Intraoperative predictors of appendiceal abnormalities in patients with mucinous ovarian neoplasms
Bibliographic record
Abstract
OBJECTIVE: To evaluate intraoperative factors predicting appendiceal pathology during gynecologic oncology surgery for suspected mucinous ovarian neoplasms. METHODS: We conducted a retrospective study on 225 patients with mucinous ovarian neoplasms who underwent surgery for an adnexal mass with concurrent appendectomy between 2000 and 2018. Regression analyses were used to evaluate intraoperative factors, such as frozen section of the ovarian mass and surgeon's impression of the appendix in predicting appendiceal pathology. RESULTS: Most patients (77.8%) had a normal appendix on final pathology. Abnormal appendix cases (n = 26) included: metastasis from high-grade adenocarcinoma of the ovary (n = 1), neuroendocrine tumor of the appendix (n = 4), and low-grade appendiceal mucinous neoplasms (n = 26; 23 associated with a mucinous ovarian adenocarcinoma, 2 with a benign mucinous ovarian cystadenoma, and 1 with a borderline mucinous ovarian tumor). Combining normal intraoperative appearance of the appendix with benign or borderline frozen section yielded a negative predictive value of 85.1%, with 14.9% of patients being misclassified, and 6.0% having a neuroendocrine tumor or low-grade appendiceal neoplasm. CONCLUSION: Benign or borderline frozen section of an ovarian mucinous neoplasm and normal appearing appendix have limited predictive value for appendiceal pathology. Appendectomy with removal of the mesoappendix should be considered in all cases of mucinous ovarian neoplasm, regardless of intraoperative findings.
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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 | 0.000 | 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 | 0.000 | 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".