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Record W4321614723 · doi:10.2147/tcrm.s400354

Research on the Influence of the Allogeneic Bone Graft in Postoperative Recovery After MOWHTO: A Retrospective Study

2023· article· en· W4321614723 on OpenAlexaboutno aff
Rui Zhong, Gang Yu, Yingming Wang, Chao Fang, Shuai Lu, Zhilin Liu, Jingyu Gao, Chengyuan Yan, Qichun Zhao

Bibliographic record

VenueTherapeutics and Clinical Risk Management · 2023
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
FundersFundamental Research Funds for the Central Universities
KeywordsMedicineHigh tibial osteotomyWOMACOsteotomyOsteoarthritisSurgeryRadiographyRetrospective cohort studyBone grafting

Abstract

fetched live from OpenAlex

Purpose: To compare the effects of an allogeneic bone graft and a non-filled bone graft on the rate of osteotomy gap union in medial opening wedge high tibial osteotomy (MOWHTO) with an opening width less than 10 mm. Methods: A total of 65 patients undergoing MOWHTO between January 2018 and December 2020 were enrolled in this retrospective study. The patients were divided into two groups: the allograft group (MOWHTO with allogeneic bone grafting, 30 patients) and the non-filling group (MOWHTO without bone void fillers, 35 patients). The clinical outcomes, including the Western Ontario and McMaster Universities Osteoarthritis index (WOMAC), Lysholm score, and post-operative complications, were compared. The radiographic evaluation included changes in hip-knee-ankle angle (HKA), medial proximal tibial angle (MPTA), femorotibial angle (FTA), and weight-bearing line ratio (WBLR) at pre-operation, at two-day post-operation, and the last follow-up. Radiographs were obtained at three, six and twelve months post-surgery, and at the time of the last follow-up to assess the fill area of the osteotomy gap. The union rate of the osteotomy gap was calculated and compared, and risk factors that may affect the rate of osteotomy gap union were also discussed. Results: The rate of osteotomy gap union at 3 and 6 months after the operation in the allograft group was significantly higher compared with the non-filling group (all P<0.05), while no significant difference was found after the 1-year post-operative and at the last follow-up. Also, the WOMAC and Lysholm scores of the allograft group were significantly higher than those of the non-filling group (all P<0.05), and there was no significant difference between the two groups at the last follow-up. Conclusion: Filling the gaps with the allograft bones may accelerate the union of osteotomy gap, improve clinical outcomes, and have important implications for patient rehabilitation in the early post-operative course. Bone grafting did not affect the final rate of osteotomy gap union and the clinical score of patients.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.069
GPT teacher head0.408
Teacher spread0.339 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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