Prodromal FTD ‐ what do we know about it and what do we still have to learn?
Bibliographic record
Abstract
Abstract Background Frontotemporal dementia (FTD) is a complex disease that can initially present with subtle symptoms across several domains including behavior, cognitive/language, psychiatric and motor. This heterogenous prodromal phase is preceded by a slowly progressive presymptomatic accumulation of biological changes. With the emergence of new potential therapeutic agents for genetic forms, there is a need for robust clinical characterization and diagnostic definitions of these disease phases. Method We performed a systematic literature review on the current state of the science on prodromal FTD and provide expert consensus recommendations on diagnostic definitions. Result The preclinical phase should extend from the first signs of protein misfolding to the first FTD symptoms, however we lack molecular biomarkers to characterize this stage, with maybe the exception of C9orf72 expansion cases. In genetic mutation carriers it is uncertain if a ‘no disease’ phase exists, or if there is a neurodevelopmental component. To account for all possible clinical presentations, the definition of the prodromal stage of FTD needs to include the possibility of symptoms emerging with behavioral/psychiatric, cognitive and/or motor features. We subsume these features under the term mild cognitive and/or behavioral and/or motor impairment due to FTD (MCBMI‐FTD). MCBMI‐FTD needs to include psychiatric symptoms outside of typical bvFTD criteria as potential initial prodromal manifestations of FTD in genetic mutation carriers, however this would not be applicable in sporadic cases given the lack of specificity of such symptoms. Conclusion Characterizing the preclinical and prodromal stages of FTD is crucial for disease detection and patient stratification for future clinical trials. However, several issues remain including the need to develop molecular biomarkers to better characterize the preclinical phase and more accurate models to predict symptom onset.
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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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".