Modeling Factors Associated with Dialysis Adequacy Using Longitudinal Data Analysis: Generalized Estimating Equation Versus Quadratic Inference Function.

IF 1.4 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Journal of research in health sciences Pub Date : 2023-06-01 DOI:10.34172/jrhs.2023.117
Khadije Gholian, Karimollah Hajian-Tilaki, Roghayeh Akbari
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Abstract

Background: In hemodialysis patients, changes in dialysis adequacy (DA) are examined longitudinally. The aim of this study was to determine factors affecting DA using the generalized estimating equation (GEE) and to compare them with the quadratic inference function (QIF).

Study design: A longitudinal study.

Methods: This longitudinal study examined the records of 153 end-stage renal disease (ESRD) patients. The longitudinal data on the DA and baseline demographic and clinical characteristics were obtained from patients' files. The GEE1, GEE2, and QIF models were fitted with different correlation structures, and then the best correlation structure was selected using the quasi-likelihood information criterion (QIC), Akaike information criterion (AIC), and Bayes information criterion (BIC) fitting criteria.

Results: The majority of patients (59.5%) had unfavorable DA (KT/V<1.2). Women and patients<60 years had more favorable DA. In the GEE model, the coefficients of female gender (β=0.079, 95% confidence interval [CI]: 0.032, 0.062), age at starting dialysis (β=-0.002, 95% CI: -0.004, -0.0001), hypertension (HTN, β=-0.055, 95% CI: -0.007, -0.103), diabetes (β=-0.088,95% CI: -0.021, -0.155), dialysis duration (β=0.132, 95% CI: 0.085, 0.178), and weight (β=-0.004, 95% CI: -0.006, -0.003) demonstrated a significant relationship with DA. The three models resulted in a similar estimate of regression coefficients. The relative efficiencies of QIF versus GEE1, QIF versus GEE2, and GEE2 versus GEE1 were 1.175, 1.056, and 1.113, respectively.

Conclusion: DA is not optimal in most hemodialysis patients, and gender, age at the start of dialysis, HTN, diabetes, dialysis duration, and weight had a significant association with DA. The three different models yielded quite similar coefficient estimates, but the QIF model resulted more efficient than GEE1 and GEE2.

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利用纵向数据分析与透析充分性相关的建模因素:广义估计方程与二次推理函数。
背景:在血液透析患者中,透析充分性(DA)的变化是纵向检测的。本研究的目的是利用广义估计方程(GEE)确定影响DA的因素,并将其与二次推理函数(QIF)进行比较。研究设计:纵向研究。方法:这项纵向研究检查了153例终末期肾病(ESRD)患者的记录。从患者档案中获得DA和基线人口统计学和临床特征的纵向数据。对GEE1、GEE2和QIF模型采用不同的相关结构进行拟合,然后利用准似然信息准则(QIC)、Akaike信息准则(AIC)和Bayes信息准则(BIC)拟合准则选择最佳的相关结构。结果:绝大多数患者(59.5%)有不良DA (KT/ v)。结论:大多数血液透析患者DA不理想,性别、透析开始年龄、HTN、糖尿病、透析时间、体重与DA有显著相关。三种不同的模型产生了相当相似的系数估计,但QIF模型的结果比GEE1和GEE2更有效。
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来源期刊
Journal of research in health sciences
Journal of research in health sciences PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
2.30
自引率
13.30%
发文量
7
期刊介绍: The Journal of Research in Health Sciences (JRHS) is the official journal of the School of Public Health; Hamadan University of Medical Sciences, which is published quarterly. Since 2017, JRHS is published electronically. JRHS is a peer-reviewed, scientific publication which is produced quarterly and is a multidisciplinary journal in the field of public health, publishing contributions from Epidemiology, Biostatistics, Public Health, Occupational Health, Environmental Health, Health Education, and Preventive and Social Medicine. We do not publish clinical trials, nursing studies, animal studies, qualitative studies, nutritional studies, health insurance, and hospital management. In addition, we do not publish the results of laboratory and chemical studies in the field of ergonomics, occupational health, and environmental health
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