Fragilidad: en busca de herramientas de evaluación preoperatoria
Bibliographic record
Abstract
Background: In the perioperative context, a frailty evaluation scale must consider certain characteristics such as validation, execution speed, simplicity, the capacity to measure multiple dimensions and not being dependent on a cognitive or physical test that could not be performed prior to surgery. The test should select patients that could benefit from interventions aimed to improve their postoperative outcomes. Aim: To validate two frailty evaluation scales for the perioperative period. Material and Methods: The Risk Analysis Index with local modifications (RAI-M) were applied to 201 patients aged 73 +/- 7years (49% women) and the Edmonton frailty scale were applied in 151 patients aged 73 +/- 7 years (49% women) in the preoperative period. Their results were compared with the Rockwood frailty index. Results: The Edmonton frail scale showed adequate psychometric properties and assessed multiple dimensions through 8 of the 11 original questions, achieving a discrimination power over 80% compared to the Rockwood Index. The RAI- M, demonstrated solid psychometric properties with a tool that examines 4 dimensions of frailty through 15 questions and reviewing the presence of 11 medical comorbidities. This scale had a discrimination power greater than 85% and it was significantly associated with prolongation of the planned hospital stay and mortality. Conclusions: RAI-M is a short and easily administered scale, useful to detect frailty in the preoperative period.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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; both teacher heads agree on what is shown here.
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".