Uncovering pathology, subjective cognitive complaints, and sex in early Alzheimer's disease
Bibliographic record
Abstract
BackgroundSubjective cognitive complaints may correlate with cerebral amyloid-β (Aβ) levels in the early phases of Alzheimer's disease (AD). The relationship between sex, AD pathology, and complaints remains unclear.ObjectiveOur study aims to (1) explore the relationship between Aβ pathology, assessed with two complementary measures, and subjective cognitive complaints across multiple domains in cognitively unimpaired (CU) individuals and those with mild cognitive impairment (MCI); (2) assess which subjective cognitive complaints can differentiate Aβ-positive from Aβ-negative individuals, CU from MCI, and progressors from non-progressors; and (3) evaluate sex differences in these relationships.MethodsIn 418 CU older adults and 408 with MCI from the ADNI cohort, we examined associations between Aβ, subjective cognitive complaints and sex, controlling for age, education, depression, and anxiety.ResultsIn CU individuals, higher Aβ levels correlated with more severe language and visuospatial complaints. MCI individuals with elevated Aβ reported more severe memory, language, and planning complaints. Memory, language, planning, and organization complaints predicted risk of MCI and clinical progression. Sex differences emerged in the association between Aβ and visuospatial complaints, and in complaint types predicting Aβ positivity and cognitive impairment.ConclusionsSubjective cognitive complaints in memory and non-memory domains (language, visuospatial, and executive functions) may signal cognitive decline risk due to their association with AD biomarkers and clinical progression. Sex differences highlight the need for personalized approaches in AD early diagnosis and disease progression monitoring.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".