Correlation of serum uric acid, cystatin C and high-sensitivity C-reactive protein with cognitive impairment in lacunar cerebral infarction.
Bibliographic record
Abstract
OBJECTIVE: To study the correlation of serum uric acid (UA), cystatin C (Cys-C) and high-sensitivity C-reactive protein (hs-CRP) with cognitive impairment in lacunar cerebral infarction. METHODS: Total 198 patients with lacunar cerebral infarction were selected and divided into 4 groups according to their cognitive function, with 65 cases in the normal group, 72 cases in the mild cognitive impairment group, 38 cases in the moderate cognitive impairment group and 23 cases in the severe cognitive impairment group. The hs-CRP, serum UA, Cys-C and Montreal Cognitive Assessment (MoCA) were measured upon admission. RESULTS: There were statistical differences in hs-CRP, UA and Cys-C among the four groups (all P<0.001). MoCA was negatively correlated with hs-CRP, UA and Cys-C (all P<0.001). Multivariate logistic regression analysis showed that elevated levels of hs-CRP, UA and Cys-C were the influencing factors of cognitive impairment in patients with lacunar cerebral infarction (all P<0.05). CONCLUSION: The levels of hs-CRP, UA and Cys-C in patients with lacunar cerebral infarction increase with the aggravation of cognitive impairment, and high hs-CRP, UA and Cys-C are independent risk factors of cognitive impairment in patients with lacunar cerebral infarction.
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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 | 0.002 |
| 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 | 0.000 |
| 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".