Efficacy analysis of neuroprotective drugs in patients with acute ischemic stroke based on network meta-analysis
Bibliographic record
Abstract
Objective: This network meta-analysis aims to explore the efficacy and safety of neuroprotective agents in patients with ischemic stroke and attempts to identify which drug is the most effective in improving outcomes for patients with acute ischemic stroke (AIS) through a ranking method. Methods: We comprehensively searched the PubMed, Medline, Embase, Web of Science, and Cochrane library databases from their establishment to 30 June 2024. Data were extracted from the studies identified, and their quality was assessed using the Cochrane risk-of-bias tool or the Newcastle-Ottawa Scale (NOS). The outcome measures were for a favorable prognosis, based on the modified Rankin Scale score (mRS) or National Institutes of Health Stroker Scale (NIHSS) score, mortality, and adverse effect with different drug regimens. We utilized Stata version 16.0 and Review Manager (RevMan) version 5.3.0 for statistical analysis. Results: A total of 35 studies were included: 25 randomized control trials, eight retrospective studies, and two prospective studies. The total sample size was 18,423 cases and included nine interventions: citicoline, edaravone (EDV), edaravone dexborneol, cinepazide maleate, cerebrolysin, minocycline, ginkgolide, ginkgo diterpene lactone meglumine (GDLM), and conventional (CON) treatment. Our analysis revealed that, except for edaravone dexborneol, the ginkgolide, EDV, cinepazide maleate, citicoline, cerebrolysin, minocycline, and GDLM treatment schemes reduced the mortality of patients with AIS compared with CON. Each drug regimen significantly improved the neural function of these patients compared with CON, which from highest to lowest was citicoline + vinpocetine, GDLM, citicoline, edaravone dexborneol, cinepazide maleate, ginkgolide, EDV, and CON. Moreover, we also found that, except for citicoline, the ginkgolide, EDV, edaravone dexborneol, GDLM, and cinepazide maleate treatment schemes had a high total treatment effective rate in these patients, the order from highest to lowest being ginkgolide, EDV, edaravone dexborneol, GDLM, cinepazide maleate, CON, and citicoline. In terms of the ineffective rate, we found that, compared with CON, the edaravone dexborneol, EDV, citicoline, GDLM, ginkgolide, and cinepazide maleate treatment schemes all had a lower ineffective rate. Finally, our analysis revealed that, except for cinepazide maleate and ginkgolide, the EDV, minocycline, edaravone dexborneol, GDLM, citicoline, and cerebrolysin schemes all had a higher rate of adverse effect on patients compared to CON. Based on the impact of the adverse effect with different surgical interventions, we further analyzed the effect of these drug treatments by the total treatment effective rate combined with adverse effect, revealing that EDV, ginkgolide, and edaravone dexborneol were the safest and most effective treatments. Conclusion: In patients with AIS, ginkgolide, EDV, cinepazide maleate, citicoline, cerebrolysin, minocycline, and GDLM were associated with a reduction in mortality rate. Moreover, ginkgolide, EDV, edaravone dexborneol, and GDLM treatment schemes revealed not only a high total treatment effective rate but also a low rate of treatment inefficacy. When considering the combination of the total treatment effective rate with adverse effect, EDV, ginkgolide, and edaravone dexborneol were revealed as the safest and most effective.
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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) | 0.006 | 0.003 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".