Minimally Invasive Compared to Open Colorectal Cancer Resection for Older Adults
Bibliographic record
Abstract
OBJECTIVE: We sought to compare long-term healthcare dependency and time-at-home between older adults undergoing minimally invasive surgery (MIS) for colorectal cancer (CRC) and those undergoing open resection. BACKGROUND: Although the benefits of MIS for CRC resection are established, data specific to older adults are lacking. Long-term functional outcomes, central to decision-making in the care for older adults, are unknown. METHODS: We performed a population-based analysis of patients ≥70years old undergoing CRC resection between 2007 to 2017 using administrative datasets. Outcomes were receipt of homecare and "high" time-at-home, which we defined as years with ≤14 institution-days, in the 5years after surgery. Homecare was analyzed using time-to-event analyses as a recurrent dichotomous outcome with Andersen-Gill multivariable models. High timeat-home was assessed using Cox multivariable models. RESULTS: Of 16,479 included patients with median follow-up of 4.3 (interquartile range 2.1-7.1) years, 7822 had MIS (47.5%). The MIS group had lower homecare use than the open group with 22.3% versus 31.6% at 6 months and 14.8% versus 19.4% at 1 year [hazard ratio 0.87,95% confidence interval (CI) 0.83-0.92]. The MIS group had higher probability ofhigh time-at-home than open surgery with 54.9% (95% CI 53.6%-56.1%) versus 41.2% (95% CI 40.1%-42.3%) at 5years (hazard ratio 0.71, 95% CI 0.68-0.75). CONCLUSIONS: Compared to open surgery, MIS for CRC resection was associated with lower homecare needs and higher probability of high time-at-home in the 5 years after surgery, indicating reduced long-term functional dependence. These are important patient-centered endpoints reflecting the overall long-term treatment burden to be taken into consideration in decision-making.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".