The race for the classification of proximal periprosthetic femoral fractures : Vancouver vs Unified Classification System (UCS) - a systematic review
Bibliographic record
Abstract
BACKGROUND: Periprosthetic femoral fractures (PFFs) represent a major cause for surgical revision after hip arthroplasty with detrimental consequences for patients. The Vancouver classification has been traditionally used since its introduction in 1995. The Unified Classification System (UCS) was described in 2014, to widen the spectrum by aiming for a more comprehensive approach. The UCS also aimed to replace the Vancouver classification by expanding the idea of the Vancouver classification to the whole musculoskeletal apparatus. After introduction of the UCS, the question was raised, whether the UCS found its place in the field of analysing PFFs. Therefore, this systematic review was performed to investigate, the use of the UCS compared to the established Vancouver classification. METHODS: Medline was searched for reports published between 1 January 2016 and 31 November 2020, without language restriction. Included were original articles, irrespective of the level of evidence and case reports reporting on a PFF and using either the Vancouver or the UCS to classify the fractures. Excluded were reviews and systematic reviews. RESULTS: One hundred forty-six studies were included in the analysis. UCS has not been used in a single registry study, giving a pooled cohort size of 3299 patients, compared to 59,178 patients in studies using the Vancouver classification. Since 2016, one study using UCS was published in a top journal, compared to 37 studies using the Vancouver classification (p=0.29). During the study period, the number of yearly publications remained stagnant (p=0.899). CONCLUSIONS: Despite valuable improvement and expansion of the latter UCS, to date, the Vancouver system clearly leads the field of classifying PFFs in the sense of the common use.
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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 | 0.014 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".