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Reply to the Letter to the Editor: No Difference Between Trabecular Metal Cones and Femoral Head Allografts in Revision TKA: Minimum 5-year Followup

2018· letter· en· W2809937494 on OpenAlexaff
Nemandra A. Sandiford

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2018
Typeletter
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineFemoral headOrthopedic surgerySection (typography)OrthodonticsSurgery

Abstract

fetched live from OpenAlex

To the Editor, I would like to thank Chen and colleagues for their interest in our work, and for continuing the discussion on this topic. The authors are correct in noting that of the 45 TKA revisions, surgeons used femoral head allograft for 30 TKA revisions (66.7%, not 75%) and that surgeons used trabecular metal cones for 15 TKA revisions (33.3%, not 25%). Additionally, in the Trabecular Metal Cone Technique section, the authors found a discrepancy between the data presented in the text and Table 1. The data presented in the text is correct—four Type 2B and two Type 3 femoral defects and two Type 2A and seven Type 2B tibial defects were treated using trabecular metal cones. We have created an erratum to correct these errors. Regarding the conclusions drawn from this study, readers should consider the second paragraph in the Discussion section, where we mention the small number of patients in our study group. We also stated in the Methods section that, at our institution, trabecular metal cones became the “preferred technique as a result of their relative ease of use” [1]. We used these cones when we encountered Anderson Orthopaedic Research Institute Type 3 defects, however, we do not believe that our conclusions should be overstated since we only used the cones on two patients with Type 3 defects. In our study, the use of both femoral head allograft and trabecular metal cones are associated with encouraging results and low rates of complications. Allografts can be used in this situation with encouraging results [2]. Regarding radiostereometric analysis (RSA), we agree that RSA is an accurate method for assessment of migration patterns of the cones, but this was not the focus of our study. Our goal was to compare the results of femoral head allograft and trabecular metal cones in revisions TKA. The radiographs in our study were performed in our center using standardized techniques and reviewed by at least two independent orthopaedic surgeons to minimize interpretation errors.

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)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.015
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0150.018
Insufficient payload (model declined to judge)0.0050.004

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 head0.084
GPT teacher head0.399
Teacher spread0.315 · 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 designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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