Bibliographic record
Abstract
The proximal modular neck in total hip arthroplasty is not a new concept, but there has been a recent resurgence in interest with multiple companies offering proximal modularity. Proponents of neck modularity suggest that inherent advantages include improved soft tissue balancing and decreased risk of dislocation, particularly in cases with difficult anatomy. Favourable results have been reported in DDH and other cases with excessive femoral anteversion, for example. There are numerous theoretical and published negative aspects of proximal neck modularity that should be considered. Modular necks can be an additional source of corrosion and fretting, and specific systems have been recalled over such concerns. There are case reports of dissociation and fracture at the junction. Fracture appears to be a significant issue in some systems. Retroversion of the neck to reduce the chance of dislocation is not necessarily benign with respect to implant fixation and stability, with RSA data suggesting caution in the application of retroverted necks. Modular necks are difficult to dissociate when in vivo , negating the long-term benefit of modular conversion. Finally, proximal neck modularity significantly increases the cost of the implant, without any documented improvement in long-term outcome. Modular necks offer limited advantages with significant potential downside. On balance of the evidence, the routine use of modular necks in primary total hip arthroplasty is difficult to justify.
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 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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.002 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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.
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".