Brazilian Subjective Cognitive Decline (BRASCODE) Cohort: protocol and preliminary results
Bibliographic record
Abstract
BACKGROUND: Subjective Cognitive Decline (SCD) is a condition characterized by consistent cognitive complaints in cognitively unimpaired (CU) individuals and is associated with progressive cognitive impairment, especially in the context of Alzheimer's disease (AD). We aimed to show the study protocol and the preliminary results of the Brazilian Subjective Cognitive Decline (BRASCODE) Cohort. METHOD: CU individuals with > 65 years old and cognitive complaints were recruited. Exclusion criteria were previous diagnosis of dementia, uncontrolled neuropsychiatric/clinical illness, or cerebrovascular disease. The assessment was performed exclusively by phone calls. It consisted of a brief cognitive (Modified Telephone Interview for Cognitive Status - TICS-M) and anxiety/depression screenings, in addition to the SCD-scale (Figure 1). RESULT: Between March and November 2022, 52 SCD patients were included, 73.1% (n = 38) women. Their median interquartile range (IQR) age was 70 (68-73) years old, with 16 (9.25-19) years of formal education and median score of 28.5 (IQR 26,30) on Mini Mental State Examination (MMSE) (Table 1). Percentage of agreement on the presence of cognitive complaints between informants and patients was 38.5%. The main SCD-plus criteria were the age at onset of SCD ≥ 60 years old (84.6%, n = 44) and concerns associated with SCD (78.8%, n = 41). The key findings of the neuropsychological assessment are reported in Table 2. Deficits were observed mainly in memory and executive functioning domains. Explorative analysis showed that Cognitive Reserve Scale scores correlated positively with MMSE (rho = 0.311; p = 0.02) and with formal education (rho = 0.541; p<0.001) and negatively with CDR-sum of boxes (rho = -0.307; p = 0.03). The prevalence of APOE ε4 carriers was 29.8% (n = 14) and a dementia family history was more frequent in APOE ε4 carriers - 12 (85.7%) - than non-carries, 12 (36.4%). CONCLUSION: The increase in the sample size, especially with individuals with low education, associated with AD biomarkers analysis and long-term follow-up may bring valuable information about the progression of SCD to cognitive decline in Brazil. We estimate that a total of 150 individuals will be included by the end of 2023.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".