Added value of functional neuroimaging to assess decision-making capacity of older adults with neurocognitive disorders: protocol for a prospective, monocentric, single-arm study (IMAGISION)
Bibliographic record
Abstract
INTRODUCTION: Assessment of decision-making capacity (DMC) is essential in daily life as well as for defining a person-centred care plan. Nevertheless, in ageing, especially if signs of dementia appear, it becomes difficult to assess decision-making ability and raises ethical questions. Currently, the assessment of DMC is based on the clinician's evaluation, completed by neuropsychological tests. Functional MRI (fMRI) could bring added value to the diagnosis of DMC in difficult situations. METHODS AND ANALYSIS: IMAGISION is a prospective, monocentric, single-arm study evaluating fMRI compared with clinical assessment of DMC. The study will begin during Fall 2021 and should be completed by Spring 2023. Participants will be recruited from a memory clinic where they will come for an assessment of their cognitive abilities due to decision-making needs to support ageing in place. They will be older people over 70 years of age, living at home, presenting with a diagnosis of mild dementia, and no exclusion criteria of MRI. They will be clinically assessed by a geriatrician on their DMC, based on the neuropsychological tests usually performed. Participants will then perform a behavioural task in fMRI (Balloon Analogue Risk Task) to analyse the activation areas. Additional semistructured interviews will be conducted to explore real life implications. The main analysis will study concordance/discordance between the clinical classification and the activation of fMRI regions of interest. Reclassification as 'capable', based on fMRI, of patients for whom clinical diagnosis is 'questionable' will be considered as a diagnostic gain. ETHICS AND DISSEMINATION: IMAGISION has been authorised by a research ethics board (Comité de Protection des Personnes, Bordeaux, II) in France, in accordance with French legislation on interventional biomedical research, under the reference IDRCB number 2019-A00863-54, since 30 September 2020. Participants will sign an informed consent form. The results of the study will be presented in international peer-reviewed scientific journals, international scientific conferences and public lectures. TRIAL REGISTRATION NUMBER: NCT03931148.
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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 | 0.035 | 0.027 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 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".