The mix and match approach in primary total hip arthroplasty reveals comparable or lower revision rates to matched components: a systematic review
Bibliographic record
Abstract
INTRODUCTION: The mix and match (stem and cup from different manufacturers/systems, MM) approach in primary total hip arthroplasty (THA) involves combining components from different manufacturers. Despite various configurations discussed in literature and evidence supporting the safety of MM, controversy persists regarding safety and long term outcomes compared to matched components. Our study aimed to compare the revision rates of MM versus matched components. MATERIALS AND METHODS: Two databases were searched for English full-text articles published until January, 2024 that evaluated revision rates after primary MM THA. Additionally, MM revision rates data was extracted from the German Arthroplasty Registry (EPRD). The Newcastle-Ottawa Scale (NOS) for cohort studies was used for quality assessment. RESULTS: Three national and one hospital registry studies were included, of which three demonstrate MM as a common practice (19-24%). All studies found comparable revision rates for MM cohorts, or even slightly improved survival rates in MM cohorts concerning revision rate and PROMs, mostly lacking clinical relevance. These findings align with the data reported in the EPRD, with revision rates of approximately 3.6% after 6 years in both MM and matched THA. CONCLUSIONS: Employing MM in primary THA presents a feasible and safe approach, capable of providing custom fit tailored to individual patients with revision rates comparable to those of matched THA.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".