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Record W4401768450 · doi:10.1177/17531934241270116

Clinical outcome of elbow extension restoration by posterior deltoid-to-triceps transfer in tetraplegia: a retrospective review of 51 patients

2024· review· en· W4401768450 on OpenAlexaboutno aff
Silvia Schibli, Sabrina Koch‐Borner, Ursina Arnet, Jan Fridén

Bibliographic record

VenueJournal of Hand Surgery (European Volume) · 2024
Typereview
Languageen
FieldMedicine
TopicNerve Injury and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDeltoid curveTetraplegiaElbowDeltoid musclePosterior shoulderRetrospective cohort studyPhysical therapySurgery

Abstract

fetched live from OpenAlex

In this study, we report the functional and perceived outcomes of 51 posterior deltoid-to-triceps transfers in patients with tetraplegia. With a minimum follow-up of 12 months, patients were divided into two subcategories based on preoperative posterior deltoid strength: Medical Research Council (MRC) 3 and MRC 4/5. At 12-month follow-up, all patients achieved antigravity elbow extension. Patients with a stronger posterior deltoid (MRC 4/5) attained an elbow extension with a strength grade MRC 3.7 (SD 0.6), while those with a weaker posterior deltoid (MRC 3) reached an elbow extension of MRC 3.1 (SD 0.6). Patient-reported outcome measure was evaluated using the Canadian Occupational Performance Measure (COPM) and demonstrated a significant improvement for both performance and satisfaction. No difference in the COPM scores could be found between the two subcategories. This study indicates that tetraplegic patients with a posterior deltoid strength grade of both MRC 4/5 as well as MRC 3 benefit from the procedure. Level of evidence: 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 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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.716
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.378
Teacher spread0.322 · 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.

Study designOther design
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

Citations2
Published2024
Admission routes1
Has abstractyes

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