Optimal Timing for Dialysis Preparation in CKD

Background: Determining the optimal timing for dialysis preparation is a clinical challenge. As unplanned dialysis initiation increases morbidity and mortality, early planning is essential. This study aimed to develop a model to estimate the appropriate timing for dialysis preparation in patients with chronic kidney disease (CKD). Methods: We retrospectively analyzed CKD patients followed in division of nephrology for ≥1 year who progressed to end-stage kidney disease (ESKD) and started hemodialysis (HD) between January 2011 and June 2024. Those with prior renal replacement therapy (RRT) or who discontinued HD within three months were excluded. A multiple linear regression (MLR) model was developed to predict eGFR six months prior to HD initiation (eGFR_6M), considered the optimal time for dialysis preparation. Results: A total of 507 patients (299 males; mean age 61 ± 14 years) were included. The mean time from first nephrology visit to HD initiation was 69.0 ± 52.7 months. Significant predictors in the final MLR model included sex, impaired mobility, diabetes mellitus (DM), cardiovascular disease (CVD), dementia, ejection fraction (EF), blood urea nitrogen (BUN), and phosphorus (P). The equation was: eGFR_6M = 13.029 − 1.28 × (female) + 1.66 × (impaired mobility) + 0.903 × (DM) + 1.15 × (CVD) + 1.951 × (dementia) − 0.068 × (EF) + 3.528 × (BUN ≦60) + 2.564 × (P ≦5.5) The model demonstrated an adjusted R2 of 0.325 and a Durbin-Watson statistic of 2.009. A validation cohort of 50 patients under the same criteria showed a mean eGFR at 6 months before HD of 10.97 ± 3.60 mL/min/1.73 m2. Using the model, 74% (n = 37) of patients had predicted eGFR within ±3.60 mL/min/1.73 m2. Conclusion: This model may assist nephrologists in identifying the optimal timing for dialysis preparation and vascular access planning, potentially improving outcomes in CKD care. Table 1. Multivariate analysis of eGFR_6M - Variable B SE p-value Intercept 13.029 1.711 <0.001 Sex (Female) -1.280 0.440 0.004 Impaired mobility 1.660 0.633 0.009 DM 0.903 0.453 0.047 CVD 1.150 0.460 0.013 Dementia 1.951 0.986 0.049 Echocardiography_EF -0.068 0.021 0.002 BUN ≦ 60 mg/dL 3.528 0.481 <0.001 Phosphorus ≦ 5.5 mg/dL 2.564 0.660 <0.001

Authors

Institutions

Publication Details

Journal
Journal of the American Society of Nephrology
Published
2025-10-01
DOI
https://doi.org/10.1681/asn.2025apmdfygp
Primary Topic
Dialysis and Renal Disease Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimal Timing for Dialysis Preparation in CKD

Yong Seon Choi
Journal of the American Society of Nephrology
Dialysis and Renal Disease Management
article

Optimal Timing for Dialysis Preparation in CKD

Yong Seon Choi
article en

Abstract

Background: Determining the optimal timing for dialysis preparation is a clinical challenge. As unplanned dialysis initiation increases morbidity and mortality, early planning is essential. This study aimed to develop a model to estimate the appropriate timing for dialysis preparation in patients with chronic kidney disease (CKD). Methods: We retrospectively analyzed CKD patients followed in division of nephrology for ≥1 year who progressed to end-stage kidney disease (ESKD) and started hemodialysis (HD) between January 2011 and June 2024. Those with prior renal replacement therapy (RRT) or who discontinued HD within three months were excluded. A multiple linear regression (MLR) model was developed to predict eGFR six months prior to HD initiation (eGFR_6M), considered the optimal time for dialysis preparation. Results: A total of 507 patients (299 males; mean age 61 ± 14 years) were included. The mean time from first nephrology visit to HD initiation was 69.0 ± 52.7 months. Significant predictors in the final MLR model included sex, impaired mobility, diabetes mellitus (DM), cardiovascular disease (CVD), dementia, ejection fraction (EF), blood urea nitrogen (BUN), and phosphorus (P). The equation was: eGFR_6M = 13.029 − 1.28 × (female) + 1.66 × (impaired mobility) + 0.903 × (DM) + 1.15 × (CVD) + 1.951 × (dementia) − 0.068 × (EF) + 3.528 × (BUN ≦60) + 2.564 × (P ≦5.5) The model demonstrated an adjusted R2 of 0.325 and a Durbin-Watson statistic of 2.009. A validation cohort of 50 patients under the same criteria showed a mean eGFR at 6 months before HD of 10.97 ± 3.60 mL/min/1.73 m2. Using the model, 74% (n = 37) of patients had predicted eGFR within ±3.60 mL/min/1.73 m2. Conclusion: This model may assist nephrologists in identifying the optimal timing for dialysis preparation and vascular access planning, potentially improving outcomes in CKD care. Table 1. Multivariate analysis of eGFR_6M - Variable B SE p-value Intercept 13.029 1.711 <0.001 Sex (Female) -1.280 0.440 0.004 Impaired mobility 1.660 0.633 0.009 DM 0.903 0.453 0.047 CVD 1.150 0.460 0.013 Dementia 1.951 0.986 0.049 Echocardiography_EF -0.068 0.021 0.002 BUN ≦ 60 mg/dL 3.528 0.481 <0.001 Phosphorus ≦ 5.5 mg/dL 2.564 0.660 <0.001

Journal of the American Society of NephrologyVol. 36(10S)
Bucheon University (KR)
Openalex Percentile: Top 65%
Dialysis and Renal Disease Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.