Acetabular reconstruction with an ice‐cream cone prosthesis following resection of pelvic tumors: Does computer navigation improve surgical outcome?
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Acetabular reconstruction with a coned-stem prosthesis has been one of the reliable procedures following pelvic tumor resections but is associated with a risk of complications and postoperative morbidity. We investigated whether navigated reconstruction could decrease the complication rate and optimize outcomes. METHODS: A retrospective study was conducted on 33 patients who underwent acetabular resection and reconstruction with ice-cream cone prostheses; outcomes were compared between the navigated and nonnavigated groups. RESULTS: A clear margin was obtained in 91% and 82% of the navigated and nonnavigated groups, respectively. The local recurrence (LR) rate was 12%, and all LRs occurred in the nonnavigated group. The rate of major complications requiring surgical intervention was significantly lower in the navigated group (9%) than in the nonnavigated group (50%; P = .024). Two implant failures occurred in the nonnavigated group. Functional outcomes were significantly correlated with the occurrence of major complications (P = .010) and the use of navigation (P = .043); superior functional scores were observed in the navigated group (Musculoskeletal Tumor Society, 73% vs 55%; Toronto Extremity Salvage Score, 73% vs 56%). CONCLUSION: Ice-cream cone prosthesis is an acceptable reconstruction modality following periacetabular tumor resections, and computer navigation are useful to facilitate proper resection margins and implant position.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".