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Archives of Medical Research Feb 2024Fibrates are widely used in the treatment of dyslipidemia and associated metabolic abnormalities; however, their effects on adipokines are unclear. (Meta-Analysis)
Meta-Analysis
BACKGROUND
Fibrates are widely used in the treatment of dyslipidemia and associated metabolic abnormalities; however, their effects on adipokines are unclear.
AIM OF THE STUDY
This meta-analysis of clinical trials aimed to evaluate the effect of fibrates on circulating adipokine levels.
METHODS
Only randomized controlled trials investigating the impact/effect of fibrate treatment on circulating adipokine levels were included from searches in PubMed-Medline, SCOPUS, ClinicalTrials.gov, Web of Science, and Google Scholar databases. A random effects model and the generic inverse variance method were used for the meta-analysis. Sensitivity analysis was conducted using the leave-one-out method.
RESULTS
This meta-analysis of 22 clinical trials showed a significant reduction on/in leptin (WMD: -1.58 ng/mL, 95% CI: -2.96, -0.20, p = 0.02, I = 0%), plasminogen activator inhibitor-1 (PAI-1) (WMD: -13.86 ng/mL, 95% CI: -26.70, -1.03, p = 0.03, I = 99%), and visfatin (WMD: -1.52 ng/mL, 95% CI: -2.49, -0.56, p = 0.002, I = 0%) after fibrate therapy; no significant effect was observed on adiponectin (WMD: -0.69 µg/ml, 95% CI: -1.40, 0.02, p = 0.06, I = 83%) and resistin (WMD: -2.27 ng/mL, 95% CI: -7.11, 2.57, p = 0.36, I = 0%). The sensitivity analysis was robust only for visfatin, while the effect size was sensitive to one arm for leptin, four for adiponectin, and two for PAI-1.
CONCLUSION
This meta-analysis showed that fibrate treatment significantly improves adipokine levels with a decrease in leptin, PAI-1, and visfatin, suggesting potential additional clinical therapeutic benefits through/of fibrate treatment on adipose tissue.
Topics: Leptin; Fibric Acids; Adipokines; Plasminogen Activator Inhibitor 1; Nicotinamide Phosphoribosyltransferase; Adiponectin; Randomized Controlled Trials as Topic
PubMed: 38266418
DOI: 10.1016/j.arcmed.2024.102957 -
PloS One 2024The effectiveness of administering argatroban as a treatment approach following antiplatelet therapy or alteplase thrombolytic therapy in patients with acute stroke is... (Meta-Analysis)
Meta-Analysis
Can the combination of antiplatelet or alteplase thrombolytic therapy with argatroban benefit patients suffering from acute stroke? a systematic review, meta-analysis, and meta-regression.
BACKGROUND
The effectiveness of administering argatroban as a treatment approach following antiplatelet therapy or alteplase thrombolytic therapy in patients with acute stroke is presently uncertain. However, it is important to highlight the potential benefits of combining this medication with known thrombolytics or antiplatelet therapy. One notable advantage of argatroban is its short half-life, which helps minimize excessive anticoagulation and risk of bleeding complications in inadvertent cases of hemorrhagic stroke. By conducting a meticulous review and meta-analysis, we aim to further explore the common use of argatroban and examine the plausible advantages of combining this medication with established thrombolytic and antiplatelet therapies.
METHOD
In this study, we performed a rigorous and methodical search for both randomized controlled trials and retrospective analyses. Our main objective was to analyze the impact of argatroban on the occurrence of hemorrhagic events and the mRS scores of 0-2. We utilized a meta-analysis to assess the relative risk (RR) associated with using argatroban versus not using it.
RESULTS
In this study, we analyzed data from 11 different studies, encompassing a total of 8,635 patients. Out of these patients, 3999(46.3%) received argatroban treatment while the remaining 4636(53.7%)did not. The primary outcome of 90-day functional independence (modified Rankin scale (mRS) score≤2) showed that the risk ratio (RR) for patients using argatroban after alteplase thrombolytic therapy compared to those not using argatroban was(RR, 1.00 ([95% CI, 0.92-1.09]; P = 0.97), indicating no statistical significance. However, for patients using argatroban after antiplatelet therapy, was (RR,1.09 [95% CI, 1.04-1.14]; P = 0.0001), which was statistically significant. In terms of hemorrhagic events, the RR for patients using argatroban compared to those not using argatroban was (RR,1.08 [95% CI, 0.88-1.33]; P = 0.46), indicating no statistical significance.
CONCLUSION
The results of this study suggest that further research into combination therapy with argatroban and antiplatelet agents may be warranted, however more rigorous RCTs are needed to definitively evaluate the effects of combination treatment.
Topics: Humans; Platelet Aggregation Inhibitors; Tissue Plasminogen Activator; Retrospective Studies; Stroke; Hemorrhage; Fibrinolytic Agents; Thrombolytic Therapy; Treatment Outcome; Randomized Controlled Trials as Topic; Arginine; Pipecolic Acids; Sulfonamides
PubMed: 38412157
DOI: 10.1371/journal.pone.0298226 -
Frontiers in Neurology 2023To identify and compare published models that use related factors to predict the risk of intracranial hemorrhage (ICH) in acute ischemic stroke patients receiving...
OBJECTIVES
To identify and compare published models that use related factors to predict the risk of intracranial hemorrhage (ICH) in acute ischemic stroke patients receiving intravenous alteplase treatment.
METHODS
Risk prediction models for ICH in acute ischemic stroke patients receiving intravenous alteplase treatment were collected from PubMed, Embase, Web of Science, and the Cochrane Library up to April 7, 2023. A meta-analysis was performed using Stata 13.0, and the included models were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST).
RESULTS
A total of 656 references were screened, resulting in 13 studies being included. Among these, one was a prospective cohort study. Ten studies used internal validation; five studies used external validation, with two of them using both. The area under the receiver operating characteristic (ROC) curve for subjects reported in the models ranged from 0.68 to 0.985. Common predictors in the prediction models include National Institutes of Health Stroke Scale (NIHSS) (OR = 1.17, 95% CI 1.09-1.25, < 0.0001), glucose (OR = 1.54, 95% CI 1.09-2.17, < 0.05), and advanced age (OR = 1.50, 95% CI 1.15-1.94, < 0.05), and the meta-analysis shows that these are independent risk factors. After PROBAST evaluation, all studies were assessed as having a high risk of bias but a low risk of applicability concerns.
CONCLUSION
This study systematically reviews available evidence on risk prediction models for ICH in acute ischemic stroke patients receiving intravenous alteplase treatment. Few models have been externally validated, while the majority demonstrate significant discriminative power.
PubMed: 38249727
DOI: 10.3389/fneur.2023.1224658