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Record W2058881666 · doi:10.2214/ajr.13.11935

Efficacy of Ultrasound-Guided Percutaneous Needle Treatment of Calcific Tendinitis

2014· review· en· W2058881666 on OpenAlexaff
K. Nithin Vignesh, Adam McDowall, Nicole Simunovic, Mohit Bhandari, Hema Choudur

Bibliographic record

VenueAmerican Journal of Roentgenology · 2014
Typereview
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineCalcific tendinitisPercutaneousRadiologyTendinitisUltrasoundSurgeryTendon

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to conduct a systematic review of the efficacy of ultrasound-guided needle lavage in treating calcific tendinitis. MATERIALS AND METHODS: Two independent assessors searched medical databases and screened studies for eligibility. RESULTS: Eleven articles were included. Heterogeneity among included studies precluded meta-analysis. Results of randomized controlled trials suggested no difference in pain relief between needle lavage and other interventions, but the studies were of low quality. CONCLUSION: Additional high-quality evidence is required to determine the relative efficacy of ultrasound-guided needle lavage in the management of calcific tendinitis of the rotator cuff.

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)0.007
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.383
Teacher spread0.329 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations30
Published2014
Admission routes1
Has abstractyes

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