Preoperative frailty assessment with Robinson Frailty Score (RFS) and Edmonton Frail Scale (EFS) in older surgical patients with cancer.
Bibliographic record
Abstract
e24033 Background: In general geriatric surgical patients, frailty has been shown to predict higher rates of postoperative adverse outcomes. A little is known about how to optimally assess older adults with cancer for preoperative frailty. We evaluated the potential utility of the RFS [Robinson Am J Surg. 2013], EFS [Rolfson Age Ageing. 2006] and Geriatric 8 (G8) for prediction of postoperative adverse events. Methods: This cohort study included older adults who were prospectively evaluated by geriatric oncology service at Kyushu Cancer Center in Japan before undergoing oncological surgery between September 2018 and December 2019. The RFS measures cognition, function (activities of daily living (ADLs) and Timed Up & GO (TUG)), history of falls, comorbidity, albumin and hematocrit (score 0 to 1: fit (n = 71), 2 to 3: prefrail (n = 30) and 4 to 7: frail (n = 13)). The EFS evaluates cognition, function (IADLs and TUG), incontinence, self-perceived health, mood, nutrition, polypharmacy and social support (score 0 to 3: fit, 4 to 7: prefrail and 8 to 17: frail). G8 was dichotomized at previously studied cut-off value of 14. The primary outcome was composite adverse events (AEs), including 30-day postoperative complications (Clavien-Dindo grade ≥ 2) and discharge to an institutional care facility. Severity of surgery was assessed using the Operative Stress Score (OSS) [Shinall JAMA Surg. 2019]. Results: Of 114 patients (median age 80 years, range 72-96), surgery type was GI in 62%, HEENT in 20%, GYN in 8%, and other in 10%. 100 patients had ECOG PS 0 to 1. Using the OSS, surgical procedures were classified as very low to low stress (9%), moderate stress (31%), high stress (46%) and very high stress (15%). 45 patients had AEs. After adjusting for the OSS, preoperative frailty based on the RFS was associated with the occurrence of AEs (fit: 25%, prefrail: 49%, frail: 77%; p < 0.01). However, neither the EFS (fit: 30%, prefrail: 37%, frail: 60%; p = 0.14) nor G8 was significantly associated with a risk of AEs (score > 14: 17%, score ≤ 14: 41%; p = 0.07). Conclusions: Preoperative frailty status defined by the RFS is predictive of postoperative adverse outcomes in older adults undergoing elective surgery for 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".