Wade Mercer (steamring45)

To assess the feasibility of a modified workflow that uses machine learning and crowdsourcing to identify studies for potential inclusion in a systematic review. This was a substudy to a larger randomized study; the main study sought to assess the performance of single screening search results versus dual screening. This substudy assessed the performance in identifying relevant randomized controlled trials (RCTs) for a published Cochrane review of a modified version of Cochrane's Screen4Me workflow which uses crowdsourcing and machine learning. We included participants who had signed up for the main study but who were not eligible to be randomized to the two main arms of that study. The records were put through the modified workflow where a machine learning classifier divided the data set into "Not RCTs" and "Possible RCTs." The records deemed "Possible RCTs" were then loaded into a task created on the Cochrane Crowd platform, and participants classified those records as either "Potentially relevant" or "Not relevant" to the review. Using a prespecified agreement algorithm, we calculated the performance of the crowd in correctly identifying the studies that were included in the review (sensitivity) and correctly rejecting those that were not included (specificity). The RCT machine learning classifier did not reject any of the included studies. In terms of the crowd, 112 participants were included in this substudy. Of these, 81 completed the training module and went on to screen records in the live task. Applying the Cochrane Crowd agreement algorithm, the crowd achieved 100% sensitivity and 80.71% specificity. Using a crowd to screen search results for systematic reviews can be an accurate method as long as the agreement algorithm in place is robust. Open Science Framework https//osf.io/3jyqt. Open Science Framework https//osf.io/3jyqt.Coronavirus-triggered pulmonary and systemic disease, i.e. systemic inflammatory response to virally triggered lung injury, named COVID-19, and ongoing discussions on refining immunomodulation in COVID-19 without COX2 inhibition prompted us to search the related literature to show a potential target (COX2) and a weapon (celecoxib). The concept of selectively targeting COX2 and closely related cascades might be worth trying in the treatment of COVID-19 given the substantial amount of data showing that COX2, p38 MAPK, IL-1b, IL-6 and TGF-β play pivotal roles in coronavirus-related cell death, cytokine storm and pulmonary interstitial fibrosis. Considering the lack of definitive treatment and importance of immunomodulation in COVID-19, COX2 inhibition might be a valuable adjunct to still-evolving treatment strategies. Celecoxib has properties that should be evaluated in randomized controlled studies and is also available for off-label use. The global push for the use of hydroxychloroquine (HCQ) and chloroquine (CQ) against COVID-19 has resulted in an ongoing discussion about the effectivity and toxicity of these drugs. Recent studies report no effect of (H)CQ on 28-day mortality. see more We investigated the effect of HCQ and CQ in hospitalized patients on the non-ICU COVID-ward. A nationwide, observational cohort study was performed in The Netherlands. Hospitals were given the opportunity to decide independently on the use of three different COVID-19 treatment strategies HCQ, CQ, or no treatment. We compared the outcomes between these groups. The primary outcomes were 1) death on the COVID-19 ward, and 2) transfer to the intensive care unit (ICU). The analysis included 1064 patients from 14 hospitals 566 patients received treatment with either HCQ (n = 189) or CQ (n = 377), and 498 patients received no treatment. In a multivariate propensity-matched weighted competing regression analysis, there was no significant effect of (H)CQ on mortality on tom the regular ward to the ICU. Recent prospective studies have rep