Surgery for osteitis pubis.
Bibliographic record
Abstract
BACKGROUND: Osteitis pubis is a rare and self-limited condition. Surgery may be necessary in 5%-10% of cases. The outcome after surgery for osteitis pubis is not known. METHODS: To determine the success of surgical intervention for osteitis pubis, we used a computerized data registry to identify patients (10 women [mean age 40 yr]) who underwent surgery for osteitis pubis. A retrospective chart review was carried out. We also searched the literature for all cases of osteitis pubis managed surgically and identified 73 cases. RESULTS: The 10 patients in our series had had symptoms for a mean of 4 years preoperatively. Onset of pain was insidious in 4 patients, it followed childbirth in 4 and it followed trauma in 2. Depending on the surgeon's preference, either a wedge resection of the symphysis pubis was performed or a symphysiodesis. At the latest follow-up (average 26 mo), although all patients had some improvement, only 6 of 10 patients were satisfied with the outcome. From the literature review, we identified 3 categories of patients with osteitis pubis: elite athletes, patients with postoperative or infectious osteitis pubis and the remainder, which would include the patients in our series. CONCLUSIONS: Four types of surgical intervention are described: curettage, arthrodesis, wedge resection and wide resection. The elite athletes respond well to curettage. Patients with osteitis pubis following urologic or gynecologic procedures or have a proven infection require surgery in roughly 50% of cases. The third group has an unpredictable outcome.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 0.002 |
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".