Clinical Trial Data on Hemodialysis Modalities and Toxin Clearance

A prospective randomized study of 60 maintenance hemodialysis patients assigned to three treatment modalities. The dataset, authored by Peng Zhang and last updated in May 2026, contains results assessing the clearance of protein-bound toxins like p-cresyl sulfate and indoxyl sulfate, with analysis including multivariable regression and machine learning.

Use Cases

• Comparing the efficacy of different hemodialysis modalities (HDF, HD+HA130, HD+KHA130) based on the described clinical trial.
• Modeling the relationship between dialysis vintage and toxin clearance using the U-shaped pattern identified for PCS.
• Identifying key predictors (e.g., dialysis vintage, age, CRP) of p-cresyl sulfate clearance using machine learning methods like LASSO and Elastic Net.
• Investigating interaction effects between treatment modality and patient dialysis vintage for solutes like β2-microglobulin and indoxyl sulfate.

Strengths

• Data originates from a prospective randomized study with 60 patients, providing a structured clinical trial foundation.
• Analysis includes multiple statistical methods (multivariable linear regression, interaction analysis, machine learning) as described.
• Clear, significant results are reported, such as HD+KHA130 improving PCS clearance with a β of 45.26.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (537.3 KB), indicating limited scope.

Provenance

Source

figshare, author Peng Zhang

Collection Method

Prospective randomized clinical trial

Freshness

Last updated 2026-05-29 06:18:35; freshness should be verified.