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Background and Purpose: Fluoxetine is a drug commonly used to treat mental disorders, such as depression and obsessive–compulsive disorder, and some studies have shown that fluoxetine can improve motor and function recovery after stroke. Therefore, we performed a meta-analysis to investigate the efficacy and safety of fluoxetine in the treatment of post-stroke neurological recovery.Methods: PubMed, Embase, and Cochrane Library were searched for randomized controlled trials (RCTs) that were performed to assess the efficacy and safety of fluoxetine for functional and motor recovery in subacute stroke patients up to October 2020. Review Manager 5.3 software was used to assess the data. The risk ratio (RR) and standardized mean difference (SMD) were analyzed and calculated with a fixed effects model.Results: We pooled 6,788 patients from nine RCTs. The primary endpoint was modified Rankin Scale (mRS). Fluoxetine did not change the proportion of mRS ≤ 2 (P = 0.47). The secondary endpoints were Fugl-Meyer Motor Scale (FMMS), Barthel Index (BI), and National Institutes of Health Stroke Scale (NIHSS). Fluoxetine improved the FMMS (P < 0.00001) and BI(P < 0.0001) and showed a tendency of improving NIHSS (P = 0.08). In addition, we found that fluoxetine reduced the rate of new-onset depression (P < 0.0001) and new antidepressants (P < 0.0001).Conclusion: In post-stroke treatment, fluoxetine did not improve participants' mRS and NIHSS but improved FMMS and BI. This difference could result from heterogeneities between the trials: different treatment duration, clinical scales sensitivity, patient age, delay of inclusion, and severity of the deficit.

The terahertz EIT graphene metamaterial, consisting of two coupled split ring resonators placed in orthogonally twisted fashion, was proposed by patterning graphene. An actively controlled EIT peak can be obtained by changing relaxation time or Fermi energy of graphene.