Quality of Life and Symptom Control after Stent Placement or Surgical Palliation of Malignant Colorectal Obstruction
Bibliographic record
Abstract
BACKGROUND: Emergent surgical management of malignant large bowel obstruction (LBO) carries a high rate of morbidity and mortality. Self-expanding metal stents have emerged as an alternative for palliation of malignant LBO. However, there are few long-term studies documenting the effect of surgical palliation or colonic stents on symptoms or quality of life (QoL). STUDY DESIGN: Between 2003 and 2006, patients with unresectable-for-cure malignancies presenting with LBO were enrolled in this prospective study. Patients elected to undergo stent placement or surgical palliation. Patients completed a symptom questionnaire and a QoL instrument (Functional Assessment of Cancer Therapy-Colorectal [FACT-C]) at weeks 1, 2, 4, 8, 12, and 24 after palliation. Symptoms were assessed using the Colon Obstruction Score, a novel instrument comprising nausea, vomiting, pain, distension, and bowel movement frequency scores. RESULTS: Thirty patients had successful stent placement; 14 underwent surgical diversion. Colon Obstruction Scores immediately improved after both stent placement and surgery (p < 0.05 for all time points). Composite FACT-C scores progressively improved after stent placement (p = NS), with the colon symptoms subscale improving after 1 month (p < 0.05). FACT-C scores declined initially after surgery and then returned to baseline, with modest improvements seen in the Colon Symptoms subscale (p = NS). CONCLUSIONS: Both stent placement and surgical diversion provide durable improvement in symptoms from LBO, as readily assessed by the Colon Obstruction Score. QoL is difficult to assess in terminal cancer patients, but colon stent placement is associated with improved overall QoL and QoL related to gastrointestinal symptoms.
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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 | 0.003 |
| 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) | 0.001 | 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".