Validation of the Self-Reported Domains of the Edmonton Frail Scale in Patients 65 Years of Age and Older
Bibliographic record
Abstract
Abstract Introduction: In the era of virtual care, self-reported tools are beneficial for preoperative assessments and facilitating postoperative planning. We have previously reported the use of the Edmonton Frailty Scale (EFS) as a valid preoperative assessment tool. Objective: We wished to validate the self-reported domains of the EFS (srEFS) by examining its association with loss of independence (LOI) and mortality. Methods: This is a single-institution observational study of patients ≥ 65 years undergoing multi-specialty surgical procedures who were assessed preoperatively with the EFS. Exploratory data analysis of the EFS was used to determine the threshold for identifying frailty on the srEFS. Procedures were classified using the Operative Stress Score (OSS) scored 1 – 5 (lowest to highest). Hierarchical Condition Category (HCC) was utilized to risk-adjust. LOI was described as a change in functional status at discharge and mortality was defined as in-hospital or up to 30 days following discharge. Receiver operating characteristic (ROC) curves were used to estimate areas under the curves for srEFS versus EFS in relation to LOI and 30-day mortality. Results: 535 patients were included. Exploratory analysis confirmed best positive predictive value for srEFS was ³5. Overall, 113 (21%) patients were frail and 179 (33.5%) patients had an 0SS ³5. LOI occurred in 38 (7%) patients and the mortality rate was 4% (21 patients). ROC analysis showed that the srEFS performed similarly the standard EFS with no difference in discriminatory thresholds for predicting LOI and mortality. Examination of the domains of the EFS demonstrated a lack of association between cognitive decline and the outcomes of interest. However, functional status assessed with either the Get up and Go or self-reported ADLs was independently associated with increased risk for LOI.Conclusion: This study shows that self-reported components EFS are sufficiently valid as a high-risk assessment and are useful in virtual preoperative evaluation to help predict LOI and mortality.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".