The Gap Between Clinical Research and Standard of Care: A Review of Frailty Assessment Scales in Perioperative Surgical Settings
Bibliographic record
Abstract
The elderly population in the United States is increasing exponentially in tandem with risk for frailty. Frailty is described by a clinically significant state where a patient is at risk for developing complications requiring increased assistance in daily activities. Frailty syndrome studied in geriatric patients is responsible for an increased risk for falls, and increased mortality. In efforts to prepare for and to intervene in perioperative complications and general frailty, a universal scale to measure frailty is necessary. Many methods for determining frailty have been developed, yet there remains a need to define clinical frailty and, therefore, the most effective way to measure it. This article reviews six popular scales for measuring frailty and evaluates their clinical effectiveness demonstrated in previous studies. By identifying the most time-efficient, criteria comprehensive, and clinically effective scale, a universal scale can be implemented into standard of care and reduce complications from frailty in both non-surgical and surgical settings, especially applied to the perioperative surgical home model. We suggest further evaluation of the Edmonton Frailty Scale for inclusion in patient care.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".