Management of Malignant Bowel Obstruction
Bibliographic record
Abstract
BACKGROUND: Malignant bowel obstruction (MBO) in patients with advanced gynecologic cancer (GyCa) can negatively impact clinical outcomes and quality of life. Oncology nurses can support these patients with adequate tools/processes. PROBLEM: Patients with GyCa with/at risk of MBO endure frequent emergency or hospital admissions, impacting patient care. APPROACH: Optimizing oncology nurses' role to improve care for patients with GyCa with/at risk of MBO, the gynecology oncology interprofessional team collaborated to develop a proactive outpatient nurse-led MBO model of care (MOC). OUTCOMES: The MBO MOC involves a risk-based algorithm engaging interdisciplinary care, utilizing standardized tools, risk-based assessment, management, and education for patients and nurses. The MOC has improved patient-reported confidence level of bowel self-management and decreased hospitalization. Following education, nurses demonstrated increased knowledge in MBO management. CONCLUSIONS: An outpatient nurse-led MBO MOC can improve patient care and may be extended to other cancer centers, fostering collaboration and best practice.
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 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 | 0.000 |
| 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 | 0.000 |
| 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".