Outcomes in elderly patients following surgery for colorectal cancer in the veterans affairs health care system
Bibliographic record
Abstract
AIM: To compare 30-day and 5-year mortality in elderly vs. younger patients following surgical resection for colorectal cancer. METHODS: A cohort study of patients admitted to VA hospitals with a new diagnosis of colorectal cancer who underwent surgical resection between October 1990 and September 2000. Cumulative survival rates (30-day and 5-year) were calculated from Kaplan-Meier estimates and adjusted risks of death were estimated using Cox proportional hazards models. RESULTS: We identified 34,888 individuals with a new diagnosis of colorectal cancer between October 1990 and September 2000, of whom 22 633 (65%) underwent surgical resection. The 30-day mortality following resection for rectal and colon cancer, respectively, for patients <65 years was 2.1 and 2.8% compared with 4.9 and 5.6% for those > or =65 years. The 5-year cumulative survival for rectal and colon cancer for patients <65 years was 54.0 and 57.6% compared with 44.5 and 46.6% for those > or =65 years. In patients > or =65 years with rectal or colon cancer, after adjustment, 30-day mortality was 2 times greater and 5-year mortality was 1 times greater than in younger patients. CONCLUSIONS: Older age is an independent predictor of increased short-term and long-term mortality following surgery in patients with rectal and colon cancer.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".