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Long-term follow-up of unoperated, nonscissoring spiral metacarpal fractures

2014· article· en· W315930832 on OpenAlexaff
Brittany B Macdonald, Amanda Higgins, Susan Kean, Carolyn Smith, Donald H. Lalonde

Bibliographic record

VenuePlastic Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsNova Scotia Health AuthorityDalhousie UniversitySaint John Regional HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineGrip strengthMetacarpophalangeal jointSurgeryThumb

Abstract

fetched live from OpenAlex

BACKGROUND: Spiral metacarpal fractures can result in shortening of the metacarpal shaft, which may lead to extension lag at the metacarpophalangeal joint and reduced grip strength. These fractures have been surgically treated to restore metacarpal length; however, there are complications associated with surgery, postoperative management and wound healing, which further threaten power recovery in the hand. OBJECTIVE: To determine the effect of conservative management of un-operated, nonscissoring spiral metacarpal fractures. METHODS: Sixty-one consecutive patients presenting with nonscissoring spiral metacarpal fractures were treated nonoperatively and studied prospectively to determine the natural history of their power outcome. Thumb fractures and those requiring surgical intervention for scissoring were excluded. RESULTS: Follow-up data of a minimum of five months (mean follow-up 87 weeks) were available for 13 patients. Mean grip strength at final follow-up was 36.18 kg on the uninjured side and 36.58 kg on the injured side. The strength-difference values did not differ significantly from zero (P=0.72). CONCLUSION: The loss of metacarpal length associated with these fractures may not cause a power deficit sufficiently large to significantly affect grip strength and functional recovery in the hand. A prospective randomized controlled trial of operated versus unoperated, nonscissoring metacarpal fractures is warranted.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.021
GPT teacher head0.273
Teacher spread0.252 · 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 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

Citations9
Published2014
Admission routes1
Has abstractyes

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