Deep brain stimulation (DBS) is a neurosurgical procedure indicated for patients with advanced Parkinson’s disease (PD). Whether similar benefits may be realized by patients with early PD, however, is currently unclear, especially given the potential risks of the procedure. This systematic review and meta-analysis aimed to investigate the relative efficacy and safety of DBS in comparison to best medical therapy (BMT) in the treatment of PD. It also aimed to compare the efficacy of DBS between patients with early and advanced PD.A systematic search was performed in Medline, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL). Randomized controlled trials (RCTs) comparing DBS to BMT in PD patients were included. Outcome measures were impairment/disability using the Unified Parkinson’s Disease Rating Scale (UPDRS), quality of life (QoL) using the Parkinson's Disease Questionnaire (PDQ-39), levodopa equivalent dose (LED) reduction, and rates of serious adverse events (SAE).Eight eligible RCTs (n = 1,189) were included in the meta-analysis, two of which recruited early PD patients. Regarding efficacy outcomes, there were significant improvements in UPDRS, PDQ-39, and LED scores in favour of DBS (P < 0.00001). There was a significantly greater reduction of LED in patients with early PD (P < 0.00001), but no other differences between early and advanced PD patients were found. The risk of a patient experiencing an SAE was significantly higher in the DBS group (P = 0.005), as was the total number of SAEs (P < 0.00188).Overall, DBS was superior to BMT at improving impairment/disability, QoL, and reducing medication doses, but these benefits need to be weighed against the higher risk of SAEs. There was insufficient evidence to determine the impact of the PD stage on the efficacy of DBS.
Direct oral anticoagulants (DOACs) have predictable pharmacokinetics and pharmacodynamics, limited potential for drug to drug interactions, and can be given at fixed doses without the need for routine coagulation monitoring, which makes them a very attractive alternative to vitamin K antagonists. DOACs act by specifically targeting a single coagulation factor, such as Factor Xa or thrombin. Rivaroxaban is a direct Factor Xa inhibitor and has been approved for use in several thromboembolic disorders, such as the prevention of stroke and systemic embolism in adults with non-valvular atrial fibrillation and the prevention of recurrent deep vein thrombosis and pulmonary embolism in adult patients. This review aimed to provide an overview of the mechanism of action of rivaroxaban and outline its pharmacokinetic properties (absorption, distribution, metabolism, and excretion) in healthy adult subjects.
Heart failure (HF) is a multi-faceted clinical condition affecting up to 2% of the population in the developed world and is linked to significant morbidity and mortality, therefore posing a major public health concern. To this date, pharmacotherapy for HF has mainly focused on chronic HF with reduced ejection fraction (HFrEF), with angiotensin converting enzyme inhibitors (ACEi) being at the centre of the management plan, alongside angiotensin-receptor-blockers (ARBs), β-blockers (BB) and mineralocorticoid receptor antagonists (MRAs). A novel and recently approved therapy, however, involving angiotensin receptor–neprilysin inhibitors (ARNI), has shown very promising results and comparable to those of ACEi, which raises the question of whether ACEi should remain the first-line treatment option for HFrEF. In this review, the evidence regarding the clinical efficacy of ACEi and ARNI in the treatment of HFrEF is discussed, with emphasis placed on the major landmark trials.
Background The scale and quality of the global scientific response to the COVID-19 pandemic have unquestionably saved lives. However, the COVID-19 pandemic has also triggered an unprecedented “infodemic”; the velocity and volume of data production have overwhelmed many key stakeholders such as clinicians and policy makers, as they have been unable to process structured and unstructured data for evidence-based decision making. Solutions that aim to alleviate this data synthesis–related challenge are unable to capture heterogeneous web data in real time for the production of concomitant answers and are not based on the high-quality information in responses to a free-text query. Objective The main objective of this project is to build a generic, real-time, continuously updating curation platform that can support the data synthesis and analysis of a scientific literature framework. Our secondary objective is to validate this platform and the curation methodology for COVID-19–related medical literature by expanding the COVID-19 Open Research Dataset via the addition of new, unstructured data. Methods To create an infrastructure that addresses our objectives, the PanSurg Collaborative at Imperial College London has developed a unique data pipeline based on a web crawler extraction methodology. This data pipeline uses a novel curation methodology that adopts a human-in-the-loop approach for the characterization of quality, relevance, and key evidence across a range of scientific literature sources. Results REDASA (Realtime Data Synthesis and Analysis) is now one of the world’s largest and most up-to-date sources of COVID-19–related evidence; it consists of 104,000 documents. By capturing curators’ critical appraisal methodologies through the discrete labeling and rating of information, REDASA rapidly developed a foundational, pooled, data science data set of over 1400 articles in under 2 weeks. These articles provide COVID-19–related information and represent around 10% of all papers about COVID-19. Conclusions This data set can act as ground truth for the future implementation of a live, automated systematic review. The three benefits of REDASA’s design are as follows: (1) it adopts a user-friendly, human-in-the-loop methodology by embedding an efficient, user-friendly curation platform into a natural language processing search engine; (2) it provides a curated data set in the JavaScript Object Notation format for experienced academic reviewers’ critical appraisal choices and decision-making methodologies; and (3) due to the wide scope and depth of its web crawling method, REDASA has already captured one of the world’s largest COVID-19–related data corpora for searches and curation.
Depression is a common psychiatric disorder affecting more than 300 million people worldwide. According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), the diagnosis of depression requires at least two weeks of either low mood or anhedonia as well as four or more other symptoms such as appetite or weight changes, insomnia or hypersomnia, psychomotor agitation or retardation, loss of energy, inability to concentrate, feelings of worthlessness or excessive guilt, and suicidality. Selective serotonin reuptake inhibitors (SSRIs) target the monoaminergic system and are the commonest drugs used for treating depression, but have certain limitations, such as their delayed onset of action. Ketamine, a non-competitive NMDA receptor antagonist, has shown in several randomized controlled trials (RCTs) promising results with rapid antidepressant effects, especially in patients with severe treatment-resistant depression (TRD), which is depression that has not responded to more than two antidepressants. In this review, the clinical efficacy of ketamine in TRD has been discussed, with emphasis placed on the evidence from RCTs.
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