Early identification and severity prediction of acute respiratory infection (ESAR): a study protocol for a randomized controlled trial.

BACKGROUND: The outbreak of SARS-CoV-2 at the end of 2019 sounded the alarm for early inspection on acute respiratory infection (ARI). However, diagnosis pathway of ARI has still not reached a consensus and its impact on prognosis needs to be further explored. METHODS: ESAR is a multicenter, open-label, randomized controlled, non-inferiority clinical trial on evaluating the diagnosis performance and its impact on prognosis of ARI between mNGS and multiplex PCR. Enrolled patients will be divided into two groups with a ratio of 1:1. Group I will be directly tested by mNGS. Group II will firstly receive multiplex PCR, then mNGS in patients with severe infection if multiplex PCR is negative or inconsistent with clinical manifestations. All patients will be followed up every 7 days for 28 days. The primary endpoint is time to initiate targeted treatment. Secondary endpoints include incidence of significant events (oxygen inhalation, mechanical ventilation, etc.), clinical remission rate, and hospitalization length. A total of 440 participants will be enrolled in both groups. DISCUSSION: ESAR compares the efficacy of different diagnostic strategies and their impact on treatment outcomes in ARI, which is of great significance to make precise diagnosis, balance clinical resources and demands, and ultimately optimize clinical diagnosis pathways and treatment strategies. Trial registration Clinicaltrial.gov, NCT04955756, Registered on July 9th 2021.

Risk assessment of venous thromboembolism and bleeding in COVID-19 patients.

BACKGROUND: The coronavirus disease 2019 (COVID-19) is a newly recognized illness that has spread rapidly all over the world. More and more reports highlight the risk of venous thromboembolism (VTE) in COVID-19. Our study aims to identify in-hospital VTE risk and bleeding risk in COVID-19 patients. METHODS: We retrospectively studied 138 consecutively enrolled patients with COVID-19 and identified in-hospital VTE and bleeding risk by Padua Prediction Score and Improve bleed risk assessment model. The clinical data and features were analyzed in VTE patients. RESULTS: Our findings identified that 23 (16.7%) patients with COVID-19 were at high risk for VTE according to Padua prediction score and 9 (6.5%) patients were at high risk of bleeding for VTE prophylaxis according to Improve prediction score. Fifteen critically ill patients faced double high risk from thrombosis (Padua score more than 4 points in all 15 [100%] patients) and hemorrhage (Improve score more than 7 points in 9 [60.0%] patients). Thrombotic events were identified in four patients (2.9%) of all COVID-19 patients. All of them were diagnosed with deep vein thrombosis by ultrasound 3 to 18 days after admission. Three (75.0%) were critically ill patients, which means that the incidence of VTE among critically ill patients was 20%. One major hemorrhage happened in critically ill patients during VTE treatment. CONCLUSION: Critically ill patients with COVID-19 suffered both a high risk of thrombosis and bleeding risks. More effective VTE prevention strategies based on an individual assessment of bleeding risks were necessary for critically ill patients with COVID-19.

Power system load forecasting using mobility optimization and multi-task learning in COVID-19.

Affected by the new coronavirus (COVID-19) pandemic, global energy production and consumption have changed a lot. It is unknown whether conventional short-term load forecasting methods based on single-task, single-region, and conventional indicators can accurately capture the load pattern during the COVID-19 and should be carefully studied. In this paper, we make the following contributions: 1) A mobility-optimized load forecasting method based on multi-task learning and long short-term memory network is innovatively proposed to alleviate the impact of the COVID-19 on short-term load forecasting. The incorporation of mobility data and data sharing layers potentially reduces the difficulty of capturing the load patterns and improves the generalization of the load forecasting models. 2) The real public data collected from multiple agencies and companies in the United States and European countries are used to conduct horizontal and vertical tests. These tests prove the failure of the conventional models and methods in the COVID-19 and demonstrate the high accuracy (error mostly less than 1%) and robustness of the proposed model. 3) The Shapley additive explanations technology based on game theory is innovatively introduced to improve the objectivity of the models. It visualizes that mobility indicators are of great help to the accurate load forecasting. Besides, the non-synchronous relationships between the indicators' correlations and contributions to the load have been proved.

Early predicting indicators of conversion from mild to moderate in overseas-imported COVID-19 cases.

BACKGROUND: Due to the ongoing pandemic of coronavirus disease 2019 (COVID-19) in foreign countries and regions, many overseas people arrive in China by air. Currently, most of the new cases of COVID-19 were imported from overseas. Here, we evaluated the predictive effect of the level of blood albumin (ALB) and serum prealbumin (PA) level in overseas-imported cases on the conversion of mild COVID-19 to moderate and its value in guiding nutritional support for these travelers. METHODS: We retrospectively analyzed serum levels of ALB and PA of 193 patients with imported COVID-19 admitted to the Shanghai Public Health Clinical Center at the time of admission on April 8, 2020. RESULTS: Since the first overseas-imported case was admitted to Shanghai on March 5, 2020, 195 overseas-imported cases have been treated in the Shanghai Public Health Clinical Center. The disease was mild or moderate. A total of 193 patients (111 males and 82 females) entered our analysis and the disease was moderate in 108 patients and mild in 85 patients. Patients were aged 6 to 66 years (mean: 28 years). There was a strong negative correlation between the proportion of moderate type and ALB (P=0.0073); thus, patients with a lower level of ALB were more likely to be diagnosed with moderate type. The correlation coefficient was close to 0 in the scatter plot, indicating that there was no linear correlation between PA and the diagnosis of moderate type (P>0.05). There was a strong negative correlation between age and ALB level (P<0.001), while length of hospital stay did not show a linear correlation with ALB or PB levels (both P>0.05). Therefore, older patients had lower levels of ALB and were more likely to develop moderate COVID-19. CONCLUSIONS: The serum ALB level can be an early predictive indicator for the conversion of mild COVID-19 to moderate in cases imported overseas and may guide nutritional support.

Assessing risk factors for SARS-CoV-2 infection in patients presenting with symptoms in Shanghai, China: a multicentre, observational cohort study.

Background: The outbreak of COVID-19 has led to international concern. We aimed to establish an effective screening strategy in Shanghai, China, to aid early identification of patients with COVID-19. Methods: We did a multicentre, observational cohort study in fever clinics of 25 hospitals in 16 districts of Shanghai. All patients visiting the clinics within the study period were included. A strategy for COVID-19 screening was presented and then suspected cases were monitored and analysed until they were confirmed as cases or excluded. Logistic regression was used to determine the risk factors of COVID-19. Findings: We enrolled patients visiting fever clinics from Jan 17 to Feb 16, 2020. Among 53 617 patients visiting fever clinics, 1004 (1·9%) were considered as suspected cases, with 188 (0·4% of all patients, 18·7% of suspected cases) eventually diagnosed as confirmed cases. 154 patients with missing data were excluded from the analysis. Exposure history (odds ratio [OR] 4·16, 95% CI 2·74-6·33; p<0·0001), fatigue (OR 1·56, 1·01-2·41; p=0·043), white blood cell count less than 4 × 109 per L (OR 2·44, 1·28-4·64; p=0·0066), lymphocyte count less than 0·8 × 109 per L (OR 1·82, 1·00-3·31; p=0·049), ground glass opacity (OR 1·95, 1·32-2·89; p=0·0009), and having both lungs affected (OR 1·54, 1·04-2·28; p=0·032) were independent risk factors for confirmed COVID-19. Interpretation: The screening strategy was effective for confirming or excluding COVID-19 during the spread of this contagious disease. Relevant independent risk factors identified in this study might be helpful for early recognition of the disease. Funding: National Natural Science Foundation of China.