Associations between Informant-Reported Cognitive Complaint and Longitudinal Cognitive Decline in Subjective Cognitive Decline A 7-Year Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: This study aimed to determine the predictive values of informant-reported memory decline (IMD) among subjective cognitive decline (SCD) older adults from a 7-year community-based cohort study. METHOD: Ninety SCD participants were included. Demographic data and neuropsychological test scores at both baseline and 7-year follow-up were collected. Differences between SCD with IMD (+IMD) and SCD without IMD (-IMD) were compared. Logistic regression models were used to determine whether baseline IMD could predict diagnostic outcomes at 7-year follow-up. RESULTS: Forty-one percent of SCD adults had IMD. At baseline, the +IMD group showed more depressive symptoms (p = 0.016) than the -IMD group. Furthermore, the Beijing-version Montreal Cognitive Assessment (MoCA), Digit Span Test-Forward, Visual Matching and Reasoning, and Wechsler Adult Intelligence Scale-RC Picture Completion (WAIS-PC) scores in the +IMD group were significantly lower than those in the -IMD group. Fifty-four percent of +IMD participants converted to mild cognitive impairment (MCI) or dementia at follow-up, and 22.6% of the -IMD participants converted to MCI. Follow-up Mini-Mental State Examination, MoCA, and Verbal Fluency Test scores of the +IMD group were significantly lower than those in the -IMD group. The +IMD group was more likely to progress to cognitive impairment at 7-year follow-up (OR = 3.361, p = 0.028). CONCLUSIONS: SCD participants with +IMD may have poorer cognition and are more likely to convert to cognitive impairment over time. Our long-term follow-up study confirmed the importance of informants' perceptions of SCD, which can help clinicians identify individuals at risk of cognitive decline.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| 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".