The effect of alcohol and tobacco consumption, and apolipoprotein E genotype, on the age of onset in Alzheimer's disease
Bibliographic record
Abstract
OBJECTIVE: This study examined the association between a history of heavy alcohol use and smoking, presence of the apolipoprotein-E epsilon 4 allele (APOE epsilon4), and age of disease onset in a community dwelling sample of 685 Alzheimer's disease (AD) patients spanning three ethnic groups. DESIGN: Cross-sectional study of AD patients evaluated at a University-affiliated outpatient memory disorders clinic. SUBJECTS: A clinic-based cohort of white non-Hispanic (WNH; n = 397), white Hispanic (WH; n = 264), and African-American (AA; n = 24) patients diagnosed with possible or probable AD according to NINCDS-ADRDA diagnostic criteria. MEASUREMENTS: The age of onset of AD was obtained from a knowledgeable family member. All patients were assessed for APOE genotype. History of alcohol and tobacco consumption prior to the onset of dementia was obtained via an interview with the patient and the primary caregiver. A history of heavy drinking was defined as >2 drinks per day and a history of heavy smoking was defined as > or =1 pack per day. RESULTS: Presence of an APOE epsilon4 allele, a history of heavy drinking, or a history of heavy smoking were each associated with an earlier onset of AD by 2-3 years. Patients with all three risk factors were likely to be diagnosed with AD nearly 10 years earlier than those with none of the risk factors. CONCLUSION: The results suggest that APOE epsilon4 and heavy drinking and heavy smoking lower the age of onset for AD in an additive fashion.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".