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SARS-CoV-2 proteins

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    Artificial intelligence-based CT metrics in relation with clinical outcome of COVID-19 MESHD in young and middle-aged adults

    Authors: Sihui Zeng; Weihong Liu; Xudong Yu; Yanli Li; Jiao Gao; Jiawei Li; Hanhui Li; Liang Mao; Chuanmiao Xie; Jianye Liang

    doi:10.21203/rs.3.rs-24561/v1 Date: 2020-04-22 Source: ResearchSquare

    Purposes: Currently, most researchers mainly analyzed COVID-19 MESHD pneumonia visually MESHD or qualitatively, probably somewhat time-consuming and not precise enough. This study aimed to excavate more information, such as differences in distribution, density, and severity of pneumonia lesions MESHD between males and females in a specific age group using artificial intelligence (AI)-based CT metrics. Besides, these metrics were incorporated into a clinical regression model to predict the short-term outcome.Methods: The clinical, laboratory information and a series of HRCT images from 49 patients, aged from 20 to 50 years and confirmed with COVID-19 MESHD, were collected. The volumes and percentages of infection (POI) among bilateral lungs and each bronchopulmonary segment were extracted using uAI-Discover- NCP PROTEIN software (version R001). The POI in three HU ranges, (i.e. <-300, -300~49 and ≥50 HU representing ground-glass opacity (GGO), mixed opacity and consolidation), were also extracted. Hospital stay was predicted with several POIs after adjusting days from illness onset to admission, leucocytes, lymphocytes, c-reactive protein HGNC, age and gender using a multiple linear regression model.Results: Right lower lobes had the highest POI, followed by left lower lobes, right upper lobes, middle lobes MESHD and left upper lobes. The distributions in lung lobes and segments were different between the sexes. Men had a higher total POI and GGO of the lungs, but less consolidation than women in initial CT (all p<0.05). The total POI, percentage of consolidation on initial CT and changed POI were positively correlated with hospital stay in the model.Conclusion: Both men and women had characteristic distributions in lung lobes MESHD and bronchopulmonary segments. AI-based CT quantitative metrics can provide more precise information regarding lesion distribution and severity to predict clinical outcome.

    Risk factors for severe corona virus disease 2019 ( COVID-19 MESHD) patients : a systematic review and meta analysis

    Authors: Lizhen Xu; mao yaqian; Gang Chen

    doi:10.1101/2020.03.30.20047415 Date: 2020-04-01 Source: medRxiv

    Importance: With the increasing number of infections for COVID-19 MESHD, the global health resources are deficient. At present, we don't have specific medicines or vaccines against novel coronavirus pneumonia MESHD ( NCP PROTEIN) and our assessment of risk factors for patients with severe pneumonia MESHD was limited. In order to maximize the use of limited medical resources, we should distinguish between mild and severe patients as early as possible. Objective: To systematically review the evidence of risk factors for severe corona virus disease MESHD 2019 ( COVID-19 MESHD) patients. Evidence Review: We conducted a comprehensive search for primary literature in both Chinese and English electronic bibliographic data bases including China National Knowledge Infrastructure (CNKI), Wanfang, Weipu, Chinese Biomedicine Literature Database (CBM-SinoMed), MEDLINE (via PubMed), EMBASE, Cochrane Central Register, and Web of science. The American agency for health research and quality (AHRQ) tool were used for assessing risk of bias. Mata-analysis was undertaken using STATA version 15.0. Results: 20 articles (N=4062 participants) were eligible for this systematic review and meta-analysis. First in this review and meta-analysis, we found that elderly male patients with a high body mass index, high breathing rate and a combination of underlying diseases (such as hypertension MESHD, diabetes MESHD, cardiovascular disease MESHD, and chronic obstructive pulmonary disease MESHD) were more likely to develop into critically ill MESHD patients. second, compared with ordinary patients, severe patients had more significant symptom such as fever MESHD and dyspnea MESHD. Besides, the laboratory test results of severe patients had more abnormal than non-severe patients, such as the elevated levels of white-cell counts, liver enzymes, lactate dehydrogenase, creatine kinase, c-reactive protein HGNC and procalcitonin, etc, while the decreased levels of lymphocytes and albumin, etc. Interpretation: This is the first systematic review investigating the risk factors for severe corona virus disease MESHD 2019 ( COVID-19 MESHD) patients. The findings are presented and discussed by different clinical characteristics. Therefore, our review may provide guidance for clinical decision-making and optimizes resource allocation.

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MeSH Disease
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