Naoxintong capsules in treating vascular cognitive impairment
Bibliographic record
Abstract
Objective To investigate the clinical effect of Naoxintong capsules in treating patients with vascular cognitive impairment(VCI).Methods Sixty patients with VCI were randomly divided into treatment group(30 cases)and control group(30 cases).The treatment group were treated with Naoxintong capsules(3 capsules,tid,for 3 months).The control group were treated with Nimotop tablets (1 pills,tid,for 3 months).Mini-Mental State Examination(MMSE),Montreal Cognitive Assessment (MoCA)were used for screening patients with VCI.All selected patients were followed up the MMSE,MoCA scores and the measured value of TG,TC,HDL-C,LDL-C and hs-CRP before treatment and 1 month later,2 months later,and 3 months after treatment.Their peripheral blood specimen were collected in the above-mentioned four time points.Results MMSE and MoCA scores were improved in both groups after treatment.There were significant differences before and after treatment in the two groups (P＜0.05).The time when MMSE and MoCA scores changed significantly was a little bit later in the treatment group than that in the control group,but there were no significant difference between the two groups after three months of treatment(P＞0.05).There were significant differences in the levels of TG,TC,HDL-C,LDL-C and hs-CRP before and after treatment in the treatment group(P＜0.05).But there were no significant differences in the levels of the above-mentioned serum lipid and hs-CRP in the control group before and after treatment(P＞0.05).Conclusions Naoxintong capsules have a certain effect in treating patients with vascular cognitive impairment.Its effect on improving the cognitive function is equal to Nimotop,and has effect of regulating blood tipids and reducing hs-CRP level,which Nimotop doesn't have. Key words: Naoxintong capsules; Nimotop; Vascular cognitive impairment; Cognitive function
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".