First MRI impact on belief revision and decision making in FTD diagnostic evaluation
Bibliographic record
Abstract
Abstract Background MRI has a central value in frontotemporal dementia (FTD) diagnostic workup. We set out to examine how MRI results impact FTD cases workup and clinician belief revision. Method Questionnaire to Neuropsychiatry International Consortium Frontotemporal Dementia (NIC‐FTD) members in February 2021 (n = 23) with follow‐up questionnaire in June 2021 (n = 13). Result About 90.9% of respondents indicated that a first MRI would exclude a diagnosis of FTD in less than 20% of cases. About 59.1% of clinicians indicated that over 60% of their FTD cases were confirmed with the first MRI (22.7% indicated that between 40% and 60% of cases were confirmed with the first MRI and 18.2% indicated that less than 40% of cases were confirmed with the first MRI). Those who felt most of their FTD cases were confirmed with a first MRI preferred a second MRI as follow‐up imaging (69.2%) rather than PET imaging (30.8%). Those who felt most of their FTD cases were not confirmed with a first MRI preferred PET scan (75.0%) over a second MRI (25.0%). The first MRI ended less than 20% FTD investigations for 55.6% or clinicians and ended less than 40% FTD investigations for 77.8% clinicians. About 91.3% of respondents indicated that the first MRI impacted which tests they would order next (table 1.) About 77.8% of clinicians indicated that the first MRI lead to belief revision in less than 40% of FTD cases and 44.4% indicated belief revision in less than 20% of cases. Conclusion There is discrepancy between first MRI impact on belief revision compared to its impact on FTD cases workup. Rather than being a Bayesian oddity, this illustrates the distinction between belief revision and acceptance attitudes revision, which refers to how we follow clinical guidelines independently of our own beliefs. Social desirability bias is also relevant: respondents might want to indicate they feel confident in their intuition regarding FTD diagnosis while still ordering tests that are expected. Current limitations include sample size and aforementioned bias. Further research into belief revision, how the first MRI impact FTD investigation algorithm, and how to volumetric imaging can supplement MRI interpretation may also be warranted.
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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 | 0.017 | 0.165 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".