Changes in Serum Cystatin C Levels and the Associations With Cognitive Function in Alzheimer's Disease Patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Cystatin C is indicated to be involved in the pathogenesis of Alzheimer's disease (AD) and cognitive impairment. Our objective is to examine the serum Cystatin C levels, and to clarify the correlations between serum Cystatin C and cognitive performance in Chinese AD patients. METHODS: The serum Cystatin C concentrations in AD patients and age, sex, and body mass index (BMI) matched-healthy controls were measured. The cognitive functions of the AD patients were evaluated by using the Mini-mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). The severity of dementia was determined with clinical dementia rating (CDR). RESULTS: A total of 463 AD patients and 1,389 matched healthy subjects were included. AD patients had higher serum Cystatin C than healthy controls. Serum cystatin C levels were correlated with MoCA scores in AD patients. In an ordinal logistic regression model, AD patients with higher serum cystatin C levels had increased odds of severe cognitive dysfunction. CONCLUSION: Our study suggested that AD patients had higher levels of serum cystatin C than age/sex/BMI-matched normal control subjects. Higher serum cystatin C may be associated with worse cognitive performance, but more studies are required to verify such association.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".