National resilience assessment and improvement based on multi-source data: Evidence from countries along the belt and road.

National resilience is a consensus benchmark to characterize the ability of disaster resistance of a country. The occurrence of various disasters and the ravages of COVID-19 have created urgent needs in assessing and improving the national resilience of countries, especially for countries along the Belt and Road (i.e., B&R countries) with multiple disasters with high frequency and great losses. To accurately depict the national resilience profile, a three-dimensional assessment model based on multi-source data is proposed, where the diversity of losses, fusion utilization of disaster and macro-indicator data, and several refined elements are involved. Using the proposed assessment model, the national resilience of 64 B&R countries is clarified based on more than 13,000 records involving 17 types of disasters and 5 macro-indicators. However, their assessment results are not optimistic, the dimensional resilience are generally trend-synchronized and individual difference in a single dimension, and approximately one-half of countries do not obtain resilience growth over time. To further explore the applicable solutions for national resilience improvement, a coefficient-adjusted stepwise regression model with 20 macro-indicator regressors is developed based on more than 19,000 records. This study provides the quantified model support and a solution reference for national resilience assessment and improvement, which contributes to addressing the global national resilience deficit and promoting the high-quality development of B&R construction.

Protection from COVID-19 disease in hamsters vaccinated with subunit SARS-CoV-2 S1 mucosal vaccines adjuvanted with different adjuvants.

Introduction: Adjuvant plays an important role in directing the immune responses induced by vaccines. In previous studies, we have shown that a mucosal SARS-CoV-2 S1 subunit vaccine adjuvanted with a combination of CpG, Poly I:C and IL-15 (named CP15) induced effective mucosal and systemic immunity and conferred nearly sterile protection against SARS-CoV-2 viral replication in macaque models. Methods: In this study, we used a hamster model, which mimics the human scenario and reliably exhibits severe SARS-CoV-2 disease similar to hospitalized patients, to investigate the protection efficacy of the vaccines against COVID-19 disease. We compared the weight loss, viral loads (VLs), and clinical observation scores of three different vaccine regimens. All three regimens consisted of priming/boosting with S1 subunit vaccines, but adjuvanted with alum and/or CP15 administrated by either intramuscular (IM) or intranasal (IN) routes: Group 1 was adjuvanted with alum/alum administrated IM/IM; Group 2 was alum-IM/CP15-IN; and Group 3 was CP15-IM/CP15-IN. Results: After challenge with SARS-CoV-2 WA strain, we found that the alum/CP15 group showed best protection against weight loss, while the CP15 group demonstrated best reduction of oral SARS-CoV-2 VLs, suggesting that the protection profiles were different. Sex differences for VL and clinical scores were observed. Humoral immunity was induced but not correlated with protection. Moreover, S1-specific binding antibody titers against beta, omicron BA.1, and BA.2 variants showed 2.6-, 4.9- and 2.8- fold reduction, respectively, compared to the Wuhan strain. Discussion: Overall, the data suggested that adjuvants in subunit vaccines determine the protection profiles after SARS-CoV-2 infection and that nasal/oral mucosal immunization can protect against systemic COVID-19 disease.

Safety and Effectiveness of SA58 Nasal Spray Against COVID-19 Infection in Medical Personnel: An Open-Label, Blank-Controlled Study - Hohhot City, Inner Mongolia Autonomous Region, China, 2022.

What is already known about this topic?: The active ingredient of the SA58 Nasal Spray is a broad-spectrum neutralizing antibody with a high neutralizing capacity against different Omicron sub-variants in vitro studies. What is added by this report?: This study demonstrated the safety and effectiveness of SA58 Nasal Spray against coronavirus disease 2019 (COVID-19) infection in medical personnel for the first time. What are the implications for public health practice?: This study provides an effective approach for the public to reduce their risk of COVID-19 infection. The findings of this research have the potential to significantly reduce the risk of infection and limit human-to-human transmission in the event of a COVID-19 outbreak.

An intranasally administrated SARS-CoV-2 beta variant subunit booster vaccine prevents beta variant replication in rhesus macaques.

Emergence of SARS-CoV-2 variants and waning of vaccine/infection-induced immunity pose threats to curbing the COVID-19 pandemic. Effective, safe, and convenient booster vaccines are in need. We hypothesized that a variant-modified mucosal booster vaccine might induce local immunity to prevent SARS-CoV-2 infection at the port of entry. The beta-variant is one of the hardest to cross-neutralize. Herein, we assessed the protective efficacy of an intranasal booster composed of beta variant-spike protein S1 with IL-15 and TLR agonists in previously immunized macaques. The macaques were first vaccinated with Wuhan strain S1 with the same adjuvant. A total of 1 year later, negligibly detectable SARS-CoV-2-specific antibody remained. Nevertheless, the booster induced vigorous humoral immunity including serum- and bronchoalveolar lavage (BAL)-IgG, secretory nasal- and BAL-IgA, and neutralizing antibody against the original strain and/or beta variant. Beta-variant S1-specific CD4+ and CD8+ T cell responses were also elicited in PBMC and BAL. Following SARS-CoV-2 beta variant challenge, the vaccinated group demonstrated significant protection against viral replication in the upper and lower respiratory tracts, with almost full protection in the nasal cavity. The fact that one intranasal beta-variant booster administrated 1 year after the first vaccination provoked protective immunity against beta variant infections may inform future SARS-CoV-2 booster design and administration timing.

Research on antibody changes and nucleic acid clearance in COVID-19 patients treated with convalescent plasma

Purpose: To investigate changes in the production of IgM and IgG antibodies and the negative transformation of viral nucleic acids in COVID-19 patients after convalescent plasma therapy, and also to discuss the clinical therapeutic effect, so as to provide a basis for the treatment of COVID-19 using specific antibodies. Methods: The convalescent plasma of recovered patients from COVID-19 was used to treat other patients, and the levels of antibodies IgM and IgG and the nucleic acid genes ORF1ab and N in the patients were tested regularly for statistical comparison and analysis. Results: In general, the Ct value and concentration of IgM and IgG antibodies in the plasma infusion group were significantly higher (1-3 times higher) than those in the non-plasma infusion group, respectively, but these differences were not significant (P>0.05). However, the content of antibodies in severe patients in the plasma transfusion group was significantly higher than those in the non-plasma transfusion group at discharge, the results being statistically significant (P<0.05). Conclusions: The application of convalescent plasma significantly increases the antibody content in severe and critical inpatients, effectively enhances immune function, accelerates the clearance of virus and the nucleic acid negative conversion rate, and significantly promotes early improvement in COVID-19 patients.

Twin peaks of in-hospital mortality among patients with STEMI across five phases of COVID-19 outbreak in China: a nation-wide study.

Lockdown and re-opening may become cyclical due to the recurrent waves of the COVID-19 epidemic. Few studies have examined temporal trends and determinants of in-hospital mortality among patients with ST-segment elevation myocardial infarction (STEMI), a life-threatening condition that requires emergency medical care. Using nation-wide data before, during and after the Wuhan lockdown, we aimed to depict temporal patterns and major determinants of STEMI in-hospital mortality in China across five time periods of the COVID-19 epidemic. We analyzed the data of 283,661 STEMI patients who were admitted to 4,487 chest-pain-centers across China, from January 1, 2019 to May 31, 2020. Compared with the period before the lockdown, STEMI in-hospital mortality increased by 25% (OR 1.25, 95%CI 1.16-1.34) during Early Lockdown, by 12% (OR 1.12, 95%CI 1.03-1.22) during Later Lockdown, by 35% (OR 1.35, 95%CI 1.21-1.50) during Early Lift, and returned to pre-COVID risk (OR 1.04, 95%CI 0.95-1.14) during Later Lift. For each time-period, we observed a clear mortality gradient by timing and types of revascularization procedure. In conclusion, the COVID-19 epidemic had a significant adverse impact on STEMI in-hospital mortality, with bimodal peaks during early lockdown and early lift periods and clear mortality gradients by timing and types of revascularization procedure, independent of the time periods.

2019冠状病毒病(COVID-19)诊疗浙江经验 Management of COVID-19: the Zhejiang experience

当前2019冠状病毒病（COVID-19）疫情仍处于胶着状态。浙江大学医学院附属第一医院是国家感染性疾病临床医学中心，浙江省COVID-19患者救治中心。疫情一线的专家集智攻关，以国家卫生健康委员会和国家中医药管理局发布的COVID-19诊治指南为依据，以抗病毒、抗休克、抗低氧血症、抗继发感染、维持水电解质和酸碱平衡、维持微生态平衡的“四抗二平衡”救治策略为核心，总结完善诊治方案，聚焦临床实践的一些具体问题，为COVID-19患者临床诊治提供借鉴。推荐以多学科协作诊治个性化治疗提高COVID-19患者救治质量。建议病原学检测、炎症指标监测和肺部影像学动态观察指导临床诊治。痰液的病毒核酸检测阳性率最高，约10%的急性期患者血液中检测到病毒核酸，50%的患者粪便中检测到病毒核酸，粪便中可分离出活病毒，须警惕粪便是否具有传染性；开展细胞因子等炎症指标监测有助于发现是否出现细胞因子风暴，判断是否需要人工肝血液净化治疗。通过以“四抗二平衡”为核心的综合治疗提高治愈率、降低病死率；早期抗病毒治疗能减少重症、危重症发生，前期使用阿比多尔联合洛匹那韦/利托那韦抗病毒显示出一定效果。休克和低氧血症多为细胞因子风暴所致，人工肝血液净化治疗能迅速清除炎症介质，阻断细胞因子风暴，对维持水电解质酸碱平衡也有很好的作用，可以提高危重型患者的疗效。重型病例疾病早期可适量、短程应用糖皮质激素。氧疗过程中，患者氧合指数小于200 mmHg时应及时转入重症医学科治疗；采用保守氧疗策略，不推荐常规进行无创通气；机械通气患者应严格执行集束化呼吸机相关性肺炎预防管理策略；氧合指数大于150 mmHg时，及早减、停镇静剂并撤机拔管。不推荐预防性使用抗菌药物，对于病程长，体温反复升高和血降钙素原水平升高的患者可酌情使用抗菌药物；要关注COVID-19患者继发真菌感染的诊治。COVID-19患者有肠道微生态紊乱，肠道乳酸杆菌、双歧杆菌等有益菌减少，推荐对所有患者进行营养和胃肠道功能评估，以营养支持和补充大剂量肠道微生态调节剂，纠正肠道微生态失衡，减少细菌移位和继发感染。COVID-19患者普遍存在焦虑和恐惧心理，应建立动态心理危机干预和处理。提倡中西医结合辨证施治；优化重型患者护理促进康复。严重急性呼吸综合征冠状病毒2（SARS-CoV-2）感染后病毒清除规律仍不明了，出院后仍须居家隔离2周，并定期随访。以上经验和建议在本中心实行，取得较好效果，但COVID-19是一种新的疾病，其诊治方案及策略仍有待进一步探索与完善。

COVID-19 Diagnosis from Chest X-ray Images Using a Robust Multi-Resolution Analysis Siamese Neural Network with Super-Resolution Convolutional Neural Network.

Chest X-ray (CXR) is becoming a useful method in the evaluation of coronavirus disease 19 (COVID-19). Despite the global spread of COVID-19, utilizing a computer-aided diagnosis approach for COVID-19 classification based on CXR images could significantly reduce the clinician burden. There is no doubt that low resolution, noise and irrelevant annotations in chest X-ray images are a major constraint to the performance of AI-based COVID-19 diagnosis. While a few studies have made huge progress, they underestimate these bottlenecks. In this study, we propose a super-resolution-based Siamese wavelet multi-resolution convolutional neural network called COVID-SRWCNN for COVID-19 classification using chest X-ray images. Concretely, we first reconstruct high-resolution (HR) counterparts from low-resolution (LR) CXR images in order to enhance the quality of the dataset for improved performance of our model by proposing a novel enhanced fast super-resolution convolutional neural network (EFSRCNN) to capture texture details in each given chest X-ray image. Exploiting a mutual learning approach, the HR images are passed to the proposed Siamese wavelet multi-resolution convolutional neural network to learn the high-level features for COVID-19 classification. We validate the proposed COVID-SRWCNN model on public-source datasets, achieving accuracy of 98.98%. Our screening technique achieves 98.96% AUC, 99.78% sensitivity, 98.53% precision, and 98.86% specificity. Owing to the fact that COVID-19 chest X-ray datasets are low in quality, experimental results show that our proposed algorithm obtains up-to-date performance that is useful for COVID-19 screening.

WMR-DepthwiseNet: A Wavelet Multi-Resolution Depthwise Separable Convolutional Neural Network for COVID-19 Diagnosis.

Timely discovery of COVID-19 could aid in formulating a suitable treatment plan for disease mitigation and containment decisions. The widely used COVID-19 test necessitates a regular method and has a low sensitivity value. Computed tomography and chest X-ray are also other methods utilized by numerous studies for detecting COVID-19. In this article, we propose a CNN called depthwise separable convolution network with wavelet multiresolution analysis module (WMR-DepthwiseNet) that is robust to automatically learn details from both spatialwise and channelwise for COVID-19 identification with a limited radiograph dataset, which is critical due to the rapid growth of COVID-19. This model utilizes an effective strategy to prevent loss of spatial details, which is a prevalent issue in traditional convolutional neural network, and second, the depthwise separable connectivity framework ensures reusability of feature maps by directly connecting previous layer to all subsequent layers for extracting feature representations from few datasets. We evaluate the proposed model by utilizing a public domain dataset of COVID-19 confirmed case and other pneumonia illness. The proposed method achieves 98.63% accuracy, 98.46% sensitivity, 97.99% specificity, and 98.69% precision on chest X-ray dataset, whereas using the computed tomography dataset, the model achieves 96.83% accuracy, 97.78% sensitivity, 96.22% specificity, and 97.02% precision. According to the results of our experiments, our model achieves up-to-date accuracy with only a few training cases available, which is useful for COVID-19 screening. This latest paradigm is expected to contribute significantly in the battle against COVID-19 and other life-threatening diseases.

COVID-19 Pneumonia Classification Based on NeuroWavelet Capsule Network.

Since it was first reported, coronavirus disease 2019, also known as COVID-19, has spread expeditiously around the globe. COVID-19 must be diagnosed as soon as possible in order to control the disease and provide proper care to patients. The chest X-ray (CXR) has been identified as a useful diagnostic tool, but the disease outbreak has put a lot of pressure on radiologists to read the scans, which could give rise to fatigue-related misdiagnosis. Automatic classification algorithms that are reliable can be extremely beneficial; however, they typically depend upon a large amount of COVID-19 data for training, which are troublesome to obtain in the nick of time. Therefore, we propose a novel method for the classification of COVID-19. Concretely, a novel neurowavelet capsule network is proposed for COVID-19 classification. To be more precise, first, we introduce a multi-resolution analysis of a discrete wavelet transform to filter noisy and inconsistent information from the CXR data in order to improve the feature extraction robustness of the network. Secondly, the discrete wavelet transform of the multi-resolution analysis also performs a sub-sampling operation in order to minimize the loss of spatial details, thereby enhancing the overall classification performance. We examined the proposed model on a public-sourced dataset of pneumonia-related illnesses, including COVID-19 confirmed cases and healthy CXR images. The proposed method achieves an accuracy of 99.6%, sensitivity of 99.2%, specificity of 99.1% and precision of 99.7%. Our approach achieves an up-to-date performance that is useful for COVID-19 screening according to the experimental results. This latest paradigm will contribute significantly in the battle against COVID-19 and other diseases.

Elevated resting heart rates are a risk factor for mortality among patients with coronavirus disease 2019 in Wuhan, China.

BACKGROUND: We evaluated the association between higher resting heart rates (RHRs) and adverse events in COVID-19 patients. METHODS: One hundred and thirty-six patients with laboratory-confirmed COVID-19 were admitted. Outcomes of patients with different RHRs were compared. RESULTS: Twenty-nine patients had RHRs of <80 bpm (beat per min), 85 had 80-99 bpm and 22 had ≥100 bpm as tachycardia. Those with higher RHRs had lower pulse oxygen saturation (SpO2) and higher temperatures, and there was a higher proportion of men upon admission (all P < 0.05). Patients with higher RHRs showed higher white blood cell counts and D-dimer, cardiac troponin I (TnI), N-terminal pro-B-type natriuretic peptide and hypersensitive C-reactive protein levels, but lower albumin levels (all P < 0.05) after admission. During follow-up, 26 patients died (mortality rate, 19.1%). The mortality rate was significantly higher among patients with tachycardia than among the moderate and low RHR groups (all P < 0.001). Kaplan-Meier survival curves showed that the risks of death and ventilation use increased for patients with tachycardia (P < 0.001). Elevated RHR as a continuous variable and a mean RHR as tachycardia were independent risk factors for mortality and ventilator use (all P < 0.05) in the multivariable adjusted Cox proportional hazards regression model. CONCLUSIONS: Elevated average RHRs during the first 3 days of hospitalisation were associated with adverse outcomes in COVID-19 patients. Average RHRs as tachycardia can independently predict all-cause mortality.

Intelligent financial fraud detection practices in post-pandemic era.

The great losses caused by financial fraud have attracted continuous attention from academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus pandemic (COVID-19) unexpectedly shocks the global financial system and accelerates the use of digital financial services, which brings new challenges in effective financial fraud detection. This paper provides a comprehensive overview of intelligent financial fraud detection practices. We analyze the new features of fraud risk caused by the pandemic and review the development of data types used in fraud detection practices from quantitative tabular data to various unstructured data. The evolution of methods in financial fraud detection is summarized, and the emerging Graph Neural Network methods in the post-pandemic era are discussed in particular. Finally, some of the key challenges and potential directions are proposed to provide inspiring information on intelligent financial fraud detection in the future.

Joint Predictive Value of cTnI and NT-proBNP on Mortality in Patients with Coronavirus Disease 2019: A Retrospective Research in Wuhan, China.

BACKGROUND AND OBJECTIVES: The pandemic of coronavirus disease 2019 (COVID-19) remains to be the biggest public threat all over the world. Because of the rapid deterioration in some patients, markers that could predict poor clinical outcomes are urgently required. This study was to evaluate the predictive values of cardiac injury parameters, including cardiac troponin I (cTnI) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels, on mortality in COVID-19 patients. METHODS: COVID-19 patients in Zhongfaxincheng branch of Tongji Hospital (Wuhan, China) from February 8-28, 2020, were enrolled in this study. We followed up the patients for 30 days after admission. RESULTS: A total of 134 patients were included in the study. Multivariate Cox regression showed that 1) patients with elevated cTnI levels had a higher risk of death (hazard ratio [HR] 7.33, 95% confidence interval [CI] 2.56-21.00) than patients with normal cTnI levels; 2) patients with elevated NT-proBNP levels had a higher risk of death (HR 27.88, 95% CI 3.55-218.78) than patients with normal NT-proBNP levels; 3) patients with both elevated cTnI and NT-proBNP levels had a significantly higher risk of death (HR 53.87, 95% CI 6.31-459.91, P < 0.001) compared to patients without elevated cTnI or NT-proBNP levels; 4) the progressions of cTnI and NT-proBNP levels were also correlated with death (HR 12.70, 95% CI 3.94-40.88, P < 0.001 and HR 51.09, 95% CI 5.82-448.26, P < 0.001). CONCLUSIONS: In COVID-19 patients, cTnI and NT-proBNP levels could be monitored to identify patients at a high risk of death in their later course of disease.

SARS-CoV-2 Spike Protein Suppresses ACE2 and Type I Interferon Expression in Primary Cells From Macaque Lung Bronchoalveolar Lavage.

SARS-CoV-2 virus causes upper and lower respiratory diseases including pneumonia, and in some cases, leads to lethal pulmonary failure. Angiotensin converting enzyme-2 (ACE2), the receptor for cellular entry of SARS-CoV-2 virus, has been shown to protect against severe acute lung failure. Here, we provide evidence that SARS-CoV-2 spike protein S1 reduced the mRNA expression of ACE2 and type I interferons in primary cells of lung bronchoalveolar lavage (BAL) from naïve rhesus macaques. The expression levels of ACE2 and type I interferons were also found to be correlated with each other, consistent with the recent finding that ACE2 is an interferon-inducible gene. Furthermore, induction of ACE2 and type I interferons by poly I:C, an interferon inducer, was suppressed by S1 protein in primary cells of BAL. These observations suggest that the downregulation of ACE2 and type I interferons induced by S1 protein may directly contribute to SARS-CoV-2-associated lung diseases.

Protection against SARS-CoV-2 infection by a mucosal vaccine in rhesus macaques.

Effective SARS-CoV-2 vaccines are urgently needed. Although most vaccine strategies have focused on systemic immunization, here we compared the protective efficacy of 2 adjuvanted subunit vaccines with spike protein S1: an intramuscularly primed/boosted vaccine and an intramuscularly primed/intranasally boosted mucosal vaccine in rhesus macaques. The intramuscular-alum-only vaccine induced robust binding and neutralizing antibody and persistent cellular immunity systemically and mucosally, whereas intranasal boosting with nanoparticles, including IL-15 and TLR agonists, elicited weaker T cell and Ab responses but higher dimeric IgA and IFN-α. Nevertheless, following SARS-CoV-2 challenge, neither group showed detectable subgenomic RNA in upper or lower respiratory tracts versus naive controls, indicating full protection against viral replication. Although mucosal and systemic protective mechanisms may differ, results demonstrate both vaccines can protect against respiratory SARS-CoV-2 exposure. In summary, we have demonstrated that the mucosal vaccine was safe after multiple doses and cleared the input virus more efficiently in the nasal cavity and thus may act as a potent complementary reinforcing boost for conventional systemic vaccines to provide overall better protection.

Clinical Characteristics of Patients Infected With the Novel 2019 Coronavirus (SARS-Cov-2) in Guangzhou, China.

BACKGROUND: The clinical manifestations and factors associated with the severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections outside of Wuhan are not clearly understood. METHODS: All laboratory-confirmed cases with SARS-Cov-2 infection who were hospitalized and monitored in Guangzhou Eighth People's Hospital were recruited from January 20 to February 10. RESULTS: A total of 275 patients were included in this study. The median patient age was 49 years, and 63.6% had exposure to Wuhan. The median virus incubation period was 6 days. Fever (70.5%) and dry cough (56.0%) were the most common symptoms. A decreased albumin level was found in 51.3% of patients, lymphopenia in 33.5%, and pneumonia based on chest computed tomography in 86%. Approximately 16% of patients (n = 45) had severe disease, and there were no deaths. Compared with patients with nonsevere disease, those with severe disease were older, had a higher frequency of coexisting conditions and pneumonia, and had a shorter incubation period (all P < .05). There were no differences between patients who likely contacted the virus in Wuhan and those who had no exposure to Wuhan. Multivariate logistic regression analysis indicated that older age, male sex, and decreased albumin level were independently associated with disease severity. CONCLUSIONS: Most of the patients infected with SARS-CoV-2 in Guangzhou, China are not severe cases and patients with older age, male, and decreased albumin level were more likely to develop into severe ones.

Association Between Average Plasma Potassium Levels and 30-day Mortality During Hospitalization in Patients with COVID-19 in Wuhan, China.

Background: Coronavirus disease 2019 (COVID-19) has resulted in more than 610,000 deaths worldwide since December 2019. Given the rapid deterioration of patients' condition before death, markers with efficient prognostic values are urgently required. During the treatment process, notable changes in plasma potassium levels have been observed among severely ill patients. We aimed to evaluate the association between average plasma potassium (Ka +) levels during hospitalization and 30-day mortality in patients with COVID-19. Methods: Consecutive patients with COVID-19 hospitalized in the Zhongfaxincheng branch of Tongji Hospital in Wuhan, China from February 8 to 28, 2020 were enrolled in this study. We followed patients up to 30 days after admission. Results: A total of 136 patients were included in the study. The average age was 62.1±14.6 years and 51.5% of patients were male. The median baseline potassium level was 4.3 (3.9-4.6) mmol/L and Ka + level during hospitalization was 4.4 (4.2-4.7) mmol/L; the median number of times that we measured potassium was 4 (3-5). The 30-day mortality was 19.1%. A J-shaped association was observed between Ka + and 30-day mortality. Multivariate Cox regression showed that compared with the reference group (Ka + 4.0 to <4.5 mmol/L), 30-day mortality was 1.99 (95% confidence interval [CI]=0.54-7.35, P=0.300), 1.14 (95% CI=0.39-3.32, P=0.810), and 4.14 (95% CI=1.29-13.29, P=0.017) times higher in patients with COVID-19 who had Ka + <4.0, 4.5 to <5.0, and ≥5.0 mmol/L, respectively. Conclusion: Patients with COVID-19 who had a Ka + level ≥5.0 mmol/L had a significantly increased 30-day mortality compared with those who had a Ka + level 4.0 to <4.5 mmol/L. Plasma potassium levels should be monitored routinely and maintained within appropriate ranges in patients with COVID-19.