Custom Hydroxyapatite‐Coated Stem Collar With Extracortical Plate Provides Excellent Long‐Term Results Against Aseptic Loosening in Revision, Including Short‐Segment, Endoprosthetic Tumour Reconstruction
Bibliographic record
Abstract
BACKGROUND: Aseptic loosening from endoprosthetic reconstructions following bone tumour resection is a major issue, especially in the revision/multiple revisions settings. The objective was to present long-term outcomes of revision limb salvage surgery using a custom hydroxyapatite-coated stem collar with an extracortical plate at the bone-implant junction specifically designed to prevent aseptic loosening. METHODS: Fifteen (15) patients with an initial extremity bone tumour resection and reconstruction who underwent revision surgery utilizing this implant specification between 2004 and 2016 were included. Multiple prior surgeries and short-segment stem fixation (< 100 mm) were observed in six and nine patients, respectively. Outcomes of interest were rates of aseptic loosening and radiographic evidence of osseointegration along with clinical and functional outcomes. RESULTS: At mean 12-year follow-up (range 6.5 to 18), no patient had evidence of radiographic or clinical aseptic loosening. The distal femur location (p = 0.044), endoprosthetic reconstruction as index procedure (p = 0.026), mechanical failure as reason for revision (p = 0.0047) and additional fixation to the extracortical plate (p = 0.041) were associated with higher bone ingrowth scores. All but two patients, who had mild pain only, were pain-free. Joint range of motion (p < 0.0001) and limb-length discrepancy (p = 0.021) significantly improved. The mean Musculoskeletal Tumor Society score was 26.1 (excellent). CONCLUSIONS: This study demonstrated excellent results in preventing long-term aseptic loosening with this custom implant specification, which is useful particularly for revisions/multiple revisions and short-segment fixation. However, further larger scale and multicentric studies are needed to validate the data to the broader population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".