Fever Patterns, Cytokine Profiles, and Outcomes in COVID-19

COVID-19 patients hospitalized after the fourth wave of the pandemic period in Vietnam: Clinical, laboratory, therapeutic features, and clinical outcomes

BACKGROUND/PURPOSE

Despite having relatively high COVID-19 vaccine coverage in Vietnam, a fraction of COVID-19 patients required hospitalization due to severe symptoms. The purpose of this study was to describe the clinical, laboratory, complications, and treatment of COVID-19 patients hospitalized during the pandemic's fourth wave.

METHODS

Genome sequencing was performed on COVID-19 patients. Data on clinical characteristics, treatment, complications, and outcomes were consistently collected.

RESULTS

The clinical classifications were mild (37.43%), moderate (24.2%), and severe (38.37%). Patients with co-morbidities, high fever >39 °C, hypertension, tachycardia, tachypnea, and SpO2<90%, had a 1.2-4 folds higher of severe progression than those with mild/moderate. Serious consequences were much more common in the severe patients than in the mild/moderate. The respiratory system of severe patients was generally documented as fine, coarse crackles, and CT scanner shown ground glass, consolidation, and opacity, with Delta variant accounting for 92.6%. Complications were common in the severe patients, including bacteria pneumonia (36.42%), ARDS (61.11%), blood clotting disorder (7.14%), infection (46.92%), and acute kidney injury (12.35%). Antiviral, antifungal, corticosteroid, anticoagulant, and ECMO regimens were utilized. Patients died mostly as a result of co-morbidities, low SpO2, lung injury, and complications such as bacterial + fungal pneumonia (83.9%), ARDS (83.9%), bacteremia (56.5%), injury acute renal failure (27.4%), and coagulopathy (12.9%).

CONCLUSION

Severe and critical COVID-19 patients frequently have several comorbidities, multiple lung lesions along with a variety of clinical signs. Despite receiving antivirals, antibiotics, corticosteroids, anticoagulants, and even ECMO therapy, the patient encountered multiple complications, with a fatality rate of up to 38.27%.

Transmission dynamics, responses, and clinical features for the first 1100 COVID-19 cases in South Batinah, Oman: Major lessons from a provincial perspective

Objectives

This study was aimed at exploring and analyzing the epidemiological profile, surveillance, and response to COVID-19, including transmission dynamics and cluster formation.

Methodology

This was a retrospective analysis of surveillance data, including contact tracing, risk factors, and clinical information. Binary logistic regressions were used to assess the likelihood of admission, cluster formation, and of each individual being an index patient. Clusters were demonstrated through geographic data systems, network analysis, and visualization software.

Results

A total of 1100 COVID-19 cases were diagnosed from 20 March to 7 June 2020, of which 144 (13.1%) were asymptomatic. The median time from symptom onset to admission was 7 days (IQR, 4.5-10), and the median symptom duration was 5 days (IQR, 3-9). Eighty-nine clusters containing 736 patients were identified. The surveillance and control actions were divided into three phases. Clusters began to form in phase 2 and became more pronounced in phase 3. Patients ≥50 years of age and patients presenting with fever had relatively higher odds of admission: OR = 12.85 (95% CI 5.13-32.19) and 2.53 (95% CI 1.24-5.17), respectively. Cluster formation was observed among females, asymptomatic patients, and people living in Awabi: OR = 2.3 (95% CI 1.7-3.1), 6.39 (95% CI 2.33-17.2), and 3.54 (95% CI 2.06-6.07), respectively. Patients working in the police and defense sectors had higher odds of being an index patient: OR = 7.88 (95% CI 3.35-18.52).

Conclusion

Case-based interventions should be supported by population-wide measures, particularly movement restrictions. Establishing prevention teams or district units, or primary care will be crucial for the control of future pandemics. Prevention should always be prioritized for vulnerable populations.

Out-of-hospital cardiac arrest and in-hospital mortality among COVID-19 patients: A population-based retrospective cohort study

BACKGROUND/PURPOSE

Predictors for out-of-hospital cardiac arrest (OHCA) in COVID-19 patients remain unclear. We identified the predictors for OHCA and in-hospital mortality among such patients in community isolation centers.

METHODS

From May 15 to June 20, 2021, this cohort study recruited 2555 laboratory-confirmed COVID-19 patients admitted to isolation centers in Taiwan. All patients were followed up until death, discharge from the isolation center or hospital, or July 16, 2021. OHCA was defined as cardiac arrest confirmed by the absence of circulation signs and occurring outside the hospital. Multinomial logistic regressions were used to determine factors associated with OHCA and in-hospital mortality.

RESULTS

Of the 37 deceased patients, 7 (18.9%) had OHCA and 30 (81.1%) showed in-hospital mortality. The mean (SD) time to OHCA was 6.6 (3.3) days from the symptom onset. After adjusting for demographics and comorbidities, independent predictors for OHCA included age ≥65 years (adjusted odds ratio [AOR]: 13.24, 95% confidence interval [CI]: 1.85-94.82), fever on admission to the isolation center (AOR: 12.53, 95% CI: 1.68-93.34), and hypoxemia (an oxygen saturation level below 95% on room air) (AOR: 26.54, 95% CI: 3.18-221.73). Predictors for in-hospital mortality included age ≥65 years (AOR: 10.28, 95% CI: 2.95-35.90), fever on admission to the isolation centers (AOR: 7.27, 95% CI: 1.90-27.83), and hypoxemia (AOR: 29.87, 95% CI: 10.17-87.76).

CONCLUSIONS

Time to OHCA occurrence is rapid in COVID-19 patients. Close monitoring of patients' vital signs and disease severity during isolation is important, particularly for those with older age, fever, and hypoxemia.

SARS-CoV-2 in brief: from virus to prevention

The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ahighly transmissible virus with a likely animal origin, has posed major and unprecedentedchallenges to millions of lives across the affected nations of the world. This outbreak firstoccurred in China, and despite massive regional and global attempts shortly thereafter, itspread to other countries and caused millions of deaths worldwide. This review presents keyinformation about the characteristics of SARS-CoV-2 and its associated disease (namely,coronavirus disease 2019) and briefly discusses the origin of the virus. Herein, we also brieflysummarize the strategies used against viral spread and transmission.

Clinical characteristics and analysis of risk factors for disease progression of patients with SARS-CoV-2 Omicron variant infection: A retrospective study of 25207 cases in a Fangcang hospital

OBJECTIVES

To summarize the clinical characteristics of patients infected by SARS-CoV-2 omicron variant and explore the risk factors affecting the progression in a Fangcang hospital, Shanghai, China.

METHODS

A total of 25,207 patients were retrospectively enrolled. We described the clinical characteristics and performed univariate and multivariate logistic regression analysis to identify the risk factors for non-severe to severe COVID-19 or death.

RESULTS

According to the outcomes, there were 39 severe patients (including 1 death) and 25,168 non-severe patients enrolled in this study. Among the 25,207 cases, the median age was 45 years (IQR 33-54), and 65% patients were male. Cough (44.5%) and expectoration (38.4%) were the most two common symptoms. Hypertension (10.4%) and diabetes (3.5%) were most two common comorbidities. Most patients (81.1%) were fully vaccinated. The unvaccinated and partially vaccinated patients were 15.1% and 3.9%, respectively. The length of viral shedding time was six days (IQR 4-9) in non-severe patients. Multivariate logistic regression analysis suggested that age (OR=1.062, 95%CI 1.034-1.090, p&lt;0.001), fever (OR=2.603, 95%CI 1.061-6.384, p=0.037), cough (OR=0.276, 95%CI 0.119-0.637, p=0.003), fatigue (OR=4.677, 95%CI 1.976-11.068, p&lt;0.001), taste disorders (OR=14.917, 95%CI 1.884-118.095, p=0.010), and comorbidity (OR=2.134, 95%CI 1.059-4.302, p=0.034) were predictive factors for deterioration of SARS-CoV-2 omicron variant infection.

CONCLUSIONS

Non-critical patients have different clinical characteristics from critical patients. Age, fever, cough, fatigue, taste disorders, and comorbidity are predictors for the deterioration of SARS-CoV-2 omicron variant infection.

Prevalence and Predictors of Persistent Symptoms After Clearance of SARS-CoV-2 Infection: A Multicenter Study from Egypt

Background and Aim

Little is known about the persistence of symptoms after clearance of SARS-CoV-2 infection. Our study aimed to assess persistent symptoms in COVID-19 patients after clearance of SARS-CoV-2 infection.

Methodology

A multi-center survey was conducted on first wave COVID-19 patients with confirmed SARS-CoV-2 infection. Sociodemographic and clinical characteristics, including presenting symptoms and persistent symptoms after viral clearance and possible factors contributing to persistence of such symptoms, were collected using an online multicomponent questionnaire. Descriptive and inferential statistical analysis was performed to detect the most persisting symptoms and factors contributing to their persistence.

Results

Overall, 538 patients were enrolled. Mean age was 41.17 (±SD 14.84), 54.1% were males, and 18.6% were smokers. Hypertension and diabetes were the most reported co-morbidities. Mild symptoms were reported in 61.3% of patients, 51.3% were admitted to hospital and 6.5% were admitted to the intensive care unit. Our study identified 49 types of persisting symptoms. Fatigue (59.1%), sense of fever (46.5%), anorexia (24.3%) and diarrhea (24.3%) were the most commonly reported persisting symptoms followed by loss of taste and smell (22.3%), headache (21.4%), cough (20.8) and dyspnea (21%). The use of hydroxychloroquine, azithromycin and multivitamins were significantly associated with persistence of symptoms (OR = 8.03, 8.89 and 10.12, respectively).

Conclusion

Our study revealed that in COVID-19 recovered patients, many patients reported persistence of at least one symptom, particularly fatigue and sense of fever. Follow-up of patients after discharge from hospital is recommended until complete resolution of symptoms.

Coronavirus Disease 2019 Temperature Trajectories Correlate With Hyperinflammatory and Hypercoagulable Subphenotypes

OBJECTIVES

Body temperature trajectories of infected patients are associated with specific immune profiles and survival. We determined the association between temperature trajectories and distinct manifestations of coronavirus disease 2019.

DESIGN

Retrospective observational study.

SETTING

Four hospitals within an academic healthcare system from March 2020 to February 2021.

PATIENTS

All adult patients hospitalized with coronavirus disease 2019.

INTERVENTIONS

Using a validated group-based trajectory model, we classified patients into four previously defined temperature trajectory subphenotypes using oral temperature measurements from the first 72 hours of hospitalization. Clinical characteristics, biomarkers, and outcomes were compared between subphenotypes.

MEASUREMENTS AND MAIN RESULTS

The 5,903 hospitalized coronavirus disease 2019 patients were classified into four subphenotypes: hyperthermic slow resolvers (n = 1,452, 25%), hyperthermic fast resolvers (1,469, 25%), normothermics (2,126, 36%), and hypothermics (856, 15%). Hypothermics had abnormal coagulation markers, with the highest d-dimer and fibrin monomers (p < 0.001) and the highest prevalence of cerebrovascular accidents (10%, p = 0.001). The prevalence of venous thromboembolism was significantly different between subphenotypes (p = 0.005), with the highest rate in hypothermics (8.5%) and lowest in hyperthermic slow resolvers (5.1%). Hyperthermic slow resolvers had abnormal inflammatory markers, with the highest C-reactive protein, ferritin, and interleukin-6 (p < 0.001). Hyperthermic slow resolvers had increased odds of mechanical ventilation, vasopressors, and 30-day inpatient mortality (odds ratio, 1.58; 95% CI, 1.13-2.19) compared with hyperthermic fast resolvers. Over the course of the pandemic, we observed a drastic decrease in the prevalence of hyperthermic slow resolvers, from representing 53% of admissions in March 2020 to less than 15% by 2021. We found that dexamethasone use was associated with significant reduction in probability of hyperthermic slow resolvers membership (27% reduction; 95% CI, 23-31%; p < 0.001).

CONCLUSIONS

Hypothermics had abnormal coagulation markers, suggesting a hypercoagulable subphenotype. Hyperthermic slow resolvers had elevated inflammatory markers and the highest odds of mortality, suggesting a hyperinflammatory subphenotype. Future work should investigate whether temperature subphenotypes benefit from targeted antithrombotic and anti-inflammatory strategies.

Prevalence and Biochemical Associations of Fever in Adults With Reverse Transcription Polymerase Chain Reaction Proven Coronavirus Disease Presenting at Tertiary Care Hospitals in Rawalpindi

Background

Clinically most apparent symptoms of COVID-19 include fever and cough, which in some patients show a worsening trend but are completely non-apparent in patients who present with an asymptomatic course of the disease. The aim of this study was to identify clinical and biochemical differences among polymerase chain reaction (PCR) positive patients who are either febrile or afebrile.

Methods

This study was conducted in Rawalpindi Medical University and Allied Hospitals between September and December 2020. All patients who tested positive for reverse transcription polymerase chain reaction (RT-PCR) COVID-19 were included in the study. After evaluation of 146 patients, 100 were selected, and with a response rate of 97%, a total of 97 patients were included in the final analysis. Depending on the presence of fever, the participants were divided into two groups. Both groups were then compared for baselines vitals and laboratory investigations. Data was entered and analyzed in SPSS v23.0 (IBM Inc., Armonk, New York).

Results

Among the 97 patients, 66 (68%) of the participants were male, and 31 (32%) were females. The mean age of the study participants was 45.23±18.08 years. Fever was present in 39 (40.2%) of the participants. When compared with patients with no fever, the patients with fever had greater severity of disease (p<0.001), higher heart rate (p<0.001), decreased oxygen saturation (p<0.001). Among the laboratory investigations, the fever group had a greater tendency of having deranged alanine aminotransferase (ALT) (70.82±29.23 vs. 32.83±16.22, p=0.010), Lymphocytes (1.56±0.54 vs. 2.12±0.94, p=0.003) and serum total bilirubin (1.06±0.36 vs. 0.55±0.21, p=0.009). Based on multiple regression analysis, the presence of fever is a predictor of derangement in ALT (OR=1.034, CI=1.001-1.068 p=0.025) and total bilirubin (OR=4.38, CI=2.14-6.78, p=0.021).

Conclusion

Fever may not be present among all patients presenting with COVID-19 infection, but those who have a fever have a greater risk of having deranged liver function tests. Hence, it is important to monitor liver function tests (LFTs) in COVID-19 patients presenting with fever. 

A Model Predicting Mortality of Hospitalized Covid-19 Patients Four Days After Admission: Development, Internal and Temporal-External Validation

Objective

To develop and validate a prognostic model for in-hospital mortality after four days based on age, fever at admission and five haematological parameters routinely measured in hospitalized Covid-19 patients during the first four days after admission.

Methods

Haematological parameters measured during the first 4 days after admission were subjected to a linear mixed model to obtain patient-specific intercepts and slopes for each parameter. A prediction model was built using logistic regression with variable selection and shrinkage factor estimation supported by bootstrapping. Model development was based on 481 survivors and 97 non-survivors, hospitalized before the occurrence of mutations. Internal validation was done by 10-fold cross-validation. The model was temporally-externally validated in 299 survivors and 42 non-survivors hospitalized when the Alpha variant (B.1.1.7) was prevalent.

Results

The final model included age, fever on admission as well as the slope or intercept of lactate dehydrogenase, platelet count, C-reactive protein, and creatinine. Tenfold cross validation resulted in a mean area under the receiver operating characteristic curve (AUROC) of 0.92, a mean calibration slope of 1.0023 and a Brier score of 0.076. At temporal-external validation, application of the previously developed model showed an AUROC of 0.88, a calibration slope of 0.95 and a Brier score of 0.073. Regarding the relative importance of the variables, the (apparent) variation in mortality explained by the six variables deduced from the haematological parameters measured during the first four days is higher (explained variation 0.295) than that of age (0.210).

Conclusions

The presented model requires only variables routinely acquired in hospitals, which allows immediate and wide-spread use as a decision support for earlier discharge of low-risk patients to reduce the burden on the health care system.

Clinical Trial Registration

Austrian Coronavirus Adaptive Clinical Trial (ACOVACT); ClinicalTrials.gov, identifier NCT04351724.

Age and clinical signs as predictors of COVID-19 symptoms and cycle threshold value

Many COVID-19 infected people remain asymptomatic, and hence the diagnosis at first presentation remains a challenge. Assessment at a presentation in primary care settings is usually done by visual triaging and basic clinical examination. This retrospective study involved investigating the medical e-records of COVID-19 positive patients who presented to a COVID-19 centre in Qatar for July 2020. The presence (symptomatic group) or the absence (asymptomatic group) of symptoms along with objective vital examination (ie; heart-rate (HR), temperature, haemoglobin saturation (SpO₂)) were analysed and linked to the viral load (ie; cycle threshold (Ct)) of COVID-19 positive patients. Four hundred eighty-one symptomatic (230 males) and 216 asymptomatic (101 males) patients were included. Compared to the asymptomatic male group, the symptomatic male group was older, had lower Ct value and SpO₂, and higher temperature and HR. Compared to the females asymptomatic group, the symptomatic females group had lower Ct value, and higher temperature. Compared to the asymptomatic group, the symptomatic group had lower Ct value and SpO₂, and higher temperature and HR. Compared to the asymptomatic group, the symptomatic group had lower Ct values (age groups [21–30], [31–40], [41–50] and [51–60]), higher temperature (age groups [21–30] and [31–40], Ct ranges [20.01–25.00] and [25.01–30.00]), higher HR (age groups [21–30] and [31–40], Ct range [15.01–20.00]); and lower SpO₂ (age groups [41–50] and [51–60], Ct ranges [15.01–20.00] and [35.01–40.00]). Compared with asymptomatic patients, symptomatic patients with COVID-19 are most likely to be febrile, tachycardic, hypoxic and having higher viral load. Higher viral load was associated with higher HR, higher temperature, lower SpO₂, but there was no relation between viral load and age.

Predictors of intubation and mortality in COVID-19 patients: a retrospective study

Background

Estimating the risk of intubation and mortality among COVID-19 patients can help clinicians triage these patients and allocate resources more efficiently. Thus, here we sought to identify the risk factors associated with intubation and intra-hospital mortality in a cohort of COVID-19 patients hospitalized due to hypoxemic acute respiratory failure (ARF).

Results

We included retrospectively a total of 187 patients admitted to the subintensive and intensive care units of the University Hospital “Maggiore della Carità” of Novara between March 1st and April 30th, 2020. Based on these patients’ demographic characteristics, early clinical and laboratory variables, and quantitative chest computerized tomography (CT) findings, we developed two random forest (RF) models able to predict intubation and intra-hospital mortality. Variables independently associated with intubation were C-reactive protein (p < 0.001), lactate dehydrogenase level (p = 0.018) and white blood cell count (p = 0.026), while variables independently associated with mortality were age (p < 0.001), other cardiovascular diseases (p = 0.029), C-reactive protein (p = 0.002), lactate dehydrogenase level (p = 0.018), and invasive mechanical ventilation (p = 0.001). On quantitative chest CT analysis, ground glass opacity, consolidation, and fibrosis resulted significantly associated with patient intubation and mortality. The major predictors for both models were the ratio between partial pressure of arterial oxygen and fraction of inspired oxygen, age, lactate dehydrogenase, C-reactive protein, glycemia, CT quantitative parameters, lymphocyte count, and symptom onset.

Conclusions

Altogether, our findings confirm previously reported demographic, clinical, hemato-chemical, and radiologic predictors of adverse outcome among COVID-19-associated hypoxemic ARF patients. The two newly developed RF models herein described show an overall good level of accuracy in predicting intra-hospital mortality and intubation in our study population. Thus, their future development and implementation may help not only identify patients at higher risk of deterioration more effectively but also rebalance the disproportion between resources and demand.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44158-021-00016-5.

Role of systemic corticosteroids in preventing hypoxia among patients with mild COVID-19: An observational study

Use of systemic corticosteroids is well-established in COVID-19 patients with hypoxia; however, there is scant data on its role in patients with mild disease and prolonged symptoms as a measure to prevent disease progression. The aim of this study is to evaluate the role of systemic corticosteroids in preventing hypoxia (SpO₂ ≤ 93% on room-air) among mild COVID-19 patients. An observational study was conducted among symptomatic COVID-19 patients taking oral corticosteroids and attending institute teleconsultation facility between 10th-30th June 2021. Patients who were already on corticosteroids for other indication or required oxygen supplementation before or within 24-hours of initiation of corticosteroids were excluded. A total of 140 consecutive symptomatic COVID-19 patients were included. Higher baseline C-reactive protein (OR: 1.03, 95% CI: 1.02-1.06, p < 0.001) and early systemic corticosteroid (within 7 days) initiation (OR: 6.5, 95% CI: 2.1-20.1, p = 0.001) were independent risk factors for developing hypoxia (SpO₂ ≤ 93%). Progression to hypoxia was significantly higher in patients who received corticosteroids before day 7 of illness (36.7%, 95% CI, 23.4-51.7%) compared to ≥ 7 of illness (14.3%, 95% CI, 7.8-23.2%) for persistent fever. Systemic corticosteroids within 7 days from symptom-onset were harmful and increased the risk of progression to hypoxia, whereas it may decrease the risk of progression when administered on or beyond 7 days in patients with mild COVID-19 and persistent symptoms. A well-designed randomised controlled trial is required to validate the findings.

Predictors of Mortality in Hospitalized COVID-19 Patients Complicated With Hypotension and Hypoxemia: A Retrospective Cohort Study

Introduction: COVID-19 patients with hypotension and hypoxemia had a significantly worse outcome. The purpose of this research was to ascertain the risk factors affecting the prognoses of these patients and to develop appropriate prognostic prediction tools.

Methods: From March 1, 2020, to April 16, 2020, a retrospective cohort analysis of COVID-19 patients with hypotension and hypoxemia was performed. The univariate and multivariate analyses were performed to identify the associated risk factors influencing the prognosis of COVID-19 patients with hypotension and hypoxemia, and the selected variables were then utilized to construct and validate the prediction model for these patients.

Results: Three hundred and twenty-seven COVID-19 patients with hypotension and hypoxemia who met the inclusion and exclusion criteria were included in this study. Age, temperature, troponin, and blood glucose were related to mortality in COVID-19 patients with hypotension and hypoxemia in both univariate and multivariate analyses. The MFP model (multiple fractional polynomial model), full model, and stepwise model were utilized to build the prediction model, and their AUCs were, respectively, 0.902 (0.868, 0.936), 0.902 (0.868, 0.936), and 0.902 (0.868, 0.936). Because the sample size for this research was limited, we utilized bootstrapping for internal validation. The AUCs of Bootstrap full and Bootstrap stepwise were 0.902 (0.867, 0.936) and 0.902 (0.868, 0.936), respectively.

Conclusion: Age, temperature, troponin, and blood glucose levels were associated with mortality in COVID-19 patients with hypotension and hypoxemia. Additionally, the prediction model developed using the variables above showed a high predictive value for predicting the prognosis of these individuals.

Wearable sensor derived decompensation index for continuous remote monitoring of COVID-19 diagnosed patients

The COVID-19 pandemic has accelerated the adoption of innovative healthcare methods, including remote patient monitoring. In the setting of limited healthcare resources, outpatient management of individuals newly diagnosed with COVID-19 was commonly implemented, some taking advantage of various personal health technologies, but only rarely using a multi-parameter chest-patch for continuous monitoring. Here we describe the development and validation of a COVID-19 decompensation index (CDI) model based on chest patch-derived continuous sensor data to predict COVID-19 hospitalizations in outpatient-managed COVID-19 positive individuals, achieving an overall AUC of the ROC Curve of 0.84 on 308 event negative participants, and 22 event positive participants, out of an overall study cohort of 400 participants. We retrospectively compare the performance of CDI to standard of care modalities, finding that the machine learning model outperforms the standard of care modalities in terms of both numbers of events identified and with a lower false alarm rate. While only a pilot phase study, the CDI represents a promising application of machine learning within a continuous remote patient monitoring system.

Core body temperature estimation by eyeglass-type device: thermal analysis of radiation heat measured from caruncle

This paper describes a method for estimating core body temperature from radiation heat of the caruncle and an eyeglass-type device for measuring the temperature of the caruncle to prescreen for infectious diseases such as COVID-19. As a precise prescreening method, monitoring a person's continuous core body temperature is desired. By monitoring the continuous core body temperature, including circadian rhythm, in our daily life, infections can potentially be discovered when body temperature is higher than normal. Although monitoring the core body temperature is effective, continuous and precise monitoring requires the use of an invasive instrument. To overcome this, we (1) design an eyeglass-type device for measuring the caruncle temperature and (2) model the correlation between the caruncle temperature and the core body temperature. Experimental results revealed that hypothalamic temperature could be estimated within ± 0.3 °C between 20 and 30 °C by using the eyeglass-type device.

A model for COVID-19-induced dysregulation of ACE2 shedding by ADAM17

The angiotensin Converting Enzyme 2 (ACE2) receptor is a key component of the renin-angiotensin-aldesterone system (RAAS) that mediates numerous effects in the cardiovascular system. It is also the cellular point of contact for the coronavirus spike protein. Cleavage of the receptor is both important to its physiological function as well as being necessary for cell entry by the virus. Shedding of ACE2 by the metalloprotease ADAM17 releases a catalytically active soluble form of ACE2, but cleavage by the serine protease TMPRSS2 is necessary for virion internalization. Complicating the issue is the observation that circulating ACE2 can also bind to the virus effectively blocking attachment to the membrane-bound receptor. This work investigates the possibility that the inflammatory response to coronavirus infection can abrogate shedding by ADAM17, thereby favoring cleavage by TMPRSS2 and thus cell entry by the virion.

Competitive ELISA for a serologic test to detect dengue serotype-specific anti-NS1 IgGs using high-affinity UB-DNA aptamers

Serologic tests to detect specific IgGs to antigens related to viral infections are urgently needed for diagnostics and therapeutics. We present a diagnostic method for serotype-specific IgG identification of dengue infection by a competitive enzyme-linked immunosorbent assay (ELISA), using high-affinity unnatural-base-containing DNA (UB-DNA) aptamers that recognize the four categorized serotypes. Using UB-DNA aptamers specific to each serotype of dengue NS1 proteins (DEN-NS1), we developed our aptamer-antibody sandwich ELISA for dengue diagnostics. Furthermore, IgGs highly specific to DEN-NS1 inhibited the serotype-specific NS1 detection, inspiring us to develop the competitive ELISA format for dengue serotype-specific IgG detection. Blood samples from Singaporean patients with primary or secondary dengue infections confirmed the highly specific IgG detection of this format, and the IgG production initially reflected the serotype of the past infection, rather than the recent infection. Using this dengue competitive ELISA format, cross-reactivity tests of 21 plasma samples from Singaporean Zika virus-infected patients revealed two distinct patterns: 8 lacked cross-reactivity, and 13 were positive with unique dengue serotype specificities, indicating previous dengue infection. This antigen-detection ELISA and antibody-detection competitive ELISA combination using the UB-DNA aptamers identifies both past and current viral infections and will facilitate specific medical care and vaccine development for infectious diseases.

Alterations of frontal-temporal gray matter volume associate with clinical measures of older adults with COVID-19

COVID-19, the infectious disease caused by the most recently discovered severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has become a global pandemic. It dramatically affects people's health and daily life. Neurological complications are increasingly documented for patients with COVID-19. However, the effect of COVID-19 on the brain is less studied, and existing quantitative neuroimaging analyses of COVID-19 were mainly based on the univariate voxel-based morphometry analysis (VBM) that requires corrections for a large number of tests for statistical significance, multivariate approaches that can reduce the number of tests to be corrected have not been applied to study COVID-19 effect on the brain yet. In this study, we leveraged source-based morphometry (SBM) analysis, a multivariate extension of VBM, to identify changes derived from computed tomography scans in covarying gray matter volume patterns underlying COVID-19 in 120 neurological patients (including 58 cases with COVID-19 and 62 patients without COVID-19 matched for age, gender and diseases). SBM identified that lower gray matter volume (GMV) in superior/medial/middle frontal gyri was significantly associated with a higher level of disability (modified Rankin Scale) at both discharge and six months follow-up phases even when controlling for cerebrovascular diseases. GMV in superior/medial/middle frontal gyri was also significantly reduced in patients receiving oxygen therapy compared to patients not receiving oxygen therapy. Patients with fever presented significant GMV reduction in inferior/middle temporal gyri and fusiform gyrus compared to patients without fever. Patients with agitation showed GMV reduction in superior/medial/middle frontal gyri compared to patients without agitation. Patients with COVID-19 showed no significant GMV differences from patients without COVID-19 in any brain region. Results suggest that COVID-19 may affect the frontal-temporal network in a secondary manner through fever or lack of oxygen.

Acute Symptoms of Mild to Moderate COVID-19 Are Highly Heterogeneous Across Individuals and Over Time

Background

The symptoms of coronavirus disease 2019 (COVID-19) appear to be heterogenous, and the typical course of these symptoms is unknown. Our objectives were to characterize the common trajectories of COVID-19 symptoms and to assess how symptom course predicts other symptom changes as well as clinical deterioration.

Methods

One hundred sixty-two participants with acute COVID-19 responded to surveys up to 31 times for up to 17 days. Several statistical methods were used to characterize the temporal dynamics of these symptoms. Because 9 participants showed clinical deterioration, we explored whether these participants showed any differences in symptom profiles.

Results

Trajectories varied greatly between individuals, with many having persistently severe symptoms or developing new symptoms several days after being diagnosed. A typical trajectory was for a symptom to improve at a decremental rate, with most symptoms still persisting to some degree at the end of the reporting period. The pattern of symptoms over time suggested a fluctuating course for many patients. Participants who showed clinical deterioration were more likely to present with higher reports of severity of cough and diarrhea.

Conclusions

The course of symptoms during the initial weeks of COVID-19 is highly heterogeneous and is neither predictable nor easily characterized using typical survey methods. This has implications for clinical care and early-treatment clinical trials. Additional research is needed to determine whether the decelerating improvement pattern seen in our data is related to the phenomenon of patients reporting long-term symptoms and whether higher symptoms of diarrhea in early illness presages deterioration.

Characteristics of Patients Co-infected with Severe Acute Respiratory Syndrome Coronavirus 2 and Dengue Virus, Buenos Aires, Argentina, March-June 2020

An epidemic of dengue virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) co-infections occurred in Argentina during 2020. We describe the clinical characteristics and outcomes in a cohort of patients hospitalized because of co-infection. We retrospectively identified 13 patients from different hospitals in Buenos Aires who had confirmed infection with SARS-CoV-2 and dengue virus and obtained clinical and laboratory data from clinical records. All patients had febrile disease when hospitalized. Headache was a common symptom. A total of 8 patients had respiratory symptoms, 5 had pneumonia, and 3 had rash. Nearly all patients had lymphopenia when hospitalized. No patients were admitted to an intensive care unit or died during follow up. Co-infection with SARS-CoV-2 and dengue virus can occur in patients living in areas in which both viruses are epidemic. The outcome of these patients did not seem to be worse than those having either SARS-CoV-2 or dengue infection alone.