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Record W4296050157 · doi:10.1177/20514158221122521

Recurrent triamcinolone injections for the treatment of Hunner’s lesions in bladder pain syndrome

2022· article· en· W4296050157 on OpenAlexaff
Sarah Neu, Jennifer A. Locke, Karla Rebullar, Lesley K. Carr, Sender Herschorn

Bibliographic record

VenueJournal of Clinical Urology · 2022
Typearticle
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineTriamcinolone acetonideAnesthesiaSurgeryOpioidLesionInternal medicine

Abstract

fetched live from OpenAlex

Objective: To determine if periodic triamcinolone injections into Hunner’s lesion in patients with bladder pain syndrome (BPS) reduces the need for opioids and other pain treatments. Methods: This is a retrospective analysis of 28 patients receiving endoscopic injections of 0.5–1.0 cc of triamcinolone acetate into Hunner’s lesions between 2010 and 2018. Wilcoxon signed-rank test was used to compare pain regimens before and after injections. Results: Median age at first triamcinolone injection was 63 (IQR 54–73). Median number of injections/patient was 3 (IQR 2–5.5), at a mean of 8-month intervals (2–80). The median number of pain treatments prior to triamcinolone was 4 (0–13), and 25% of patients were using opioids. With one or more injections, 92.9% had improvement in pain symptoms. There was a significant decrease in number of pain treatments following triamcinolone injections (4.1 vs 0.8, p = 0.006). Fifty-seven percent managed with triamcinolone injections alone, with no other pain treatments. Of the seven patients using opioids, four discontinued opioids altogether. Conclusions: Repeat triamcinolone injections into Hunner’s lesions are associated with a significant reduction in the number of pain treatments used for BPS, with an associated decrease in opioid use. Level of evidence: 4

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 integrity0.0000.001
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 head0.190
GPT teacher head0.469
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations1
Published2022
Admission routes1
Has abstractyes

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