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Record W3127216038 · doi:10.1002/jso.26405

Osteoarticular allograft reconstruction after distal radius tumor resection: Reoperation and patient reported outcomes

2021· article· en· W3127216038 on OpenAlexaboutno aff
Jonathan Lans, Sarah E. Ballatori, René M. Castelein, Neal C. Chen, Santiago A. Lozano‐Calderón

Bibliographic record

VenueJournal of Surgical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWristSurgeryArthrodesisInternal fixationFixation (population genetics)Population

Abstract

fetched live from OpenAlex

BACKGROUND: The aims of this study are to evaluate the rate of wrist joint preservation, allograft retention, factors associated with reoperation and to report the patient reported outcomes after osteoarticular allograft reconstruction of the distal radius. METHODS: Retrospective chart review identified 33 patients who underwent distal radius resection followed by osteoarticular allograft reconstruction, including 27 giant cell tumors and 6 primary malignancies. Ten patients with a preserved wrist joint completed the QuickDASH, PROMIS-CA physical function, and Toronto extremity salvage score (TESS) at a median of 13 years postoperatively. RESULTS: The allograft retention rate was 89%, and an allograft fracture predisposed to conversion to wrist arthrodesis. The reoperation rate was 55% and 36% underwent wrist arthrodesis at a median of 4.2 years following index surgery. The use of locking plate fixation was associated with lower reoperation and allograft fracture rates. Patients reported a median QuickDASH of 10.2 (range: 0-52.3), a mean PROMIS physical function of 57.8 (range: 38.9-64.5) and the median TESS was 95.5 (range: 67.0-98.4). CONCLUSION: Osteoarticular allograft reconstruction results in acceptable long-term patient reported outcomes, despite a high revision rate. Allograft fixation with locking plates seems to reduce the number of reoperations and allograft fractures, along with reduction in wrist arthrodesis rates.

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)0.000
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 score0.462
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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".

Quick stats

Citations12
Published2021
Admission routes1
Has abstractyes

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