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基于主成分分析法的肝衰竭患者疾病进展恐惧相关因素分析

Related factors of fear of disease progression in patients with liver failure based on principal component analysis

    摘要
  • 摘要:
    目的 采用主成分分析法改进的Logistic回归模型分析肝衰竭患者疾病进展恐惧(FoP)的相关影响因素。
    方法 本研究纳入肝衰竭患者122例，采用家庭坚韧力量表(FHI)、中文版全面健康素养调查量表、中文版正负性情绪量表(PANAS)、心理弹性量表(CD-RISC)、MOS社会支持量表(MOS-SSS)评估患者家庭支持、健康素养、负性情绪、心理弹性和社会支持情况; 采用汉化恐惧疾病进展简化量表(FoP-Q-SF)对患者FoP进行评估，以FoP-Q-SF评分为34分为临界值，将患者分为FoP组(n=74)和对照组(n=48)。对比2组患者临床资料和问卷调查评分情况; 对原始变量进行共线性诊断，采用主成分分析法改进的Logistic回归模型分析影响肝衰竭患者FoP的相关因素。
    结果 FoP组患者PANAS评分、肝衰竭分期晚期占比高于对照组，年龄、月收入、职工医保占比、健康素养评分、CD-RISC评分、FHI评分、MOS-SSS评分低于对照组，差异有统计学意义(P < 0.05)。采用主成分分析改进的Logistic回归分析得到5个独立相关因素，其中肝衰竭分期为晚期(OR=3.903)是肝衰竭患者FoP的独立危险因素，年龄(OR=0.901)、月收入>5 000元人民币(OR=0.171)、CD-RISC评分高(OR=0.874)、FHI评分高(OR=0.927)是肝衰竭患者FoP的独立保护因素(P < 0.05)。
    结论 肝衰竭患者FoP的发生是多种因素共同作用的结果，采用主成分分析法改进的Logistic回归模型可以消除不同因素之间的共线性关系，得到更具科学性的模型。

     

    Abstract:
    Objective To analyze the related influencing factors of fear of disease progression(FoP)in patients with liver failure using a modified Logistic regression model based on principal component analysis.
    Methods A total of 122 patients with liver failure were included in the study. The family support, health literacy, negative emotions, psychological resilience, and social support were evaluated using the Family Resilience Scale(FHI), Chinese version of the Comprehensive Health Literacy Survey Scale, Positive and Negative Affect Scale(PANAS), Connor Davidson Resilience Scale(CD-RISC) and MOS Social Support Scale (MOS-SSS). Fear of Progression Questionnaire-Short Form(FoP-Q-SF) was used to evaluate FoP condition, and the patients were divided into FoP group (n=74) and control group (n=48) with a FOP-Q-SF score of 34 as the critical value. The original variables were diagnosed collinearly, and the related factors affecting FoP in patients with liver failure were analyzed by using the Logistic regression model improved by principal component analysis.
    Results PANAS score and liver failure stage in the FoP group were higher than those in the control group, while the age, monthly income, employee medical insurance ratio, health literacy score, CD-RISC score, FHI score, and MOS-SSS score were lower than those in the control group (P < 0.05). Five independent related factors were analyzed using improved Logistic regression using principal component analysis. Among them, liver failure stage(advanced stage) (OR=3.903) was an independent risk factor for FoP in patients with liver failure, and age (OR=0.901), monthly income>5 000 Yuan RMB (OR=0.171), higher CD-RISC score (OR=0.874), and higher FHI score (OR=0.927) were independent protective factors for FoP in patients with liver failure (P < 0.05).
    Conclusion The occurrence of FoP in patients with liver failure is the result of a combination of multiple factors. The improved Logistic regression model using principal component analysis can eliminate the collinearity relationship among different factors and obtain a more scientific model.

     

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