A Bibliometric Visualization Analysis on Vaccine Development of Coronavirus Disease 2019 (COVID-19).

Coronavirus disease 2019 (COVID-19), beginning in December 2019, has spread worldwide, leading to the death of millions. Owing to the absence of definitive treatment, vaccination against COVID-19 emerged as an effective strategy against the spread of the pandemic. Acceptance of the COVID-19 vaccine has advanced considerably, and vaccine-related research has significantly increased over the past three years. This study aimed to evaluate the content and external characteristics of COVID-19 vaccine-related literature for tracking research trends related to the global COVID-19 vaccine with the means of bibliometrics and visualization maps. A total of 18,285 records in 3499 journals were retrieved in the Web of Science Core Collection database and included in the final analysis. China was the first to focus on COVID-19 vaccine research, while European and American countries started late but developed rapidly. The USA and the UK are the top contributors to COVID-19 vaccine development, with the largest number of publications. The University of Washington and Harvard Medical School were the leading institutions, while Krammer, F. from Icahn School of Medicine at Mount Sinai was the author most active and influential to the topic. The New England Journal of Medicine had the highest number of citations and the highest TLS, and was the most cited and influential journal in the field of COVID-19 vaccine research. COVID-19 vaccine research topics and hotspots focused on populations' attitudes towards vaccination, immunity-related information analysis of spike proteins, the effectiveness and side effects of the COVID-19 vaccine, and the public management of epidemic transmission. The findings of this study provide the global status, research hotspots and potential trends in the field of COVID-19 vaccine research, which will assist researchers in mastering the knowledge structure, and evaluating and guiding future developmental directions of COVID-19 vaccine.

Use of low molecular weight heparin and hemoglobin fall in COVID-19 patients: A STROBE-compliant study.

In patients with coronavirus disease 2019 (COVID-19), anticoagulation was suggested as a mitigating strategy. However, little research has been conducted on the adverse consequences of anticoagulant medication. This study aimed to investigate the adverse effect of low molecular weight heparin (LMWH) on hemoglobin fall in COVID-19 treatment. The electronic medical records of COVID-19 patients with pneumonia were collected (including clinical characteristics, vaccination status, complete blood count, coagulation profile, inflammatory cytokines, serum biochemical indicators, and computerized tomography imaging score). Whether they received LMWH, patients were divided into the LMWH group and the control group. Count data were represented as frequency distribution, and a 2-tailed test was used to compare the 2 groups. Spearman rank correlation was used to evaluate the interrelation between changes in hemoglobin and LMWH. The confounding factors were excluded by logistic regression analysis. A total of 179 COVID-19 pneumonia patients were enrolled (81 in the LMWH group and 98 in the control group). The change in hemoglobin was -6.0g/L (IQR -10.8 to 1.0) in the LMWH group and -2.0g/L (IQR -7.0 to 4.0) in the control group (P < .001, between-group difference, -5.0 g/L; 95% confidence interval, -7.0 to -3.0, calculated with the use of the Mann-Whitney U test and the Hodges-Lehmann estimate of confidence intervals for pseudo-medians). The results of multivariate regression analysis showed that after adjusting for confounding factors, LMWH use was not associated with a decrease in hemoglobin (P > .05). In nonsevere COVID-19 patients with pneumonia, the preventive use of LMWH did not lower hemoglobin.

Use of low molecular weight heparin and hemoglobin fall in COVID-19 patients: A STROBE-compliant study

In patients with coronavirus disease 2019 (COVID-19), anticoagulation was suggested as a mitigating strategy. However, little research has been conducted on the adverse consequences of anticoagulant medication. This study aimed to investigate the adverse effect of low molecular weight heparin (LMWH) on hemoglobin fall in COVID-19 treatment. The electronic medical records of COVID-19 patients with pneumonia were collected (including clinical characteristics, vaccination status, complete blood count, coagulation profile, inflammatory cytokines, serum biochemical indicators, and computerized tomography imaging score). Whether they received LMWH, patients were divided into the LMWH group and the control group. Count data were represented as frequency distribution, and a 2-tailed test was used to compare the 2 groups. Spearman rank correlation was used to evaluate the interrelation between changes in hemoglobin and LMWH. The confounding factors were excluded by logistic regression analysis. A total of 179 COVID-19 pneumonia patients were enrolled (81 in the LMWH group and 98 in the control group). The change in hemoglobin was −6.0g/L (IQR −10.8 to 1.0) in the LMWH group and −2.0g/L (IQR −7.0 to 4.0) in the control group (P < .001, between-group difference, −5.0 g/L;95% confidence interval, −7.0 to −3.0, calculated with the use of the Mann–Whitney U test and the Hodges–Lehmann estimate of confidence intervals for pseudo-medians). The results of multivariate regression analysis showed that after adjusting for confounding factors, LMWH use was not associated with a decrease in hemoglobin (P > .05). In nonsevere COVID-19 patients with pneumonia, the preventive use of LMWH did not lower hemoglobin.

Impact of COVID-19 pandemic on patients with Parkinson's disease: A meta-analysis of 13,878 patients.

BACKGROUND: The clinical, neuropsychological, and socioeconomic factors affecting Parkinson's disease (PD) during COVID-19 pandemic across different populations have not been systematically studied. To address this, we conducted a meta-analysis of factors that impact the well-being of PD patients during the pandemic. METHODS: Medline and Embase were searched for articles published between 2020 and 2022. We conducted random-effects pooling of estimates and meta-regression. RESULTS: Twenty-seven studies involving 13,878 patients from America, Europe, Asia, and Africa were included. There is a high prevalence of decreased physical activity and exercise, and worsening motor and neuropsychiatric symptoms (17-56%). Patients in lower-income countries more frequently reported worsening anxiety (adjusted OR [aOR] 8.94, 95% confidence interval [CI] 1.62-49.28, p = 0.012), sleep (aOR 5.16, 95% CI 1.15-23.17, p = 0.032), and PD symptoms (aOR 3.57, 95% CI 0.96-13.34, p = 0.058). Lockdown was associated with decreased exercise levels (aOR 0.13, 95% CI 0.02-0.78, p = 0.025) and worsening mood (aOR 0.48, 95% CI 0.24-0.95, p = 0.035). Younger age correlated with decreased physical activity (ß -0.30, 95% CI -0.53 to -0.07, p = 0.012), exercise (ß -0.11, 95% CI -0.15 to -0.07, p < 0.001), worsening PD symptoms (ß -0.08, 95% CI -0.15 to -0.01, p = 0.018), and sleep (ß -0.14, 95% CI -0.27 to 0, p = 0.044). Female PD patients reported a greater decrease in physical activity (ß 11.94, 95% CI 2.17-21.71, p = 0.017) and worse sleep (ß 10.76, 95% CI 2.81-18.70, p = 0.008). CONCLUSION: This large meta-analysis of PD patients in diverse populations identified a high prevalence of physical and mental worsening during the COVID-19 pandemic, with patients in lower-income countries being exceptionally vulnerable.

Clinical Characteristics of COVID-19 Patients' Postvaccination.

To investigate the clinical characteristic of domestic coronavirus disease 2019 (COVID-19) patients after vaccination campaign conducted in China. According to vaccination status and months from first vaccine dose to infection detection, patients were divided into unvaccinated, <3 months, 3-6 months, and >6 months groups. The information of demographic and clinical characteristics, laboratory and thoracic computed tomography (CT) findings, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid and IgM, IgG antibodies was retrospectively collected. Therapeutic approaches, temperature-normalizing and viral shedding times, outcomes were also summarized. SARS-CoV-2 antibody levels were further analyzed based on the other following variables: time from second vaccine dose to infection, vaccine dose, the interval from the first to the second dose, and vaccine brand. Among 208 COVID-19 patients, 13 (6.28%) were unvaccinated. No significant differences in demographic and clinical characteristics, laboratory and CT findings, and SARS-CoV-2 nucleic acid loads were detected between groups (all p > 0.05). In comparison with the unvaccinated group, the median SARS-CoV-2 IgG levels were noticeably increased in those vaccinated groups (0.603 in unvaccinated, 15.925 in <3 months, 14.04 in 3-6 months, and 4.94 in >6 months, respectively, p < 0.05). However, SARS-CoV-2 IgG levels were not altered between groups divided based on the other variables. Vaccination does not affect the clinical characteristics in COVID-19 patients. COVID-19 patients with vaccination have high SARS-CoV-2 IgG levels. Underscore the necessity of rapid implementation of vaccination campaigns can be speculated.

Six-month follow-up of functional status in discharged patients with coronavirus disease 2019.

BACKGROUND: The long-term functional outcome of discharged patients with coronavirus disease 2019 (COVID-19) remains unresolved. We aimed to describe a 6-month follow-up of functional status of COVID-19 survivors. METHODS: We reviewed the data of COVID-19 patients who had been consecutively admitted to the Tumor Center of Union Hospital (Wuhan, China) between 15 February and 14 March 2020. We quantified a 6-month functional outcome reflecting symptoms and disability in COVID-19 survivors using a post-COVID-19 functional status scale ranging from 0 to 4 (PCFS). We examined the risk factors for the incomplete functional status defined as a PCFS > 0 at a 6-month follow-up after discharge. RESULTS: We included a total of 95 COVID-19 survivors with a median age of 62 (IQR 53-69) who had a complete functional status (PCFS grade 0) at baseline in this retrospective observational study. At 6-month follow-up, 67 (70.5%) patients had a complete functional outcome (grade 0), 9 (9.5%) had a negligible limited function (grade 1), 12 (12.6%) had a mild limited function (grade 2), 7 (7.4%) had moderate limited function (grade 3). Univariable logistic regression analysis showed a significant association between the onset symptoms of muscle or joint pain and an increased risk of incomplete function (unadjusted OR 4.06, 95% CI 1.33-12.37). This association remained after adjustment for age and admission delay (adjusted OR 3.39, 95% CI 1.06-10.81, p = 0.039). CONCLUSIONS: A small proportion of discharged COVID-19 patients may have an incomplete functional outcome at a 6-month follow-up; intervention strategies are required.

Chinese herbal injections for coronavirus disease 2019 (COVID-19): A narrative review.

BACKGROUND: The outbreak of Coronavirus disease 2019 (COVID-19) has caused more than 180 million infections and 3.9 million deaths. To date, emerging clinical evidence has shown the synergetic benefits of Chinese herbal injections in treating this contagious respiratory disease. This review aims to summarize and analyze the efficacy and safety of Chinese herbal injections in the therapy of COVID-19. METHODS: The literature from 3 electronic databases, PubMed, CNKI, and Web of Science, were searched using the search terms "COVID-19", "SARS-CoV-2", "traditional Chinese medicine", "herb", "herbal", and "injection". Then the identified articles were comprehensively evaluated. RESULTS: Limited data demonstrated that Chinese herbal injections could significantly improve the clinical outcomes of COVID-19 patients, especially in combination with conventional treatment strategies. The benefits of which were mainly associated with the relief of symptoms, prevention of secondary infection, regulation of inflammation and immune function. There was also evidence showing the inhibitory effects on SARS-CoV-2 replication in vitro. Nevertheless, available real-world data suggested the increased risk of adverse event. Furthermore, the defects of existing researches and the insights for discovering novel antiviral drugs were prospectively discussed. CONCLUSION: Evidence-based advances revealed that Chinese herbal injections such as XueBiJing injection and ShenMai injection, exerted potent effects against COVID-19. Further laboratory researches and clinical evaluation are needed to gather scientific evidence on the efficacy and safety.

Prognostic value of neutrophil-to-lymphocyte ratio, lactate dehydrogenase, D-dimer, and computed tomography score in patients with coronavirus disease 2019.

BACKGROUND: This study aimed to explore the significance of neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH), D-dimer, and CT score in evaluating the severity and prognosis of coronavirus disease 2019 (COVID-19). METHODS: Patients with laboratory-confirmed COVID-19 were retrospectively enrolled. The baseline data, laboratory findings, chest computed tomography (CT) results evaluated by CT score on admission, and clinical outcomes were collected and compared. Logistic regression was used to assess the independent relationship between the baseline level of the four indicators (NLR, LDH, D-dimer, and CT score) and the severity of COVID-19. RESULTS: Among the 432 patients, 125 (28.94%) and 307 (71.06%) were placed in the severe and non-severe groups, respectively. As per the multivariate logistic regression, high levels of NLR and LDH were independent predictors of severe COVID-19 (OR=2.163; 95% CI=1.162-4.026; p=0.015 for NLR>3.82; OR=2.298; 95% CI=1.327-3.979; p=0.003 for LDH>246 U/L). Combined NLR>3.82 and LDH>246 U/L increased the sensitivity of diagnosis in patients with severe disease (NLR>3.82 [50.40%] vs. combined diagnosis [72.80%]; p=0.0007; LDH>246 [59.2%] vs. combined diagnosis [72.80%]; p<0.0001). CONCLUSIONS: High levels of serum NLR and LDH have potential value in the early identification of patients with severe COVID-19. Moreover, the combination of LDH and NLR can improve the sensitivity of diagnosis.

Uric acid as a prognostic factor and critical marker of COVID-19.

The purpose of this study is to explore whether uric acid (UA) can independently act as a prognostic factor and critical marker of the 2019 novel corona virus disease (COVID-19). A multicenter, retrospective, and observational study including 540 patients with confirmed COVID-19 was carried out at four designated hospitals in Wuhan. Demographic, clinical, laboratory data were collected and analyzed. The primary end point was in-hospital death of patients with COVID-19. The concentration of admission UA (adUA) and the lowest concentration of uric acid during hospitalization (lowUA) in the dead patients were significantly lower than those in the survivors. Multivariate logistic regression analysis showed the concentration of lowUA (OR 0.986, 95% CI 0.980-0.992, p < 0.001) was able to independently predict the risk of in-hospital death. The mean survival time in the low-level group of lowUA was significantly lower than other groups. When lowUA was ≤ 166 µmol/L, the sensitivity and specificity in predicting hospital short-term mortality were 76.9%, (95% CI 68.5-85.1%) and 74.9% (95% CI 70.3-78.9%). This retrospective study determined that the lowest concentration of UA during hospitalization can be used as a prognostic indicator and a marker of disease severity in severe patients with COVID-19.

PAM-DenseNet: A Deep Convolutional Neural Network for Computer-Aided COVID-19 Diagnosis.

Currently, several convolutional neural network (CNN)-based methods have been proposed for computer-aided COVID-19 diagnosis based on lung computed tomography (CT) scans. However, the lesions of pneumonia in CT scans have wide variations in appearances, sizes, and locations in the lung regions, and the manifestations of COVID-19 in CT scans are also similar to other types of viral pneumonia, which hinders the further improvement of CNN-based methods. Delineating infection regions manually is a solution to this issue, while excessive workload of physicians during the epidemic makes it difficult for manual delineation. In this article, we propose a CNN called dense connectivity network with parallel attention module (PAM-DenseNet), which can perform well on coarse labels without manually delineated infection regions. The parallel attention module automatically learns to strengthen informative features from both channelwise and spatialwise simultaneously, which can make the network pay more attention to the infection regions without any manual delineation. The dense connectivity structure performs feature maps reuse by introducing direct connections from previous layers to all subsequent layers, which can extract representative features from fewer CT slices. The proposed network is first trained on 3530 lung CT slices selected from 382 COVID-19 lung CT scans, 372 lung CT scans infected by other pneumonia, and 200 normal lung CT scans to obtain a pretrained model for slicewise prediction. We then apply this pretrained model to a CT scans dataset containing 94 COVID-19 CT scans, 93 other pneumonia CT scans, and 93 normal lung scans, and achieve patientwise prediction through a voting mechanism. The experimental results show that the proposed network achieves promising results with an accuracy of 94.29%, a precision of 93.75%, a sensitivity of 95.74%, and a specificity of 96.77%, which is comparable to the methods that are based on manually delineated infection regions.

Blockchain-Enabled Trustworthy Group Communications in UAV Networks

Unmanned Aerial Vehicles (UAVs) are increasingly deployed in networked environments, such as places of mass gatherings, smart cities and smart nations. For example, UAVs can be deployed to detect violations of lockdown, stay-at-home or social / physical distancing directives during pandemics (e.g. COVID-19). There are, however, security and privacy considerations in such deployments. To achieve secure and efficient authentication of UAVs, solutions such as those based on Point-to-Point (P2P) or a Point- to-Multipoint (P2M) communications have been proposed in the literature. In this article, we present a novel blockchain-based technique to support multi-party authentication to facilitate trustworthy group communications. Specifically, this allows us to provide secure P2P wireless communications and trusted group communication management for UAV networks, while ensuring service efficiency. Evaluation findings from both real-world implementation and simulations demonstrate the utility of the proposed approach.

Does pre-existent physical inactivity have a role in the severity of COVID-19?

BACKGROUND AND AIMS: Physical inactivity is considered an important lifestyle factor for overweight and cardiovascular disease. We aimed to investigate the association between pre-existent physical inactivity and the risk of severe coronavirus disease 2019 (COVID-19). METHODS: We included 164 (61.8 ± 13.6 years) patients with COVID-19 who were admitted between 15 February and 14 March 2020 in this retrospective study. We evaluated the association between pre-existent physical inactivity and severe COVID-19 using a logistic regression model. RESULTS: Of 164 eligible patients with COVID-19, 103 (62.8%) were reported to be physically inactive. Univariable logistic regression analysis showed that physical inactivity was associated with an increased risk of severe COVID-19 [unadjusted odds ratio (OR) 6.53, 95% confidence interval (CI) 1.88-22.62]. In the multivariable regression analysis, physical inactivity remained significantly associated with an increased risk of severe COVID-19 (adjusted OR 4.12, 95% CI 1.12-15.14) after adjustment for age, sex, stroke, and overweight. CONCLUSION: Our data showed that pre-existent physical inactivity was associated with an increased risk of experiencing severe COVID-19. Our findings indicate that people should be encouraged to keep physically active to be at a lower risk of experiencing a severe illness when COVID-19 infection seems unpredicted.The reviews of this paper are available via the supplemental material section.

Association of Early Inflammation with Age and Asymptomatic Disease in COVID-19.

BACKGROUND: Disease severity in COVID-19 ranges from asymptomatic infection to severe disease and death, especially in older subjects. The risk for severe infection and death has been reported to be 2X in those between 30 and 40 years, 3X in those between 40 and 50 years, and 4X in those between 50 and 65 years, compared to the reference group of 18-29 years. OBJECTIVE: To investigate the early changes in host immune responses that are altered with age and the difference in the early host inflammatory response that dictates a symptomatic versus asymptomatic course of COVID-19. PATIENTS AND METHODS: COVID-19 subjects were identified by screening at the airport upon arrival from a foreign destination to China. Patients were either asymptomatic or had a mild disease when the first oro-pharyngeal (OP) swab samples were collected. Patients were quarantined and blood and throat swabs were collected during the course of the disease, allowing identification of the earliest host response to COVID-19. These patients were followed until their OP sample turned COVID-19 negative. RESULTS: Data were obtained from 126 PCR-confirmed COVID-19 patients. The blood samples were obtained within 48 days of qPCR confirmation of viral infection. Older subjects (>30 years) had significantly elevated levels of anti-inflammatory cytokine IL-10, a significant decrease in the percentage of CD8+ T cells, and expansion in NKT cell fraction. This was associated with significantly elevated viral load and a delayed humoral response in older subjects. Compared to symptomatic subjects, asymptomatic patients had an early increase in pro-inflammatory cytokine IL-2, while a decrease in both T regulatory cells and anti-inflammatory cytokine IL-10. Further, asymptomatic disease was associated with early humoral response and faster viral clearance. CONCLUSION: Early inflammatory response potentially plays a critical role for host-defense in COVID-19. The impaired early inflammatory response was associated with older age while a robust early inflammation was associated with asymptomatic disease.

Risk factors for mortality of coronavirus disease-2019 (COVID-19) patients in two centers of Hubei province, China: A retrospective analysis.

PURPOSE: Since the outbreak in late December 2019 in Wuhan, China, coronavirus disease-2019 (COVID-19) has become a global pandemic. We analyzed and compared the clinical, laboratory, and radiological characteristics between survivors and non-survivors and identify risk factors for mortality. METHODS: Clinical and laboratory variables, radiological features, treatment approach, and complications were retrospectively collected in two centers of Hubei province, China. Cox regression analysis was conducted to identify the risk factors for mortality. RESULTS: A total of 432 patients were enrolled, and the median patient age was 54 years. The overall mortality rate was 5.09% (22/432). As compared with the survivor group (n = 410), those in the non-survivor group (n = 22) were older, and they had a higher frequency of comorbidities and were more prone to suffer from dyspnea. Several abnormal laboratory variables indicated that acute cardiac injury, hepatic damage, and acute renal insufficiency were detected in the non-survivor group. Non-surviving patients also had a high computed tomography (CT) score and higher rate of consolidation. The most common complication causing death was acute respiratory distress syndrome (ARDS) (18/22, 81.8%). Multivariate Cox regression analysis revealed that hemoglobin (Hb) <90 g/L (hazard ratio, 10.776; 95% confidence interval, 3.075-37.766; p<0.0001), creatine kinase (CK-MB) >8 U/L (9.155; 2.424-34.584; p = 0.001), lactate dehydrogenase (LDH) >245 U/L (5.963; 2.029-17.529; p = 0.001), procalcitonin (PCT) >0.5 ng/ml (7.080; 1.671-29.992; p = 0.008), and CT score >10 (39.503; 12.430-125.539; p<0.0001) were independent risk factors for the mortality of COVID-19. CONCLUSIONS: Low Hb, high LDH, PCT, and CT score on admission were the predictors for mortality and could assist clinicians in early identification of poor prognosis among COVID-19 patients.

Six-month follow-up of functional status in discharged patients with coronavirus disease 2019 (preprint)

Background The long-term functional outcome of discharged patients with coronavirus disease 2019 (COVID-19) remains unresolved. We aimed to describe a six-month follow-up of functional status of COVID-19 survivors.Methods We reviewed the data of COVID-19 patients who had been consecutively admitted to the Tumor Center of Union Hospital (Wuhan, China) between 15 February and 14 March 2020. We quantified a six-month functional outcome reflecting symptoms and disability in COVID-19 survivors using a post-COVID-19 functional status scale ranging from 0 to 5 (PCFS). We examined the risk factors for the incomplete functional status defined as a PCFS > 0 at a six-month follow-up after discharge.Results We included a total of 95 COVID-19 survivors with a median age of 62 (IQR 53-69) who had a complete functional status (PCFS grade 0) at baseline in this retrospective observational study. At six-month follow-up, 67 (70.5%) patients had a complete functional outcome (grade 0), 9 (9.5%) had a negligible limited function (grade 1), 12 (12.6%) had a mild limited function (grade 2), 7 (7.4%) had moderate limited function (grade 3). Univariable logistic regression analysis showed a significant association between the onset symptoms of muscle or joint pain and an increased risk of incomplete function (unadjusted OR 4.06, 95%CI 1.33 - 12.37). This association remained after adjustment for age and admission delay (adjusted OR 3.39, 95%CI 1.06 - 10.81, p = 0.039).Conclusions A small proportion of discharged COVID-19 patients may have an incomplete functional outcome at a six-month follow-up; intervention strategies are required.

Nutritional risk and therapy for severe and critical COVID-19 patients: A multicenter retrospective observational study.

OBJECTIVE: To evaluate the nutritional risk and therapy in severe and critical patients with COVID-19. METHODS: A total of 523 patients enrolled from four hospitals in Wuhan, China. The inclusion time was from January 2, 2020 to February 15. Clinical characteristics and laboratory values were obtained from electronic medical records, nursing records, and related examinations. RESULTS: Of these patients, 211 (40.3%) were admitted to the ICU and 115 deaths (22.0%). Patients admitted to the ICU had lower BMI and plasma protein levels. The median Nutrition risk in critically ill (NUTRIC) score of 211 patients in the ICU was 5 (4, 6) and Nutritional Risk Screening (NRS) score was 5 (3, 6). The ratio of parenteral nutrition (PN) therapy in non-survivors was greater than that in survivors, and the time to start nutrition therapy was later than that in survivors. The NUTRIC score can independently predict the risk of death in the hospital (OR = 1.197, 95%CI: 1.091-1.445, p = 0.006) and high NRS score patients have a higher risk of poor outcome in the ICU (OR = 1.880, 95%CI: 1.151-3.070, p = 0.012). After adjusted age and sex, for each standard deviation increase in BMI, the risk of in-hospital death was reduced by 13% (HR = 0.871, 95%CI: 0.795-0.955, p = 0.003), and the risk of ICU transfer was reduced by 7% (HR = 0.932, 95%CI:0.885-0.981, p = 0.007). The in-hospital survival time of patients with albumin level ≤35 g/L was significantly decreased (15.9 d, 95% CI: 13.7-16.3, vs 24.2 d, 95% CI: 22.3-29.7, p < 0.001). CONCLUSION: Severe and critical patients with COVID-19 have a high risk of malnutrition. Low BMI and protein levels were significantly associated with adverse events. Early nutritional risk screening and therapy for patients with COVID-19 are necessary.

[Application of laboratory diagnostic technologies for SARS-CoV-2: current progress and prospect].

Since the outbreak of COVID-19 pandemic, the detection capability has been improving and the detection techniques have been evolving with innovations. qRT- PCR and mNGS, which represent the current mainstay diagnostic technologies, play key roles in disease diagnosis and monitoring of virus variation. The detection technologies based on serum and plasma IgM and IgG antibodies are important for auxiliary diagnosis. RT-LAMP is highly specific for a diagnostic purpose. Digital PCR could quantitatively detect nucleic acid and SHERLOCK has a higher sensitivity. These techniques all have great potential for future development and application for pathogen detection. In this review the authors summarize the basic rationales, technical characteristics and the current application of the SARS-CoV-2 detection techniques.

Prevalence and outcomes of re-positive nucleic acid tests in discharged COVID-19 patients.

The prevalence and outcomes of patients who had re-activation of coronavirus disease 2019 (COVID-19) after discharge remain poorly understood. We included 126 consecutively confirmed cases of COVID-19 with 2-month follow-up data after discharge in this retrospective study. The upper respiratory specimen using a reverse-transcription polymerase chain reaction test of three patients (71 years [60-76]) were positive within 11-20 days after their discharge, with an event rate of 19.8 (95%CI 2.60-42.1) per 1,000,000 patient-days. Moreover, all re-positive patients were asymptomatic. Our findings suggest that few recovered patients may still be virus carriers even after reaching the discharge criteria.

Real-time naive case fatality rates can reflect timeliness of case confirmation during pandemics.

An objective law was observed that naive case fatality rates (CFRs) of a disease will decrease early and then gradually increase infinitely near the true CFR as time went on during an outbreak. The normal growth of naive CFR was an inherent character rather than indicating the disease was becoming more severe. According to the law, by monitoring real-time naive CFRs, it can help outbreak-controllers know if there were many cases left unconfirmed or undiscovered in the outbreak. We reflected on the use of the naive CFR in the context of COVID-19 outbreaks. The results showed that Hubei Province of China, France and South Korea had cases that were not confirmed in a timely manner during the initial stages of the outbreak. Delayed case confirmations existed for long periods of time in France, Italy, the United Kingdom, the Netherlands and Spain. Monitoring of real-time naive CFRs could be helpful for decision-makers to identify under-reporting of cases during pandemics.