CT of Preoperative and Postoperative Acetabular Fractures Revisited
Bibliographic record
Abstract
OBJECTIVE: We compared preoperative and postoperative computed tomography (CT) versus radiographic imaging in the evaluation of acetabular fractures (AFs). METHODS: Fifty-four patients who underwent imaging for AFs were retrospectively evaluated. Postoperative reduction quality was assessed on radiographs and CT scan by 2 observers. Rate of reintervention was noted. Radiation exposure from CT was calculated. RESULTS: After reduction, 24 patients had significant findings on postoperative CT. Five patients required reintervention, all of whom had significant postoperative CT findings and complex fractures. Notably, only 1 of the 5 patients had an indication for reintervention based on radiographs alone.The average dose for preoperative/postoperative CT study was 11.5/12.3 mSv, respectively, with a cumulative average dose of 23.8 mSv. CONCLUSIONS: Although reoperation rate is low after fixation of AFs, CT is required to identify those requiring reintervention. However, postoperative CT should be used judicially, only in patients presenting with complex acetabular fractures.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".