Implementation and Outcomes of a Perioperative Geriatrics Strategy, PRIME, for Older Adults Undergoing Gastrointestinal Cancer Surgery
Bibliographic record
Abstract
INTRODUCTION: The number of older adults living with frailty undergoing gastrointestinal cancer surgery is increasing. To address the unique needs of the population, a whole pathway perioperative geriatrics strategy-PRIME-was developed to integrate geriatric principles into surgical care. The objective of this study was to evaluate the implementation of PRIME using validated structural, process, and outcome quality indicators. MATERIALS AND METHODS: This retrospective cohort study included 106 consecutive patients aged 70 years and older who underwent gastrointestinal surgery for cancer or pre-cancerous lesions at a single institution between 1 July 2020 and 5 October 2023. The whole pathway perioperative geriatrics strategy, PRIME, includes preoperative comprehensive geriatric assessment (CGA), collaborative care between surgery, geriatrics, and anesthesia, and post-operative co-management. Implementation was evaluated using validated structural, process, and outcome quality indicators. RESULTS: = 102) received CGA prior to or within 24 h of admission. Adherence to screening was high: 97.2% for dementia, 96.2% for functional status, and 95.3% for frailty. The median number interventions resulting from CGA was 17 (IQR 14-20). Serious complication, delirium, and functional decline occurred in 19.8%, 27.1%, and 19.8%, respectively. CONCLUSIONS: Implementation of a perioperative geriatrics strategy for older adults undergoing gastrointestinal cancer/pre-cancer lesion surgery is feasible, with high adherence to structural and process quality indicators.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".