P2‐119: Transitions in cognitive status in people with vascular cognitive impairment
Bibliographic record
Abstract
Little is known about progression of vascular cognitive impairment. On average, cognitive function worsens over time, but some people have periods of relatively stable status and even improvement in some functions. We present a multi-state Markov model to summarize 30-month transitions in cognitive function in elderly Canadians and analyze how known risk factors influence such transitions. The Consortium to Investigate Vascular Impairment of Cognition (CIVIC) was a multi-centre (nine university affiliated dementia centers). The patients were expected to have a baseline and two follow up visits one year apart from each other. The mini-mental scale examination (MMSE) score was used in assessing cognitive status of participants (n=1301) of whom 134 died over the course of the 30 month period. The cognitive states were defined by the errors in MMSE after combining them appropriately (e.g., MMSE score of 30 and 29 were represented by the zero cognitive error state, and so forth). A modified Poisson model with four parameters was used to model the probabilities of transition between cognitive states (two parameters) and death (the other two parameters). The stratified analysis was conducted to analyze the influence of the risk factors (age, sex, and education level) to cognitive transitions and death. The model fitted data with a very high accuracy, with the coefficient of correlation between observed and calculated transition probabilities from 0.85 to 0.94 for different strata. No significant difference between men and women were found neither in cognitive transitions nor mortality. The older sample (age >74) showed had significantly worse cognitive performance in the follow-up (p<0.01) but no significant differences in the probability of dying. The different pattern of transitions was shown between the groups with more or less than 11 years of education. Less educated people showed higher level of cognitive decline comparing to more educated group (p<0.05). A stochastic model can be used to calculate the chances of changes in cognitive performance (including improvement and decline) and death and in estimating the effect of the risks factors and demographic conditions to these changes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".