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Record W4415912630 · doi:10.1017/s0022215125103794

KTP laser therapy for refractory chronic myringitis: a case series and comparative outcomes

2025· article· en· W4415912630 on OpenAlexaff

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2025
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsRefractory (planetary science)Laser therapyLaserLaser treatmentSeries (stratigraphy)

Abstract

fetched live from OpenAlex

Abstract Objectives The aim of this study was to compare KTP (potassium titanyl phosphate) laser therapy and dextracin ear drops for treatment of chronic myringitis. Methods A case series involving 31 patients (18 laser group; 13 dextracin group). Primary outcomes included otorrhoea resolution, improvement in Chronic Ear Survey scores and endoscopic resolution. Secondary outcomes included hearing outcome and complications. Statistical analyses were performed using Mann-Whitney U , Wilcoxon signed-rank and Fisher’s exact tests. Results The laser group had a higher rate of otorrhoea resolution 66.67 per cent ( n = 12) vs 15.38 per cent ( n = 2) ( p = 0.006), showed significant improvement in symptom scores (median 31.43; p = 0.005) and medical resource use (16.67; p < 0.001) and had a significant myringitis area reduction of 31.84 per cent ( p < 0.001). No significant differences were observed in Chronic Ear Survey scores and area reduction in the dextracin group. One laser-group patient developed a permanent perforation. Conclusion KTP laser therapy is effective for refractory chronic myringitis, offering superior symptom relief and reduced healthcare utilisation compared to topical treatment.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.331
Teacher spread0.297 · 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 designCase report
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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