Network meta-analysis of the efficacy of pharmacological treatments for post-stroke cognitive impairment and vascular cognitive impairment
Bibliographic record
Abstract
Background Based on recent reviews, vascular cognitive impairment (VCI) encompasses a spectrum of cognitive deficits caused by cerebrovascular disease and its risk factors, ranging from mild cognitive impairment to dementia, and often coexists with neurodegenerative conditions like Alzheimer’s disease. VCI is categorized into four clinical-imaging subtypes, including post-stroke cognitive impairment (PSCI)—a common stroke complication and major VCI subtype. Current guidelines recommend cholinesterase inhibitors and NMDA receptor antagonists as first-line treatments for VCI, with expert consensus supporting donepezil and rivastigmine for PSCI. However, existing evidence primarily derives from placebo-controlled or head-to-head drug comparisons, lacking comprehensive evaluations of multiple cognitive enhancers. This study aims to systematically assess the efficacy and safety of cognitive-enhancing drugs in VCI, with a focused analysis on PSCI, to better inform clinical decision-making and improve patient outcomes. Methods We systematically searched four databases using predefined search strategies. Eligible studies were selected based on predetermined criteria. The included studies were analyzed with StataSE 16.0, RevMan 5.3, and Grade software to compare the efficacy and safety of cognitive-enhancing drugs to identify the optimal treatment for VCI and PSCI. Results Sixteen studies (5,599 participants) were included. In terms of cognitive outcomes, sailuotong was superior to placebo on the Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-cog) (MD = −3.00, 95% CI: −4.50, −1.50) and ranked best (SUCRA 88.5%). Memantine was most effective on the Mini-Mental State Examination (MMSE) (MD = 1.23, 95% CI: 0.23–2.23; SUCRA 80.8%). For the secondary outcome, the MoCA assessment showed that Ginkgo biloba extract significantly improved Montreal Cognitive Assessment (MoCA) scores compared to placebo (MD = 1.29, 95% CI: 1.24, 1.35). Regarding safety, donepezil significantly increased the risk of overall adverse events compared to placebo (OR: 1.57; 95% CI: 1.19–2.06). Conclusion Our network meta-analysis suggests that memantine might have the best effect for PSCI, with sailuotong potentially serving as a secondary option. However, these estimates are based on a small randomized controlled trial and a sparse network. Therefore, the current evidence is limited, highlighting the need for more high-quality studies to robustly validate the therapeutic potential of these interventions for VCI and PSCI. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/ , identifier in PROSPERO (CRD420250627957).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.045 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".