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Record W2246352995 · doi:10.1093/ndt/gfv169.15

FP091A POSITIVE RENAL VEIN RENIN LATERALISATION RATIO INDEPENDENTLY PREDICTS BLOOD PRESSURE BENEFIT FROM ANGIOPLASTY IN RENAL ARTERY STENOSIS: A RETROSPECTIVE STUDY

2015· article· en· W2246352995 on OpenAlexaff
Rémi Goupil, Diane Cowley, Martin Wolley, Ashraf Ahmed, Richard D. Gordon, Michael Stowasser

Bibliographic record

VenueNephrology Dialysis Transplantation · 2015
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMedicineRenal artery stenosisAngioplastyRenal veinRenal Artery ObstructionInternal medicineStenosisBlood pressureCardiologyRenal arteryVeinRetrospective cohort studyRenin–angiotensin systemKidney

Abstract

fetched live from OpenAlex

Introduction and Aims: Recent randomized trials failed to demonstrate greater benefit from angioplasty compared to medical treatment of renal artery stenosis (RAS). However, not all RAS are hemodynamically significant and identification of patients likely to benefit from angioplasty remains essential. In this regard, renal vein renin studies remain controversial and we examined whether performing them under stringent conditions might predict blood pressure (BP) improvement. Methods: Patients with RAS ≥ 60% who underwent renal vein renin studies in 2008-2013 were identified. Before the renal vein renin measurements, agents known to affect renin levels were withdrawn and replaced with non-interfering drugs. After a 5 days admission with a < 40 mmol/d sodium diet, patients were kept in a recumbent position from midnight and until the end of the procedure. Simultaneous renal and peripheral veins renin samples were collected before and after stimulation with enalaprilat/captopril. Lateralisation ratios (RVRR) were calculated by dividing renin levels ipsilateral to the RAS with contralateral levels and a positivity was ≥ 1.5. Beneficial clinical response was defined as BP < 140/90 mmHg without medication, 10% decreased mean BP without increased daily defined doses (DDD) or decreased DDD without significant increase of mean BP. Variables associated with clinical response were analysed by logistic regression.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.242
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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