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Introduction: Coronavirus disease-19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still posing detrimental effects on people. An association between contracting COVID-19 and the ABO blood group type has been determined. However, factors that determine the severity of COVID-19 are not yet fully understood. Thus, the current study aimed to investigate whether the ABO blood group type has a role in the severity of complications due to COVID-19. Materials and methods: Eighty-Six ICU-admitted COVID-19 patients and 80 matched -healthy controls were recruited in the study from Baish general hospital, Saudi Arabia. ABO blood grouping, complete blood count (CBC), CBC-derived inflammatory markers, coagulation profile, D-Dimer and anti-T antigen were reported. Results: Our data showed that patients with blood groups O and B are more protective against severe complications from COVID-19, as compared to patients with blood groups A and AB. This could be partially attributed to the presence of anti-T in blood group A individuals, compared to non-blood group A. Conclusion: The current study reports an association between the ABO blood group and the susceptibility to severe complications from COVID-19, with a possible role of anti-T in driving the mechanism of the thrombotic tendency, as it was also correlated with an elevation in D-dimer levels.
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INTRODUCTION: During the COVID-19 pandemic, the burden on the healthcare system makes it critical to examine readmission patterns. In this study, we evaluated the readmission rates and risk factors associated with COVID-19 from the large SCCM Discovery VIRUS: COVID-19 Registry. METHOD(S): This was a retrospective, cohort study including hospitalized adult patients from 181 hospitals in 24 countries within the VIRUS: COVID-19 Registry. Demographic, clinical, and outcome data were extracted and divided into two groups: Patients with readmission with COVID-19 in 30 days from discharge and those who were not. A univariate analysis is done using chi-square and t-test as appropriate. Multivariable logistic regression was used to measure risk factor associations with 30-day readmission. RESULT(S): Among 20,283 patients, 1,195 (5.9%) were readmitted within 30 days from discharge. The median (IQR) age of readmitted patients was 66 (55-78) years and 45.2% were female, 60.2% were white, and 78.9% non-Hispanic. Higher odds of readmission were observed in patients aged >60 vs 18-40 years (OR 2.76;95% CI, 2.23-3.41), moderate COVID-19 disease (WHO Ordinal scale 4-5) vs Severe COVID-19 (WHO Ordinal scale 6-9) (OR 1.23;95% CI, 1.10-1.39), no ICU admission at index hospitalization (OR 1.70;95% CI, 1.32-1.80), and Hospital length of stay <=14 vs >14 days (OR 1.53;95% CI, 1.32-1.80) vs those not readmitted (p= < 0.001). Comorbidities including coronary artery disease (OR 2.14;95% CI 1.84-2.48), hypertension (OR 1.58;95% CI 1.40-1.78), congestive Heart Failure (OR 2.54;95% CI 2.16-2.98), chronic pulmonary disease (OR 2.26;95% CI 1.94-2.63), diabetes (OR 1.32;95% CI 1.17-1.49) or chronic kidney disease (CKD) (OR 2.41;95% CI 1.2.09-2.78) were associated with higher odds of readmission. In multivariate logistic regression adjusted for age group, hospital length of stay <=14 days and, highest WHO COVID-19 ordinal scale and index ICU admission coronary artery disease, congestive heart failure, chronic pulmonary disease, chronic kidney disease, hospital length of stay <=14 days and age >60 years remained independent risk factors for readmission within 30 days. CONCLUSION(S): Among hospitalized patients with COVID-19, those readmitted had a higher burden of comorbidities compared to those non-readmitted.
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Recently Coronavirus Disease-2019 (COVID-19) pandemic has caused major problems throughout the world. Apart from all morbidity and deaths due to this virus many patients with other chronic illness have also suffered due to lack of follow-up. Many general and specialised hospitals were turned into COVID centres and partial or complete lockdown was enforced by Governments. Due to this, patient with Cerebral Palsy (CP) were not able to follow their scheduled physical appointments. Many CP patients who were taking calibrated medication for different complication and following individualised rehabilitation programs were in turmoil without guidance of specialist doctors. This has led to exponential rise in use of telemedicine appointments. Telemedicine has both advantages and disadvantages which are discussed in this review. This review also focuses on rehabilitation of cerebral palsy patients using telemedicine in this dire situation where it is difficult for most patients to visit hospitals for physical appointments. Copyright © 2022 Journal of Clinical and Diagnostic Research. All rights reserved.
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In this paper, we examined informatics challenges and opportunities related to emergency department visit data during public health emergencies. We investigated the impact of COVID-19 pandemic on the volume and acuity of adult patients visiting the emergency department (ED) of a medical center in Arizona during the pandemic compared to the pre-pandemic period. We performed a negative binomial regression analysis to understand how different public health-related mandates and statewide business opening/closing orders in Arizona affected the daily emergency department visits. The results of this study show that the average daily ED visits decreased by 20% during the COVID-19 pandemic in comparison with the same period in 2019. In addition, the business closure order had the most impact on emergency department visits in comparison to other public health mandates.
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AI has the immense caliber to perform efficiently according to the industry's needs. One of the reasons is AI's image processing technology. Since ophthalmology requires the processing of images of the eyes for different eye conditions, AI is playing a significant role in the field. It has allowed the growth of 'intelligent diagnosis' Through this study, a model will be proposed for the earliest detection of glaucoma using AI specifically Deep Learning (DL) and Virtual Reality (VR). This would help patients to begin treatment at the earliest stages to prevent complete loss of vision. The idea of designing this model as compared to more efficient yet complex techniques available in hospitals is because in the delay of glaucoma detection, precious time is lost and with it, irreparable damage is inflicted upon the eye. The diagnosis of glaucoma depends on the optic disc and surrounding retinal nerve fiber layer assessment performed by a trained professional. Therefore, the detection of glaucoma has always been limited in its economic value due to the precise skills required and its labor-intensive nature. Given the growing public health concern, especially after the COVID-19 pandemic, improvements towards the field of screening and diagnosis of glaucoma are endorsed. The proposed methodology would consist of a VR environment for obtaining information required like maximum peripheral distance combined with various inputs that would be taken for the DL model, an efficient and precise diagnosis would be expected which would highly cut the cost of performing expensive eyes tests. © 2021 IEEE.
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The present study is first of its kind as it attempts to ascertain publications output on coronavirus as reflected in Scopus database from the Chinese perspective. The most productive contributors, institutions, journals and core subjects in coronavirus publications are identified in this study. The highly cited articles on coronavirus are also identified. The VOS-viewer software is used to identify the collaborative network of authors, countries and occurrence of keywords. During 2011-2020 a total of 1331 publications were published in this field. The highest number 190 publications were published in 2018. The most prolific contributor was Jiang, S. who contributed 63 Publications followed by Du, L. with 51 publications. Chinese Academy of Agricultural Sciences, Beijing was found to be highly contributing institution with 144 publications followed by Chinese Academy of Sciences with 143 publications. The Journal of Virology was most productive journal with 84 publications followed by Plos One with 55 publications. The United States was leading collaborative country in coronavirus research with 271 publications. Out of total publications, 1319 were produced by multiple authors while only 12 by single authors. The word “non-human” was found to be the most frequently used keyword in publications with 910 occurrences. © 2020. All Rights Reserved.