Comparison of epidemiological and clinical characteristics of COVID-19 patients with and without Wuhan exposure history in Zhejiang Province, China

Evaluations of modes of pooling specimens for COVID-19 screened by quantitative PCR and droplet digital PCR

Though pooling samples for SARS-CoV-2 detection has effectively met the need for rapid diagnostic and screening tests, many factors can influence the sensitivity of a pooled test. In this study, we conducted a simulation experiment to evaluate modes of pooling specimens and aimed at formulating an optimal pooling strategy. We focussed on the type of swab, their solvent adsorption ability, pool size, pooling volume, and different factors affecting the quality of preserving RNA by different virus solutions. Both quantitative PCR and digital PCR were used to evaluate the sampling performance. In addition, we determined the detection limit by sampling which is simulated from the virus of different titers and evaluated the effect of sample-storage conditions by determining the viral load after storage. We found that flocked swabs were better than fibre swabs. The RNA-preserving ability of the non-inactivating virus solution was slightly better than that of the inactivating virus solution. The optimal pooling strategy was a pool size of 10 samples in a total volume of 9 mL. Storing the collected samples at 4 °C or 25 °C for up to 48 h had little effect on the detection sensitivity. Further, we observed that our optimal pooling strategy performed equally well as the single-tube test did. In clinical applications, we recommend adopting this pooling strategy for low-risk populations to improve screening efficiency and shape future strategies for detecting and managing other respiratory pathogens, thus contributing to preparedness for future public health challenges.

Neurological complications and effects of COVID-19: Symptoms and conceivable mechanisms

A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in December 2019 in Wuhan, China. The new coronavirus disease (COVID-19) was declared a global pandemic by the World Health Organization (WHO) in March 2020. SARS-CoV-2 can invade the nervous system aside from infecting the respiratory system as its primary target. The most common nervous system symptoms of COVID-19 are stated as headache, myalgia, fatigue, nausea, vomiting, sudden and unexplained anosmia, and ageusia. More severe conditions such as encephalomyelitis, acute myelitis, thromboembolic events, ischemic stroke, intracerebral hemorrhage, Guillain-Barré-syndrome, Bell's palsy, rhabdomyolysis, and even coma have also been reported. Cohort studies revealed that neurological findings are associated with higher morbidity and mortality. The neurological symptoms and manifestations caused by SARS-CoV-2 and COVID-19 are examined and summarized in this article.

Asthma and risk of infection, hospitalization, ICU admission and mortality from COVID-19: Systematic review and meta-analysis

OBJECTIVE

As COVID-19 spreads across the world, there are concerns that people with asthma are at a higher risk of acquiring the disease, or of poorer outcomes. This systematic review aimed to summarize evidence on the risk of infection, severe illness and death from COVID-19 in people with asthma.

DATA SOURCES AND STUDY SELECTION

A comprehensive search of electronic databases including preprint repositories and WHO COVID-19 database was conducted (until 26 May 2020). Studies reporting COVID-19 in people with asthma were included. For binary outcomes, we performed Sidik-Jonkman random effects meta-analysis. We explored quantitative heterogeneity by subgroup analyses, meta regression and evaluating the I2 statistic.

RESULTS

Fifty-seven studies with an overall sample size of 587 280 were included. The prevalence of asthma among those infected with COVID-19 was 7.46% (95% CI = 6.25-8.67). Non-severe asthma was more common than severe asthma (9.61% vs. 4.13%). Pooled analysis showed a 14% risk ratio reduction in acquiring COVID-19 (95% CI = 0.80-0.94; p < 0.0001) and 13% reduction in hospitalization with COVID-19 (95% CI = 0.77-0.99, p = 0.03) for people with asthma compared with those without. There was no significant difference in the combined risk of requiring admission to ICU and/or receiving mechanical ventilation for people with asthma (RR = 0.87 95% CI = 0.94-1.37; p = 0.19) and risk of death from COVID-19 (RR = 0.87; 95% CI = 0.68-1.10; p = 0.25).

CONCLUSION

The findings from this study suggest that the prevalence of people with asthma among COVID-19 patients is similar to the global prevalence of asthma. The overall findings suggest that people with asthma have a lower risk than those without asthma for acquiring COVID-19 and have similar clinical outcomes.

Clinical and biochemical profile of COVID-19 patients admitted in a tertiary care hospital in Visakhapatnam, India during post unlock 2.0 - a retrospective study

There have been more than 31378143 confirmed coronavirus disease 2019 (COVID-19) cases in India. It was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. Because the risk of severe COVID-19 is not consistent across all individuals, uncertainty is linked to disease development. COVID-19 results have been related to systemic inflammation as a predictor. In COVID-19, increased levels of inflammatory markers have been associated with cytokine storm, coagulopathy, and endothelial dysfunction. A significant amount of research suggests that these results have a role in the cause of death in individuals suffering from a severe form of COVID-19. We aim to show our experience of COVID-19 at GITAM Institute of Medical Sciences and Research (GIMSR), Visakhapatnam. We analyzed data on 558 patients admitted to our dedicated COVID hospital during post unlock (UL) 2.0 in India from August 2 to August 31, 2020. The mean age was 43.65 years; 69% of them were male. Using MoHFW India severity guidelines, 68.10% were mild, 18.64% were moderate, and 13.26% were severe cases. Fatigue (66.13%) was the most common complaint, followed by anosmia (63.80%), fever (57.53%), diarrhea (56.09%), shortness of breath (22.40%), and others. The most common preexisting comorbidity seen in our patients was diabetes mellitus and hypertension, respectively. Laboratory parameters revealed mean hemoglobin of 13.04±1.91 gm/dl, mean total leukocyte count of 7378.49±3229 cells/cumm, mean platelet count of 2.3±0.8 lakhs/cumm, mean erythrocyte sediment rate of 40±30 mm/hr, mean ferritin level of 335.96 ng/ml, mean D-dimer level of 794.88 ng/ml and mean CRP of 23.27 mg/l. Severity was associated with higher age, symptomatic presentation, elevated leucocytes, and elevated inflammatory markers.

The characteristics of and responses to the two COVID-19 outbreak waves in Hebei Province of China, January 2020 to February 2021

Hebei Province was affected by two coronavirus disease 2019 (COVID-19) outbreak waves during the period 22 January 2020 through 27 February 2020 (wave 1) and 2 January 2021 through 14 February 2021 (wave 2). To evaluate and compare the epidemiological characteristics, containment delay, cluster events and social activity, as well as non-pharmaceutical interventions of the two COVID-19 outbreak waves, we examined real-time update information on all COVID-19-confirmed cases from a publicly available database. Wave 1 was closely linked with the COVID-19 pandemic in Wuhan, whereas wave 2 was triggered, to a certain extent, by the increasing social activities such as weddings, multi-household gatherings and church events during the slack agricultural period. In wave 2, the epidemic spread undetected in the rural areas, and people living in the rural areas had a higher incidence rate than those living in the urban areas (5.3 vs. 22.0 per 1 000 000). Furthermore, Rt was greater than 1 in the early stage of the two outbreak waves, and decreased substantially after massive non-pharmaceutical interventions were implemented. In China's 'new-normal' situation, development of targeted and effective intervention remains key for COVID-19 control in consideration of the potential threat of new coronavirus strains.

Neurological Manifestations in COVID-19 Patients: A Meta-Analysis

Common symptoms such as dizziness, headache, olfactory dysfunction, nausea, vomiting, etc. in COVID-19 patients have indicated the involvement of the nervous system. However, the exact association of the nervous system with COVID-19 infection is still unclear. Thus, we have conducted a meta-analysis of clinical studies associated with neurological problems in COVID-19 patients. We have searched for electronic databases with MeSH terms, and the studies for analysis were selected based on inclusion and exclusion criteria and quality assessment. The Stats Direct (version 3) was used for the analysis. The pooled prevalence with 95% confidence interval of various neurological manifestations reported in the COVID-19 patients was found to be headache 14.6% (12.2-17.2), fatigue 33.6% (29.5-37.8), olfactory dysfunction 26.4% (21.8-31.3), gustatory dysfunction 27.2% (22.3-32.3), vomiting 6.7% (5.5-8.0), nausea 9.8% (8.1-11.7), dizziness 6.7% (4.7-9.1), myalgia 21.4% (18.8-24.1), seizure 4.05% (2.5-5.8), cerebrovascular diseases 9.9% (6.8-13.4), sleep disorders 14.9% (1.9-36.8), altered mental status 17.1% (12.3-22.5), neuralgia 2.4% (0.8-4.7), arthralgia 19.9% (15.3-25.0), encephalopathy 23.5% (14.3-34.1), encephalitis 0.6% (0.2-1.3), malaise 38.3% (24.7-52.9), confusion 14.2% (6.9-23.5), movement disorders 5.2% (1.7-10.4), and Guillain-Barre syndrome 6.9% (2.3-13.7). However, the heterogeneity among studies was found to be high. Various neurological manifestations related to the central nervous system (CNS) and peripheral nervous system (PNS) are associated with COVID-19 patients.

Sociodemographic determinants and clinical risk factors associated with COVID-19 severity: a cross-sectional analysis of over 200,000 patients in Tehran, Iran

Background

Defining socio-demographic factors, clinical presentations and underlying diseases associated with COVID-19 severity could be helpful in its management. This study aimed to further clarify the determinants and clinical risk factors of the disease severity in patients infected with COVID-19.

Methods

A multi-centre descriptive study on all patients who have been diagnosed with COVID-19 in the province of Tehran from March 2020 up to Dec 2020 was conducted. Data on socio-demographic characteristics, clinical presentations, comorbidities, and the health outcomes of 205,654 patients were examined. Characteristics of the study population were described. To assess the association of study variables with the disease severity, the Chi-Squared test and Multiple Logistic Regression model were applied.

Results

The mean age of the study population was 52.8 years and 93,612 (45.5%) were women. About half of the patients have presented with low levels of blood oxygen saturation. The ICU admission rate was 17.8% and the overall mortality rate was 10.0%. Older age, male sex, comorbidities including hypertension, cancer, chronic respiratory diseases other than asthma, chronic liver diseases, chronic kidney diseases, chronic neurological disorders, and HIV/AIDS infection were risk markers of poor health outcome. Clinical presentations related with worse prognosis included fever, difficulty breathing, impaired consciousness, and cutaneous manifestations.

Conclusion

These results might alert physicians to pay attention to determinants and risk factors associated with poor prognosis in patients with COVID-19. In addition, our findings aid decision makers to emphasise on vulnerable groups in the public health strategies that aim at preventing the spread of the disease and its mortalities.

Development and validation of an individualized nomogram for early prediction of the duration of SARS-CoV-2 shedding in COVID-19 patients with non-severe disease

With the number of cases of coronavirus disease-2019 (COVID-19) increasing rapidly, the World Health Organization (WHO) has recommended that patients with mild or moderate symptoms could be released from quarantine without nucleic acid retesting, and self-isolate in the community. This may pose a potential virus transmission risk. We aimed to develop a nomogram to predict the duration of viral shedding for individual COVID-19 patients. This retrospective multicentric study enrolled 135 patients as a training cohort and 102 patients as a validation cohort. Significant factors associated with the duration of viral shedding were identified by multivariate Cox modeling in the training cohort and combined to develop a nomogram to predict the probability of viral shedding at 9, 13, 17, and 21 d after admission. The nomogram was validated in the validation cohort and evaluated by concordance index (C-index), area under the curve (AUC), and calibration curve. A higher absolute lymphocyte count (P=0.001) and lymphocyte-to-monocyte ratio (P=0.013) were correlated with a shorter duration of viral shedding, while a longer activated partial thromboplastin time (P=0.007) prolonged the viral shedding duration. The C-indices of the nomogram were 0.732 (95% confidence interval (CI): 0.685‒0.777) in the training cohort and 0.703 (95% CI: 0.642‒0.764) in the validation cohort. The AUC showed a good discriminative ability (training cohort: 0.879, 0.762, 0.738, and 0.715 for 9, 13, 17, and 21 d; validation cohort: 0.855, 0.758, 0.728, and 0.706 for 9, 13, 17, and 21 d), and calibration curves were consistent between outcomes and predictions in both cohorts. A predictive nomogram for viral shedding duration based on three easily accessible factors was developed to help estimate appropriate self-isolation time for patients with mild or moderate symptoms, and to control virus transmission.

Kidney Complications of COVID-19: A Systematic Review and Meta-Analysis

Background: Some patients with coronavirus disease 2019 (COVID-19) have been reported to have developed mild to severe kidney injuries. The current systematic review and meta-analysis was carried out to estimate the prevalence and incidence of acute kidney injury (AKI) among COVID-19 patients.

Study design: A systematic review and meta-analysis

Methods: PubMed, Embase, Scopus, Web of Science, and MedRxiv databases were searched from December 1, 2019, up to July 27, 2020. Two independent co-authors completed the screening process, data extraction, and quality assessment of the retrieved records. Random-effects meta-analyses were used to determine the pooled prevalence and 95% confidence interval (CI) of AKI among COVID-19 patients.

Results: Out of 2,332 unique identified records, 51 studies were included in the review. Overall, the studies were carried out on 25,600 patients. A total of 6,505 patients (in 18 cross-sectional studies) were included to estimate the pooled prevalence of AKI, and 18,934 patients (in 27 cohort studies) were included to determine the pooled incidence of AKI. The pooled prevalence of AKI was estimated as 10.08% (95% CI: 4.59, 17.32; I ²=98.56%; P<0.001). Furthermore, the pooled incidence of AKI was 12.78% (95% CI: 7.38, 19.36; I ²=99.27%; P<0.001). The mean (95% CI) values of serum creatinine (SCr), blood urea nitrogen (BUN), potassium, and sodium were 76.10 (69.36, 82.84), 4.60 (4.04, 5.30), 3.94 (3.78, 4.11), and 139.30 (138.26, 140.36) mmol/L, respectively.

Conclusions: The AKI is a considerable complication among COVID-19 patients and should be screened for on clinical examinations. The BUN, SCr, potassium, and sodium levels were within the normal ranges.

Neurological manifestations of COVID-19: a systematic review and meta-analysis of proportions

BACKGROUND

Coronaviruses mainly affect the respiratory system; however, there are reports of SARS-CoV and MERS-CoV causing neurological manifestations. We aimed at discussing the various neurological manifestations of SARS-CoV-2 infection and to estimate the prevalence of each of them.

METHODS

We searched the following electronic databases; PubMed, MEDLINE, Scopus, EMBASE, Google Scholar, EBSCO, Web of Science, Cochrane Library, WHO database, and ClinicalTrials.gov . Relevant MeSH terms for COVID-19 and neurological manifestations were used. Randomized controlled trials, non-randomized controlled trials, case-control studies, cohort studies, cross-sectional studies, case series, and case reports were included in the study. To estimate the overall proportion of each neurological manifestations, the study employed meta-analysis of proportions using a random-effects model.

RESULTS

Pooled prevalence of each neurological manifestations are, smell disturbances (35.8%; 95% CI 21.4-50.2), taste disturbances (38.5%; 95%CI 24.0-53.0), myalgia (19.3%; 95% CI 15.1-23.6), headache (14.7%; 95% CI 10.4-18.9), dizziness (6.1%; 95% CI 3.1-9.2), and syncope (1.8%; 95% CI 0.9-4.6). Pooled prevalence of acute cerebrovascular disease was (2.3%; 95%CI 1.0-3.6), of which majority were ischaemic stroke (2.1%; 95% CI 0.9-3.3), followed by haemorrhagic stroke (0.4%; 95% CI 0.2-0.6), and cerebral venous thrombosis (0.3%; 95% CI 0.1-0.6).

CONCLUSIONS

Neurological symptoms are common in SARS-CoV-2 infection, and from the large number of cases reported from all over the world daily, the prevalence of neurological features might increase again. Identifying some neurological manifestations like smell and taste disturbances can be used to screen patients with COVID-19 so that early identification and isolation is possible.

Global prevalence and pathogenesis of headache in COVID-19: A systematic review and meta-analysis

Background: This study was conducted to determine the prevalence of headache in coronavirus disease 2019 (COVID-19) and to assess its association as a predictor for COVID-19. This study also aimed to discuss the possible pathogenesis of headache in COVID-19. Methods: Available articles from PubMed, Scopus, and Web of Science were searched as of September 2 nd, 2020. Data on characteristics of the study, headache and COVID-19 were extracted following the PRISMA guidelines. Biases were assessed using the Newcastle-Ottawa scale. The cumulative prevalence of headache was calculated for the general population (i.e. adults and children). The pooled odd ratio (OR) with 95% confidence intervals (95%CI) was calculated using the Z test to assess the association between headache and the presence of COVID-19 cases. Results: We included 104,751 COVID-19 cases from 78 eligible studies to calculate the global prevalence of headache in COVID-19 and 17 studies were included to calculate the association of headache and COVID-19. The cumulative prevalence of headache in COVID-19 was 25.2% (26,464 out of 104,751 cases). Headache was found to be more prevalent, approximately by two-fold, in COVID-19 patients than in non-COVID-19 patients with symptoms of other respiratory viral infections, OR: 1.73; 95% CI: 1.94, 2.5 with p=0.04. Conclusion: Headache is common among COVID-19 patients and seems to be more common in COVID-19 patients compared to those with the non-COVID-19 viral infection. No definitive mechanisms on how headache  emerges in COVID-19 patients but several possible hypotheses have been proposed. However, extensive studies are warranted to elucidate the mechanisms. PROSPERO registration: CRD42020210332 (28/09/2020).

Global prevalence and pathogenesis of headache in COVID-19: A systematic review and meta-analysis

Background: This study was conducted to determine the prevalence of headache in coronavirus disease 2019 (COVID-19) and to assess its association as a predictor for COVID-19. This study also aimed to discuss the possible pathogenesis of headache in COVID-19. Methods: Available articles from PubMed, Scopus, and Web of Science were searched as of September 2 nd, 2020. Data on characteristics of the study, headache and COVID-19 were extracted following the PRISMA guidelines. Biases were assessed using the Newcastle-Ottawa scale. The cumulative prevalence of headache was calculated for the general population (i.e. adults and children). The pooled odd ratio (OR) with 95% confidence intervals (95%CI) was calculated using the Z test to assess the association between headache and the presence of COVID-19 cases. Results: We included 104,751 COVID-19 cases from 78 eligible studies to calculate the global prevalence of headache in COVID-19 and 17 studies were included to calculate the association of headache and COVID-19. The cumulative prevalence of headache in COVID-19 was 25.2% (26,464 out of 104,751 cases). Headache was found to be more prevalent, approximately by two-fold, in COVID-19 patients than in non-COVID-19 patients (other respiratory viral infections), OR: 1.73; 95% CI: 1.94, 2.5 with p=0.04. Conclusion: Headache is common among COVID-19 patients and seems to be more common in COVID-19 patients compared to those with the non-COVID-19 viral infection. No definitive mechanisms on how headache  emerges in COVID-19 patients but several possible hypotheses have been proposed. However, extensive studies are warranted to elucidate the mechanisms. PROSPERO registration: CRD42020210332 (28/09/2020).

Dynamic changes in clinical and CT characteristics of COVID-19 cases with different exposure histories: a retrospective study

BACKGROUND

To assess the dynamic changes in clinical and CT characteristics of COVID-19 patients with different epidemiology histories.

METHODS

Fifty-three discharged COVID-19 patients were enrolled at Beijing YouAn Hospital, Capital Medical University, between January 21 and March 10, 2020. Spearman correlation analysis was performed between CT scores and laboratory indicators. Patients were divided into the Wuhan group (lived in or with travel to Wuhan, numbering 30 cases) and non-Wuhan group (close contacts or unknown exposure, totaling 23 cases). The CT and laboratory findings were compared between and within groups during the clinical process.

RESULTS

Fever (88.7%), cough (64.2%), fatigue (34%), and abnormal laboratory indicators, including lymphopenia, reduced albumin, albumin/globulin (A/G), and elevated C-reactive protein (CRP), were mainly observed. Subpleural ground-glass opacities (86.8%) were usually detected at admission. The CT scores were highly correlated with lymphocytes, CRP, albumin, and A/G at initial and follow-ups (all p < 0.05). Four days after admission, most patients (66.7% Wuhan, 47.8% non-Wuhan) showed progression, and the CT scores of Wuhan significantly increased (p = 0.015). Eight days after admission, the vast majority of patients (69.2% Wuhan, 100% non-Wuhan, p = 0.006) presented improvement, and the CT scores of non-Wuhan were significantly lower than Wuhan (p = 0.006). Pneumonia was completely absorbed in most patients 2-4 weeks after discharge.

CONCLUSIONS

CT plays a crucial role in the early diagnosis and monitoring of changes in COVID-19. Lymphocytes, CRP, albumin, and A/G are expected to predict disease severity and prognosis. Viral pathogenicity in non-endemic areas may be weaker than core-infected areas. In most patients, lung lesions can disappear around 4 weeks after discharge.

Acute kidney injury and kidney replacement therapy in COVID-19: a systematic review and meta-analysis

BACKGROUND

Acute kidney injury (AKI) can affect hospitalized patients with coronavirus disease 2019 (COVID-19), with estimates ranging between 0.5% and 40%. We performed a systematic review and meta-analysis of studies reporting incidence, mortality and risk factors for AKI in hospitalized COVID-19 patients.

METHODS

We systematically searched 11 electronic databases until 29 May 2020 for studies in English reporting original data on AKI and kidney replacement therapy (KRT) in hospitalized COVID-19 patients. Incidences of AKI and KRT and risk ratios for mortality associated with AKI were pooled using generalized linear mixed and random-effects models. Potential risk factors for AKI were assessed using meta-regression. Incidences were stratified by geographic location and disease severity.

RESULTS

A total of 3042 articles were identified, of which 142 studies were included, with 49 048 hospitalized COVID-19 patients including 5152 AKI events. The risk of bias of included studies was generally low. The pooled incidence of AKI was 28.6% [95% confidence interval (CI) 19.8-39.5] among hospitalized COVID-19 patients from the USA and Europe (20 studies) and 5.5% (95% CI 4.1-7.4) among patients from China (62 studies), whereas the pooled incidence of KRT was 7.7% (95% CI 5.1-11.4; 18 studies) and 2.2% (95% CI 1.5-3.3; 52 studies), respectively. Among patients admitted to the intensive care unit, the incidence of KRT was 20.6% (95% CI 15.7-26.7; 38 studies). Meta-regression analyses showed that age, male sex, cardiovascular disease, diabetes mellitus, hypertension and chronic kidney disease were associated with the occurrence of AKI; in itself, AKI was associated with an increased risk of mortality, with a pooled risk ratio of 4.6 (95% CI 3.3-6.5).

CONCLUSIONS

AKI and KRT are common events in hospitalized COVID-19 patients, with estimates varying across geographic locations. Additional studies are needed to better understand the underlying mechanisms and optimal treatment of AKI in these patients.