Long-term Results for Minor Column Allografts in Revision Hip Arthroplasty
Bibliographic record
Abstract
BACKGROUND: While acetabular structural allografts provide an important alternative for reconstructions, concerns remain with long-term graft resorption, collapse, and failure. Midterm studies of minor column (shelf) allograft suggest reasonable survival but long-term survival is unknown. QUESTIONS/PURPOSES: We therefore assessed long-term graft/cup survivorship, functional scores, radiographic resorption, and complications associated with minor column allograft. METHODS: We retrospectively reviewed 74 patients (85 hips) with a mean age of 54 years (range, 28-83 years) undergoing acetabular cup revision using a minor column allograft. A minor column allograft was used in uncontained acetabular bone defects sized between 30% and 50% of the acetabulum. Graft failure was considered to occur when the graft required revision with another graft, metal augment, reconstruction cage, or excision arthroplasty. The minimum followup was 5 years (mean, 16 years; range, 5.3-25 years). RESULTS: Twenty-three patients (27 hips) had rerevision for all causes at a mean time to rerevision of 6.9 years (range, 0.1-23). Fifteen grafts failed at a mean time-to-rerevision of 6.1 years (range, 0.5-23.2). The 15- and 20-year Kaplan-Meier survivorships were 61% and 55% for cups and 78% for grafts with rerevision for all causes as end point. With rerevision for aseptic loosening as end point, survivorships were 67% and 61% for cups and 81% for grafts. The mean modified Harris hip scores were 41 (range, 20-60) preoperatively, 73 (range, 40-95) at 1 year postoperatively and 73 (range, 26-93) at last followup. CONCLUSION: The data may provide a long-term benchmark by which future treatments for Type III defects can be measured.
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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".