3D CNN-Based Classification of Severity in COVID-19 Using CT Images

With the pandemic worldwide due to COVID-19, several detections and diagnostic methods have been in place. One of the standard modes of detection is computed tomography imaging. With the availability of computing resources and powerful GPUs, the analyses of extensive image data have been possible. Our proposed work initially deals with the classification of CT images as normal and infected images, and later, from the infected data, the images are classified based on their severity. The proposed work uses a 3D convolution neural network model to extract all the relevant features from the CT scan images. The results are also compared with the existing state-of-the-art algorithms. The proposed work is evaluated in accuracy, precision, recall, kappa value, and Intersection over Union. The model achieved an overall accuracy of 94.234% and a kappa value of 0.894. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Age-specific contribution of contacts to transmission of SARS-CoV-2 in Germany.

Current estimates of pandemic SARS-CoV-2 spread in Germany using infectious disease models often do not use age-specific infection parameters and are not always based on age-specific contact matrices of the population. They also do usually not include setting- or pandemic phase-based information from epidemiological studies of reported cases and do not account for age-specific underdetection of reported cases. Here, we report likely pandemic spread using an age-structured model to understand the age- and setting-specific contribution of contacts to transmission during different phases of the COVID-19 pandemic in Germany. We developed a deterministic SEIRS model using a pre-pandemic contact matrix. The model was optimized to fit age-specific SARS-CoV-2 incidences reported by the German National Public Health Institute (Robert Koch Institute), includes information on setting-specific reported cases in schools and integrates age- and pandemic period-specific parameters for underdetection of reported cases deduced from a large population-based seroprevalence studies. Taking age-specific underreporting into account, younger adults and teenagers were identified in the modeling study as relevant contributors to infections during the first three pandemic waves in Germany. For the fifth wave, the Delta to Omicron transition, only age-specific parametrization reproduces the observed relative and absolute increase in pediatric hospitalizations in Germany. Taking into account age-specific underdetection did not change considerably how much contacts in schools contributed to the total burden of infection in the population (up to 12% with open schools under hygiene measures in the third wave). Accounting for the pandemic phase and age-specific underreporting is important to correctly identify those groups of the population in which quarantine, testing, vaccination, and contact-reduction measures are likely to be most effective and efficient. Age-specific parametrization is also highly relevant to generate informative age-specific output for decision makers and resource planers.

Association Between Smoking and SARS-CoV-2 Infection: Cross-sectional Study of the EPICOVID19 Internet-Based Survey.

BACKGROUND: Several studies have reported a low prevalence of current smoking among hospitalized COVID-19 cases; however, no definitive conclusions can be drawn. OBJECTIVE: We investigated the association of tobacco smoke exposure with nasopharyngeal swab (NPS) test results for SARS-CoV-2 infection and disease severity accounting for possible confounders. METHODS: The nationwide, self-administered, cross-sectional web-based Italian National Epidemiological Survey on COVID-19 (EPICOVID19) was administered to an Italian population of 198,822 adult volunteers who filled in an online questionnaire between April 13 and June 2, 2020. For this study, we analyzed 6857 individuals with known NPS test results. The associations of smoking status and the dose-response relationship with a positive NPS test result and infection severity were calculated as odds ratios (ORs) with 95% CIs by means of logistic and multinomial regression models adjusting for sociodemographic, clinical, and behavioral characteristics. RESULTS: Out of the 6857 individuals (mean age 47.9 years, SD 14.1; 4516/6857, 65.9% female), 63.2% (4334/6857) had never smoked, 21.3% (1463/6857) were former smokers, and 15.5% (1060/6857) were current smokers. Compared to nonsmokers, current smokers were younger, were more educated, were less affected by chronic diseases, reported COVID-19-like symptoms less frequently, were less frequently hospitalized, and less frequently tested positive for COVID-19. In multivariate analysis, current smokers had almost half the odds of a positive NPS test result (OR 0.54, 95% CI 0.45-0.65) compared to nonsmokers. We also found a dose-dependent relationship with tobacco smoke: mild smokers (adjusted OR [aOR] 0.76, 95% CI 0.55-1.05), moderate smokers (aOR 0.56, 95% CI 0.42-0.73), and heavy smokers (aOR 0.38, 95% CI 0.27-0.53). This inverse association also persisted when considering the severity of the infection. Current smokers had a statistically significantly lower probability of having asymptomatic (aOR 0.50, 95% CI 0.27-0.92), mild (aOR 0.65, 95% CI 0.53-0.81), and severe infections (aOR 0.27, 95% CI 0.17-0.42) compared to those who never smoked. CONCLUSIONS: Current smoking was negatively associated with SARS-CoV-2 infection with a dose-dependent relationship. Ad hoc experimental studies are needed to elucidate the mechanisms underlying this association. TRIAL REGISTRATION: ClinicalTrials.gov NCT04471701; https://clinicaltrials.gov/ct2/show/NCT04471701.

Comparison of the Covid-19 Infection Severity in Known Diabetic Patients vs. Known Hypertensive Patients Admitted in A Tertiary Care Hospital in Peshawar

Objectives: To compare the severity of COVID-19 infection among known diabetic and known hypertensive patients who were admitted in a tertiary care hospital in Peshawar, Pakistan. Methodology: A cross-sectional clinical study was conducted for comparison in diabetic vs hypertensive patients in the department of medicine of Lady Reading Hospital, Peshawar during the period from April-June 2021. All the patients were admitted in COVID ward and COVID ICU, showed their full consent and active participation in this study. Along with patient's ECG and Echo report, a questionnaire based on Canadian categorization employed for angina grading and NYHA categorization to classify shortness of breath was used. Result(s): The mean age group taken for the sample was (n=140) with maximum age of 84 years. Majority were 102(72.9%) males and females were 38(27.1%). According to laboratory tests performed on patients of COVID-19 about 48(34.4%) of patients showed positive diabetes mellitus findings. Also, patients with positive hypertension found were 67(47.9%). The average stays of patients, at the hospital, was 15-40 days. About 58.3% of mortality was noted in patients with diabetes mellitus, a bulk of patients expired were from ICU-COVID-UNIT and 55.2% was the mortality rate in patients with positive hypertension according to our clinical findings and assessment. About 7.9% of COVID inpatients had cardiac infraction with severe condition and such patients who faced congestive heart failure expired. Almost 56(40%) of the patients were found with severe condition and 63(45%) were diagnosed with moderate condition during their stay at hospital. Conclusion(s): Regardless of age, gender and disease the death rate evaluated was 50%. Moreover, in diabetics and hypertensive patients there should be raised awareness for preventing the severity of disease. Copyright © 2022 Lahore Medical And Dental College. All rights reserved.

Characterizing Macrophages Diversity in COVID-19 Patients Using Deep Learning.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent responsible for coronavirus disease 2019 (COVID-19), has affected the lives of billions and killed millions of infected people. This virus has been demonstrated to have different outcomes among individuals, with some of them presenting a mild infection, while others present severe symptoms or even death. The identification of the molecular states related to the severity of a COVID-19 infection has become of the utmost importance to understanding the differences in critical immune response. In this study, we computationally processed a set of publicly available single-cell RNA-Seq (scRNA-Seq) data of 12 Bronchoalveolar Lavage Fluid (BALF) samples diagnosed as having a mild, severe, or no infection, and generated a high-quality dataset that consists of 63,734 cells, each with 23,916 genes. We extended the cell-type and sub-type composition identification and our analysis showed significant differences in cell-type composition in mild and severe groups compared to the normal. Importantly, inflammatory responses were dramatically elevated in the severe group, which was evidenced by the significant increase in macrophages, from 10.56% in the normal group to 20.97% in the mild group and 34.15% in the severe group. As an indicator of immune defense, populations of T cells accounted for 24.76% in the mild group and decreased to 7.35% in the severe group. To verify these findings, we developed several artificial neural networks (ANNs) and graph convolutional neural network (GCNN) models. We showed that the GCNN models reach a prediction accuracy of the infection of 91.16% using data from subtypes of macrophages. Overall, our study indicates significant differences in the gene expression profiles of inflammatory response and immune cells of severely infected patients.

Smoking status and SARS-CoV-2 infection severity among Lebanese adults: a cross-sectional study.

BACKGROUND: A paradoxical hypothesis about the effect of smoking on patients infected with severe acute respiratory syndrom 2 (SARS-CoV-2) infection still exists. Furthermore, gender-discrepancy in the impact of smoking on COVID-19 severity was given little attention. Thus, the aims of the present study were to evaluate the prevalence of smoking and the COVID-19 infection severity in a sample of adult patients diagnosed with COVID-19 and to explore the relationship between smoking status and SARS-CoV-2 infection severity in the overall sample and stratified by gender. METHODS: A retrospective analytical study was conducted on patients diagnosed with COVID-19 cases between December, 2020 and April, 2021 from three leading laboratories in Lebanon. Sociodemographic characteristics, smoking status and clinical symptoms were collected. Multinomial logistic regression analysis was used to explore the relationship between smoking status and SARS-CoV-2 infection severity. RESULTS: A total of 901 confirmed COVID-19 cases participated in the study, 50.8% were females. The mean age of patients was 38.4 years (SD = 15.3). Of the total sample, 521(57.8%) were current smokers. Regarding infection severity, 14.8% were asymptomatic, 69.9% had mild symptoms, while 15.3% had severe infection. In the overall sample, smoking status, smoking types and dose-response were not significantly associated with infection severity. Upon stratifying the entire sample by gender, no association was found between all the considered variables with infection severity among females. However, a significant association was found among male with mild infection compared to their asymptomatic counterparts (OR = 1.78 95% CI (1.01-3.13)). Waterpipe smoking was found to be associated with infection severity among male with mild infection (OR 2.64 (95% CI 1.32-5.27)) and severe infection 2.79, 95% CI (1.19-6.53) compared to their asymptomatic counterparts. CONCLUSION: Our fundings highlight sex differences in the association between tobacco smoking and COVID-19 severity. Current tobacco smoking was not associated with SARS-CoV-2 infection severity among female patients, however, tobacco smoking, particularly waterpipe, was found to be associated with infection severity among male. Thus, the battle against smoking should continue by assisting smokers to successfully and permanently quit.

Association Between the LZTFL1 rs11385942 Polymorphism and COVID-19 Severity in Colombian Population.

Genetic and non-genetic factors are responsible for the high interindividual variability in the response to SARS-CoV-2. Although numerous genetic polymorphisms have been identified as risk factors for severe COVID-19, these remain understudied in Latin-American populations. This study evaluated the association of non-genetic factors and three polymorphisms: ACE rs4646994, ACE2 rs2285666, and LZTFL1 rs11385942, with COVID severity and long-term symptoms by using a case-control design. The control group was composed of asymptomatic/mild cases (n = 61) recruited from a private laboratory, while the case group was composed of severe/critical patients (n = 63) hospitalized in the Hospital Universitario Mayor-Méderi, both institutions located in Bogotá, Colombia. Clinical follow up and exhaustive revision of medical records allowed us to assess non-genetic factors. Genotypification of the polymorphism of interest was performed by amplicon size analysis and Sanger sequencing. In agreement with previous reports, we found a statistically significant association between age, male sex, and comorbidities, such as hypertension and type 2 diabetes mellitus (T2DM), and worst outcomes. We identified the polymorphism LZTFL1 rs11385942 as an important risk factor for hospitalization (p < 0.01; OR = 5.73; 95% CI = 1.2-26.5, under the allelic test). Furthermore, long-term symptoms were common among the studied population and associated with disease severity. No association between the polymorphisms examined and long-term symptoms was found. Comparison of allelic frequencies with other populations revealed significant differences for the three polymorphisms investigated. Finally, we used the statistically significant genetic and non-genetic variables to develop a predictive logistic regression model, which was implemented in a Shiny web application. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC = 0.86; 95% confidence interval 0.79-0.93). These results suggest that LZTFL1 rs11385942 may be a potential biomarker for COVID-19 severity in addition to conventional non-genetic risk factors. A better understanding of the impact of these genetic risk factors may be useful to prioritize high-risk individuals and decrease the morbimortality caused by SARS-CoV2 and future pandemics.

Sex- and gender-related differences linked to SARS-CoV-2 infection among the participants in the web-based EPICOVID19 survey: the hormonal hypothesis.

Objective To investigate sex- and gender-based differences linked to SARS-COV-2 infection and to explore the role of hormonal therapy (HT) in females. Study design Data from the self-administered, cross-sectional, web-based EPICOVID19 survey of 198,822 adults living in Italy who completed an online questionnaire during the first wave of the epidemic in Italy (April-May 2020) were analyzed. Main outcomes measures Multivariate binary logistic and multinomial regression models were respectively used to estimate the odds ratios (ORs) with 95% confidence intervals (CIs) for positive nasopharyngeal swab (NPS) test results and severe SARS-CoV-2 infection. Results The data from 6,873 participants (mean age 47.9 ± 14.1 years, 65.8% females) who had a known result from an NPS test were analyzed. According to the multivariate analysis, females had lower odds of a positive result from the NPS test (aOR 0.75, 95%CI 0.66-0.85) and of having a severe infection (aOR 0.46, 95%CI 0.37-0.57) than did their male counterparts. These differences were greater with decreasing age in both sexes. In addition, females aged ≥60 years receiving HT (N = 2,153, 47.6%) had a 46% lower probability of having a positive NPS test (aOR 0.54, 95%CI 0.36-0.80) than their same-aged peers who had never used HT; there were no differences in the younger age groups with respect to HT status. Conclusion Female sex was associated with an age-dependent lower risk of having a severe SARS-CoV-2 infection than their male counterparts. Age seemed to modify the relationship between HT status and infection: while the two were not related among younger participants, it was negative in the older ones. Future prospective studies are needed to elucidate the potential protective role sex hormones may play. Trial registration ClinicalTrials.gov NCT04471701.

Heart Rate in Patients with SARS-CoV-2 Infection: Prevalence of High Values at Discharge and Relationship with Disease Severity.

The most common arrhythmia associated with COronaVIrus-related Disease (COVID) infection is sinus tachycardia. It is not known if high Heart Rate (HR) in COVID is simply a marker of higher systemic response to sepsis or if its persistence could be related to a long-term autonomic dysfunction. The aim of our work is to assess the prevalence of elevated HR at discharge in patients hospitalized for COVID-19 and to evaluate the variables associated with it. We enrolled 697 cases of SARS-CoV2 infection admitted in our hospital after February 21 and discharged within 23 July 2020. We collected data on clinical history, vital signs, laboratory tests and pharmacological treatment. Severe disease was defined as the need for Intensive Care Unit (ICU) admission and/or mechanical ventilation. Median age was 59 years (first-third quartile 49, 74), and male was the prevalent gender (60.1%). 84.6% of the subjects showed a SARS-CoV-2 related pneumonia, and 13.2% resulted in a severe disease. Mean HR at admission was 90 ± 18 bpm with a mean decrease of 10 bpm to discharge. Only 5.5% of subjects presented HR > 100 bpm at discharge. Significant predictors of discharge HR at multiple linear model were admission HR (mean increase = ß = 0.17 per bpm, 95% CI 0.11; 0.22, p < 0.001), haemoglobin (ß = -0.64 per g/dL, 95% CI -1.19; -0.09, p = 0.023) and severe disease (ß = 8.42, 95% CI 5.39; 11.45, p < 0.001). High HR at discharge in COVID-19 patients is not such a frequent consequence, but when it occurs it seems strongly related to a severe course of the disease.

In Silico Identification and Clinical Validation of a Novel Long Non-Coding RNA/mRNA/miRNA Molecular Network for Potential Biomarkers for Discriminating SARS CoV-2 Infection Severity.

(1) Background: The coronavirus (COVID-19) pandemic is still a major global health problem, despite the development of several vaccines and diagnostic assays. Moreover, the broad symptoms, from none to severe pneumonia, and the various responses to vaccines and the assays, make infection control challenging. Therefore, there is an urgent need to develop non-invasive biomarkers to quickly determine the infection severity. Circulating RNAs have been proven to be potential biomarkers for a variety of diseases, including infectious ones. This study aimed to develop a genetic network related to cytokines, with clinical validation for early infection severity prediction. (2) Methods: Extensive analyses of in silico data have established a novel IL11RA molecular network (IL11RNA mRNA, LncRNAs RP11-773H22.4 and hsa-miR-4257). We used different databases to confirm its validity. The differential expression within the retrieved network was clinically validated using quantitative RT-PCR, along with routine assessment diagnostic markers (CRP, LDH, D-dimmer, procalcitonin, Ferritin), in100 infected subjects (mild and severe cases) and 100 healthy volunteers. (3) Results: IL11RNA mRNA and LncRNA RP11-773H22.4, and the IL11RA protein, were significantly upregulated, and there was concomitant downregulation of hsa-miR-4257, in infected patients, compared to the healthy controls, in concordance with the infection severity. (4) Conclusion: The in-silico data and clinical validation led to the identification of a potential RNA/protein signature network for novel predictive biomarkers, which is in agreement with ferritin and procalcitonin for determination of COVID-19 severity.

Mental Health of Chinese People During the COVID-19 Pandemic: Associations With Infection Severity of Region of Residence and Filial Piety.

This study aims to investigate mental health among Chinese people living in areas with differing levels of infection severity during the COVID-19 outbreak. It also assesses the association between reciprocal and authoritarian filial piety and mental health in times of crises. A sample of 1,201 Chinese participants was surveyed between April and June 2020. Wuhan city (where 23.4% of participants resided), Hubei province outside Wuhan (13.4% of participants), and elsewhere in China (63.1% of participants) were categorized into high, moderate, and low infection severity areas, respectively. The Depression, Anxiety, and Stress Scale's severity cut-points were used to categorize participants. In the overall sample, 20.9, 34.2, and 29.0% of the participants showed elevated (mild to extremely severe) levels of stress, anxiety, and depression. Those in the highest infection severity group were significantly more likely to be categorized as having elevated levels of stress, anxiety, and depression. General linear modeling was performed on a composite mental distress variable (taking into account stress, anxiety, and depression scores). This model indicated that, even after adjusting for group differences in age, gender, education, and filial piety, the high infection severity group displayed more mental distress than the low infection severity groups. The model also found reciprocal filial piety to have a negative association with mental distress. Conversely, authoritarian filial piety was found to be unrelated to mental distress when controlling for the other variables in the model. No evidence was found for an interaction between either authoritarian or reciprocal filial piety and infection severity, which suggests that the negative association observed between reciprocal filial piety and mental distress was relatively consistent across the three infection severity groups. The findings suggest that future public health programs may integrate the promotion of filial piety as a strategy to help Chinese people maintain good mental health in the face of pandemic crises.

Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in COVID-19 and to analyse its underlying mechanism. METHODS: Chest high-resolution computer tomography (CT) images and laboratory examination data of 31 patients with COVID-19 were extracted, and the lesion areas in CT images were quantitatively segmented and calculated using a deep learning (DL) system. A cross-sectional study method was carried out to explore the differences among the proportions of lung lobe infection and to correlate the percentage of infection (POI) of the whole lung in all patients with clinical laboratory examination values. RESULTS: No significant difference in the proportion of infection was noted among various lung lobes (P > 0.05). The POI of total lung was negatively correlated with the peripheral blood lymphocyte percentage (L%) (r = - 0.633, P < 0.001) and lymphocyte (LY) count (r = - 0.555, P = 0.001) but positively correlated with the neutrophil percentage (N%) (r = 0.565, P = 0.001). Otherwise, the POI was not significantly correlated with the peripheral blood white blood cell (WBC) count, monocyte percentage (M%) or haemoglobin (HGB) content. In some patients, as the infection progressed, the L% and LY count decreased progressively accompanied by a continuous increase in the N%. CONCLUSIONS: Lung lesions in COVID-19 patients are significantly correlated with the peripheral blood lymphocyte and neutrophil levels, both of which could serve as prognostic indicators that provide warning implications, and contribute to clinical interventions in patients.

SARS-CoV-2 Infection Severity Is Linked to Superior Humoral Immunity against the Spike.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a global pandemic. The antigen specificity of the antibody response mounted against this novel virus is not understood in detail. Here, we report that subjects with a more severe SARS-CoV-2 infection exhibit a larger antibody response against the spike and nucleocapsid protein and epitope spreading to subdominant viral antigens, such as open reading frame 8 and nonstructural proteins. Subjects with a greater antibody response mounted a larger memory B cell response against the spike, but not the nucleocapsid protein. Additionally, we revealed that antibodies against the spike are still capable of binding the D614G spike mutant and cross-react with the SARS-CoV-1 receptor binding domain. Together, this study reveals that subjects with a more severe SARS-CoV-2 infection exhibit a greater overall antibody response to the spike and nucleocapsid protein and a larger memory B cell response against the spike.IMPORTANCE With the ongoing pandemic, it is critical to understand how natural immunity against SARS-CoV-2 and COVID-19 develops. We have identified that subjects with more severe COVID-19 disease mount a more robust and neutralizing antibody response against SARS-CoV-2 spike protein. Subjects who mounted a larger response against the spike also mounted antibody responses against other viral antigens, including the nucleocapsid protein and ORF8. Additionally, this study reveals that subjects with more severe disease mount a larger memory B cell response against the spike. These data suggest that subjects with more severe COVID-19 disease are likely better protected from reinfection with SARS-CoV-2.

Antibody Profiles According to Mild or Severe SARS-CoV-2 Infection, Atlanta, Georgia, USA, 2020.

Among patients with coronavirus disease (COVID-19), IgM levels increased early after symptom onset for those with mild and severe disease, but IgG levels increased early only in those with severe disease. A similar pattern was observed in a separate serosurveillance cohort. Mild COVID-19 should be investigated separately from severe COVID-19.