Su1776 Risk of Serious Upper Gastrointestinal (UGI) Complications in Patients Receiving Multiple Non-Selective NSAIDs for at Least 4 Weeks: A Series of Systematic Reviews and Meta-Analyses of Randomized Controlled Trials (RCT), Cohort and Case Control Studies

2012 ◽  
Vol 142 (5) ◽  
pp. S-501
Author(s):  
Grigorios I. Leontiadis ◽  
Yuhong Yuan ◽  
Frances Tse ◽  
Richard H. Hunt ◽  
Paul Moayyedi
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xia-tian Zhang ◽  
Xin-yi Li ◽  
Chen Zhao ◽  
Ye-yin Hu ◽  
Yi-yi Lin ◽  
...  

Objectives. To review the evidence of acupuncture for acute and preventive treatment of migraine for further awareness of the effect of acupuncture for migraine. Design. An overview of systematic reviews and meta-analyses (SR/MAs) for randomized controlled trials. Material and Methods. We searched PubMed, Embase, the Cochrane Library, China Knowledge Resource Integrated Database, VIP Chinese Journal Full Text Database, WANFANG Data, and China Biology Medicine disc from their establishment to May 27, 2018. SR/MAs of randomized controlled trials comparing the effect of the acupuncture intervention with another treatment control in migraine patients were included. Results. 428 SRs were identified, and 15 of them were included. Only 4 SR/MAs were assessed by GRADE, which showed certainty of most evidence being low or very low. Assessed by AMSTAR-2, fourteen was critically low rating overall confidence in the results, and 1 was low rating overall confidence in the results. Evidence suggested that acupuncture has a significant advantage of pain improvement, efficacy, and safety relative to blank control, sham acupuncture, or drug treatment, but some of these results are contradictory. Conclusions. We found that acupuncture on treating migraine has the advantage for pain improvement and safety, but the quality of SR/MAs of acupuncture for migraine remains to be improved.


10.2196/22422 ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. e22422
Author(s):  
Tomohide Yamada ◽  
Daisuke Yoneoka ◽  
Yuta Hiraike ◽  
Kimihiro Hino ◽  
Hiroyoshi Toyoshiba ◽  
...  

Background Performing systematic reviews is a time-consuming and resource-intensive process. Objective We investigated whether a machine learning system could perform systematic reviews more efficiently. Methods All systematic reviews and meta-analyses of interventional randomized controlled trials cited in recent clinical guidelines from the American Diabetes Association, American College of Cardiology, American Heart Association (2 guidelines), and American Stroke Association were assessed. After reproducing the primary screening data set according to the published search strategy of each, we extracted correct articles (those actually reviewed) and incorrect articles (those not reviewed) from the data set. These 2 sets of articles were used to train a neural network–based artificial intelligence engine (Concept Encoder, Fronteo Inc). The primary endpoint was work saved over sampling at 95% recall (WSS@95%). Results Among 145 candidate reviews of randomized controlled trials, 8 reviews fulfilled the inclusion criteria. For these 8 reviews, the machine learning system significantly reduced the literature screening workload by at least 6-fold versus that of manual screening based on WSS@95%. When machine learning was initiated using 2 correct articles that were randomly selected by a researcher, a 10-fold reduction in workload was achieved versus that of manual screening based on the WSS@95% value, with high sensitivity for eligible studies. The area under the receiver operating characteristic curve increased dramatically every time the algorithm learned a correct article. Conclusions Concept Encoder achieved a 10-fold reduction of the screening workload for systematic review after learning from 2 randomly selected studies on the target topic. However, few meta-analyses of randomized controlled trials were included. Concept Encoder could facilitate the acquisition of evidence for clinical guidelines.


2021 ◽  
Author(s):  
Laura Paige Penkert ◽  
Ruogu Li ◽  
Jing Huang ◽  
Anil Gurcan ◽  
Mei Chun Chung ◽  
...  

Pork is a frequently consumed red meat that provides substantial amounts of energy, macronutrients, and micronutrients to the diet. Its role in human nutrition and health is controversial and a plethora of data exist in the peer-reviewed scientific literature. Therefore, we conducted a scoping review of clinical and population-based studies to assess the effects of pork consumption on human nutrition and health. Results are reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews. Data were extracted from 86 studies, including 16 randomized controlled trials, 1 uncontrolled trial, 7 cohort studies, 4 nonrandomized controlled trials, 4 case-cohort and nested case-control studies, 33 case-control studies, and 21 cross-sectional studies. Intervention studies were conducted in healthy individuals and were short to moderate in duration. The effect of pork intake on patients’ nutrient status was the most commonly assessed outcome. The majority of observational studies assessed the effect of pork on cancer incidence, but no studies assessed the effects of pork on inflammation or oxidative stress. No interventional studies explored diabetes mellitus risk, and only one study assessed cancer risk associated with pork consumption. Several micronutrients in pork, including zinc, iron, selenium, choline, thiamin, and vitamins B6 and vitamin B12, are thought to influence cognitive function and may prove to be a unique area of research. To date, there is a dearth of high-quality randomized controlled trials assessing the effects of pork intake on disease risk factors and outcomes. This review helps highlight the many research gaps that future studies should be designed to address.


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