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Record W4406844849 · doi:10.1016/j.ekir.2024.11.675

WCN25-3548 RENAL DENERVATION IN LOIN PAIN HEMATURIA SYNDROME: A FEASIBILITY RANDOMIZED CONTROL TRIAL

2025· article· en· W4406844849 on OpenAlexaff
Bhanu Prasad, Aarti Garg, Aditi Sharma, Francisco J. Blanco, Kunal Goyal, Mohammed Nayeemuddin

Bibliographic record

VenueKidney International Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicVascular anomalies and interventions
Canadian institutionsCypress Health RegionUniversity of SaskatchewanRegina General HospitalUniversity of Regina
Fundersnot available
KeywordsMedicineDenervationPain controlUrologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Loin pain hematuria syndrome (LPHS) is characterized by intractable, unilateral, or bilateral loin pain that is localized to the kidney but not caused by any identifiable urinary tract disease. Renal denervation (RDN) is a promising treatment option for LPHS. While observational studies have shown promise, no RCTs have been conducted to date. To address this gap, we conducted a feasibility study comparing RDN with a sham arm.

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)0.004
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.011
GPT teacher head0.306
Teacher spread0.295 · 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 designRandomized trial
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
Published2025
Admission routes1
Has abstractyes

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