Identifying Severity of COVID-19 Medical Images by Categorizing Using HSDC Model

Since COVID-19 infections are increasing all over the world,there is a need for developing solutions for its early and accurate diagnosis is a must.Detectionmethods for COVID-19 include screeningmethods like Chest X-rays and Computed Tomography(CT)scans.More work must be done on preprocessing the datasets,such as eliminating the diaphragm portions,enhancing the image intensity,and minimizing noise.In addition to the detection of COVID-19,the severity of the infection needs to be estimated.The HSDC model is proposed to solve these problems,which will detect and classify the severity of COVID-19 from X-ray and CT-scan images.For CT-scan images,the histogram threshold of the input image is adaptively determined using the ICH Swarm Optimization Segmentation(ICHSeg)algorithm.Based on the Statistical and Shape-based feature vectors(FVs),the extracted regions are classified using a Hybrid model for CT images(HSDCCT)algorithm.When the infections are detected,it’s classified as Normal,Moderate,and Severe.A fused FHI is formed for X-ray images by extracting the features of Histogram-oriented gradient(HOG)and Image profile(IP).The FHI features of X-ray images are classified using Hybrid Support Vector Machine(SVM)and Deep Convolutional Neural Network(DCNN)HSDCX algorithm into COVID-19 or else Pneumonia,or Normal.Experimental results have shown that the accuracy of the HSDC model attains the highest of 94.6 for CT-scan images and 95.6 for X-ray images when compared to SVM and DCNN.This study thus significantly helps medical professionals and doctors diagnose COVID-19 infections quickly,which is the most needed in current years.

Fuzzy Based Decision Making Approach for Evaluating the Severity of COVID-19 Pandemic in Cities of Kingdom of Saudi Arabia

The World Health Organization declared COVID-19 a pandemic on March 11,2020 stating that it is a worldwide danger and requires imminent preventive strategies to minimise the loss of lives.COVID-19 has now affected millions across 211 countries in the world and the numbers continue to rise.The information discharged by the WHO till June 15,2020 reports 8,063,990 cases of COVID-19.As the world thinks about the lethal malady for which there is yet no immunization or a predefined course of drug,the nations are relentlessly working at the most ideal preventive systems to contain the infection.The Kingdom of Saudi Arabia(KSA)is additionally combating with the COVID-19 danger as the cases announced till June 15,2020 reached the count of 132,048 with 1,011 deaths.According to the report released by the KSA on June 14,2020,more than 4,000 cases of COVID-19 pandemic had been registered in the country.Tending to the impending requirement for successful preventive instruments to stem the fatalities caused by the disease,our examination expects to assess the severity of COVID-19 pandemic in cities of KSA.In addition,computational model for evaluating the severity of COVID-19 with the perspective of social influence factor is necessary for controlling the disease.Furthermore,a quantitative evaluation of severity associated with specific regions and cities of KSA would be a more effective reference for the healthcare sector in Saudi Arabia.Further,this paper has taken the Fuzzy Analytic Hierarchy Process(AHP)technique for quantitatively assessing the severity of COVID-19 pandemic in cities of KSA.The discoveries and the proposed structure would be a practical,expeditious and exceptionally precise evaluation system for assessing the severity of the pandemic in the cities of KSA.Hence these urban zones clearly emerge as the COVID-19 hotspots.The cities require suggestive measures of health organizations that must be introduced on a war footing basis to counter the pandemic.The analysis tabulated in our study will assist in mapping the rules and building a systematic structure that is immediate need in the cities with high severity levels due to the pandemic.

Artificial intelligence computed tomography helps evaluate the severity of COVID-19 patients:A retrospective study

BACKGROUND:Computed tomography(CT)is a noninvasive imaging approach to assist the early diagnosis of pneumonia.However,coronavirus disease 2019(COVID-19)shares similar imaging features with other types of pneumonia,which makes differential diagnosis problematic.Artificial intelligence(AI)has been proven successful in the medical imaging field,which has helped disease identification.However,whether AI can be used to identify the severity of COVID-19 is still underdetermined.METHODS:Data were extracted from 140 patients with confirmed COVID-19.The severity of COVID-19 patients(severe vs.non-severe)was defined at admission,according to American Thoracic Society(ATS)guidelines for community-acquired pneumonia(CAP).The AI-CT rating system constructed by Hangzhou YITU Healthcare Technology Co.,Ltd.was used as the analysis tool to analyze chest CT images.RESULTS:A total of 117 diagnosed cases were enrolled,with 40 severe cases and 77 non-severe cases.Severe patients had more dyspnea symptoms on admission(12 vs.3),higher acute physiology and chronic health evaluation(APACHE)II(9 vs.4)and sequential organ failure assessment(SOFA)(3 vs.1)scores,as well as higher CT semiquantitative rating scores(4 vs.1)and AI-CT rating scores than non-severe patients(P<0.001).The AI-CT score was more predictive of the severity of COVID-19(AUC=0.929),and ground-glass opacity(GGO)was more predictive of further intubation and mechanical ventilation(AUC=0.836).Furthermore,the CT semiquantitative score was linearly associated with the AI-CT rating system(Adj R2=75.5%,P<0.001).CONCLUSIONS:AI technology could be used to evaluate disease severity in COVID-19 patients.Although it could not be considered an independent factor,there was no doubt that GGOs displayed more predictive value for further mechanical ventilation.

Approach for Training Quantum Neural Network to Predict Severity of COVID-19 in Patients

Currently,COVID-19 is spreading all over the world and profoundly impacting people’s lives and economic activities.In this paper,a novel approach called the COVID-19 Quantum Neural Network(CQNN)for predicting the severity of COVID-19 in patients is proposed.It consists of two phases:In the first,the most distinct subset of features in a dataset is identified using a Quick Reduct Feature Selection(QRFS)method to improve its classification performance;and,in the second,machine learning is used to train the quantum neural network to classify the risk.It is found that patients’serial blood counts(their numbers of lymphocytes from days 1 to 15 after admission to hospital)are associated with relapse rates and evaluations of COVID-19 infections.Accordingly,the severity of COVID-19 is classified in two categories,serious and non-serious.The experimental results indicate that the proposed CQNN’s prediction approach outperforms those of other classification algorithms and its high accuracy confirms its effectiveness.

Association between Blood Type and Severity of Covid-19 Infection among Patients in Kaski District, Nepal

Novel Coronavirus (SARS-CoV-2) first broke out in China and speeded globally. With the considerable number of Covid-19 infections and deaths, the situation has brought up major public health and governance concerns. This research study is conducted to understand if there is any association between blood group and Covid-19 disease severity. Study is conducted in Life care diagnostic and research center, New road Pokhara. A total of 1050 people who underwent RT-PCR test at Life Care Diagnostic and identified positive are used as the sample to conduct this research study. Our findings reveal that Covid-19 severity is uncommon in people with blood group O and Rh negative whereas those with blood group AB and B types are found to be severely affected. We also have an impression that individuals with rhesus negative (Rh-negative) blood groups have higher resistance for Covid-19 infection and severity.

A Nomogram for Predicting the Severity of COVID-19 Using Laboratory Examination and CT Findings

Background: The outbreak of COVID-19 has a significant impact on the health of people around the world. In the clinical condition of COVID-19, the condition of critical cases changes rapidly with a high mortality rate. Therefore, early prediction of disease severity and active intervention play an important role in the prognosis of severe patients. Methods: All the patients with COVID-19 in Taizhou city were retrospectively included and segregated into the non-severe and severe group according to the severity of the disease. The clinical manifestations, laboratory examination results, and imaging findings of the 2 groups were analyzed for comparing the differences between the 2 groups. Univariate and multivariate logistic regression were used for screening the factors that could predict the disease, and the nomogram was constructed. Results: A total of 143 laboratory-confirmed cases were included in the study, including 110 non-severe patients and 33 severe patients. The median age of patients was 47 years (range, 4 - 86 years). Fever (73.4%) and cough (63.6%) were the most common initial clinical symptoms. By using the method of multivariate logistic regression, the variables to construct nomogram include age (OR: 1.052, 95% CI: 1.020 - 1.086, P = 0.001), body temperature (OR: 2.252, 95% CI: 1.139 - 4.450, P = 0.020), lymphocyte count (OR: 1.128, 95% CI: 1.000 - 1.272, P = 0.049), ADA (OR: 1.163, 95% CI: 1.023 - 1.323, P = 0.021), PaO2 (OR: 0.972, 95% CI: 0.953 - 0.992, P = 0.007), IL-10 (OR: 1.184, 95% CI: 1.037 - 1.351, P = 0.012), and bronchiectasis (OR: 3.818, 95% CI: 1.694 - 8.605, P = 0.001). The AUC of the established nomogram was 0.877. Conclusions: This study analyzed the cases of patients with COVID-19 in Taizhou city and constructed a model to predict the illness severity. When patients showed the features including older age, high body temperature, low lymphocyte count, low ADA value, low PaO2, high IL-10, and bronchiectasis sign in CT predicts a greater likelihood of severe COVID-19.

Lymphocyte count predicts the severity of COVID-19:Evidence from a meta-analysis

BACKGROUND In December 2019,coronavirus disease 2019(COVID-19)was reported firstly in Wuhan,China.COVID-19 is currently a global pandemic.AIM To assess the suitability of lymphocyte count as a biomarker of COVID-19 severity.METHODS Five literature databases(PubMed/MEDLINE,Web of Science,Google Scholar,Embase,and Scopus)were searched to identify eligible articles.A meta-analysis was performed to calculate the standard mean difference(SMD)and 95%confidence interval(CI)of lymphocyte counts in coronaviral pneumonia cases.RESULTS Eight studies,including 1057 patients,were integrated in the meta-analysis.Lymphocyte counts were associated with severe coronavirus(CoV)infection(SMD=1.35,95%CI:1.97 to 0.37,P<0.001,I2=92.6%).In the subgroup analysis stratified by prognosis,lymphocytes were associated with CoV infection mortality(n=2,SMD=0.42,95%CI:0.66 to 0.19,P<0.001,I2=0.0%),severity(n=2,SMD=0.93,95%CI:1.20 to 0.67,P<0.001,I2=0.0%),and diagnostic rate(n=4,SMD=2.32,95%CI:3.60 to 1.04,P<0.001,I2=91.2%).CONCLUSION Lymphocyte count may represent a simple,rapid,and commonly available laboratory index with which to diagnosis infection and predict the severity of CoV infections,including COVID-19.

Risk Factors Contributing in Increased Susceptibility and Severity of COVID-19 Infection during Pregnancy

The corona virus disease 2019 (COVID-19) pandemic has spread globally and pregnant women are considerably prone to COVID-19 infection with increased maternal and perinatal complications. Aim: This study aims to explore the risk factors that contribute to susceptibility and severity of COVID-19 infection among pregnant women. Method: A literature search of articles relating to COVID-19 infection during pregnancy, was conducted, using PubMed, Scopus and Google scholar engine. Result: A total of 168 articles were initially identified. Eighty four papers were excluded for failing to address the aim of the study. After screening titles and abstracts, eighty four full-text articles were retrieved for eligibility analysis. Nineteen studies addressed the susceptibility related to pregnancy, twenty-two studies evaluated the associated comorbidities, nineteen focused on immune system, thirty-six articles concentrated on the risk of coagulopathy and eleven addressed more than one risk factor. Conclusion: Pregnancy, associated comorbidities, modulated immune response during pregnancy and risk of coagulopathy are considerable risk factors contributing to COVID-19 pathogenesis among pregnant women and may predict the outcome.

Retrospective analysis of aspirin's role in the severity of COVID-19 pneumonia

BACKGROUND Since December 2019,an outbreak of pneumonia caused by severe acute respiratory syndrome-coronavirus-2(SARS-CoV-2)has led to a life-threatening ongoing pandemic worldwide.A retrospective study by Chow et al showed aspirin use was associated with decreased intensive care unit(ICU)admissions in hospitalized coronavirus disease 2019(COVID-19)patients.Recently,the RECOVERY TRIAL showed no associated reductions in the 28-d mortality or the progression to mechanical ventilation of such patients.With these conflicting findings,our study was aimed at evaluating the impact of daily aspirin intake on the outcome of COVID-19 patients.AIM To study was aimed at evaluating the impact of daily aspirin intake on the outcome of COVID-19 patients.METHODS This retrospective cohort study was conducted on 125 COVID-19 positive patients.Subgroup analysis to evaluate the association of demographics and comorbidities was undertaken.The impact of chronic aspirin use was assessed on the survival outcomes,need for mechanical ventilation,and progression to ICU.Variables were evaluated using the chi-square test and multinomial logistic regression analysis.RESULTS 125 patients were studied,30.40%were on daily aspirin,and 69.60%were not.Cross-tabulation of the clinical parameters showed that hypertension(P=0.004),hyperlipidemia(0.016),and diabetes mellitus(P=0.022)were significantly associated with aspirin intake.Regression analysis for progression to the ICU,need for mechanical ventilation and survival outcomes against daily aspirin intake showed no statistical significance.CONCLUSION Our study suggests that daily aspirin intake has no protective impact on COVID-19 illnessassociated survival outcomes,mechanical ventilation,or progression to ICU level of care.

COVID-19 Vaccination Status and Severe Outcomes among Patients Hospitalized for COVID-19 in West Africa, Togo, 2021

Objectives: More than a year after its introduction, COVID-19 vaccination coverage was low in the Togolese population and little data were available on its benefits for hospitalized patients. This study aimed to describe the impact of COVID-19 vaccination on the prognosis of hospitalized patients. Methods: This was a retrospective cohort study of patients admitted to the Centre Hospitalier Régional Lomé Commune (Togo) between June 1, 2021 and May 31, 2022. Primary outcomes (admission to the intensive care unit and death) were presented with frequency and proportion. Mortality rates were presented by sociodemographic and clinical characteristics and compared by appropriate statistical tests. Factors associated with inpatient death were described by performing a Cox proportional hazard regression. Results: A total of 604 patients were hospitalized (50.0% women). The mean age was 54.03 ±17.1 years. Only 55 patients were fully vaccinated (9.1%). ICU admission was significantly more frequent in unvaccinated patients than in vaccinated ones (63.0% vs. 38.2%;p Conclusion: COVID-19 vaccination had a significant benefit for patients with COVID-19 infection in terms of reducing the risk of death. Based on real-world data from sub-Saharan Africa, this information can help optimize the benefit of COVID-19 vaccination by raising community awareness and increasing vaccine coverage while reducing hesitancy.

Effect of Prone Position in Severe Covid-19 Patients in a Referral Center: A Cohort Retrospective Study

Introduction: Covid-19 is defined as a pandemic disease by WHO, in November 2023, WHO recorded 772.1 million confirmed cases and 6.9 million deaths, including 68,382 confirmed cases and 1426 deaths in Madagascar. The management of severe cases of Covid-19 remains a challenge for the healthcare system in a resource-limited country, due to the consumption of human resources, the shortage of medical resources and the lack of capacity in resource-limited countries. Prone position (PP) improves survival in acute respiratory distress, and numerous studies have shown that during Covid-19, it reduces mortality rates at 28 and 90 days, and increases the number of days without mechanical ventilation. However, data on the beneficial effects of PP remain limited in low-income countries. In this context, our study aims to evaluate the benefits of the prone position for severe Covid-19 patients in a referral center in Madagascar. Method: This is a retrospective cohort study, during the 2nd and 3rd waves of COVID-19, over a period of 11 months in two wards managing COVID-19 cases. We included all patients aged 15 and over with severe forms of COVID-19 who required 6 l/min of oxygen therapy. Results: We enrolled 123 patients, including 40 in the prone position and 83 in the supine position, with a mean age of 60.5 ± 12 years. The prone position (DV) reduced the risk of probable complications of COVID-19 with a strong association in terms of use of respiratory assistance (OR = 0.15;95% CI = 0.05 - 0.47), respiratory deterioration (OR = 0.22;95% CI = 0.09 - 0.58), shock (OR = 0.30;95% CI = 0.11 - 0.79) and hemodynamic instability (OR = 0.33;95% CI = 0.12 - 0.95). Univariate analysis of the effect of prone position on SpO2 showed improvement with significant associations with SpO2 at Day 1- Day 3, D4 - D7, D8 - D14, and persisting even at D15 - D21, D3 and D2 before discharge, and at discharge. In the overall population, the mean length of hospital stay was 22.8 ± 22.1 days, with extremes of 1 and 67 days. Univariate analysis of the effect of the prone position showed a reduction in length of hospital stay with a strong association (p = 0.001) and a mean difference of 14 days. The prone position reduced mortality with a significant association (OR = 0.44;95% CI = 0.20 - 0.98). Conclusion: Awake prone position prevents complications of COVID, improves SPO2 even up to hospital discharge and reduces hospital stay. This practice is simple, less costly and suitable in low income countries.

Comparison of the Clinical Profile and Severity Factors of COVID-19 during the First 4 Waves in a Paediatric Population of Yaounde

Introduction: COVID-19 is an infectious disease that has been causing a global pandemic since 2019. Although clinical forms are generally less severe in children than in adults, children nevertheless present polymorphous clinical forms and severe cases that can lead to death. Objective: To describe the clinical presentations found in the different waves of COVID-19, and to highlight the different factors of severity. Materials and Methods: We conducted a cross-sectional study with retrospective and prospective data collection which lasted 7 months (from November 2021 to June 2022) and covered a study period from 6 March 2020 to 22 June 2022, i.e. 27 months. All patients aged 0 to 18 years, suspected of having COVID-19, confirmed by real-time RT-PCR or an antigenic Rapid Diagnostic Test or antibody were included. These patients were to be managed in the Mother and Child Centre of the Chantal Biya Foundation, as well as in the Specialised Centre for the Management of COVID patients, annex number II of the Yaoundé Central Hospital. The results were analysed using IBM SPSS.23 software. Results: We included 163 patients in our study. No paediatric patients were registered during the 3rd wave. The mean age of the patients in the study population was 13 ± 5 years with extremes from 15 days to 18 years. We had a female predominance with a sex ratio of 0.83. The most common comorbidity was asthma. The first wave presented mainly with respiratory symptoms such as dry cough and signs of respiratory distress. The second wave presented mainly with digestive symptoms such as diarrhoea, abdominal pain and vomiting. The fourth wave presented with ENT signs such as sore throat, and rhinorrhea. Factors associated with severity were mainly age less than five years (OR = 17.69), vomiting (OR = 6.50), presence of comorbidities (OR = 3.39), and alteration of vital parameters such as bradypnoea (OR = 19.68), bradycardia (OR = 6.34), tachycardia (OR = 3.73), oxygen saturation Conclusion: Clinical presentations varied between waves and the main risk factor was age under 5 years. The fourth wave was less severe than the second wave, which in turn was less severe than the first. (4th nd st) which allows us to humbly recommend more screening for patients under 18 years of age with respiratory, ENT and digestive signs and special attention for those under 5 years of age.

Investigating the Relationship between TyG, TyG-BMI Index and Laboratory Indicators and COVID-19 Severity

Objective: The objective of this study was to investigate the relationship between the triglyceride-glucose (TyG) index, triglyceride-glucose-BMI (TyG-BMI) index, laboratory indices, and disease severity in patients with COVID-19. Methods: A retrospective analysis of COVID-19 patients treated at a tertiary hospital in Mianyang City, Sichuan Province, China, from 1 May to 31 May 2023 was performed. The patients were divided into two groups: 66 cases in the moderate group and 61 cases in the severe group. Additionally, 69 uninfected individuals from the medical examination center during the same period were selected as the control group. Spearman rank correlation was used to determine the correlation between the indices and COVID-19 severity. Multiple logistic regression analysis was performed to identify the factors affecting COVID-19 severity. ROC curves were constructed to assess the predictive value of the TyG and TyG-BMI indices for severe COVID-19. Results: There were significant differences in smoking and diabetes between the three groups (P Conclusion: Smoking, AST, ALB, TyG index, and TyG-BMI index are valuable in assessing the severity of COVID-19, with the TyG-BMI index having a higher predictive value than the TyG index.

SARS-CoV-2 induced liver injury:Incidence,risk factors,impact on COVID-19 severity and prognosis in different population groups

Liver is unlikely the key organ driving mortality in coronavirus disease 2019(COVID-19)however,liver function tests(LFTs)abnormalities are widely observed mostly in moderate and severe cases.According to this review,the overall prevalence of abnormal LFTs in COVID-19 patients ranges from 2.5%to 96.8%worldwide.The geographical variability in the prevalence of underlying diseases is the determinant for the observed discrepancies between East and West.Multifactorial mechanisms are implicated in COVID-19-induced liver injury.Among them,hypercytokinemia with“bystander hepatitis”,cytokine storm syndrome with subsequent oxidative stress and endotheliopathy,hypercoagulable state and immuno-thromboinflammation are the most determinant mechanisms leading to tissue injury.Liver hypoxia may also contribute under specific conditions,while direct hepatocyte injury is an emerging mechanism.Except for initially observed severe acute respiratory distress syndrome corona virus-2(SARS-CoV-2)tropism for cholangiocytes,more recent cumulative data show SARS-CoV-2 virions within hepatocytes and sinusoidal endothelial cells using electron microscopy(EM).The best evidence for hepatocellular invasion by the virus is the identification of replicating SARS-CoV-2 RNA,S protein RNA and viral nucleocapsid protein within hepatocytes using in-situ hybridization and immunostaining with observed intrahepatic presence of SARS-CoV-2 by EM and by in-situ hybridization.New data mostly derived from imaging findings indicate possible long-term sequelae for the liver months after recovery,suggesting a post-COVID-19 persistent live injury.

Cardiovascular sequelae in post-COVID-19 patients with moderate to severe CT severity score: A follow-up study

Objective:To study cardiovascular sequelae of post-COVID-19 patients with moderate to severe computed tomography(CT)severity score.Methods:A prospective,non-randomized,observational study was conducted on 100 post-COVID-19 patients with moderate to severe CT severity scores from January 2021 to December 2021.Fifty-nine were male[mean age(54.1±12.2)years]and 41 were female[mean age(46.9±15.1)years].Patients with previous cardiovascular disease,previous chronic lung disease,and pre-existing primary or secondary pulmonary hypertension were excluded.Patients were examined,and serial electrocardiogram and 2D echocardiography were performed to detect any cardiovascular abnormality.Results:Post-COVID-19 patients had persistent symptoms,the most common being fatigue(59%).Most of these symptoms were relieved on follow-up.A rise in systolic,diastolic blood pressure,and pulse rate was observed.The electrocardiographic evaluation revealed ST-T segment changes,sinus tachycardia,ventricular hypertrophy,and arrhythmias among a considerable number of patients.On echocardiography,left ventricular diastolic dysfunction was most common(43%).Pulmonary hypertension,as evidenced by elevated pulmonary artery systolic pressure,was seen in 15%of patients.Conclusions:The present findings reveal an increased incidence of cardiovascular complications after recovery from COVID-19 infection in those without pre-existing cardiovascular or chronic lung disease.

Risk and predictors of severity and mortality in patients with type 2 diabetes and COVID-19 in Dubai

BACKGROUND Globally,patients with diabetes suffer from increased disease severity and mortality due to coronavirus disease 2019(COVID-19).Old age,high body mass index(BMI),comorbidities,and complications of diabetes are recognized as major risk factors for infection severity and mortality.AIM To investigate the risk and predictors of higher severity and mortality among inhospital patients with COVID-19 and type 2 diabetes(T2D)during the first wave of the pandemic in Dubai(March–September 2020).METHODS In this cross-sectional nested case-control study,a total of 1083 patients with COVID-19 were recruited.This study included 890 men and 193 women.Of these,427 had T2D and 656 were non-diabetic.The clinical,radiographic,and laboratory data of the patients with and without T2D were compared.Independent predictors of mortality in COVID-19 non-survivors were identified in patients with and without T2D.RESULTS T2D patients with COVID-19 were older and had higher BMI than those without T2D.They had higher rates of comorbidities such as hypertension,ischemic heart disease,heart failure,and more life-threatening complications.All laboratory parameters of disease severity were significantly higher than in those without T2D.Therefore,these patients had a longer hospital stay and a significantly higher mortality rate.They died from COVID-19 at a rate three times higher than patients without.Most laboratory and radiographic severity indices in non-survivors were high in patients with and without T2D.In the univariate analysis of the predictors of mortality among all COVID-19 non-survivors,significant associations were identified with old age,increased white blood cell count,lymphopenia,and elevated serum troponin levels.In multivariate analysis,only lymphopenia was identified as an independent predictor of mortality among T2D non-survivors.CONCLUSION Patients with COVID-19 and T2D were older with higher BMI,more comorbidities,higher disease severity indices,more severe proinflammatory state with cardiac involvement,and died from COVID-19 at three times the rate of patients without T2D.The identified mortality predictors will help healthcare workers prioritize the management of patients with COVID-19.

Effect of vaccination status on CORADS and computed tomography severity score in hospitalized COVID-19 patients:A retrospective study

BACKGROUND The coronavirus disease 2019(COVID-19)pandemic is continuing.The disease most commonly affects the lungs.Since the beginning of the pandemic thorax computed tomography(CT)has been an indispensable imaging method for diagnosis and follow-up.The disease is tried to be controlled with vaccines.Vaccination reduces the possibility of a severe course of the disease.AIM The aim of this study is to investigate whether the vaccination status of patients hospitalized due to COVID-19 has an effect on the CT severity score(CT-SS)and CORADS score obtained during hospitalization.METHODS The files of patients hospitalized between April 1,2021 and April 1,2022 due to COVID-19 were retrospectively reviewed.A total of 224 patients who were older than 18 years of age,whose vaccination status was accessible,whose severe acute respiratory syndrome coronavirus 2 polymerase chain reaction result was positive,and who had a Thorax CT scan during hospitalization were included in the study.RESULTS Among the patients included in the study,52.2%were female and the mean age was 61.85 years.The patients applied to the hospital on the average 7th day of their complaints.While 63 patients were unvaccinated(Group 1),20 were vaccinated with a single dose of CoronaVac(Group 2),24 with a single dose of BioNTech(Group 3),38 with 2 doses of CoronaVac(Group 4),40 with 2 doses of BioNTech(Group 5),and 39 with 3 doses of vaccine(2 doses of CoronaVac followed by a single dose of BioNTech,Group 6).CT-SS ranged from 5 to 23,with a mean of 12.17.RESULTS CT-SS mean of the groups were determined as 14.17,13.35,11.58,10.87,11.28,10.85,respectively.Accordingly,as a result of the comparisons between the groups,the CT-SS levels of the unvaccinated patients found to be significantly higher than the other groups.As the vaccination rates increased,the rate of typical COVID-19 findings on CT was found to be significantly lower.CONCLUSION Increased vaccination rates in COVID-19 patients reduce the probability of typical COVID-19 symptoms in the lungs.It also reduces the risk of severe disease and decreases CT Severity Scores.This may lead to a loss of importance of Thorax CT in the diagnosis of COVID-19 pneumonia as the end of the pandemic approaches.

Clinical Evaluation of the Safety and Efficacy of the Phytomedicine APIVIRINE Based on Aqueous Extracts of Dichrostachys glomerata (Forssk.). Chiov. (D. cinerea) in COVID-19 Patients without Signs of Severity

Background: Since the appearance of the COVID-19 pandemic, several drugs have also been proposed for the treatment of the COVID-19, but the therapeutic effectiveness of those drugs is not satisfactory. This situation has led to the search for therapeutic solutions based on recipes from traditional medicine. Aims: This study aimed to evaluate the clinical safety, efficacy and tolerability of the phytomedicine APIVIRINE in patients with non-severe COVID-19. Methods: Patients were included following defined criteria and followed on an outpatient basis until recovery in accordance with national guidelines for the management of single cases of COVID-19 in Burkina Faso. Vital signs, anthropometric parameters as well as electrocardiographic, hematological and biochemical examinations were measured on D4, D7, D14 and D21. Adverse events were recorded during maintenance. Results: The present study included 45 patients. The clinical signs present at inclusion were mostly cough (44.44%), asthenia (42.22%), headache (40%), and anosmia (35.55%). Dyspnoea and chest pain were less represented in 05 (11.11%) and 06 (13.33%) patients. Cough, dyspnoea, chest pain, fever, sore throat, headache, and nasal obstruction present at inclusion disappeared before Day 4 of treatment. Anosmia and asthenia disappeared before Day 7. At the inclusion visit (Day 1), CRP, WBC, and blood glucose were abnormal in 15 (33.33%), 13 (28.89%), and 11 (24.44%) patients respectively. In addition, 3 (6.66%) patients had elevated creatinine levels. Transaminases Alanine aminotransferase (ALAT) were elevated in 05 (11.11%) patients while Aspartate aminotransferase (ASAT) was elevated in 04 (8.89%) patients. After 4 days of treatment, the cure rate was 33.33% of patients and 48.89% after 7 days. The cumulative cure rate was 86.67% after 14 days of treatment. Conclusion: No serious side effects or allergic reactions were observed during treatment. No clinical complications were observed and all symptoms present resolved on the 7th day of treatment.

Risk Factors for Severity and Mortality of Patients Hospitalized for COVID-19 during the 3rd Wave of the Epidemic-Sao Tome and Principe

Rationale: In the literature, some risk factors for severity and mortality from COVID-19 have been indicated. However, these factors can change, depending on the characteristics of the population and health services. In this sense, longitudinal studies can be useful for understanding local realities and subsidizing health actions based on these realities. Objective: To analyze the risk factors for severity and death in hospitalized patients with COVID-19. Methods: A retrospective cohort of patients with COVID-19 hospitalized from August 1 to October 16, 2021 (3rd wave of the pandemic), notified by the Department of Epidemiological Surveillance of Sao Tome and Principe. We employed measures of strength of associations for the analysis of exposure risk factors. Results: We analyzed 110 hospitalized patients (31.8% severe-critical and 68.2% non-severe). The risk factors for severe forms of COVID-19 were: being aged ≥60 years (RR = 3.3), being male (RR = 2), having comorbidities (RR = 2) and the risk increases to 10-fold for multicomorbidities, with emphasis on obesity, neoplasia, skin-muscle-surgical infection, dementia and to some degree CVD. 62.9% of patients with severe forms of the disease were not vaccinated. Risk factors for death among hospitalized and severe/critical cases, respectively, were having comorbidities (RR = 8 and 2.4) multicomorbidities (RR = 10 and 2.8 for those with 2 comorbidities and RR = 33.3 and 4 for those with 3 or 4 comorbidities), especially diabetes, dementia, neoplasia, cutaneous-muscular infection, and obesity. Although CVD was not associated with risk factors for death, these were the most frequently found among the severely hospitalized and deaths. In addition, important risk factors associated with death were not using corticoids (RR = 3.3, 230-fold risk) and not using anticoagulants-heparin (RR = 1.3, 30% risk) more compared to the severe cases that did use them. Most of the patients who died (63.2%) were not vaccinated. Moreover, having only 1 dose of the vaccine was a risk factor 1.9 times more for death among all hospitalized patients, but in the severe cases, there was no association between the variable vaccination and death. Among those hospitalized with 2 doses, it was a 0.5-fold protective factor among those hospitalized. The Delta variant of Sarscov-2 was the one found among severe cases and deaths investigated by genetic sequencing, with more exuberant clinical features compared to the other 2 previous vaccinations. Conclusion: Being elderly, male and presenting comorbidities, mainly multicomorbidities were the main characteristics associated with severity of COVID-19. On the other hand, comorbidities, and even worse, multicomorbidities, hospitalization for respiratory failure, lowered level of consciousness, no use of corticoid and no use of anticoagulation in critically ill patients, and not having at least 2 doses of vaccine for covid-19, were characteristics associated with death by COVID-19. These results will help inform healthcare providers so that the best interventions can be implemented to improve outcomes for patients with COVID-19. Public health interventions must be carefully tailored and implemented in these susceptible groups to reduce the risk of mortality in patients with COVID-19 and then the risk of major complications. Intensive and regular follow-up is needed to detect early occurrences of clinical conditions.

基于CiteSpace及VOSviewer的COVID-19相关心律失常的文献计量学分析

目的:分析新型冠状病毒感染(COVID-19)相关心律失常的文献,探索该领域的研究现状、热点并预测未来的趋势,为后来的研究者提供借鉴。方法:选择Web of Science的核心合集数据库,每项研究都进行了文献计量和视觉分析,使用CiteSpace和VOSviewer软件生成知识图谱。结果:共鉴定出768篇文章,发文涉及美国、意大利和中国为首的319个国家/地区和4 366个机构,领先的研究机构是梅奥诊所和哈佛医学院。New England Journal of Medicine是该领域最常被引用的期刊。在6 687位作者中,Arbelo Elena撰写的研究最多,Guo T被共同引用的次数最多,心房纤颤是最常见的关键词。结论:随着COVID-19的暴发,对COVID-19所致新发/进行性心律失常事件的研究蓬勃发展,未来的研究者可能会对COVID-19感染后新发或遗留的快速性心律失常/缓慢性心律失常的发生机制进行进一步的探索。