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      COVID 19 in pregnant women and neonates: Clinical characteristics and laboratory and imaging findings. An overview of systematic reviews

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          Summary

          Explora los efectos de la infección por SARS-CoV-2 en embarazadas y recién nacidos. Nuestro artículo analiza las características clínicas, resultados de laboratorio e imágenes en madres con COVID-19 y sus bebés.

          Abstract

          Introduction: SARS-CoV-2 infection in the perinatal period may be associated with an increased risk of morbidity and mortality in both the mother and the neonate. Objective: To describe the clinical characteristics and, laboratory and imaging findings in pregnant women with COVID-19 and their newborns. Materials and methods: We searched PubMed, Scopus, Web of Science, and Cochrane databases for systematic reviews published between February 1, 2020, and May 30, 2021, describing clinical characteristics and laboratory and imaging (chest) findings in pregnant women with COVID-19 and their newborns; there were no language restrictions. Data were reanalyzed by means of Bayesian meta-analysis using Markov Chain Monte Carlo methods. The study protocol is registered in PROSPERO under code CRD42020178329. Results: Six systematic reviews were retrieved (for a total of 617 primary studies). A narrative synthesis of the proportions of signs, symptoms, and imaging and laboratory findings of both mothers and neonates was performed. The Odds ratios (OR) between pregnant women with and without COVID-19 were as follows: fetal well-being involvement: 1.9 (95%CI:1.09-3.63); stillbirth: 1.73 (95%CI:1.01-2.94); preterm birth: 1.77 (95%CI:1.25-2.61); maternal admission to the intensive care unit (ICU): 6.75 (95%CI:1-31.19). Regarding symptomatology, the following OR was obtained for myalgia between pregnant women and non-pregnant women with COVID-19: 0.67 (95% CI:0.51-0.93). Conclusions: Cough, fever, dyspnea, and myalgia are the most common symptoms in pregnant women with COVID-19; in addition, there is a higher risk of admission to the ICU. Regarding complementary testing, the most frequent alterations are lymphopenia and the evidence of lesions in chest imaging studies. The presence of COVID-19 in pregnant women is associated with premature birth. It seems that SARS-CoV-2 infection in neonates is not serious and the risk of vertical transmission is low, since no data about congenital malformations attributable to the virus were found.

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            A pneumonia outbreak associated with a new coronavirus of probable bat origin

            Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats 1–4 . Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans 5–7 . Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV.
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              Rayyan—a web and mobile app for systematic reviews

              Background Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Results Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.
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                Author and article information

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                Journal
                Revista de la Facultad de Medicina
                Rev. Fac. Med.
                Universidad Nacional de Colombia
                2357-3848
                0120-0011
                December 23 2021
                March 25 2022
                : 71
                : 1
                : e97588
                Article
                10.15446/revfacmed.v71n1.97588
                42546bbc-c678-43a7-ad18-e900a41671a6
                © 2022

                http://creativecommons.org/licenses/by/3.0/

                History

                Medicine,Obstetrics & Gynecology,Neonatology
                Recien nacidos,Embarazadas,Teorema de Bayes,Covid-19
                Medicine, Obstetrics & Gynecology, Neonatology
                Recien nacidos, Embarazadas, Teorema de Bayes, Covid-19

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                Es una revision sistematica donde se aplica metodos Bayesianos para los metanálisis 

                2023-06-12 02:11 UTC
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