Searching for an Operational Definition of Frailty: A Delphi Method Based Consensus Statement. The Frailty Operative Definition-Consensus Conference Project
Bibliographic record
Abstract
BACKGROUND: There is no consensus regarding the definition of frailty for clinical uses. METHODS: A modified Delphi process was used to attempt to achieve consensus definition. Experts were selected from different fields and organized into five Focus Groups. A questionnaire was developed and sent to experts in the area of frailty. Responses and comments were analyzed using a pre-established strategy. Statements with an agreement more than or equal to 80% were accepted. RESULTS: Overall, 44% of the statements regarding the concept of frailty and 18% of the statements regarding diagnostic criteria were accepted. There was consensus on the value of screening for frailty and about the identification of six domains of frailty for inclusion in a clinical definition, but no agreement was reached concerning a specific set of clinical/laboratory biomarkers useful for diagnosis. CONCLUSIONS: There is agreement on the usefulness of defining frailty in clinical settings as well as on its main dimensions. However, additional research is needed before an operative definition of frailty can be established.
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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 | 0.240 | 0.185 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".