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Record W3089211279 · doi:10.1097/gox.0000000000003023

Wide Awake Local Anesthesia No Tourniquet Forearm Triple Tendon Transfer in Radial Nerve Palsy

2020· article· en· W3089211279 on OpenAlexaff
Shalimar Abdullah, Amir Adham Ahmad, Donald H. Lalonde

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2020
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsSaint John Regional Hospital
Fundersnot available
KeywordsMedicineTourniquetRadial nerveLidocaineTendon transferAnesthesiaForearmThumbTendonWristSurgeryAnatomyExtensor Digitorum Communis

Abstract

fetched live from OpenAlex

Tendon transfer for radial nerve palsy is a common procedure done under general anesthesia. We describe a surgical technique of triple tendon transfer with wide awake local anesthesia no tourniquet (WALANT). We transfer flexor carpi radialis to extensor digitorum communis, palmaris longus to extensor pollicis longus, and pronator teres to extensor carpi radialis brevis. This is commonly known as the Brand transfer. Our anesthetic or WALANT solution consists of up to 200 mL of 1:400,000 epinephrine, 0.25% lidocaine buffered with sodium bicarbonate. This technique overcomes the problem of judging the appropriate amount of transfer tension by observing awake patients actively extend their fingers, thumb, and wrist during the surgery and making adjustments before we close the wound. In our experience, there is no need of brain retraining because a patient is able to immediately use the flexor muscles to perform extension movements. WALANT is a safe and viable option for radial nerve tendon transfers.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.261
Teacher spread0.238 · 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

Citations21
Published2020
Admission routes1
Has abstractyes

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