Inoperable Bowel Obstruction in Ovarian Cancer: Prevalence, Impact and Management Challenges
Bibliographic record
Abstract
Eduardo Gonzalez-Ochoa,1 Husam A Alqaisi,1 Gita Bhat,1 Nazlin Jivraj,1 Stephanie Lheureux1,2 1Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada; 2Department of Medicine, University of Toronto, Toronto, Ontario, CanadaCorrespondence: Stephanie Lheureux, Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada, Tel +1 416-946-2818, Email stephanie.lheureux@uhn.caAbstract: Malignant bowel obstruction (MBO) is one of the most severe complications in patients with advanced ovarian cancer, with an estimated incidence up to 50%. Its presence is related to poor prognosis and a life expectancy measured in weeks for inoperable cases. Symptoms are usually difficult to manage and often require hospitalization, which carries a high burden on patients, caregivers and the healthcare system. Management is complex and requires a multidisciplinary approach to improve clinical outcomes. Patients with inoperable MBO are treated medically with analgesics, antiemetics, steroids and antisecretory agents. Parenteral nutrition and gut decompression with nasogastric tube, venting gastrostomy or stenting may be used as supportive therapy. Treatment decision-making is challenging and often based on clinical expertise and local policies, with lack of high-quality evidence to optimally standardize management. The present review summarizes current literature on inoperable bowel obstruction in ovarian cancer, focusing on epidemiology, prognostic factors, clinical outcomes, medical management, multidisciplinary interventions and quality of life.Keywords: bowel obstruction, inoperable, ovarian cancer, medical management, multidisciplinary
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".