Plos One
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Meta Analysis
Efficacy and harms of remdesivir for the treatment of COVID-19: A systematic review and meta-analysis.
Efficacy and safety of treatments for hospitalized COVID-19 are uncertain. We systematically reviewed efficacy and safety of remdesivir for the treatment of COVID-19. ⋯ There is paucity of adequately powered and fully reported RCTs evaluating effects of remdesivir in hospitalized COVID-19 patients. Until stronger evidence emerges, we cannot conclude that remdesivir is efficacious for treating COVID-19.
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In face-to-face communication there are multiple paralinguistic and gestural features that facilitate recognition of a speaker's intended meaning, features that are lacking when people communicate digitally (e.g., texting). As a result, substitutes have emerged (expressive punctuation, capitalization, etc.) to facilitate communication in these situations. However, little is known about the comprehension processes involved in digital communication. ⋯ This effect did not occur when the question was a request for action, a more conventional type of indirect reply. Overall, then, this research demonstrates that emoji can sometimes facilitate the comprehension of meaning. Future research is needed to examine the boundary conditions for this effect.
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Arterial hypotension during the early phase of anesthesia can lead to adverse outcomes such as a prolonged postoperative stay or even death. Predicting hypotension during anesthesia induction is complicated by its diverse causes. We investigated the feasibility of developing a machine-learning model to predict postinduction hypotension. ⋯ This was higher than that for the Naïve Bayes (0.778; 95% CI: 0.65-0.898), logistic regression (0.756; 95% CI: 0.630-0.881), and artificial-neural-network (0.760; 95% CI: 0.640-0.880) models. The most important features affecting the accuracy of machine-learning prediction were a patient's lowest systolic blood pressure, lowest mean blood pressure, and mean systolic blood pressure before tracheal intubation. We found that machine-learning models using data obtained from various anesthesia machines between the start of anesthesia induction and immediately before tracheal intubation can predict hypotension occurring during the period between tracheal intubation and incision.
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Influential theoretical accounts take the position that classical conditioning can induce placebo effects through conscious expectancies. In the current study two different conditioning procedures (hidden and open) were used to separate expectancy from conditioning in order to reveal the role of expectancy in the formation of nocebo hyperalgesia. Eighty-seven healthy females were randomly assigned to three groups (hidden conditioning, open conditioning, and control). ⋯ The hidden conditioning procedure did not produce conscious expectancies related to pain. Nocebo hyperalgesia was induced in participants with low and high fear of pain and there was no difference in the magnitude of the nocebo effect between both groups. Nocebo hyperalgesia was not predicted by the fear of upcoming painful stimuli.
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Meta Analysis
Risk factors for predicting mortality of COVID-19 patients: A systematic review and meta-analysis.
Early and accurate prognosis prediction of the patients was urgently warranted due to the widespread popularity of COVID-19. We performed a meta-analysis aimed at comprehensively summarizing the clinical characteristics and laboratory abnormalities correlated with increased risk of mortality in COVID-19 patients. ⋯ Among the common symptoms of COVID-19 infections, fatigue, expectoration, hemoptysis, dyspnea and chest tightness were independent predictors of death. As for laboratory examinations, significantly increased pretreatment absolute leukocytosis count, LDH, PCT, D-Dimer and ferritin, and decreased pretreatment absolute lymphocyte count were found in non-survivors, which also have an unbeneficial impact on mortality among COVID-19 patients. Motoring these indicators during the hospitalization plays a very important role in predicting the prognosis of patients.