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Record W2549314457 · doi:10.1097/prs.0000000000002747

Comparison of Ulnar Intrinsic Function following Supercharge End-to-Side Anterior Interosseous–to–Ulnar Motor Nerve Transfer: A Matched Cohort Study of Proximal Ulnar Nerve Injury Patients

2016· article· en· W2549314457 on OpenAlexaff
Heather L. Baltzer, Alice Woo, Christine Oh, Steven L. Moran

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsHudbay Minerals (Canada)University Health Network
Fundersnot available
KeywordsUlnar nerveSuperchargeMedicineAnatomyUlnar neuropathyMotor nerveElbowMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: There are few studies supporting supercharge end-to-side nerve transfer for high ulnar nerve injury. The current study hypothesized that patients with a supercharge end-to-side anterior interosseous nerve-to-ulnar motor nerve transfer would demonstrate superior return of intrinsic function compared with conventional treatment only. METHODS: A retrospective matched-cohort study matched supercharge end-to-side transfer patients based on age, level of injury, and mechanism to ulnar nerve injury patients who did not have the transfer. The primary outcome was return of ulnar intrinsic function, based on clinical examination and/or electromyography. Dichotomous and continuous variables were compared with Fisher's exact and t tests, respectively. RESULTS: Thirteen supercharge end-to-side patients were identified (>1 year follow-up). The average age of both cohorts was 35 years. Ulnar nerve transection above the proximal third of the forearm represented 54 percent of patients; compressive injuries represented 46 percent. Eleven supercharge end-to-side transfer patients (84 percent) demonstrated intrinsic function recovery compared with five (38 percent) non-supercharge end-to-side patients (p < 0.05). Average time to initial motor recovery was similar between the two groups (supercharge end-to-side, 2.9 months; non-supercharge end-to-side, 3.8 months; p > 0.2). Intrinsic function return was more likely following nerve transection with the supercharge end-to-side procedure (85 percent versus 14 percent; p = 0.03), whereas compression injuries had comparable intrinsic function return regardless of the supercharge end-to-side transfer (67 percent versus 67 percent; p = 1.0). CONCLUSIONS: This matched cohort study demonstrates that the supercharge end-to-side transfer results in increased ulnar intrinsic reinnervation following ulnar nerve injury. This finding may be most relevant following transection injuries. Improved outcomes associated with supercharge end-to-side and ulnar nerve repair warrant further investigation. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.027
GPT teacher head0.271
Teacher spread0.244 · 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 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

Citations103
Published2016
Admission routes1
Has abstractyes

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