Medial Temporal Lobe Volumes in Amnestic Mild Cognitive Impairment and Late-life Depression: Research Synthesis
Bibliographic record
Abstract
There are important similarities and differences between the clinical presentation and prognosis of amnestic mild cognitive impairment (aMCI) and late-life depression (LLD). However, very little is known about the shared and distinct pathophysiological mechanisms between both conditions, even thought their frequent co-occurrence suggests a close association. In this research synthesis, we examined the extent of hippocampus (HC) and entorhinal cortex (ERC) atrophy as reported in 17 aMCI and 9 LLD studies. Total HC volume reduction was significant in almost 100% of aMCI and 50% of LLD studies when populations were compared to normal controls. Volume deficit for total and lateralized HC in LLD studies seemed fairly similar in terms of percentage to aMCI studies. Total ERC volume reduction was significant and larger than HC in all aMCI studies compared to normal controls. No LLD studies measured ERC volume. In general, exclusion criteria and demographic characteristics were fairly similar for most studies. However, imaging characteristics and segmentation protocols varied largely, which could impact the comparison of volume reductions in different studies. Future work investigating simultaneously both aMCI and LLD and using standardized imaging and segmentation protocol would be required to allow a better understanding of the association between aMCI and LLD. Keywords: Mild cognitive impairment, Depression, Alzheimer’s disease, Hippocampus; Entorhinal cortex, Magnetic resonance imaging, Late-life Depression, Neurobiology, cognition, Impairment, psychiatric
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".