Laparoscopic Approach to Ovarian Mass in Children and Adolescents: Already a Standard in Therapy
Bibliographic record
Abstract
INTRODUCTION: Functional cysts, ovarian torsion, and benign neoplasms are the most common ovarian masses among young adolescents. The laparoscopic approach to giant ovarian cysts in the pediatric population maybe difficult due the limited working space and the high risk of spillage. In this paper, we evaluate the role of laparoscopic surgery in the treatment of adnexal disease occurring in young girls. MATERIALS AND METHODS: With the approval of the institutional review board, a retrospective chart review(2007-2003) of patients with adnexal disease was conducted. RESULTS: Overall, 12 patients were evaluated with preoperative imaging, sonography, and magnetic resonance imaging (MRI) scan and laboratory values. None resulted in malignant histology. All resections of ovarian cysts were performed laparoscopically. The outcome was uneventful in all patients. CONCLUSIONS: Treatment is indicated if the diagnosis is in question, the cyst persists, in the case of ovarian torsion,or if the patient is symptomatic. Laparoscopy is becoming the favored approach by most pediatric surgeons for the treatment of ovarian cysts. All surgical procedures for ovarian cysts should spare functional ovary as much as is technically possible. Simple cysts can be fenestrated, but complex or functional cysts should be excised, with the preservation of the remaining ovary by careful dissection. The laparoscopic approach for adnexal masses can be performed in an acceptable manner, with comparable results to an open approach, plus the cosmetic advantages of minimally invasive surgery, which is an important aspect for the treated patients.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".