One-year Outcome of Shanghai Mild Cognitive Impairment Cohort Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND & OBJECTIVE: The purpose of this study is to identify the risk factors associated with the conversion from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) dementia for the early detection of AD. METHODS: The study comprised a prospective cohort study that included 400 MCI subjects with annual follow-ups for 3 years. RESULTS: During the first 12 months' follow-up, 42 subjects converted to Alzheimer's dementia (21 probable AD and 21 possible AD), two subjects converted to other types of dementia and 56 subjects lost follow. The factors associated with a greater risk of conversion from MCI to AD included gender, whole brain volume, and right hippocampal volume (rt. HV), as well as scores on the Revised Chinese version of the Alzheimer's Disease Assessment Scale-Cognitive subscale 13 (ADAS-Cog-C), Clock Drawing Test (CDT), Symbol Digit Modalities Test (SDMT), and Rey-Osterrieth Complex Figure Test (ROCFT). The risk classification of the combined ADAS-Cog-C and Alzheimer Cognitive Composite (ACC) score with the rt. HV and left Entorhinal Cortex Volume (lt. ECV) showed a conversion difference among the groups. CONCLUSION: Early detection of AD and potential selection for clinical trial design should utilize the rt. HV, as well as neuropsychological test scores, including those of the ADAS-Cog-C and ACC.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 it