Outcomes of an Anatomically Based Approach to Metastatic Disease of the Acetabulum
Bibliographic record
Abstract
Metastatic disease of the acetabulum is a common and challenging surgical problem. We asked whether acetabular reconstruction for metastatic bone disease improves functional outcome with an acceptable risk of surgical morbidity. We also asked if primary tumor type and the presence of visceral metastases predicted patient survival. We analyzed prospectively accumulated records of 62 consecutive patients who underwent 63 hip arthroplasties with acetabular reconstruction. Operative technique was guided by the extent of dome and column involvement. Demographics, functional status in the form of the Eastern Cooperative Oncology Group (ECOG) score, and survival data were analyzed. Functional scores improved from an average of 2.6 preoperatively to 1.1 postoperatively. Four patients had postoperative complications for which we performed further surgery. Mean survival for the patients with breast cancer was longer at 21 months compared to 9 months for the patients with other primary malignancies. Patients who did not present with visceral metastases had longer survival than those with visceral metastases. Despite the moderate risk of operative complications, an anatomically based approach to reconstruction of acetabular defects from metastatic disease improves functional outcome. Breast cancer as the primary malignancy and the absence of visceral metastases predicted longer survival.
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 | 0.000 | 0.003 |
| 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".