Emerging Concepts in the Surgical Management of Peri-Acetabular Metastatic Bone Disease
Bibliographic record
Abstract
The pelvis is a common site of metastatic bone disease. Peri-acetabular lesions are particularly challenging and can cause severe pain, disability and pathologic fractures. Surgical management of these lesions has historically consisted of cementoplasty for contained lesions and Harrington reconstructions for larger, more destructive lesions. Due to the limitations of these procedures, a number of novel procedures have been developed to manage this challenging problem. Percutaneous techniques-including acetabular screw fixation and cementoplasty augmented with screws-have been developed to minimize surgical morbidity. Recent literature has demonstrated a reliable reduction in pain and improvement in function in appropriately selected patients. Several adjuncts to the Harrington procedure have been utilized in recent years to reduce complication rates. The use of constrained liners and dual mobility bearings have reduced the historically high dislocation rates. Cage constructs and porous tantalum implants are becoming increasingly common in the management of large bony defects and destructive lesions. With novel and evolving surgical techniques, surgeons are presented with a variety of surgical options to manage this challenging condition. Physicians must take into account the patients' overall health status, oncologic prognosis and anatomic location and extent of disease when developing an appropriate surgical plan.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".