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Record W4392878814 · doi:10.1016/j.knee.2024.02.009

Does the use of tibial stem extensions reduce the risk of aseptic loosening in obese patients undergoing primary total knee arthroplasty: A systematic review and meta-analysis

2024· review· en· W4392878814 on OpenAlexaboutno aff
Yushy Zhou, Siddharth Rele, Osama Elsewaisy

Bibliographic record

VenueThe Knee · 2024
Typereview
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
FundersUniversity of MelbourneHCF Research Foundation
KeywordsMedicineMeta-analysisConfidence intervalRelative riskSurgeryCohort studyArthroplastyAseptic processingBody mass indexObservational studyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: ) patients with stemmed (ST) versus non-stemmed (NST) tibial implants in primary total knee arthroplasty (TKA). METHODS: A systematic review and meta-analysis were conducted following PRISMA and MOOSE guidelines. Studies reporting a direct comparison between ST and NST tibial implants in obese patients were included. The primary outcome of interest was revision for aseptic loosening. Outcomes were analysed using meta-analysis of relative risk. Risk of bias assessment was performed using the Newcastle-Ottawa Scale for observational studies and the RoB-2 Cochrane tool for randomised studies. RESULTS: Seven studies met the selection criteria, consisting of four cohort studies and three randomised controlled trials. Mean follow up time for the eligible cohort was 62.6 months. Meta-analysis demonstrated a statistically significant reduction in the risk of aseptic revision in the ST group compared with the NST group (risk ratio 0.25, 95% confidence interval 0.07 to 0.92). After removal of all zero-event studies, the results remained in favour of the ST group (risk ratio 0.15, 95% confidence interval 0.03 to 0.64). CONCLUSIONS: This study found that obese patients undergoing TKA with stemmed tibial implants may have a lower risk of aseptic revision compared with those with non-stemmed tibial implants. However, due to the lack of high-quality literature available, our study is unable to draw a definitive conclusion on this matter. We suggest that this topic should be re-evaluated using higher-quality study methods, particularly national joint registries studies and randomised controlled trials.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.757
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.074
GPT teacher head0.311
Teacher spread0.237 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations10
Published2024
Admission routes1
Has abstractyes

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