Evidence map›Paper›PMID 37571953›Full record

ArticleJournal of research in health sciences2023

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

Khadije Gholian, Karimollah Hajian-Tilaki, Roghayeh Akbari

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Article in Journal of research in health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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3 authors.

Khadije GholianStudent Research Center, Research Institute, Babol University of Medical Sciences, Babol, Iran.ORCID 0009-0000-1324-4846
Karimollah Hajian-TilakiDept of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran.ORCID 0000-0001-6830-1916
Roghayeh AkbariDept of Internal Medicine, Ayatollah Rohani Hospital, Babol University of Medical Sciences, Babol, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 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

designA longitudinal study.

methodsThis 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.

resultsThe 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.

conclusionDA 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.

Indexed as

Diabetes MellitusHypertensionKidney Failure, ChronicBayes TheoremFemaleHumansLongitudinal StudiesMaleMiddle AgedRenal DialysisEnd-stage renal diseaseHemodialysisLongitudinal studyRenal dialysisRisk factors

Identifiers

PMID37571953
PMCPMC10422138

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