XGBoost model shows good applicability for CHD and NHR.展开更多
目的:抑郁症发病率较高,常伴有不同程度的认知功能减退,指南推荐采用药物治疗合并心理治疗减缓抑郁症状。焦点解决团体治疗(solution focused group therapy,SFGT)是一种较新的团体心理治疗技术。本研究旨在探讨SFGT联用艾司西酞普兰与...目的:抑郁症发病率较高,常伴有不同程度的认知功能减退,指南推荐采用药物治疗合并心理治疗减缓抑郁症状。焦点解决团体治疗(solution focused group therapy,SFGT)是一种较新的团体心理治疗技术。本研究旨在探讨SFGT联用艾司西酞普兰与单一服用艾司西酞普兰对抑郁症患者抑郁症状和认知灵活性的影响。方法:纳入84例符合《疾病和有关健康问题的国际统计分类(第10版)》抑郁症诊断标准的患者,按照入组先后顺序将患者分为联合组(n=42)和对照组(n=42),对照组单一服用艾司西酞普兰,联合组在对照组的基础上联用SFGT,对患者进行为期8周的治疗。使用24项汉密尔顿抑郁量表(24-item Hamilton Depression Scale,HAMD-24)和认知灵活性问卷(Cognitive Flexibility Inventory,CFI)分别在基线时(T_(0))、第4周(T_(1))、第8周(T_(2))对患者进行测评,比较与分析2组患者抑郁症状和认知灵活性的差异。结果:在T_(2)时,联合组脱落8例,对照组脱落10例。2组患者在T0时HAMD、CFI总分和维度分的差异均无统计学意义(均P>0.05)。在T_(1)、T_(2)时,联合组患者的HAMD-24总分及焦虑躯体化、认知障碍、迟缓、绝望感等维度分均低于对照组,CFI总分及维度分均高于对照组,差异均具有统计学意义(均P<0.05)。结论:SFGT能够改善抑郁症患者抑郁症状中的焦虑躯体化症状、认知障碍、迟缓症状及绝望感症状,且能够提高认知灵活性。展开更多
文摘目的:探讨中性粒细胞与高密度脂蛋白胆固醇比值(NHR)对冠心病(CHD)的预测价值。方法:研究940名研究对象,包括548例冠心病组以及392例对照组。相关性分析计算CHD与NHR的相关系数。最小绝对收缩和选择算子(LASSO)回归分析筛选潜在影响。构建机器学习模型进行评估变量在诊断的重要性。采用ROC曲线分析危险因素对冠心病的预测能力。使用Spearman相关性分析来评估NHR与Gensini评分之间的关系。结果:相关性分析显示冠心病与NHR的相关系数为0.25,呈正相关(P Objective: To investigate the predictive value of the neutrophil-to-high-density lipoprotein cholesterol ratio (NHR) for coronary heart disease (CHD). Methods: A total of 940 subjects were studied, including 548 in the CHD group and 392 in the control group. Correlation analysis was conducted to calculate the correlation coefficient between CHD and NHR. LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis was performed to identify potential influencing factors. A machine learning model was constructed to evaluate the importance of variables in diagnosis. ROC (Receiver Operating Characteristic) curve analysis was used to assess the predictive ability of risk factors for CHD. Spearman correlation analysis was employed to evaluate the relationship between NHR and Gensini score. Results: Correlation analysis showed a positive correlation between CHD and NHR, with a correlation coefficient of 0.25 (P < 0.001). LASSO regression analysis revealed a significant association between NHR and CHD risk. Further analysis using machine learning algorithms demonstrated that NHR has good predictive value for CHD diagnosis. ROC curve analysis indicated that the combination of the top 7 most important risk factors improved the predictive value for CHD (AUC: 0.738, P < 0.001). Additionally, Spearman correlation analysis found that as NHR levels increased, the Gensini score also increased (r = 0.32, P < 0.001). Conclusion: NHR is an independent risk factor for CHD and is closely associated with both the prediction and SEVERITY of CHD. The XGBoost model shows good applicability for CHD and NHR.
文摘目的:抑郁症发病率较高,常伴有不同程度的认知功能减退,指南推荐采用药物治疗合并心理治疗减缓抑郁症状。焦点解决团体治疗(solution focused group therapy,SFGT)是一种较新的团体心理治疗技术。本研究旨在探讨SFGT联用艾司西酞普兰与单一服用艾司西酞普兰对抑郁症患者抑郁症状和认知灵活性的影响。方法:纳入84例符合《疾病和有关健康问题的国际统计分类(第10版)》抑郁症诊断标准的患者,按照入组先后顺序将患者分为联合组(n=42)和对照组(n=42),对照组单一服用艾司西酞普兰,联合组在对照组的基础上联用SFGT,对患者进行为期8周的治疗。使用24项汉密尔顿抑郁量表(24-item Hamilton Depression Scale,HAMD-24)和认知灵活性问卷(Cognitive Flexibility Inventory,CFI)分别在基线时(T_(0))、第4周(T_(1))、第8周(T_(2))对患者进行测评,比较与分析2组患者抑郁症状和认知灵活性的差异。结果:在T_(2)时,联合组脱落8例,对照组脱落10例。2组患者在T0时HAMD、CFI总分和维度分的差异均无统计学意义(均P>0.05)。在T_(1)、T_(2)时,联合组患者的HAMD-24总分及焦虑躯体化、认知障碍、迟缓、绝望感等维度分均低于对照组,CFI总分及维度分均高于对照组,差异均具有统计学意义(均P<0.05)。结论:SFGT能够改善抑郁症患者抑郁症状中的焦虑躯体化症状、认知障碍、迟缓症状及绝望感症状,且能够提高认知灵活性。
