Fluid biomarkers for diagnosing dementia: rationale and the Canadian Consensus on Diagnosis and Treatment of Dementia recommendations for Canadian physicians
Bibliographic record
Abstract
Fluid biomarkers improve the diagnostic accuracy in dementia and provide an objective measure potentially useful as a therapeutic response in clinical trials. The role of fluid biomarkers in patient care is a rapidly evolving field. Here, we provide a review and recommendations regarding the use of fluid biomarkers in clinical practice as discussed at the Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD4) convened in Montreal, 4 to 5 May 2012. At present, there is no consensus regarding the optimal methodology for conducting quantification of plasma amyloid-beta (Aβ) peptides. In addition, since there is insufficient evidence supporting clinical applications for plasma Aβ-peptide measures, the CCCDTD4 does not recommended plasma biomarkers either for primary care or for specialists. Evidence for CSF Aβ1-42, total tau and phosphorylated tau in the diagnosis of Alzheimer pathology is much stronger, and can be considered at the tertiary care level for selected cases to improve diagnostic certainty, particularly in those cases presenting atypical clinical features.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".