Research on the value of methionine loading test in the mild vascular cognitive impairment
Bibliographic record
Abstract
Objective To study the value of methionine loading test (MLT) in the mild vascular cognitive impairment (VCI) after acute cerebral infarction. Methods The fasting plasma homocystine (Hcy) level and homocystine level after MLT were measured by high-performance liquid chromatography methods. We chose 240 patients with normal level of fasting plasma Hcy (normal group), 159 patients with normal level of Hcy after MLT, 81 patients with hyperhomocysteinemia after MLT (hyperhomocysteinemia group), and 112 patients with fasting hyperhomocysteinemia (fasting hyperhomocysteinemia group) in this study. The Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) were conducted in normal, hyperhomocysteinemia and fasting hyperhomocysteinemia groups on admission, at 7d, 14 d, 30 d after treatment. Results Logistic regression analysis showed that the increased level of Hcy might be an independent risk factor for VCI〔OR: 1.285, 95%CI: 1.038-1.265, P 0.05). There were no significant differences in MMSE and MoCA scores between patients with fasting hyperhomocysteinemia and patients with hyperhomocysteinemia after MLT on admission, 7 d, 14 d and 30 d after treatment (P>0.05). Conclusions Hcy may be an independent risk factor for VCI. The MLT can discover the dormant vascular risk factors for VCI, which offers a valuable detection method for early intervention and prevention in the clinical medicine. Key words: Brain infarction; Cystine; Cognition disorders
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".