Management of appendiceal pseudomyxoma peritonei diagnosed during pregnancy
Bibliographic record
Abstract
BACKGROUND: The incidence of cancer during pregnancy is approximately 1 in 1000. The most common types encountered during pregnancy are cervical, breast and ovarian. Epithelial tumors of the appendix on the other hand are rare and account for only approximately 1% of all colorectal neoplasms; the occurrence of this neoplasm during pregnancy is extremely rare. CASE PRESENTATION: The medical history of a 30 year old woman diagnosed at 17 weeks gestation with an appendiceal mucinous tumor with large volume pseudomyxoma peritonei was presented. Her pregnancy was preserved and she had an early vaginal delivery of a healthy baby at 35 weeks. At 2 1/2 weeks postpartum the patient underwent extensive cytoreductive surgery and intraperitoneal chemotherapy. She remains disease-free 5 years after her initial diagnosis. A literature review of this clinical situation and a discussion of treatment plans were presented. CONCLUSION: The management of an appendiceal tumor with pseudomyxoma peritonei diagnosed during pregnancy requires full knowledge of the natural history of this disease to achieve a balance of concern for maternal survival and fetal health.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".