Does Informant-Based Reporting of Cognitive Decline Correlate with Age-Adjusted Hippocampal Volume in Mild Cognitive Impairment and Alzheimer’s Disease?
Bibliographic record
Abstract
BACKGROUND: Informant-based measures are effective screening tools for cognitive impairment. The Alzheimer's Questionnaire (AQ) is a subjective, informant-based measure that detects amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) with high sensitivity and specificity and has been shown to predict amyloid burden. OBJECTIVE: To determine whether informant-based report of cognitive decline correlates with hippocampal volume changes in MCI and AD. METHODS: Retrospective chart review of 139 clinically referred patients with clinical diagnoses of aMCI or mild dementia due to AD was conducted. Diagnostic status (clinical diagnosis made by a neurologist), NeuroQuant measured MRI brain with percentile rank hippocampal volume, Montreal Cognitive Assessment (MoCA) total, AQ-Total score, and demographic variables were extracted from medical records. Spearman correlation was used to assess the relationship between hippocampal volume and AQ-Total. The AQ was used to assign diagnostic status. Thus, the relationship between the AQ and diagnostic status was excluded. RESULTS: < 0.0001. CONCLUSION: In a mixed-clinical sample of patients presenting to an outpatient memory disorders center, higher endorseme-nts of functional impairments by caregivers were significantly associated with smaller hippocampal volumes. When used in conjunction with other available measures, these findings further support the role of the AQ in clinical decision-making and demonstrate an additional relationship between clinical measures and volumetric MRI.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".