Table 1_Risk factors and prognostic impact of continuous renal replacement therapy after h

A retrospective study of 213 heart transplant recipients from a single center between April 2018 and November 2023. The data likely contains perioperative variables used to model the risk of requiring continuous renal replacement therapy (CRRT) and its association with mortality. The model was developed by Xiang Wu and published under a CC-BY-4.0 license.

Use Cases

• Developing a risk prediction model for acute kidney injury requiring CRRT based on preoperative hemoglobin, VIS score, and lactate peak.
• Analyzing the association between intraoperative factors like cardiopulmonary bypass time and postoperative renal outcomes.
• Validating clinical prediction models using bootstrap resampling methods as described in the study.
• Studying the prognostic impact of CRRT on mortality after heart transplantation while adjusting for confounders.

Strengths

• The predictive model for CRRT was internally validated with 1,000 bootstrap resamples, suggesting methodological rigor.
• Model performance is quantified with specific metrics: an optimism-corrected AUC of 0.885 and a Hosmer-Lemeshow test p-value of 0.678.
• The study includes data on 213 patients with a clear outcome measure (30 patients, or 14.1%, received CRRT).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for some modeling tasks.
• The data is from a single-center retrospective study, which may limit generalizability.

Provenance

Source

figshare, author Xiang Wu.

Collection Method

Single-center retrospective study of patient records.

Time Range

April 2018 to November 2023.

Freshness

Last updated 2026-04-21 04:10:57; freshness should be verified.