Bibliographic record
Abstract
We would like to commend Dr. O'Neill and colleagues on their recent study into the role of clinical impression in recognising frailty in the surgical population 1. We believe that the identification of frail patients will become increasingly important to anaesthetists as evidence demonstrating higher peri-operative morbidity and mortality in this population group increases, and it is reassuring that clinical impression may be a quick and reliable tool to assist in this process. The authors assessed elective surgical patients in a clinic environment, but these findings may be even more relevant to the emergency surgical population, in whom ‘eye-balling’ in the hours, or even minutes, before surgery may be the best test available. As the authors note, much of the work in this area has been limited by difficulties in both defining and measuring frailty. There are simply too many scales and indices currently being used, and as anaesthetists we require a simple, quick and reproducible tool. One such tool is the Edmonton Frail Scale, a 17-point scale validated for use by non-geriatricians to assess frailty, which takes approximately 5 min to complete per patient 2. The scale is available as an App on both Android and iOS platforms (Create Multimedia, Evergem, Belgium) and is free to download. It includes the ‘timed up and go’ test mentioned in the accompanying editorial 3, which may preclude its use in the emergency situation, but we feel it is a useful addition to the anaesthetist's armory in assessing these patients. Casting the net even wider, we may ask whether it should even fall to the anaesthetist to make these initial impressions. For elective procedures, these tools could be utilised in primary care, identifying high-risk patients who may benefit from ‘prehabilitation’ and prescribed exercise programmes to modify outcome 4, and informing postoperative destination at the point of referral. Recent evidence suggests these patients are at higher risk in the early postoperative period 5, and there may be an argument for higher dependency care in some situations. It may also be appropriate for General Practitioners to initiate and plan for appropriate enhanced social care packages following hospital discharge. It is evident that the importance of frailty as a risk factor in both emergency and elective surgery can no longer be ignored. We feel that there needs to be a greater emphasis on the identification of these patients, both in terms of anaesthetic training, and in the primary care and surgical outpatients settings. Simple tools such as the Edmonton Frail Scale may be useful when used alongside clinical impression and we would encourage readers to get out there and try this for themselves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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 teacher head, 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".