Pre‐operative frailty is predictive of adverse post‐operative outcomes in colorectal cancer patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: An increasing number of elderly patients are presenting for elective surgery. Pre-operative risk assessment in this population is inexact due to the complex interplay between age, comorbidity and functional status. Frailty assessment may provide a surrogate measure of a patient's physiological reserve and aid operative decision-making. The aim of this study is to determine the association between pre-operative frailty, as assessed using the Edmonton Frail Scale, and post-operative outcomes in elderly patients undergoing elective colorectal cancer surgery. METHODS: A prospective analysis of 86 patients over the age of 65 undergoing elective colorectal cancer surgery at a tertiary centre between October 2017 and October 2018 was performed. Frailty assessment was conducted pre-operatively using the Edmonton Frail Scale. Primary outcomes included length of stay and post-operative complication rates. Multivariable logistic regression analyses were used to determine the influence of frailty on post-operative outcomes including mortality, prolonged hospital admission, complication rates and quality of life. RESULTS: Of 86 patients, 12 (14.0%) were identified as frail. Frailty was associated with a significantly increased median length of stay (20 days versus 6 days, incidence rate ratio 2.83, P < 0.01) and a significantly increased risk of major post-operative complications (50.0% versus 6.7%, odds ratio 13.8, P < 0.01). Frailty was not associated with a significant reduction in quality of life scores at 30 and 90 days post-operatively. CONCLUSION: Frailty is associated with adverse post-operative outcomes in elderly patients undergoing elective colorectal cancer surgery. Frailty assessment is an important component of pre-operative risk assessment and may identify targets for pre-operative optimisation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it