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Record W3081304947 · doi:10.1177/2054358120951390

Feasibility Study of a Randomized Controlled Trial Investigating Renal Denervation as a Possible Treatment Option in Patients With Loin Pain Hematuria Syndrome

2020· article· en· W3081304947 on OpenAlexafffundabout
Bhanu Prasad, Maryam Jafari, Kaval Kour, Kunal Goyal, Francisco J. Blanco

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2020
Typearticle
Languageen
FieldMedicine
TopicVascular anomalies and interventions
Canadian institutionsCypress Health RegionRegina General Hospital
FundersUniversity of Saskatchewan
KeywordsMedicineRandomized controlled trialSurgeryDenervationClinical trialNephrologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Loin Pain Hematuria Syndrome (LPHS) is a poorly understood clinical condition characterized by severe pain localized to the kidney but in the absence of identifiable urinary tract disease. There is no consensus on optimal treatment strategies for LPHS. Case reports and series have shown renal denervation via catheter-based radiofrequency ablation to be an effective therapeutic option for the treatment of LPHS. To determine whether catheter-based renal denervation is a meaningful addition to the treatment options in these often-difficult-to-treat LPHS patients, a randomized clinical trial is needed. Prior to conducting a definitive trial that focuses on patient outcomes, ensuring the feasibility of undertaking such a trial is required. As such, we will conduct a single-center randomized control feasibility trial designed to determine viability and provide framework and direction for a larger trial. OBJECTIVE: The objective of the study is to determine whether conducting a randomized trial of renal denervation versus sham procedure is feasible in terms of recruitment and eligibility, and adequacy of follow-up in LPHS patients. DESIGN: Single-center double-blinded, parallel-group, partial crossover, sham-controlled, randomized feasibility trial of 10 LPHS patients. SETTING: Regina General Hospital in Regina, Saskatchewan, Canada. PATIENTS: Ten LPHS patients who require opioid therapy. MEASUREMENTS: The main feasibility outcome measures include proportion of target patients who undergo the procedure (treatment or sham) within 6 months; proportion of randomized participants (treatment or control) who entirely complete the follow-up measures at 6 weeks, 3 and 6 months; proportion of the participants who were randomized to control group, cross over after 6 months and opt-in renal denervation treatment; proportion of the crossover participants who complete the follow-up measures at 6 weeks, 3 and 6 months. Pain will be assessed using Brief Pain Inventory Score, McGill Pain Questionnaire, and a pain diary. Mood, disability, and quality of life will be measured by Center for Epidemiologic Studies Depression Scale, Oswestry Disability Index, EuroQol-5D, and Short Form Health Survey Questionnaire, respectively. METHODS: Eligible participants will be randomized into either renal denervation (treatment group) or a sham treatment (control group). Data (pain, quality of life, mood, disability) will be collected from both groups at baseline, 6 weeks, 3 and 6 months after the intervention. After the initial 6-month follow-up is over, the participants who received the sham procedure will cross over into the treatment group and will be followed for an additional 6 months in the same manner as the treatment group. Descriptive statistics will be used to report outcomes for all patients. LIMITATIONS: Single-center study, small sample size. CONCLUSIONS: The lessons learnt from this trial will lay the framework and direction for conducting a multisite randomized controlled trial involving a larger cohort of patients. TRIAL REGISTRATION: ClinicalTrials.gov (NCT04332731).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.046
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.063
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0070.004
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.025
GPT teacher head0.285
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized 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

Citations2
Published2020
Admission routes3
Has abstractyes

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