Meta-Analysis of Naoxintong Capsule for Patients with Vascular Dementia
Bibliographic record
Abstract
Background: Vascular dementia (VaD) is the second most common form of dementia among the elderly. There is currently no unequivocal recommendation of an effective treatment option for VaD. Objective: The purpose of this study was to evaluate the efficacy and safety of Naoxintong capsule (NXT) in the treatment of VaD patients. Methods: We searched for randomized controlled trials (RCTs) published before September 2021 in PubMed, Embase, Web of Science, Cochrane Library, CNKI, VIP, and Wanfang databases. The trials assessed the efficacy and/or safety of NXT in treating patients with VaD. A meta-analysis was then performed using Stata 14.0 software. Results: A total of 33 studies comprising 2,947 patients with VaD were included in this study. The meta-analysis revealed that NXT improved cognitive function in VaD patients, increased the mini-mental state examination (MMSE) score by 3.33 points (WMD = 3.33, 95% CI (2.72, 3.94)), the Montreal Cognitive Assessment (MoCA) score by 4.31 points (WMD = 4.31, 95% CI (2.72, 5.90)), and the Hasegawa dementia scale (HDS) by 2.71 points (WMD = 2.71, 95% CI (1.26, 4.17)). Furthermore, NXT significantly improved the daily lives of VaD patients, lowering the activities of daily living (ADL) score by 5.85 points (WMD = -5.85, 95% CI (-7.03, -4.66)). NXT improved the total effective rate (TER) (OR = 2.62, 95% CI (2.09, 3.29)) of the patients without increasing the occurrence of adverse events (AEs; OR = 0.72, 95% CI (0.43, 1.22)). Subgroup analysis revealed that whether NXT was used alone or in combination with western medicine, it could enhance the overall curative effect. Conclusions: NXT may be an effective and safe treatment option for VaD. However, because of the limited number and quality of articles included, this study's findings need to be validated by additional high-quality, large-sample, and multicenter RCTs (Systematic Review Registration Number: PROSPERO; https://clinicaltrials.gov/ct2/show/CRD42021233199).
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".