Hippocampal Volume and Episodic Associative Memory Identify Memory Risk in Subjective Cognitive Decline Individuals in the CIMA-Q Cohort, Regardless of Cognitive Reserve Level and APOE4 Status
Bibliographic record
Abstract
BACKGROUND: Subjective cognitive decline (SCD) was proposed to identify older adults who complain about their memory but perform within a normal range on standard neuropsychological tests. Persons with SCD are at increased risk of dementia meaning that some SCD individuals experience subthreshold memory decline due to an underlying progression of Alzheimer's disease (AD). OBJECTIVE: Our main goal was to determine whether hippocampal volume and APOE4, which represent typical AD markers, predict inter-individual differences in memory performance among SCD individuals and can be used to identify a meaningful clinical subgroup. METHODS: Neuropsychological assessment, structural MRI, and genetic testing for APOE4 were administered to one hundred and twenty-five older adults over the age of 65 from the CIMAQ cohort: 66 SCD, 29 individuals with mild cognitive impairment (MCI), and 30 cognitively intact controls (CTRLS). Multiple regression models were first used to identify which factor (hippocampal volume, APOE4 allele, or cognitive reserve) best predicted inter-individual differences in a Face-name association memory task within the SCD group. RESULTS: Hippocampal volume was found to be the only and best predictor of memory performance. We then compared the demographic, clinical and cognitive characteristics of two SCD subgroups, one with small hippocampal volume (SCD/SH) and another with normal hippocampal volume (SCD/NH), with MCI and CTRLS. SCD/SH were comparable to MCI on neuropsychological tasks evaluating memory (i.e., test of delayed word recall), whereas SCD/NH were comparable to CTRLS. CONCLUSION: Thus, using hippocampal volume allows identification of an SCD subgroup with a cognitive profile consistent with a higher risk of conversion to 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".