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Record W1977347233 · doi:10.1007/s11552-014-9727-6

Outcomes and Complications of Ulnar Shortening Osteotomy: An Institutional Review

2014· article· en· W1977347233 on OpenAlexaff
Raghav Rajgopal, James H. Roth, Graham J.W. King, Ken Faber, Ruby Grewal

Bibliographic record

VenueHand · 2014
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsSt Joseph's Health CareWestern University
Fundersnot available
KeywordsMedicineNonunionSurgeryWristWrist painMalunion

Abstract

fetched live from OpenAlex

BACKGROUND: Ulnar impaction syndrome (UIS) is a common cause of ulnar wrist pain. Patients may be candidates for surgical intervention if nonoperative options are ineffective. At our institution, ulnar shortening osteotomy is the preferred procedure to manage this disorder. The purpose of this study was to present patient reported outcomes and complication rates of ulnar shortening osteotomy (USO) at mid-term follow-up. METHODS: A retrospective chart review of 72 patients (75 wrists) obtained from our institutional database was performed. At a mean 32 months postoperatively, telephone interviews (n = 53) were performed for all patients who were available for follow-up. The patient-rated wrist evaluation (PRWE), a validated outcome tool, was completed and complications were reviewed. RESULTS: Patient-rated outcomes were favorable; however, complications were frequent and included: delayed union (10/75, 13.3 %), nonunion (6/75, 8 %), and complex regional pain syndrome (5/75, 6.7 %). Ten patients (13.3 %) required revision surgery. Thirty-four patients (45.3 %) required hardware removal with 4/30 (11.4 %) of these patients experiencing refracture. Smokers (mean PRWE 67.1) and patients with workers' compensation claims (mean PRWE 64.9) reported higher residual pain and disability than their counterparts (mean PRWE 28.0; 25.2). CONCLUSIONS: General outcome measures were favorable. Smokers and patients with workers' compensation claims experienced significantly poorer outcomes. However, the incidence of nonunion and delayed union was higher than most reports in the literature. Furthermore, we demonstrated a high refracture rate (11.4 %) following removal of hardware.

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)0.004
metaresearch head score (Gemma)0.012
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.031
GPT teacher head0.316
Teacher spread0.286 · 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

Citations31
Published2014
Admission routes1
Has abstractyes

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