Does Iodinated Contrast Affect Residual Renal Function in Dialysis Patients? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: It is important for medical practitioners to be aware of the effect of iodinated contrast media on the residual renal function (RRF) of dialysis patients who require diagnostic or therapeutic imaging procedures. Preservation of RRF is important given that it is a robust predictor of higher survival. However, the absence of any effect would allow for easier diagnostic or therapeutic imaging tests to be performed. OBJECTIVE: This systematic review with meta-analysis will quantify the effect of intravascular administration of iodinated contrast on the residual function of adult dialysis patients. STUDY DESIGN: The selection criteria included adult (age ≥ 18 years) populations undergoing dialysis, who have been administered an intravascular contrast. The primary outcome was the measurement of residual function. Secondary outcomes were disease progression from peritoneal dialysis to hemodialysis, hospitalization following contrast administration, and all-cause mortality. RESULTS: Nine studies including 434 patients met the inclusion criteria. A meta-analysis was performed on 7 trials with complete quantitative data. The weighted difference in means was -0.16 mL/min (95% confidence interval -0.66 to 0.34 mL/min; p = 0.53), suggesting a small reduction in residual function following contrast administration. Significant heterogeneity in the data was observed, with a Cochran Q of 35.83 and an I2 of 83.25 (p < 0.0001). Subgroup analysis of retrospective versus prospective study design resolved heterogeneity. Few data were reported for clinical outcomes. LIMITATIONS: Small sample size of included studies. CONCLUSION: Intravascularly administered contrast media may not result in a significant reduction of residual function in dialysis patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.025 | 0.009 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".