Predictive model of variables associated with health-related quality of life in patients with advanced chronic kidney disease receiving hemodialysis
Predictive model of variables associated with health-related quality of life in patients with advanced chronic kidney disease receiving hemodialysis
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DOI：
10.1007/s11136-020-02454-0
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发表时间：
2020-03-02
影响因子：
3.5
通讯作者：
Collado-Boira, E.
中科院分区：
文献类型：
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作者：
Garcia-Martinez, P.;Temprado-Albalat, M. D.;Collado-Boira, E.
目的慢性肾脏病（CKD）影响全球10%以上的人口。健康相关生活质量（HRQoL）已被确定为评估慢性病患者治疗有效性的可靠指标，弹性可作为低压力水平和较高QoL的预测因子。本研究的目的是确定HRQoL，弹性，感知压力，和不同的社会人口和临床常规变量的晚期慢性肾脏病（ACKD）之间的关系。方法对西班牙巴伦西亚社区155例ACKD患者进行多中心、横断面和相关性研究。该研究的指标包括肾脏疾病生活质量36（KDQOL-36），感知压力量表10（PSS 10）和Connors-Davidson弹性量表（CD-RISC）。为了确定KDQOL-36量表和子量表上具有预测能力的变量，进行了多元回归分析。结果受试者平均年龄为67.39岁，68.4%为男性，29%为糖尿病患者，83.2%接受过动静脉血管通路置入术，Charlson合并症指数为6（SD = 2.09）。回归模型确定，年龄和韧性解释高达26.8%的KDQOL-36总分的方差。至于生活质量的身体成分，与其他临床条件，韧性，糖尿病的存在共病解释其方差的32.1%。结论心理弹性是影响健康相关生活质量的重要因素之一。因此，旨在提高恢复力水平的干预措施的发展可能对CKD患者的生活质量产生积极影响。
Purpose Chronic kidney disease (CKD) affects over 10% of the global population. Health-related quality of life (HRQoL) has been identified as a reliable indicator for assessing the effectiveness of treatment in chronic patients, and resilience as a predictor of low levels of stress and higher QoL. The aim of this research is to identify the relationship between HRQoL, resilience, perceived stress, and the different sociodemographic and clinical routine variables of advanced chronic kidney disease (ACKD). Methods Multicenter, cross-sectional, and correlational study with 155 ACKD patients in the Valencian Community (Spain). The measures for the study included the Kidney Disease Quality of Life 36 (KDQOL-36), the Perceived Stress Scale 10 (PSS10), and the Connors-Davidson Resilience Scale (CD-RISC). To identify the variables with predictive power over the scales and subscales of the KDQOL-36, multiple regression analyses were performed. Results Average participants' age was 67.39, 68.4% were male, 29% diabetic, and 83.2% had undergone arteriovenous vascular access placement with a Charlson Comorbidity Index of 6 (SD = 2.09). The regression models identified that age and resilience explained up to 26.8% of the variance of the KDQOL-36 total score. As for the physical component of QoL, comorbidity with other clinical conditions, resilience, and the presence of diabetes explained 32.1% of its variance. Conclusions Resilience was identified as one of the most important predictors of HRQoL. Thus, the development of interventions aiming to improve the level of resilience may have a positive impact over the quality of life of patients with CKD.