Establishment of differential diagnostic model for COVID-19 and influenza A based on laboratory indicators and its clinical significance. TT -.

Objective:To explore the differences in laboratory indicators test results of coronavirus disease 2019 (COVID-19) and influenza A and to establish a differential diagnosis model for the two diseases, and to clarify the clinical significance of the model for distinguishing the two diseases. Methods :A total of 56 common COVID-19 patients and 54 influenza A patients were enrolled , and 24 common COVID-19 patients and 30 influenza A patients were used for model validation. The average values of the laboratory indicators of the patients 5 d after admission were calculated,and the elastic network model and the stepwise Logistic regression model were used to screen the indicators for identifying COVID-19 and influenza A. Elastic network models were used for the first round of selection,in which the optimal cutoff of lambda was chosen by performing 10-fold cross validations. With different random seeds,the elastic net models were fit for 200 times to select the high-frequency indexes ( frequency>90% ). A Logistic regression model with AIC as the selection criterions was used in the second round of screening uses;a nomogram was used to represent the final model;an independent data were used as an external validation set,and the area under the curve (AUC) of the validation set were calculate to evaluate the predictive the performance of the model. Results:After the first round of screening, 16 laboratory indicators were selected as the high-frequency indicators. After the second round of screening,albumin/ globulin (A/G),total bilirubin (TBIL) and erythrocyte volume (HCT) were identified as the final indicators. The model had good predictive performance , and the AUC of the verification set was 0. 844 (95% CI:0. 747-0. 941). Conclusion:A differential diagnosis model for COVID-19 and influenza A based on laboratory indicators is successfully established,and it will help clinical and timely diagnosis of both diseases.Copyright © 2022 Jilin University Press. All rights reserved.

Performance, Trust, or both? COVID-19 Diagnosis and Prognosis using Deep Ensemble Transfer Learning on X-ray Imagesg±

The COVID-19 pandemic still affects most parts of the world today. Despite a lot of research on diagnosis, prognosis, and treatment, a big challenge today is the limited number of expert radiologists who provide diagnosis and prognosis on X-Ray images. Thus, to make the diagnosis of COVID-19 accessible and quicker, several researchers have proposed deep-learning-based Artificial Intelligence (AI) models. While most of these proposed machine and deep learning models work in theory, they may not find acceptance among the medical community for clinical use due to weak statistical validation. For this article, radiologists' views were considered to understand the correlation between the theoretical findings and real-life observations. The article explores Convolutional Neural Network (CNN) classification models to build a four-class viz. "COVID-19", "Lung Opacity", "Pneumonia", and "Normal"classifiers, which also provide the uncertainty measure associated with each class. The authors also employ various pre-processing techniques to enhance the X-Ray images for specific features. To address the issues of over-fitting while training, as well as to address the class imbalance problem in our dataset, we use Monte Carlo dropout and Focal Loss respectively. Finally, we provide a comparative analysis of the following classification models - ResNet-18, VGG-19, ResNet-152, MobileNet-V2, Inception-V3, and EfficientNet-V2, where we match the state-of-the-art results on the Open Benchmark Chest X-ray datasets, with a sensitivity of 0.9954, specificity of 0.9886, the precision of 0.9880, F1-score of 0.9851, accuracy of 0.9816, and receiver operating characteristic (ROC) of the area under the curve (AUC) of 0.9781 (ROC-AUC score). © 2022 ACM.

Advantages of Total Bilirubin for Predicting Malignant Obstructive Jaundice, A Combination of the Pandemic Era and Limited Resources Settings

BACKGROUND: Hepatopancreatobiliary (HPB) cancer incidence and mortality are increasing worldwide. An initial diagnostic predictor is needed for recommending further diagnostic modalities, referral, and curative or palliative decisions. There were no studies conducted in area with limited accessibility setting of the COVID-19 pandemic, coupled with limited human resources and facilities. AIM: We aimed to investigate the advantages of total bilirubin for predicting malignant obstructive jaundice, a combination of the pandemic era and limited resources settings. METHOD(S): Data from all cholestasis jaundice patients at M. Djamil Hospital in Pandemic COVID-19 period from July 2020 to May 2022 were retrospectively collected. The data included demographics, bilirubin fraction results, and final diagnosis. Bivariate analysis for obtain demographic risk factor, and Receiver Operating Characteristics (ROC) analysis for getting bilirubin value. RESULT(S): Of a total 132 patients included, 35.6% were malignant obstructive jaundice, and Pancreatic adeno ca was the most malignant etiology (34.4%). Bivariate analysis showed a significant correlation between age and malignant etiology (p = 0,024). Direct and total Bilirubin reach the same level of Area Under Curve (AUC). Total bilirubin at the cutoff point level of 10.7 mg/dl had the most optimal results on all elements of ROC output, AUC 0.88, sensitivity 76.6%, specificity 90.1%, +LR 8.14, and-LR 0.26. CONCLUSION(S): The bilirubin fraction is a good initial indicator for differentiating benign and malignant etiology (AUC 0.8-0.9) in pandemic era and resource-limited areas to improve diagnostic effectiveness and reduce referral duration.Copyright © 2023 Avit Suchitra, M. Iqbal Rivai, Juni Mitra, Irwan Abdul Rachman, Rini Suswita, Rizqy Tansa.

Liver biomarkers for prognosis in COVID-19

The novel coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).Mortality attributable to COVID-19 remains considerably high, with case fatality rates as high as 8-11%. Early medical intervention in patients who are seriously and critically ill with COVID-19 reduces fatal outcomes. Thus, there is an urgent need to identify biomarkers that could help clinicians determine which patients with SARS-CoV-2 infection are at a higher risk of developing the most adverse outcomes, which include intensive care unit (ICU) admission, invasive ventilation, and death. In COVID-19 patients experiencing the most severe form of the disease, tests of liver function are frequently abnormal and liver enzymes are found to be elevated. For this reason, we examine the most promising liver biomarkers for COVID-19 prognosis in an effort to help clinicians predict the risk of ARDS, ICU admission, and death at hospital admission. In patients meeting hospitalization criteria for COVID-19, serum albumin < 36 g/L is an independent risk factor for ICU admission, with an AUC of 0.989, whereas lactate dehydrogenase (LDH) values > 365 U/L accurately predict death with an AUC of 0.943.The clinical scores COVID-GRAM and SOFA that include measures of liver function such as albumin, LDH, and total bilirubin are also good predictors of pneumonia development, ICU admission, and death, with AUC values ranging from 0.88 to 0.978.Thus, serum albumin and LDH, together with clinical risk scores such as COVID-GRAM and SOFA, are the most accurate biomarkers in the prognosis of COVID-19.Copyright © 2021 Sociedad Medica del Hospital General de Mexico. Published by Permanyer.

In silico screening of potential compounds from begonia genus as 3CL protease (3Cl pro) SARS-CoV-2 inhibitors

Background: The emergence of Coronavirus disease (COVID-19) has been declared a pandemic and made a medical emergency worldwide. Various attempts have been made, including optimizing effective treatments against the disease or developing a vaccine. Since the SARS-CoV-2 protease crystal structure has been discovered, searching for its inhibitors by in silico technique becomes possible. Objective(s): This study aims to virtually screen the potential of phytoconstituents from the Begonia genus as 3Cl pro-SARS-CoV- 2 inhibitors, based on its crucial role in viral replication, hence making these proteases "promising" for the anti-SARS-CoV-2 target. Method(s): In silico screening was carried out by molecular docking on the web-based program DockThor and validated by a retrospective method. Predictive binding affinity (Dock Score) was used for scoring the compounds. Further molecular dynamics on Desmond was performed to assess the complex stability. Result(s): Virtual screening protocol was valid with the area under curve value 0.913. Molecular docking revealed only beta-sitosterol-3-O-beta-D-glucopyranoside with a lower docking score of -9.712 kcal/mol than positive control of indinavir. The molecular dynamic study showed that the compound was stable for the first 30 ns simulations time with Root Mean Square Deviation <3 A, despite minor fluctuations observed at the end of simulation times. Root Mean Square Fluctuation of catalytic sites HIS41 and CYS145 was 0.756 A and 0.773 A, respectively. Conclusion(s): This result suggests that beta-sitosterol-3-O-beta-Dglucopyranoside might be a prospective metabolite compound that can be developed as anti-SARS-CoV-2.Copyright © 2023, Page Press Publications. All rights reserved.

Deep learning-based COVID-19 triage tool: An observational study on an X-ray dataset

Background: Easy availability, low cost, and low radiation exposure make chest radiography an ideal modality for coronavirus disease 2019 (COVID-19) detection. Objective(s): In this study, we propose the use of an artificial intelligence (AI) algorithm to automatically detect abnormalities associated with COVID-19 on chest radiographs. We aimed to evaluate the performance of the algorithm against the interpretation of radiologists to assess its utility as a COVID-19 triage tool. Material(s) and Method(s): The study was conducted in collaboration with Kaushalya Medical Trust Foundation Hospital, Thane, Maharashtra, between July and August 2020. We used a collection of public and private datasets to train our AI models. Specificity and sensitivity measures were used to assess the performance of the AI algorithm by comparing AI and radiology predictions using the result of the reverse transcriptase-polymerase chain reaction as reference. We also compared the existing open-source AI algorithms with our method using our private dataset to ascertain the reliability of our algorithm. Result(s): We evaluated 611 scans for semantic and non-semantic features. Our algorithm showed a sensitivity of 77.7% and a specificity of 75.4%. Our AI algorithm performed better than the radiologists who showed a sensitivity of 75.9% and specificity of 75.4%. The open-source model on the same dataset showed a large disparity in performance measures with a specificity of 46.5% and sensitivity of 91.8%, thus confirming the reliability of our approach. Conclusion(s): Our AI algorithm can aid radiologists in confirming the findings of COVID-19 pneumonia on chest radiography and identifying additional abnormalities and can be used as an assistive and complementary first-line COVID-19 triage tool.Copyright © Cancer Research, Statistics, and Treatment.

Recent Development of Climate Change Mitigation in the Aviation Sector: For Better Incentive Design Between Developed and Developing Countries

During the past several years, the circumstances surrounding aviation sector have changed considerably from the environmental aspects. International aviation sector is included in neither Kyoto Protocol (1997) nor Paris Agreement (2015), although domestic aviation is covered by both. In fact, the international aviation is left to the deliberation at ICAO, a UN specialized agency. In 2016, ICAO has set the first ever global market-based measure for an entire sector, the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) in order to achieve the global sector target of 2% annual fuel efficiency improvement and carbon-neutral growth from 2020 onward. Market-based mechanism is also written in Paris Agreement (Article 6) but member states continued to negotiate its details and they are not yet agreed upon as of August 2020. It might be said that the general perception of air travel has been significantly diversified from traditional safety and efficiency only, to include more and more environment and sustainability just as we can see in the terminology of "Fly Shame.” This could be because there have been steadily growing concerns about environmentally negative aspects of aviation congestion at many air travel hubs, social and community levels of adverse effects of over-tourism, and occurrence of more and more severe natural disasters from powerful typhoons or huge wildfires, which many suspect could be caused by climate change stemming from emission of GHGs including from autos or aircrafts. Then came the COVID-19, which could fundamentally change the way of traveling, working, and even communicating in the direction of touchless, remote, or virtual relationships. Its imminent effects are overwhelming worldwide, but the medium-or longer-term effects are yet to be seen. We have now common global target and the basket of measures to achieve it in international aviation sector at ICAO. In the domestic aviation sector, which is now covered in Paris Agreement, parties also agreed on the common global target and started constructing details of the measures to achieve the target, such as market-based mechanism. The effective financial and technical aids, for example, from developed countries to the developing ones, are ever more important to incentivize and execute the necessary efforts of both sides to actually meet the global target. We are going to shed lights on the incentive design problem between developing countries and developed ones with the framework of the game theoretic analysis under asymmetric information structure focusing on the so-called double moral hazard situation of the two sides. The main results show that it is extremely difficult for both sides to achieve common optimal incentive rules about aid payments under the information asymmetry. The measures to drastically mitigate the cost of efforts, to fundamentally reduce risk averse, and to equalize damage effects of temperature anomaly between the two sides through scientific researches and long-term education on the matter are the key for such optimal incentive design. © Springer Nature Switzerland AG 2022. All rights are reserved.

Population-Based Model of the Fraction of Incidental COVID-19 Hospitalizations during the Omicron BA.1 Wave in the United States

1. Background: Some reports have suggested that as many as one-half of all hospital inpatients identified as COVID-19-positive during the Omicron BA.1 variant-driven wave were incidental cases admitted primarily for reasons other than their viral infections. To date, however, there are no prospective longitudinal studies of a representative panel of hospitals based on pre-established criteria for determining whether a patient was, in fact, admitted as a result of the disease. 2. Materials and Methods: To fill this gap, we developed a formula to estimate the fraction of incidental COVID-19 hospitalizations that relies on measurable, population-based parameters. We applied our approach to a longitudinal panel of 164 counties throughout the United States, covering a 4-week interval ending in the first week of January 2022. 3. Results: Within this panel, we estimated that COVID-19 incidence was rising exponentially at a rate of 9.34% per day (95% CI, 8.93–9.87). Assuming that only one-quarter of all Omicron BA.1 infections had been reported by public authorities, we further estimated the aggregate prevalence of active SARS-CoV-2 infection during the first week of January to be 3.45%. During the same week, among 250 high-COVID-volume hospitals within our 164-county panel, an estimated one in four inpatients was COVID-positive. Based upon these estimates, we computed that 10.6% of such COVID-19-positive hospitalized patients were incidental infections. Across individual counties, the median fraction of incidental COVID-19 hospitalizations was 9.5%, with an interquartile range of 6.7 to 12.7%. 4. Conclusion: Incidental COVID-19 infections appear to have been a nontrivial fraction of all COVID-19-positive hospitalized patients during the Omicron BA.1 wave. In the aggregate, however, the burden of patients admitted for complications of their viral infections was far greater. [ FROM AUTHOR] Copyright of COVID is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

From least cost to least risk: Producing climate change mitigation plans that are resilient to multiple risks

Our plans to tackle climate change could be thrown off-track by shocks such as the coronavirus pandemic, the energy supply crisis driven by the Russian invasion of Ukraine, financial crises and other such disruptions. We should therefore identify plans which are as resilient as possible to future risks, by systematically understanding the range of risks to which mitigation plans are vulnerable and how best to reduce such vulnerabilities. Here, we use electricity system decarbonization as a focus area, to highlight the different types of technological solutions, the different risks that may be associated with them, and the approaches, situated in a decision-making under deep uncertainty (DMDU) paradigm, that would allow the identification and enhanced resilience of mitigation pathways. Copyright © 2023 Gambhir and Lempert.

The Study of 'Preparation Guidelines' Towards Phetchabun Government Officers and Health Massage Establishments

The purpose of research was to study practices, barriers, and solutions of Phetchabun health massage establishments under COVID-19 situation. Non-participant observation, informal interview, in-depth interview, and participation observation were carried out respectively. Purposive sampling was used with 15 health consumer protection officers in charge;11 district level, 2 provincial level, 2 regional level as well as each representative of 11 districts. Results after implementation of "Preparation Guidelines for Health Spa, Health Massage, and Beauty Massage to Promote Health Tourism During COVID-19 Pandemic" were categorized into two sections. Firstly, the practices, barriers, and solutions of government officer performances included preparation for reopening, monitoring of the provider practices, and performance report. Secondly, the provider operations consisted of doing "Self-Assessment of Health Establishment", logging-in webpage before reopening, and practices for clients included screening and report of patients under investigation, establishment monitor, service, and establishment cleaning. In summary, the preparation guidelines were purposed to reopen their business with numerous contents and messages written by official language, it caused establishment providers and practitioners difficultly understood when applying. LINE Application and making calls were easy and accessible methods for their communication to reach current data and to ensure exact information. Various encouragements and having compliments were also considerable to form trust and confidence among them, they also raised their proud.Copyright © 2023, World Informations Syndicate. All rights reserved.

Usefulness of C-reactive protein to determine the severity of SARS-CoV-2 infection in Peru.

Background: Recently, many biomarkers have been studied to determine severe cases of COVID-19. C-reactive protein (CRP) has shown high sensitivity in identifying patients with severe disease and utility comparable to computed tomography. Aim(s): To determine the usefulness of CRP to predict the severity of SARS-CoV-2 infection in patients hospitalized at the Naval Medical Center of Peru during the period January-September in the year 2021. Method(s): A quantita-tive, observational, analytical, retrospective, and diagnostic test type design was used. A sample size of 503 patients was calculated, which were divided into two groups according to their severity. Result(s): An optimal cut-off point of 10.92 mg/L for CRP levels was determined for the diagnosis of severe COVID-19. An area under the curve (AUC) of 0.762 was calculated and sensitivity, specificity, positive and negative predictive values and diagnostic accuracy values of 78.88%, 66.4%;41.42%;87.01%;and 67.27%;respectively. Fagan's normogram showed a post-test probability of 41%. In the adjusted model, CRP (aOR = 4.853;95% CI 2.987-7.886;p = 0.001), ferritin (aOR = 1.001;95% CI: 1.001-1.002;p = 0.001) and hypothyroidism (adjusted OR = 4899;95% CI: 1272-18872;p = 0.021) showed significance. Conclusion(s): The present study showed an association between CRP and the severity of SARS-CoV-2 infection in an adjusted model, showing its potential utility and contributing to determine the cut-off point of CRP in the Peruvian population and its international comparison.Copyright © 2023, Sociedad Chilena de Infectologia. All rights reserved.

Sensitivity to Neutralizing Antibodies and Resistance to Type I Interferons in SARS-CoV-2 R.1 Lineage Variants, Canada.

Isolating and characterizing emerging SARS-CoV-2 variants is key to understanding virus pathogenesis. In this study, we isolated samples of the SARS-CoV-2 R.1 lineage, categorized as a variant under monitoring by the World Health Organization, and evaluated their sensitivity to neutralizing antibodies and type I interferons. We used convalescent serum samples from persons in Canada infected either with ancestral virus (wave 1) or the B.1.1.7 (Alpha) variant of concern (wave 3) for testing neutralization sensitivity. The R.1 isolates were potently neutralized by both the wave 1 and wave 3 convalescent serum samples, unlike the B.1.351 (Beta) variant of concern. Of note, the R.1 variant was significantly more resistant to type I interferons (IFN-α/ß) than was the ancestral isolate. Our study demonstrates that the R.1 variant retained sensitivity to neutralizing antibodies but evolved resistance to type I interferons. This critical driving force will influence the trajectory of the pandemic.

Clinical significance of serum interleukin 6 in elderly patients infected with severe acute respiratory syndrome coronavirus 2 omicron variant and its correlation with underlying diseases

Objective To investigate the clinical significance of serum interleukin 6 (IL-6) in elderly patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant and its correlation with underlying diseases. Methods A total of 22 elderly patients (>80 years old) infected with omicron variant, who were admitted to Department of Infectious Diseases, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. to Jun. 2022 and tested positive for SARS-CoV-2 RNA, were included. The level of serum IL-6 was measured by flow cytometry, and the level of serum C reactive protein (CRP) was measured by immunonephelometry. Patients were divided into pneumonia group (16 cases) and non-pneumonia group (6 cases) according to the imaging examination results, and were divided into severe group (severe and critical type, 5 cases) and non-severe group (mild and normal type, 17 cases) according to the condition. Binary logistic regression model and receiver operating characteristic (ROC) curve were used to analyze the correlation between serum IL-6 and CRP levels and the severity of the disease and whether it would progress to pneumonia. Meanwhile, the relationships between underlying diseases and serum IL-6 level were explored. Results Among the 22 patients, 6 were mild, 11 were normal, 3 were severe, and 2 were critical. The baseline serum IL-6 level in the pneumonia group was significantly higher than that in the non-pneumonia group ([20.16+/-12.36]pg/mL vs [5.42+/-1.57] pg/mL, P=0.009), and there was no significant difference in baseline serum CRP level between the 2 groups (P>0.05). There were no significant differences in baseline serum IL-6 or CRP levels between the severe group and the non-severe group (both P>0.05). Logistic regression analysis showed that the baseline serum IL-6 and CRP might be related to pneumonia after infection with omicron variant (odds ratio [OR]=2.407, 95% confidence interval [CI]0.915-6.328;OR=1.030, 95% CI 0.952-1.114). ROC curve analysis showed that the area under curve values of serum IL-6 and CRP in predicting the progression to pneumonia were 0.969 (95% CI 0.900-1.000) and 0.656 (95% CI 0.380-0.932), respectively, with statistical significance (Z=2.154, P=0.030). There were no significant differences in the baseline serum IL-6 level or proportions of severe patients or pneumonia patients among patients with or without hypertension, diabetes mellitus, coronary heart disease, chronic kidney disease or chronic obstructive pulmonary disease (all P>0.05). The baseline serum IL-6 levels of the omicron variant infected elderly patients with 1, 2, and 3 or more underlying diseases were 12.50 (9.15, 21.75), 23.55 (9.63, 50.10), and 10.90 (5.20, 18.88) pg/mL, respectively, with no statistical significance (P>0.05). Conclusion For omicron variant infected patients, serum IL-6 level is significantly increased in patients with pneumonia manifestations and is correlated with disease progression. Serum IL-6 level is of great guiding significance to judge disease progression and evaluate efficacy and prognosis of elderly coronavirus disease 2019 patients.Copyright © 2022, Second Military Medical University Press. All rights reserved.

Application of ultrasound-guided peripheral arterial puncture in severe patients with Coronavirus disease 2019 under three-level protection

Objective To explore the application of ultrasound-guided arterial line placement in severe patients with COVID-19. Methods From February to April 2020, we retrospectively collected and analyzed the clinical data of critical patients with COVID-19 with an indwelling peripheral arterial catheter treated by the medical team of Peking Union Medical College Hospital. Patients with ultrasound-guided peripheral arterial catheterization were taken as the study group, while patients whose arterial catheter was placed by traditional palpation were taken as the control group. The puncture condition and complication rate were compared between the two groups. Results A total of 60 severe patients with COVID-19 who met the inclusion and exclusion criteria were enrolled in this study. There were 30 cases in the study group and 30 cases in the control group. In the study group, the success rate of the first catheterization of the peripheral artery (63.3% vs. 26.7%) and the total puncture success rate [(79.43+/- 25.79)% vs. (53.07+/-30.21)%] were higher than those in the control group (all P < 0.05), the puncture times(1.43+/-0.56 vs. 2.50+/-1.28) were less than those of the control group (P < 0.05). The rates of 24-hour disuse (6.7% vs. 30.0%), local hematoma (10.0% vs. 36.7%), occlusion, and tortuous (3.3% vs. 40.0%) in the study group were lower than those in the control group (all P < 0.05). Conclusion Under the three-level protection, ultrasound-guided arterial catheter placement for severe patients with COVID-19 can improve the success rate of catheter placement, reduce puncture times, and reduce the incidence of complications.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Identification Symptoms and Underlying Diseases Related to COVID-19 And Prediction of Death Status Using Artificial Neural Network and Logistic Regression: A Data Mining Approach

Background and Objectives: Due to the high prevalence of COVID-19 disease and its high mortality rate, it is necessary to identify the symptoms, demographic information and underlying diseases that effectively predict COVID-19 death. Therefore, in this study, we aimed to predict the mortality behavior due to COVID-19 in Khorasan Razavi province. Method(s): This study collected data from 51, 460 patients admitted to the hospitals of Khorasan Razavi province from 25 March 2017 to 12 September 2014. Logistic regression and Neural network methods, including machine learning methods, were used to identify survivors and non-survivors caused by COVID-19. Result(s): Decreased consciousness, cough, PO2 level less than 93%, age, cancer, chronic kidney diseases, fever, headache, smoking status, and chronic blood diseases are the most important predictors of death. The accuracy of the artificial neural network model was 89.90% in the test phase. Also, the sensitivity, specificity and area under the rock curve in this model are equal to 76.14%, 91.99% and 77.65%, respectively. Conclusion(s): Our findings highlight the importance of some demographic information, underlying diseases, and clinical signs in predicting survivors and non-survivors of COVID-19. Also, the neural network model provided high accuracy in prediction. However, medical research in this field will lead to complementary results by using other methods of machine learning and their high power.Copyright © 2022 The Authors.

Utility of the Brixia CXR score, C-Reactive Protein and Absolute Neutrophil Count in Predicting the Need for Invasive Mechanical Ventilation, Length of Hospital Stay, and Mortality in Moderate to Severe COVID-19 Patients

Background: The Brixia Chest X-ray (CXR) score, C-reactive protein (CRP), and the absolute neutrophil count (ANC) have been useful to predict outcomes in Coronavirus disease 2019 (COVID-19 patients). We studied the utility of the Brixia CXR score, CRP, and ANC in predicting the outcomes in terms of the need for invasive mechanical ventilation, length of stay, and mortality in moderate-severe COVID-19 patients. Material(s) and Method(s): This was a single-centre, retrospective, study on 122 COVID-19 patients. Brixia CXR score, CRP, and ANC on admission to the hospital and the fifth day of hospital stay were noted along with the need for invasive mechanical ventilation (IMV), prolonged length of stay (LOS) >= 14 days, and mortality. Result(s): 122 patients were included for analysis. The median and interquartile range (IQR) for baseline CRP was 81.50 (39-151) mg/L and 11.0 (4-30) mg/L (p < 0.001) on the fifth day. The median and IQR for baseline Brixia score was 10.0 (7-13), and on the fifth day was 7 (4-11) (p <0.001). The receiver operating characteristic curve (ROC) showed that the baseline CRP >= 52.5mg/L predicted both the need for IMV, with an area under the curve (AUC) of 0.628, and prolonged LOS with an AUC of 0.608. The ROC curve depicted that the baseline ANC >8500/muL predicted IMV requirement with an AUC of 0.657. The fifth day CRP >= 32 mg/L, ANC >= 11,000/ muL and Brixia CXR score >= 7 predicted a higher mortality in hospitalized patients. Conclusion(s): Baseline CRP (> 52.5mg/L) predicts the need for IMV and a prolonged LOS, but not mortality. Baseline ANC (> 8500/muL) predicted the need for IMV. CRP, Brixia CXR score, and ANC on the fifth day were not useful to predict LOS or mortality, though there was a significant reduction in CRP and Brixia CXR score on the fifth day compared to baseline after treatment. The fifth day CRP >= 32 mg/L, ANC >= 11,000/ muL and Brixia CXR score >= 7 predicted a higher mortality.Copyright © 2023, College of Anaesthesiologists of Sri Lanka. All rights reserved.

A Rare Manifestation of Unknown Hyperparathyroidism as a Perforated Peptic Ulcer.

Hypercalcemia is a common electrolyte abnormality with different causes. Hypercalcemia is most often associated with malignancy and primary hyperparathyroidism and malignancy together account for most cases. Primary hyperparathyroidism manifests as hypercalcemia owing to the overproduction of parathyroid hormone. In most cases, primary hyperparathyroidism manifests due to a solitary parathyroid adenoma. Based on calcium levels, hypercalcemia can be classified as mild, moderate, and severe. Hypercalcemia typically presents with non-specific clinical features. Here, we present the case of a 38-year-old male patient who presented to the emergency department (ED) with acute abdominal pain and a tender abdomen with absent bowel sounds. He had chest radiography and blood tests initially. Chest radiography showed left-sided pneumoperitoneum, and the patient was suspected to have a perforated peptic ulcer due to hypercalcemia secondary to a parathyroid adenoma during the second wave of the coronavirus disease 2019 (COVID-19) pandemic. The findings were confirmed by a computerized tomography scan of the abdomen, and the patient was treated with intravenous fluids for hypercalcemia and was managed conservatively for a sealed perforated peptic ulcer following discussion in the multi-disciplinary team meeting (MDT). The COVID-19 pandemic led to a long waiting list and delays in the timely management of patients requiring elective surgical intervention, such as parathyroidectomy. The patient made a complete recovery and had parathyroidectomy of the inferior right lobe two months later.

Nirmatrelvir and Molnupiravir Coadministration Modifies Preclinical Viral Exposure

Background: Implementation of vaccination programmes has had a transformational impact on control of the SARS-CoV-2 pandemic, but the need for effective antiviral drugs remains. Molnupiravir (MPV) targets viral RNA polymerase inhibiting replication via lethal mutagenesis and nirmatrelvir (NTV) is a protease inhibitor boosted with ritonavir when given clinically. This study aimed to assess the virological efficacy of NTV and MPV individually and in combination against the SARS-CoV-2 BA.1 Omicron variant in a K18-hACE2 mouse model. Method(s): K18-hACE2 mice were inoculated intranasally with 103 PFU of SARSCoV-2 BA.1 Omicron (B.1.1.529). After 24 hours, mice were orally dosed q12H, as outlined in Figure 1. At 2, 3, and 4-days post infection mice were sacrificed, and lung samples harvested. Animals were weighed and monitored daily throughout. Subsequently, viral replication in the lung was quantified using qRT-PCR to measure total (N-gene) and sub-genomic (E-gene) viral RNA. Data were normalized to 18S for quantitation. Viral exposures expressed as Areas Under viral load Curves (AUCs) were calculated by the trapezoidal method using mean values at each timepoint. Separate studies in Syrian golden hamsters using individual drugs were also conducted, and total serum IgG was measured by ELISA at 4-days post infection. Result(s): Mice gained weight in all groups post-treatment, with no significant difference between groups. A reduction in lung viral exposure was evident in all treatment groups compared to the vehicle control dosed mice (Figure 1). Coadministration of NTV with MPV displayed a trend towards lower lung viral exposure compared to the vehicle control with ~40-and ~45-fold reduction in AUC for N-and SgE-gene assays, respectively. Dosed individually, NTV and MPV reduced viral exposure 5.7-and 7.7-fold for the N-gene assay, respectively. Differences in total serum IgG concentrations were evident between vehicle and NTV-(34-fold reduction, P=0.018), and MPV-(4.2-fold reduction, P=0.053) treated hamsters. Conclusion(s): These data show virological efficacy of NTV and MPV against the SARS-CoV-2 BA.1 Omicron variant. The combination of NTV and MPV demonstrated a lower viral RNA exposure in the lung than either drug alone, albeit not statistically significant. Initial data indicate potential immune alterations in NTV and MPV dosed hamsters. Studies to clarify the utility of NTV/ MPV combinations and further characterize the impact of antiviral therapy on IgG are warranted.

Safety and Pharmacokinetics of a Novel Double Prodrug Asc10 in Healthy Subjects

Background: ASC10 is an oral double prodrug of the active antiviral ribonucleoside analog, ASC10-A (also known as beta-d-N4-hydroxycytidine), which is a potent inhibitor of SARS-CoV-2. ASC10 is rapidly metabolized into ASC10-A in vivo after oral dosing. Here, we report the results of the first-in-human, phase 1 study to determine the safety, tolerability, and pharmacokinetics (PK) of ASC10 in healthy subjects, and to assess the food effect on the pharmacokinetics. Method(s): This study included 2 parts. Part 1 (multiple-ascending-dose) consisted of 6 cohorts (8 or 12 subjects per cohort). Eligible subjects were randomized in a 3:1 ratio to receive either twice-daily (BID) doses of 50 to 800 mg ASC10 or placebo for 5.5 days, and were then followed for 7 days for safety. In Part 2 (food effect), 12 subjects were randomized in a 1:1 ratio to either 800 mg ASC10 in the fed state followed by 800 mg in the fasted state, or vice versa, with a 7-day washout period between doses. PK blood samples were collected and measured for ASC10-A along with ASC10 and molnupiravir. Safety assessments included monitoring of adverse events (AEs), measurement of vital signs, clinical laboratory tests, and physical examinations. Result(s): ASC10-A was the major circulating metabolite ( >99.94%) in subjects after oral dosing of ASC10. ASC10-A appeared rapidly in plasma, with a median Tmax of 1.00 to 2.00 h, and declined with a geometric t1/2 of approximately 1.10 to 3.04 h. After multiple dosing for 5.5 days, both Cmax and AUC of ASC10-A increased in a dose-proportional manner from doses of 50 to 800 mg BID without accumulation. of ASC10-A in the fed state occurred slightly later, with a median of 3.99 h postdose versus 2.00 h (fasted state). However, Cmax and AUC were very similar or the same between fed and fasted states. Thus, administration of ASC10 with food is unlikely to have an effect on exposure. The incidence of AEs was similar between subjects receiving ASC10 or placebo (both 66.7%) and 95.0% of AEs were mild. There were no serious adverse events as well as no clinically significant findings in clinical laboratory, vital signs, or electrocardiography. Conclusion(s): Results of this study showed that ASC10 was well tolerated, and the increase in plasma exposure of ASC10-A was dose proportional across the range of doses tested with no accumulation and no food effect. 800 mg ASC10 BID is selected for further studies in patients infected with SARS-CoV-2.

Simulation of pharmacokinetic drug-drug interaction and dosage regimens optimization of nelfinavir and cepharanthine as a potential combination against COVID-19

The pharmacokinetic (PK) drug-drug interactions (DDIs) of nelfinavir and cepharanthine combination is limited information in human. In addition, the dosage regimen of this combination is not available for COVID-19 treatment. The objective of this study was to perform in silico simulations using GastroPlusTM software to predict physicochemical properties, PK parameters using the physiologically based pharmacokinetic (PBPK) model of healthy adults in different dosage regimens. The DDIs analysis of nelfinavir and cepharanthine combination was carried out to optimize the dosage regimens as a potential against COVID-19. The Spatial Data File (SDF) format of nelfinavir and cepharanthine structures obtained from PubChem database were used to carry out in silico predictions for physicochemical properties and PK parameters using several aspects of modules such as ADMET Predictor, Metabolism and Transporter, PBPK model. Subsequently, all data were utilized in the DDIs simulations. The dynamic simulation feature was selected to calculate and investigate the Cmax, AUC0-120, AUC0-inf, Cmax ratio, AUC0-120 ratio, and AUC0-inf ratio. The victim or nelfinavir dosage regimens were used four oral administration regimens of 500 mg and 750 mg in every 8 and 12 hours for simulations. The perpetrator or cepharanthine oral dosage regimens were used in several regimens from 10 mg to 120 mg in every 8, 12, and 24 hours. From all predicted results, the dosage regimen as a potential combination against COVID-19 was nelfinavir 500 mg every 8 hours and cepharanthine 10 mg every 12 hours.Copyright © 2023 by Faculty of Pharmacy, Mahidol University, Thailand is licensed under CC BY-NC-ND 4.0. To view a copy of this license, visit https://www.creativecommons.org/licenses/by-nc-nd/4.0/.