[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

https://backend.orbit.dtu.dk/ws/files/238108460/1_s2.0_S0092867420310084_main.pdf

Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or Mild COVID-19.

BACKGROUND

There is disagreement about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We conducted a living systematic review and meta-analysis to address three questions: (1) Amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) Amongst people with SARS-CoV-2 infection who are asymptomatic when diagnosed, what proportion will develop symptoms later? (3) What proportion of SARS-CoV-2 transmission is accounted for by people who are either asymptomatic throughout infection or presymptomatic?

METHODS AND FINDINGS

We searched PubMed, Embase, bioRxiv, and medRxiv using a database of SARS-CoV-2 literature that is updated daily, on 25 March 2020, 20 April 2020, and 10 June 2020. Studies of people with SARS-CoV-2 diagnosed by reverse transcriptase PCR (RT-PCR) that documented follow-up and symptom status at the beginning and end of follow-up or modelling studies were included. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with an adapted checklist for case series, and the relevance and credibility of modelling studies were assessed using a published checklist. We included a total of 94 studies. The overall estimate of the proportion of people who become infected with SARS-CoV-2 and remain asymptomatic throughout infection was 20% (95% confidence interval [CI] 17-25) with a prediction interval of 3%-67% in 79 studies that addressed this review question. There was some evidence that biases in the selection of participants influence the estimate. In seven studies of defined populations screened for SARS-CoV-2 and then followed, 31% (95% CI 26%-37%, prediction interval 24%-38%) remained asymptomatic. The proportion of people that is presymptomatic could not be summarised, owing to heterogeneity. The secondary attack rate was lower in contacts of people with asymptomatic infection than those with symptomatic infection (relative risk 0.35, 95% CI 0.10-1.27). Modelling studies fit to data found a higher proportion of all SARS-CoV-2 infections resulting from transmission from presymptomatic individuals than from asymptomatic individuals. Limitations of the review include that most included studies were not designed to estimate the proportion of asymptomatic SARS-CoV-2 infections and were at risk of selection biases; we did not consider the possible impact of false negative RT-PCR results, which would underestimate the proportion of asymptomatic infections; and the database does not include all sources.

CONCLUSIONS

The findings of this living systematic review suggest that most people who become infected with SARS-CoV-2 will not remain asymptomatic throughout the course of the infection. The contribution of presymptomatic and asymptomatic infections to overall SARS-CoV-2 transmission means that combination prevention measures, with enhanced hand hygiene, masks, testing tracing, and isolation strategies and social distancing, will continue to be needed.

/pdf/occurrence-and-transmission-potential-of-asymptomatic-and-27ou6uv041.pdf

Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis.

Mechanisms of SARS-CoV-2 Transmission and Pathogenesis.

South Australia is presently in the throes of major changes to its regulatory system governing land use, development of land and the development of planning policy against which development assessment decisions are to be made. Eventually the planning and development control system established under the Development Act 1993 (SA) will be replaced by a new system implemented by the Planning, Development and Infrastructure Act 2016 (SA) (the new Act).

COVID-19 Generated Changes to Planning and Development Controls in South Australia (preprint)

CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China.

The clinical course and its correlated immune status in COVID-19 pneumonia.

MiR-122-5p protects against acute lung injury via regulation of DUSP4/ERK signaling in pulmonary microvascular endothelial cells.

The number of corona virus disease 2019 cases is increasing rapidly. However, the comparison of clinical characteristics between patients ≥ 70 and those < 70 has not been implemented yet. To achieve that, we collected clinical data of consecutive 222 patients in Renmin Hospital of Wuhan University diagnosed between January 13, 2020 and February 4, 2020. We divided them into an under-70 group and an over-70 group according to their ages, comparing their clinical characteristics. Meanwhile, univariate and multivariate Cox regression analyses were performed to identify the prognostic factors. Among the patients enrolled, 37 (16.67%) were 70 or older and 185 (83.33%) were younger than 70. Higher proportions of dyspnoea, expectoration, chronic cardiovascular disease, diabetes, organ complications, severe-to-critical cases, a higher death rate, a longer hospital stay and decreased immune status were observed in the over-70 group patients compared with their younger counterparts. The risk factors for death included dyspnoea, muscle ache, elevated myocardial enzymes, elevated C3 in over-70 patients and dyspnoea, pharyngalgia, chronic cardiac disease, increased C-reactive protein, IgA, decreased platelets in under-70 patients. Overall, our research compared the clinical characteristics of the two populations with different immune status and illustrated differentiated risk factors for death in them.

Comparison of clinical characteristics of COVID-19 between elderly patients and young patients: a study based on a 28-day follow-up.

Background: In late December 2019, a pneumonia caused by SARS-CoV-2 was first reported in Wuhan and spread worldwide rapidly. Currently, no specific medicine is available to treat infection with COVID-19.
Objective: The aims of this study were to summarize the epidemiological and clinical characteristics of 175 patients with SARS-CoV-2 infection who were hospitalized in Renmin Hospital of Wuhan University from January 1 to January 31, 2020, and to establish a tool to identify potential critical patients with COVID-19 and help clinical physicians prevent progression of this disease.
Methods: In this retrospective study, clinical characteristics of 175 confirmed COVID-19 cases were collected and analyzed. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select variables. Multivariate analysis was applied to identify independent risk factors in COVID-19 progression. We established a nomogram to evaluate the probability of progression of the condition of a patient with COVID-19 to severe within three weeks of disease onset. The nomogram was verified using calibration curves and receiver operating characteristic curves.
Results: A total of 18 variables were considered to be risk factors after the univariate regression analysis of the laboratory parameters (P<.05), and LASSO regression analysis screened out 10 risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were age (OR 1.035, 95% CI 1.017-1.054; P<.001), CK level (OR 1.002, 95% CI 1.0003-1.0039; P=.02), CD4 count (OR 0.995, 95% CI 0.992-0.998; P=.002), CD8 % (OR 1.007, 95% CI 1.004-1.012, P<.001), CD8 count (OR 0.881, 95% CI 0.835-0.931; P<.001), and C3 count (OR 6.93, 95% CI 1.945-24.691; P=.003). The areas under the curve of the prediction model for 0.5-week, 1-week, 2-week and 3-week nonsevere probability were 0.721, 0.742, 0.87, and 0.832, respectively. The calibration curves showed that the model had good prediction ability within three weeks of disease onset.
Conclusions: This study presents a predictive nomogram of critical patients with COVID-19 based on LASSO and Cox regression analysis. Clinical use of the nomogram may enable timely detection of potential critical patients with COVID-19 and instruct clinicians to administer early intervention to these patients to prevent the disease from worsening.

/pdf/nomogram-for-predicting-covid-19-disease-progression-based-4sf99s1ecu.pdf

Xiaokang Shen

Papers

CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China.

The clinical course and its correlated immune status in COVID-19 pneumonia.

MiR-122-5p protects against acute lung injury via regulation of DUSP4/ERK signaling in pulmonary microvascular endothelial cells.

Comparison of clinical characteristics of COVID-19 between elderly patients and young patients: a study based on a 28-day follow-up.

Nomogram for Predicting COVID-19 Disease Progression Based on Single-Center Data: Observational Study and Model Development.