[P4–168]: THE FUNNEL STUDY: PRE‐SCREENING FOR MCI AND MILD AD PATIENTS FROM THE CHARIOT REGISTER
Bibliographic record
Abstract
To evaluate the effectiveness of delivering interventions at the earliest stages of cognitive decline, an effective and efficient pre-screening method of identifying and recruiting suitable trial participants is required. The Funnel study aimed to identify previously undiagnosed, treatment-naïve MCI patients suitable for referral to a randomized clinical trial for Mild Cognitive Impairment and mild Alzheimer's disease. This presentation describes the selection, implementation, evaluation and modification of a brief cognitive “pre-screening” assessment to identify individuals most likely to be appropriate for such trials. Participants were recruited from the Cognitive Health in Ageing Register for Interventional and Observational Trials (CHARIOT) of healthy elderly volunteers (n∼28,000), at Imperial College London (Larsen et al., 2015). Volunteers were eligible if they were aged 55–85 with subjectively-reported cognitive decline, a reliable informant, and no potentially confounding significant comorbidities. 711 CHARIOT participants underwent a pre-screening procedure to ascertain suitability for referral into an early intervention trial for MCI. The initial pre-screening protocol comprised the Informant AD-8 and RAVLT Learning Trials. This initial protocol was found to yield low rates of suitable referrals, and the protocol was extended, based on a review of available instruments, to include the full RAVLT, the MoCA, and IQCODE. We will also describe the clinical adjudication protocol for borderline cases. The initial protocol (n=418) yielded a 5% rate of patients eligible for referral. Following the introduction of the additional procedures (n=268), 54% of participants were eligible for clinical adjudication, and the rate of patients eligible for referral increased to 19%. Preliminary data suggest that performance on these additional procedures was associated with appropriateness for the trial, and that self-report cognitive decline was less strongly associated. Qualitative observations suggested increased participant satisfaction and engagement with the amended protocol. The introduction of brief pre-screening instruments that include a delayed recall/recognition component, and provision of a basic clinical adjudication procedure, potentially increases the sensitivity of protocols to select appropriate participants from the community who may be at greater risk of amnestic cognitive impairment and who are suitable for clinical trials. Self-reported cognitive difficulties appear to be less helpful to determine suitability.
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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 | 0.020 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
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".