Fracture risk during extraction of well-fixed extended cementless stems : porous versus hydroxyapatite coated
Bibliographic record
Abstract
The concern of extensive fracturing and bone damage during implant removal has been reported for ingrowing stems, in particular in extended porous coated stems, potentially impeding successful re- implantation of a femoral revision implant and consequently debilitating patients for life. The aim of the present study is to describe this particular complication and comparing the occurrence in porous coated and hydroxyapatite (HA) coated femoral implants. 62 consecutive revision hip replacements were per- formed between January 2010 and December 2016 at a single academic institution. Only revisions of a primary total hip replacement were included. All surgeries were performed by the same senior surgeon. Clinical follow-up involved examination with the Harris hip score (HHS) at 2 years post surgical intervention. Fracture occurrence and severity were compared between groups by means of the Vancouver classification for intraoperative fractures. Overall, significant higher rates of fracturing were observed in the porous coated group (81.8%, p<0.05) compared to the HA coated group (43.5%, p<0.05). Of these fractures, the majority (72,7%) were B3 fractures. There was a significant difference between the mean HHS in the porous-coated group versus the group with HA coating (mean Harris Hip Scores of 68,45 vs 86,17, p = .004). Surgeons have to be wary with implanting porous coated stems in primary hip arthroplasty, especially in younger patients who have a high likelihood of future revision surgery, due to the catastrophic peri-operative fractures associated with the removal of these stems.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".