Predictors and prognostic significance of the volume load trajectory: a longitudinal study in patients on peritoneal dialysis

Volume overload in peritoneal dialysis patients is a common issue that can lead to poor prognosis. We employed a group trajectory model to categorize volume load trajectories and examined the factors associated with each trajectory class to explore the impact of different trajectory groups on clinical prognosis and residual renal function (RRF). This single-center prospective cohort study included 214 patients on maintenance peritoneal dialysis within a tertiary hospital. The ratio of extracellular water to total body water was measured using Bioimpedance analysis. The SAS 9.4 PROC Traj procedure was used to examine the group-based trajectory of the patients. A multivariate logistic regression model was used to calculate the adjusted odds ratios (aOR) of the associated factors to predict the trajectory class of participants. The average age of the included patients was 53.56 (SD: 11.77) years, with a male proportion of 46.7% and a median follow-up time of 6 months. The normal stable group accounted for 35.05% of the total population and maintained a normal and stable level, the moderate stable group accounted for 52.8% of the total population and showed a slightly higher and stable level, and the high fluctuation group accounted for 12.15% of the total population and showed a high and fluctuating level. A multivariate logistic regression analysis revealed that age, diabetes, and albumin levels are significant factors influencing the categorization of volume load trajectories. There were statistically significant differences in both the technical survival rate and the loss of residual renal function among the three trajectory groups.

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Publication Details

Journal
Renal Failure
Published
2024-09-20
DOI
https://doi.org/10.1080/0886022x.2024.2405561
Citations
3
Primary Topic
Dialysis and Renal Disease Management
Type
article
Field-Weighted Citation Impact
1.02
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article

Predictors and prognostic significance of the volume load trajectory: a longitudinal study in patients on peritoneal dialysis

Dan Liu, Jiamei Xu, Guo Yanxiang, Tong Mengli et al.
3 citations
Renal Failure
Dialysis and Renal Disease Management
1.02
article

Predictors and prognostic significance of the volume load trajectory: a longitudinal study in patients on peritoneal dialysis

Dan Liu, Jiamei Xu, Guo Yanxiang, Tong Mengli, Ning Weng
article en
3 citations

Abstract

Volume overload in peritoneal dialysis patients is a common issue that can lead to poor prognosis. We employed a group trajectory model to categorize volume load trajectories and examined the factors associated with each trajectory class to explore the impact of different trajectory groups on clinical prognosis and residual renal function (RRF). This single-center prospective cohort study included 214 patients on maintenance peritoneal dialysis within a tertiary hospital. The ratio of extracellular water to total body water was measured using Bioimpedance analysis. The SAS 9.4 PROC Traj procedure was used to examine the group-based trajectory of the patients. A multivariate logistic regression model was used to calculate the adjusted odds ratios (aOR) of the associated factors to predict the trajectory class of participants. The average age of the included patients was 53.56 (SD: 11.77) years, with a male proportion of 46.7% and a median follow-up time of 6 months. The normal stable group accounted for 35.05% of the total population and maintained a normal and stable level, the moderate stable group accounted for 52.8% of the total population and showed a slightly higher and stable level, and the high fluctuation group accounted for 12.15% of the total population and showed a high and fluctuating level. A multivariate logistic regression analysis revealed that age, diabetes, and albumin levels are significant factors influencing the categorization of volume load trajectories. There were statistically significant differences in both the technical survival rate and the loss of residual renal function among the three trajectory groups.

Renal FailureVol. 46(2)
Zhejiang Chinese Medical University (CN)
Openalex Percentile: Top 21%
Dialysis and Renal Disease Management
1.02
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