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Record W7117325385 · doi:10.1177/22925503251404418

Cubital Tunnel Release Under Local and Regional Anesthesia: A Scoping Review

2025· article· en· W7117325385 on OpenAlexaff
Madeline E. Hubbard, Amr AlMasri, Nasimul Huq

Bibliographic record

VenuePlastic Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsRegional Municipality of NiagaraMcMaster University
Fundersnot available
KeywordsCubital tunnel syndromeComplicationCubital tunnelDecompressionCINAHLPatient satisfactionUlnar nerveLocal anesthesia

Abstract

fetched live from OpenAlex

Introduction: Cubital tunnel syndrome (CuTS) occurs due to compression or traction of the ulnar nerve at the elbow. When conservative management fails, CuTS release (including decompression and transposition) can be performed. Recently, more research has investigated local anesthesia (LA) and regional anesthesia (RA) for CuTS release. The objective of this scoping review was to summarize current literature on the safety and efficacy of LA and RA for CuTS release. Methods: A scoping review was conducted following the PRISMA-ScR protocol and reporting guidelines. A search was conducted of MEDLINE, EMBASE, Web of Science and CINAHL based on the key concepts of CuTS release, and LA or RA. Covidence was used for abstract and full-text screening. Results: A total of 21 studies consisting of 1385 patients and 1406 elbows were included. Most studies were case series or cohort studies. Patients received LA in 15 studies ( n = 429 elbows), RA in nine studies ( n = 616 elbows) and general anesthesia (GA) in six studies ( n = 361 elbows). Complication rates after surgery were 2.9% for LA, 2.3% for RA, and 2.5% for GA. Overnight hospital stay was more often required in GA compared to RA. One study reported significantly less postoperative pain using LA compared to GA. Four studies reported preference for LA or had high satisfaction with their procedures. Conclusions: Regional and local anesthetic techniques are safe and feasible for CuTS release. They have similar complication rates to GA, but may offer additional benefits such as intraoperative feedback, and better postoperative pain management.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.028
GPT teacher head0.292
Teacher spread0.263 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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