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The coronavirus disease 2019 (COVID-19) pandemic has had a devastating impact worldwide, and timely detection and quarantine of infected patients are critical to prevent spread of disease. Serological antibody testing is an important diagnostic method used increasingly in clinics, although its clinical application is still under investigation.
Multiple sclerosis is the most common demyelinating disease of the central nervous system with serious social and economic burden. Siponimod is a sphingosine-1-phosphate receptor agonist, and clinical trials in the past decade have shown good prospects for the treatment of multiple sclerosis. But there is a lack of comprehensive understanding of the dose-effect relationship and safety in different subtypes of multiple sclerosis at present.
Although many machine learning algorithms have been developed to detect anterior cruciate ligament (ACL) injury based on magnetic resonance imaging (MRI), the performance of different algorithms required further investigation. The objectives of this current systematic review are to evaluate the diagnostic accuracy of machine-learning-assisted detection for ACL injury based on MRI and find the current best algorithm.
The recent application of gene-sequencing technology has identified many new somatic mutations in patients with myelodysplastic syndromes (MDS). Among them, serine and arginine rich splicing factor 2 (SRSF2) mutations belonging to the RNA splicing pathway were of interest. Many studies have already reported the potential prognostic value of SRSF2 mutations in MDS patients, with controversial results. Therefore, a meta-analysis was performed to investigate their prognostic impact on MDS.
Evidence-based guidelines are expected to provide clinicians with explicit recommendations on how to manage health conditions and bridge the gap between research and clinical practice. However, the existing practice guidelines(CPGs) vary in quality. This study aimed to evaluate the quality of CPGs of kidney cancer.
We aimed to evaluate immune-related adverse events occurring in clinical trials of anti-programmed cell death 1 (PD-1) drugs, compared with control treatments, including chemotherapy, targeted drugs, or placebo. Further we compared the occurrence of immune -related events in patients treated with different anti-PD-1 drugs.
Background: Antipsychotic drugs may lead to side effects such as obesity, diabetes, dyslipidemia, and cardiovascular disease. The current systematic review and network meta-analysis analyzes and provides an update on the clinical performance of these add-ons in comparison to placebo on body weight and body mass index (BMI) reductions. Methods: A comprehensive literature search was performed on electronic databases: PubMed (1946-), Embase (1974-), Cochrane library (1992-), and OpenGrey (2000-) until 31 July 2018. Network meta-analyses, comparing the body weight change, BMI change and withdrawn due to adverse events of different pharmacological add-ons, was performed using a multivariate meta-regression model with random-effects, adopting a frequentist approach. To rank the prognosis for all add-ons, we used surface under the cumulative ranking (SUCRA) values. Outcomes: From 614 potential studies identified, 27 eligible studies (n = 1,349 subjects) were included. All the studies demonstrated low to moderate risk of bias. For the analysis of body weight change, all add-ons except Ranitidine showed significant weight reductions comparing to placebo. The effectiveness rank based on SUCRA results from highest to lowest was Sibutramine, Topiramate, Metformin, Reboxetine, Ranitidine, and placebo. A similar pattern was seen for BMI change. The analysis of safety outcome did not detect significantly increased withdrawn number from the add-ons. Current evidence showed relatively good tolerance and safety of using the pharmacological add-ons. Interpretation: Topiramate and Metformin are effective add-on treatments in controlling antipsychotic-induced weight gain, comparing to placebo. They are well tolerated in short-term period. Although Sibutramine has the highest rank of the effectiveness, its license has been withdrawn in many countries due to its adverse effects. Hence, Sibutramine should not be adopted to treat antipsychotic-induced weight gain.
Background: Epilepsy is one of the most prevalent chronic brain diseases worldwide and is often accompanied by cognitive impairment. Event-related potentials (ERPs) are an objectively non-invasive approach for studying information processing and cognitive functions in the brain. The P300 is an important and extensively explored late component of ERPs that has been widely applied to assess cognitive function in epilepsy in previous studies. However, consistent conclusions have not yet been reached for various reasons. Objective: We conducted a comprehensive systematic review and meta-analysis of P300-related studies to assess the latency and amplitude of the P300 in epileptic patients. Methods: PubMed, EMBASE, and Cochrane Library databases were systematically searched for eligible studies. The standard mean difference (SMD) and the 95% confidence interval (CI) were calculated as the effect size of the P300 component. Results: The main results of the present meta-analysis indicated that epileptic patients have a longer P300 latency and a lower P300 amplitude than controls. Subgroup analysis based on age group demonstrated that these differences can be observed in both children and adult patients compared with healthy controls. In addition, the P300 latency was longer in patients with the five main types of epileptic seizures than in controls. Conclusion: This study revealed that epileptic patients have abnormalities in the P300 component, which may reflect deficits in cognitive function. Thus, the P300 may be a potential objective approach for evaluating cognitive function in epileptic patients.
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