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Abstract: Investigation into the Optimal Number of Intercostal Nerve Transfers for Musculocutaneous Nerve Re-Innervation

2016· article· en· W2523116463 on OpenAlexaboutno aff
Hyuma A. Leland, Daniel J. Gould, Mitchel Seruya

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2016
Typearticle
Languageen
FieldMedicine
TopicNerve Injury and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsIntercostal nervesMusculocutaneous nerveMedicineBrachial plexusBrachial plexus injuryElbow flexionMedian nerveUlnar nerveSurgeryElbowAnesthesia

Abstract

fetched live from OpenAlex

INTRODUCTION: Intercostal nerve transfer is one approach to neurotize the musculocutaneous nerve in brachial plexus injury. This study investigates outcomes following intercostal nerve transfer with a primary focus on the number of nerve transfers required to achieve optimal return of elbow flexion. MATERIALS AND METHODS: A systematic review of the literature was performed in accordance with PRISMA guidelines searching the MEDLINE/Pubmed and Google Scholar databases. Studies investigating intercostal nerve transfer for musculocutaneous innervation following brachial plexus injury in adults were included.1–5 Citations were cross-referenced and relevant studies included for analysis. All studies evaluated return of motor function based on the British Medical Research Council scale for muscle strength. Statistics were calculated using weighted means and the student’s t test with α ≤ 0.05. With β = 20%, power calculations demonstrated a minimum of 25 patients per study arm. RESULTS: Nine studies were included for analysis. A total of 641 patients were analyzed with average age 24.9 ± 5.4 years and 93% male population. The average time to surgery was 4.0 ± 1.5 months with average follow up of 41.3 ± 3.7 months. One study reported a single intercostal transfer resulting in restoration of M3 strength elbow flexion. Eight studies reported transfer of 2 intercostals in 414 patients with 76.6% of patients achieving ≥M3 flexion. Six studies reported transfer of 3 intercostals in 218 patients with 62.4% of patients achieving ≥M3 flexion. Finally, 6 (87.5%) of the 8 patients who underwent 4 intercostal nerve transfers achieved ≥M3 flexion. There was no statistically significant difference in return of ≥M3 function between 2 vs. 3 transfers (p = 0.4), 2 vs. 4 transfers (p = 0.4), and 3 vs. 4 transfers (p = 0.07). When comparing return of M4 vs. M3 function, more patients developed M4 function when transferring 2 intercostal nerves (p = 0.05), but there was no difference when transferring 3 intercostals (p = 0.2). CONCLUSION: Intercostal nerve transfer to the musculocutaneous nerve is an operation largely performed in 25-year-old males around 4 months after brachial plexus injury. No significant difference in return of ≥M3 elbow flexion was demonstrated with increased transfer of intercostal nerves. Based on equivalent outcomes, transfer of 2 intercostal nerves is recommended. DISCLOSURE/FINANCIAL SUPPORT:None of the authors has a financial interest in any of the products, devices, or drugs mentioned in this manuscript. REFERENCES: 1. Merrell GA, Barrie KA, Katz DL, Wolfe SW. Results of nerve transfer techniques for restoration of shoulder and elbow function in the context of a meta-analysis of the English literature. J Hand Surg Am. 2001;26(2):303–14. 2. Nagano A. Intercostal nerve transfer for elbow flexion. Tech Hand Up Extrem Surg. 2001;5(3):136–40. 3. Xiao C, Lao J, Wang T, Zhao X, Liu J, Gu Y. Intercostal nerve transfer to neurotize the musculocutaneous nerve after traumatic brachial plexus avulsion: a comparison of two, three, and four nerve transfers. J Reconstr Microsurg. 2014;30(5):297–304. 4. Coulet B, Boretto JG, Lazerges C, Chammas M. A comparison of intercostal and partial ulnar nerve transfers in restoring elbow flexion following upper brachial plexus injury (C5-C6+/-C7). J Hand Surg Am. 2010;35(8):1297–303. 5. Songcharoen P. Brachial plexus injury in Thailand: a report of 520 cases. Microsurgery. 1995;16(1):35–9

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)0.001
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 score0.489
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.300
Teacher spread0.275 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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