Cerebrospinal Fluid Biomarkers and Cognition in Alzheimer Disease and Frontotemporal Dementia in a Memory Clinic Setting
Bibliographic record
Abstract
OBJECTIVE: Currently available literature on the relationships between cerebrospinal fluid (CSF) biomarkers and cognitive performance in frontotemporal dementia (FTD) is very limited and inconclusive. In this study, we investigated the association of cognitive symptoms, as measured with Montreal Cognitive Assessment (MoCA), with CSF levels of total tau (t-tau), phosphorylated tau at threonine 181 (p-tau181), and amyloid β 1-42 (Aβ1-42) in a group of patients with probable FTD and Alzheimer disease (AD). METHODS: We conducted a retrospective cohort study with participants selected from the electronic records of patients seen at Yale New Haven Hospital's Memory Clinic, CT. A total of 61 patients, 28 with FTD (mean age=64.1) and 33 with AD (mean age=66.8), with available CSF results and cognitive test scores in their chart were included in analyses. RESULTS: T-tau levels negatively and significantly correlated with total MoCA scores as well as the different MoCA index scores in patients with FTD (r=-0.47, P=0.04). There were no significant associations between MoCA scores and p-tau181 levels in patients with FTD (r=-0.22, P=0.25). Patients with AD exhibited significant correlations between MoCA scores and both t-tau (r=-0.54, P<0.01) and p-tau (r=-0.55, P<0.01) levels. Also, Aβ1-42 levels were not significantly correlated with MoCA scores in either of the FTD and AD groups. CONCLUSION: CSF concentrations of t-tau are inversely correlated to cognitive performance in patients with FTD and both t-tau and p-tau181 in AD. This study provides valuable insights into the relationship between clinical cognitive performance and tau-related pathology in FTD in comparison with AD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".