Incidental Atherosclerotic Renal Artery Stenosis Diagnosed at Cardiac Catheterization: No Difference in Kidney Function with or without Stenting
Bibliographic record
Abstract
BACKGROUND: The long-term kidney function of patients with atherosclerotic renal artery stenosis (ARAS) diagnosed incidentally at the time of cardiac catheterization is not well described despite the increasingly common practice of assessing these vessels at the time of cardiac investigation. METHODS: This is a retrospective analysis of a cohort identified prospectively at the time of non-emergent coronary angiography. Those with >or=50% ARAS were managed medically and underwent stenting if recommended by their nephrologist and/or cardiologist. Longitudinal regression analysis was used to compare the annualized change in estimated glomerular filtration rate (GFR) in stented and unstented patients. Cox regression analysis was used to determine the predictors of a decline in GFR by >or=25%. RESULTS: Of 140 patients, 67 (48%) were stented, mostly for preservation of kidney function (70.1%) and/or resistant hypertension (53.7%). Median follow-up time was 943 days. Stented patients were younger, had higher systolic blood pressure and more severe ARAS. The adjusted rate of change in GFR was -1.49 (95% CI -2.33 to -0.65) ml/min/1.73 m(2)/year in the unstented group, and -1.48 (95% CI -2.34 to -0.62) ml/min/1.73 m(2)/year in the stented group (p = 0.99). A decline of GFR >or=25% occurred in 42 (30%) patients; no patient required dialysis. Only the presence of cereberovascular disease was associated with this outcome (hazard ratio 2.52, 95% CI 1.56-5.41). CONCLUSION: We were unable to demonstrate a benefit or harm of renal artery stenting for ARAS, thus further increasing the uncertainty of the significance of these lesions and how they are best managed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".