The utility of renal venous renin studies in selection of patients with renal artery stenosis for angioplasty
Bibliographic record
Abstract
OBJECTIVES: Recent studies of renal artery stenosis (RAS) failed to demonstrate greater benefit from angioplasty in terms of blood pressure (BP) lowering than medical treatment. Not all RAS are haemodynamically significant and identification of patients likely to benefit from angioplasty remains essential. METHODS: We examined whether performing renal venous renin studies under stringent conditions might predict BP improvement. Patients with at least 60% RAS who underwent renal venous renin measurements in 2008-2013 were identified. Renal venous renin lateralization ratios (RVRRs) were calculated by dividing venous renin from the stenotic kidney with contralateral levels before and after stimulation with enalaprilat or captopril. Benefit was defined as BP less than 140/90 mmHg without medication, 10% decreased mean BP without increased daily defined doses (DDDs) or decreased DDD without a significant increase of mean BP. RESULTS: Twenty-eight patients were treated medically and 42 with angioplasty (median age 60.1 years, 41% male, 29% chronic kidney disease, 50% resistant hypertension). At 11.4 ± 3.3 months, 69% of patients treated with angioplasty had BP benefit compared with 25% with medical treatment (P < 0.001). Logistic regression identified resistant hypertension [odds ratio (OR) 0.18, 95% confidence interval (95% CI) 0.04-0.82, P = 0.03] and baseline DDD (OR 0.69, 95% CI 0.48-0.98, P = 0.04) as being negatively associated, and positive stimulated RVRR (OR 21.6, 95% CI 3.50-133.3, P = 0.001) positively associated with benefit from angioplasty. On multivariate logistic regression, only stimulated RVRR positivity predicted BP benefit (OR 20.5, 95% CI 2.9-145.0, P = 0.003). CONCLUSION: These findings suggest that a positive stimulated RVRR measured under optimal conditions may help to identify patients with RAS likely to improve from angioplasty.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".