P3‐137: Does the length of time between traumatic brain injury and the onset of Alzheimer's disease affect the rate of cognitive and functional progression?: The Cache County Dementia Progression Study
Bibliographic record
Abstract
History of traumatic brain injury (TBI) has been associated with an increased risk of Alzheimer's Disease (AD) and, in animal studies, increased amyloid deposition. However, the effects of TBI on dementia progression have not been examined. We studied this issue in a population-based sample of persons with AD, and whether recency of TBI in relation to dementia onset affected the rate of cognitive and functional decline in AD. 325 individuals with incident AD (65% female) were examined at intervals between 0.5–2 years, for a maximum of 11.18 years (mdn=1.54). Mean (sd) age of dementia onset and duration at diagnosis were 84.4 (6.4) and 1.7 (1.4) years, respectively. Cognition was assessed with a neuropsychological test battery that included measures of episodic and semantic memory, verbal fluency, constructional praxis and executive functions. Functional ability was assessed with the Clinical Dementia Rating Scale sum of boxes (CDR-sb). Lifetime history of TBI, ascertained before the onset of dementia by the subject, and updated thereafter by a caregiver was categorized as: no TBI, history of TBI less than or equal to 10 years before dementia onset (TBI LTE 10), and history of TBI greater than 10 years before onset (TBI GT 10). Linear mixed models were fitted for each outcome. Covariates tested in all models included APOE genotype, and demographic factors. 8.9% of participants were categorized as TBI LTE 10, and 19.7% as TBI GT 10. Only those in the TBI LTE 10 group declined faster on the CDR-sb (P=0.02) and on average, had lower scores on semantic memory (P=0.01) compared to those without a history of TBI. Those categorized as TBI GT 10 on average, had higher scores on list learning and recognition memory (P < 0.02). History of TBI did not predict rate 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".