A comparative study to screen dementia and APOE genotypes in an ageing East African population
Bibliographic record
Abstract
Previous studies have established cross-cultural methods to screen for ageing- related dementia and susceptibility genes, in particular \nAlzheimer’s disease (AD) among the Canadian Cree, African Americans and Yoruba in Nigeria. We determined whether the Community \nScreening Interview for Dementia (CSID), translated into Kikuyu, a major language of Kenya, could be used to evaluate dementia of the \nAlzheimer type. Using two sets of coefficients of cognitive and informant scores, two discriminant function (DF) scores were calculated for \neach of 100 elderly (>65 years) Nyeri Kenyans. When the cut-off points were selected for 100% sensitivities, the specificities of the DF \nscores were remarkably similar (93.75%) in the Kenya sample. We propose the adapted CSID can be utilised to detect dementia among East \nAfricans. We also show that apolipoprotein E 4 allele frequencies were high (∼30%) and not different between normal subjects and those \nwith probable AD. There was no evidence to suggest years of education or vascular factors were associated with dementia status.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".