Blood type A associates with critical COVID-19 and death in a Swedish cohort

Long COVID in Pakistan: a cross-sectional analysis of health and psychosocial outcomes

According to the World Health Organization-led Delphi consensus, long COVID corresponds to the occurrence of symptoms beyond twelve weeks after the onset of acute COVID-19 illness that cannot be explained by alternate diagnosis. This cross-sectional study aimed to analyse the impacts of long COVID on general health and psychosocial well-being. For this study, the participants were interviewed either face to face or via telephone, and their responses were recorded on a questionnaire capturing information on demographics, COVID-19 status, duration of symptoms and long COVID symptoms. The psychosocial impacts of the pandemic were assessed using scales like Short Mood and feeling questionnaire (sMFQ), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), Generalized Anxiety Disorder Assessment (GAD-7) and Perceived Stress Scale (PSS). Regression analysis was conducted to analyse the predictors of long COVID. A total of 300 participants were interviewed, of which 155 (52%) had COVID-19 illness. Of these 54 (35%) had persistent symptoms for a period of more than 12 weeks classified as long COVID. Muscle problems and fatigue were the most frequent (14.7%) symptoms encountered, followed by breathing problems (12.6%) and cognitive issues (12.6%). The symptoms of decrease in appetite and confusion or disorientation during the initial phase of the infection were associated with long COVID. The majority of the participants (83.3%) had moderate level of perceived stress, while moderate to severe levels of stress were observed in 17.3% of the individuals. Moreover, a high level of positive mental well-being was also observed. This study highlights the need for further research into the clinical aspects and implications of long COVID in Pakistan and emphasizes the importance of ongoing support for affected individuals.

ABO blood groups and the risk of SARS-CoV-2 infection

There is no doubt that genetic factors of the host play a role in susceptibility to infectious diseases. An association between ABO blood groups and SARS-CoV-2 infection as well as the severity of COVID-19 has been suggested relatively early during the pandemic and gained enormously high public interest. It was postulated that blood group A predisposes to a higher risk of infection as well as to a much higher risk of severe respiratory disease and that people with blood group O are less frequently and less severely affected by the disease. However, as to the severity of COVID-19, a thorough summary of the existing literature does not support these assumptions in general. Accordingly, at this time, there is no reason to suppose that knowledge of a patient's ABO phenotype should directly influence therapeutical decisions in any way. On the other hand, there are many data available supporting an association between the ABO blood groups and the risk of contracting SARS-CoV-2. To explain this association, several interactions between the virus and the host cell membrane have been proposed which will be discussed here.

Correlates of In-Hospital COVID-19 Deaths: A Competing Risks Survival Time Analysis of Retrospective Mortality Data

INTRODUCTION

Several aspects of the coronavirus disease 2019 (COVID-19) pandemic remain ambiguous, including its transmission, severity, geographic, and racial differences in mortality. These variations merit elaboration of local patterns to inform wider national policies.

METHODS

In a retrospective analysis, data of patients treated at a dedicated COVID hospital with moderate and severe illness during 8 wk of the pandemic were reviewed with attention to mortality in a competing risks framework.

RESULTS

A total of 1147 patients were hospitalized, and 312 (27.2%) died in hospital. Those who died were older (56.5 vs 47.6 y; P < 0.0001). Of these, 885 (77.2%) had tested positive on reverse transcriptase polymerase chain reaction (RT-PCR), with 219 (24.2%) deaths (incidence rate, 1.9 per 100 person-days). Median time from onset of symptoms to death was 11 days. A competing risks analysis for in-hospital death revealed an adjusted cause-specific hazard ratio of 1.4 for each decade increase in age.

CONCLUSIONS

This retrospective analysis provides broad patterns of disease presentation and mortality. Even COVID test-negative patients will receive treatment at dedicated facilities, and 33% presenting cases may die within the first 72 h, most with comorbid illness. This should be considered while planning distribution of services for effective health-care delivery.

The Genetic Risk for COVID-19 Severity Is Associated With Defective Immune Responses

Recent genome-wide association studies (GWASs) of COVID-19 patients of European ancestry have identified genetic loci significantly associated with disease severity. Here, we employed the detailed clinical, immunological and multi-omics dataset of the Human Functional Genomics Project (HFGP) to explore the physiological significance of the host genetic variants that influence susceptibility to severe COVID-19. A genomics investigation intersected with functional characterization of individuals with high genetic risk for severe COVID-19 susceptibility identified several major patterns: i. a large impact of genetically determined innate immune responses in COVID-19, with ii. increased susceptibility for severe disease in individuals with defective cytokine production; iii. genetic susceptibility related to ABO blood groups is probably mediated through the von Willebrand factor (VWF) and endothelial dysfunction. We further validated these identified associations at transcript and protein levels by using independent disease cohorts. These insights allow a physiological understanding of genetic susceptibility to severe COVID-19, and indicate pathways that could be targeted for prevention and therapy.

ABO blood group and effects on ventilatory time, length of stay and mortality in major burns a retrospective observational outcome study

Blood group has been found to be important in the development of many diseases and the outcome of several disease processes, especially cardiovascular morbidity and mortality, such as caused by trauma and sepsis. The main reason is claimed to be related to glycobiology and effects mediated through the endothelium. This study investigated the possible effect of blood group (ABO) on burn care outcome. Burn outcome prediction models are extremely accurate and as such can be used to identify outcome effects even in single centre settings. In this retrospective risk adjusted observational study, we investigated the effect of ABO blood group on ventilatory time, length of hospital stay (LOS), and 90 day mortality among patients with burns. RESULTS: A total of 225 patients were included (2008-2019) with median TBSA of 26%; interquartile range (IQR) of 20-37%; median age 45 years (IQR 22-65 years); median Baux score (age + TBSA%); 76 (IQR 53- 97); 168 (75%) were male; median duration of hospital stay was 31 days (IQR 19-56); a total of 138 (61%) received treatment with mechanical ventilation; and 29 (13%) died. In a multivariable regression model, we were unable to isolate any significant effect of any blood group (O, A, B, AB) on the outcome measures studied (ventilatory time, LOS, and mortality). IN SUMMARY: contrary to many other major areas of disease in which ABO blood groups affect outcome, we were unable to find any such effect on patients with burns. Given the precision of the outcome models presented (AUC 0.93) any such an effect, if missed due to the limited study cohort, may be considered limited and to have only a minor clinical impact.

Improved 60-day survival but impaired general health in Swedish ICU-COVID patients: An ambidirectional population-based study

Background

Survival among critically ill COVID‐19 patients varies between countries and time periods. Mortality rates up to 60% have been reported in intensive care units (ICUs). Standard‐of‐care has evolved throughout the pandemic. The purpose of the study was to explore management and mortality of COVID‐19 ICU‐patients during the first pandemic wave and assess their post‐ICU health status.

Methods

We conducted an exploratory observational ambidirectional population‐based study of ICU‐patients with COVID‐19 in a Swedish county during 1 March‐30 June 2020. Primary outcome was 60‐day mortality with secondary outcomes including treatments, complications, self‐reported general health and dyspnoea post‐discharge. Patients were consecutively divided into equal tertiles with cut‐offs on April 4 and April 20, 2020, to analyse time trends.

Results

One hundred patients, median age was 63 years, were included, and 60‐day mortality rate was 22%. Ninety‐one percent had moderate/severe ARDS and 88% required mechanical ventilation. In the first tertile of patients 60‐day mortality was 33%, declining to 15% and 18% in the following two. This reduction paralleled increased use of thromboprophylaxis, less steep rise of treated ICU‐patients per day and expanded ICU resources. Four months post‐discharge, 63% of survivors reported self‐assessed decline in general health retrospectively compared to prior COVID‐19.

Conclusions

In this cohort, the initial 60‐day mortality quickly declined, despite continuous admittance of critically ill patients. This was parallel to adaptation to increased workload and more intense thromboembolic prophylaxis. A majority of survivors reported declined general health four months after discharge. Further studies on long‐term health status of ICU‐survivors are indicated.

Variation in COVID-19 Disease Severity and Clinical Outcomes Between Different ABO Blood Groups

The primary objective of this study was to explore whether coronavirus disease 2019 (COVID-19) severity and outcomes varied between different ABO blood groups. This retrospective study included 363 COVID-19 confirmed patients who had their blood group recorded in the hospital medical records, from March to June 2020. Data representing demographics, clinical features, vital signs, laboratory findings, and COVID-19 outcomes were collected. Multivariate logistic regression was used for analysis and the results were adjusted for sociodemographic, clinical, and laboratory variables. The patients' mean age was 50 ± 17.8 years. Of the 363 patients, 30% were blood group A, 22.3% were blood group B, 8.8% were blood group AB, and 38.8% were blood group O. Bivariate analysis showed that patients with blood group AB were more likely to be free of any medical disease (65.6%) compared to other blood groups (p = 0.007). Fever was the most common presenting complaint (66.7%), and it did not significantly vary with changes in ABO blood groups (p = 0.230). Regarding laboratory characteristics, only C-reactive protein (CRP) levels were significantly associated with the blood groups, with high levels seen in blood groups A, B, and O (p = 0.036). In multivariate analysis, variations in emergency department (ED) disposition, requirement of intensive care unit care, and requirement of mechanical ventilation were not statistically significant among the different ABO blood groups. Furthermore, no correlation was found between hospital death and the different ABO blood groups. In conclusion, COVID-19 is most prevalent among patients with blood group O and least prevalent among those with blood group AB. No particular blood group had worse COVID-19 disease severity and outcomes than other blood groups. Therefore, we believe that ABO blood grouping should not be used as a major assessment tool for COVID-19 disease severity and outcome, and other known risk factors should be investigated.

Predicting mortality in SARS-COV-2 (COVID-19) positive patients in the inpatient setting using a novel deep neural network

BACKGROUND

The nextwave of COVID-19 pandemic is anticipated to be worse than the initial one and will strain the healthcare systems even more during the winter months. Our aim was to develop a novel machine learning-based model to predict mortality using the deep learning Neo-V framework. We hypothesized this novel machine learning approach could be applied to COVID-19 patients to predict mortality successfully with high accuracy.

METHODS

We collected clinical and laboratory data prospectively on all adult patients (≥18 years of age) that were admitted in the inpatient setting at Aga Khan University Hospital between February 2020 and September 2020 with a clinical diagnosis of COVID-19 infection. Only patients with a RT-PCR (reverse polymerase chain reaction) proven COVID-19 infection and complete medical records were included in this study. A Novel 3-phase machine learning framework was developed to predict mortality in the inpatients setting. Phase 1 included variable selection that was done using univariate and multivariate Cox-regression analysis; all variables that failed the regression analysis were excluded from the machine learning phase of the study. Phase 2 involved new-variables creation and selection. Phase 3 and final phase applied deep neural networks and other traditional machine learning models like Decision Tree Model, k-nearest neighbor models, etc. The accuracy of these models were evaluated using test-set accuracy, sensitivity, specificity, positive predictive values, negative predictive values and area under the receiver-operating curves.

RESULTS

After application of inclusion and exclusion criteria (n=)1214 patients were selected from a total of 1228 admitted patients. We observed that several clinical and laboratory-based variables were statistically significant for both univariate and multivariate analyses while others were not. With most significant being septic shock (hazard ratio [HR], 4.30; 95% confidence interval [CI], 2.91-6.37), supportive treatment (HR, 3.51; 95% CI, 2.01-6.14), abnormal international normalized ratio (INR) (HR, 3.24; 95% CI, 2.28-4.63), admission to the intensive care unit (ICU) (HR, 3.24; 95% CI, 2.22-4.74), treatment with invasive ventilation (HR, 3.21; 95% CI, 2.15-4.79) and laboratory lymphocytic derangement (HR, 2.79; 95% CI, 1.6-4.86). Machine learning results showed our deep neural network (DNN) (Neo-V) model outperformed all conventional machine learning models with test set accuracy of 99.53%, sensitivity of 89.87%, and specificity of 95.63%; positive predictive value, 50.00%; negative predictive value, 91.05%; and area under the receiver-operator curve of 88.5.

CONCLUSION

Our novel Deep-Neo-V model outperformed all other machine learning models. The model is easy to implement, user friendly and with high accuracy.

Uncurtaining the effect of COVID-19 in diabetes mellitus: a complex clinical management approach

The aim of the present review is to overview the common properties of corona virus and hence proofs well beginning of corona virus in persons with diabetes, and its treatment. Globally, it has been observed that according to the statistics, India has the second largest number of people with diabetes. Literature review has been implemented within the databases using suitable keywords. For persons suffering from diabetic disorder, the COVID-19 infection becomes a dual challenge. Diabetes is a severe metabolic situation which causes the sugar levels in the blood to increase than the normal level. Normally, communicable disease like COVID-19 is more prevailing in patients with diabetes. Diabetic patient has poor immune response to infections. The different bacterial, viral, parasitic, and mycotic infections showed increased probability in diabetic patients as compared to non-diabetic patient. All these conclusions clear out the intention that the diabetic patients are more susceptible to enhanced inflammatory response that may lead to rapid spreading of COVID-19 infection with high rate of mortality. In the present situation of pandemic, managing diabetes seems to be quite challenging and diabetic patient having COVID-19 infection should follow normal course of antihypertensive and antidiabetic drugs prescribed with the exception of sodium glucose co-transpoters-2 inhibitors which would increase the risk of dehydration and ketoacidosis. In view of above discussion, this article highlights the proposed mechanism of COVID-19 infection linking it with diabetes, antidiabetic drugs to be used in COVID-19 infection along with their advantages, and disadvantages and management of COVID-19 infection diabetic patient.

COVID-19 infection in a pediatric kidney transplant population: A single-center experience

BACKGROUND

The clinical course of SARS-CoV-2 in the pediatric kidney transplant population is not well described.

METHODS

We performed a retrospective cohort study of a pediatric kidney transplant population at a New York transplant center. Baseline characteristics and clinical course of patients with SARS-CoV-2 positivity (Ab or PCR) were described, and comparison between COVID-positive and COVID-negative transplant patients was performed.

RESULTS

Twenty-two patients had COVID-19 IgG testing performed, eight of whom also had PCR testing. 23% of our cohort had evidence of COVID-19 infection. Four patients had positive IgG only, and one patient had a positive PCR. All five patients with a positive COVID test were female. Two patients had COVID-19 symptoms, which were mild. Of the symptomatic patients, one had a positive PCR at time of symptoms, while the other had a negative PCR during symptoms but subsequently had positive IgG. As compared to patients with COVID-19 negative results, those with COVID-19 positivity were significantly more likely to have a known COVID-19 exposure, and were also more likely to be female. There was no significant difference in time from transplant between the groups. Those in the COVID-positive group had higher baseline antimetabolite dose and CNI troughs, although these did not reach statistical significance.

CONCLUSIONS

Pediatric kidney transplant recipients are at risk for development of COVID-19 infection. While this population may be more at risk for SARS-CoV-2 infection due to their immunosuppressed status, their clinical course appears mild and similar to a healthy pediatric population.

Systematic review and meta-analysis of the susceptibility of ABO blood group to COVID-19 infection

Background

Numerous studies investigate the association between the ABO blood groups and the occurrence of COVID-19 infection; discordant findings were reported. Therefore, the purpose of this meta-analysis was to evaluate the existing evidence on the susceptibility of the ABO blood group to COVID-19 infection.

Methods

Systematically searched published articles in PubMed, Google Scholar, Scopus, and EMBASE between 1 st January 2020 and 21 st March 2021. After quality control and the exclusion of irrelevant studies, 16 studies were included in the final analysis.

Results

Although the random-effect meta-analysis revealed a large heterogeneity among studies, I 2 = 99.197 %. The pooled event rates and (95 % CIs) for A, O, B, and AB blood group were 0.459 (95 %CI: 0.358–0.441), 0.342 (95 %CI: 0.298–0.374), 0.180 (95 %CI: 0.150–0.214), and 0.076 (95 %CI: 0.055–0.127), respectively. These results indicated that the COVID-19 infection rate was higher in persons with blood group A > O > B > AB. Overall, the ABO blood group's vulnerability to COVID-19 infection was statistically significant (pooled p -value<0.001).

Conclusion

This meta-analysis offers a further indication of blood group A individuals' vulnerability to COVID-19 infection, and blood type AB are linked to a lower risk of COVID-19 infection.

Atrial appendage angiotensin-converting enzyme-2, aging and cardiac surgical patients: a platform for understanding aging-related coronavirus disease-2019 vulnerabilities

PURPOSE OF REVIEW

Hospitalizations for COVID-19 dramatically increase with age. This is likely because of increases in fragility across biological repair systems and a weakened immune system, including loss of the cardiorenal protective arm of the renin--angiotensin system (RAS), composed of angiotensin-converting enzyme-2 (ACE2)/angiotensin-(1--7) [Ang-(1--7)] and its actions through the Mas receptor. The purpose of this review is to explore how cardiac ACE2 changes with age, cardiac diseases, comorbid conditions and pharmaceutical regimens in order to shed light on a potential hormonal unbalance facilitating SARs-CoV-2 vulnerabilities in older adults.

RECENT FINDINGS

Increased ACE2 gene expression has been reported in human hearts with myocardial infarction, cardiac remodeling and heart failure. We also found ACE2 mRNA in atrial appendage tissue from cardiac surgical patients to be positively associated with age, elevated by certain comorbid conditions (e.g. COPD and previous stroke) and increased in conjunction with patients' chronic use of antithrombotic agents and thiazide diuretics but not drugs that block the renin--angiotensin system.

SUMMARY

Cardiac ACE2 may have bifunctional roles in COVID-19 as ACE2 not only mediates cellular susceptibility to SARS-CoV-2 infection but also protects the heart via the ACE2/Ang-(1--7) pathway. Linking tissue ACE2 from cardiac surgery patients to their comorbid conditions and medical regimens provides a unique latform to address the influence that altered expression of the ACE2/Ang-(1-7)/Mas receptor axis might have on SARs-CoV-2 vulnerability in older adults.

Current understanding of the influence of environmental factors on SARS-CoV-2 transmission, persistence, and infectivity

Coronavirus disease 2019 (COVID-19) has emerged as a significant public health emergency in recent times. It is a respiratory illness caused by the novel virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was initially reported in late December 2019. In a span of 6 months, this pandemic spread across the globe leading to high morbidity and mortality rates. Soon after the identification of the causative virus, questions concerning the impact of environmental factors on the dissemination and transmission of the virus, its persistence in environmental matrices, and infectivity potential begin to emerge. As the environmental factors could have far-reaching consequences on infection dissemination and severity, it is essential to understand the linkage between these factors and the COVID-19 outbreak. In order to improve our current understanding over this topic, the present article summarizes topical and substantial observations made regarding the influences of abiotic environmental factors such as climate, temperature, humidity, wind speed, air, and water quality, solid surfaces/interfaces, frozen food, and biotic factors like age, sex, gender, blood type, population density, behavioural characteristics, etc. on the transmission, persistence, and infectivity of this newly recognized SARS-CoV-2 virus. Further, the potential pathways of virus transmission that could pose risk to population health have been discussed, and the critical areas have been identified which merits urgent research for the assessment and management of the COVID-19 outbreak. Where possible, the knowledge gaps requiring further investigation have been highlighted.

de Bree LC, de Mast Q, van de Veerdonk FL, Joosten LA, Li Y, Netea MG, Xu C. The genetic risk for COVID-19 severity is associated with defective innate immune responses.. [DOI: 10.1101/2020.11.10.20229203]

Recent genome-wide association studies (GWASs) of COVID-19 patients of European ancestry have identified genetic loci significantly associated with disease severity (1). Here, we employed the detailed clinical, immunological and multi-omics dataset of the Human Functional Genomics Projects (HFGP) to explore the physiological significance of the host genetic variants that influence susceptibility to severe COVID-19. A genomics investigation intersected with functional characterization of individuals with high genetic risk for severe COVID-19 susceptibility identified several major patterns: i. a large impact of genetically determined innate immune responses in COVID-19, with increased susceptibility for severe disease in individuals with defective monocyte-derived cytokine production; ii. genetic susceptibility related to ABO blood groups is probably mediated through the von Willebrand factor (VWF) and endothelial dysfunction. We further validated these identified associations at transcript and protein levels by using independent disease cohorts. These insights allow a physiological understanding of genetic susceptibility to severe COVID-19, and indicate pathways that could be targeted for prevention and therapy.

One Sentence summary

In this study, we explore the physiological significance of the genetic variants associated with COVID-19 severity using detailed clinical, immunological and multi-omics data from large cohorts. Our findings allow a physiological understanding of genetic susceptibility to severe COVID-19, and indicate pathways that could be targeted for prevention and therapy.