Clinical and radiological outcomes and analysis of failures of modular revisions stems at long-term follow-up: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Increasingly hip replacements at young age exposes the patient to an increased risk of failure of the implant over the years. In case of failure, revision specific stems were designed to overcome bone loss. Modularity of these devices is an important resource for the surgeon as they allow the new implant to be better adapted to the patient's anatomy. The purpose of this systematic review is to provide data about the outcome at long-term follow-up (>8 years) of hip modular revision femoral stems. Methods: This systematic review and meta-analysis were conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement guidelines. PubMed and Google Scholar databases were systematically and independently searched, according to the inclusion and exclusion criteria. Two reviewers performed the data extraction independently. In case of disagreement, the senior authors were sought to resolve the divergences. Quality of the involved studies was evaluated with National Institute for Health and Care Excellence (NICE) guidelines (eight-item list) and the Newcastle-Ottawa scale (NOS). Primary and secondary outcomes were evaluated. The statistical analysis of this meta-analysis was performed by using Excel Microsoft and the software STATA. Results: of 12.3% (P=0.332). Mean Harris Hip Score (HHS) was 83 [min: 79; max: 87.6; standard deviation (SD): 3.55]. Secondary evaluated outcomes were: subsidence >5 mm, rate of periprosthetic infection or fractures (intra- and post-operative) and dislocations. The mean value for the NICE tool was 5.5 (SD: 1.13) and 7.3 (SD: 0.79) for the NOS tool. The survival rate was >90% at long-term follow-up (min: 60%; max: 97%). Conclusions: The modular femoral revision stems have demonstrated good long-term reliability and efficacy. This meta-analysis demonstrates that the re-revision rate after 8 years of follow-up is low and 90% of the implants did not fail.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.045 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".