ABSTRACT
COVID-19 has caused havoc throughout the world in the last two years by infecting over 455 million people. Development of automatic diagnosis software tools for rapid screening of COVID-19 via clinical imaging such as X-ray is vital to combat this pandemic. An optimized deep learning model is designed in this paper to perform automatic diagnosis on the chest X-ray (CXR) images of patients and classify them into normal, pneumonia and COVID-19 cases. A convolutional neural network (CNN) is employed in optimized deep learning model given its excellent performances in feature extraction and classification. A particle swarm optimization with multiple chaotic initialization scheme (PSOMCIS) is also designed to fine tune the hyperparameters of CNN, ensuring the proper training of network. The proposed deep learning model, namely PSOMCIS-CNN, is evaluated using a public database consists of the CXR images with normal, pneumonia and COVID-19 cases. The proposed PSOMCIS-CNN is revealed to have promising performances for automatic diagnosis of COVID-19 cases by producing the accuracy, sensitivity, specificity, precision and F1 score values of 97.78%, 97.77%, 98.8%, 97.77% and 97.77%, respectively. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The world has never been more united than it is now. COVID-19 has succeeded where many other multilateral agencies have failed. The SARSCoV- 2 virus has bonded humanity and aligned national interests in a way not seen since the last Great War. As the COVID-19 virus continues to evolve, we are on a global mission to uncover everything about SARSCoV- 2 to strengthen our pandemic responses for future pandemics. This book addresses the molecular biology and evolution of SARS-CoV-2 and the virus–host interactions, and discusses the clinical management, detection technologies, transmission dynamics, and public health efforts to stem the onslaught of COVID-19. The chapters in Uncovering the Science of COVID-19 have been contributed by health experts and scientists from around the world, who have contributed their experiences and expertise freely to tackle the challenges of this unprecedented pandemic, and to ameliorate the impact of the ones to come. © 2023 by World Scientific Publishing Co. Pte. Ltd.
ABSTRACT
Objective: Although SARS-CoV2 vaccines have been developed with multiple novel technologies and rapidly disseminated worldwide, the full profile of adverse effects has not been known. Recently, there are sporadic but increasing reports of endocrinopathies in relation to SARS-CoV2 vaccination. Here, we report a rare case of hypophysitis with acute onset of diabetes insipidus after SARS-CoV2 vaccination. Case Report: A 48-year-old female who had been in her usual state of health until she received the first SARS-CoV2 vaccine. Two days after the vaccination, she started to have flu-like symptoms including severe headache and myalgia as well as persistent headache, polydipsia and polyuria. On presentation, her vital signs were stable, with her pulse being 81 bpm, BP: 122/84 mm Hg, temperature: 98.6F. Her physical examination was unremarkable. Laboratory evaluation revealed normal values of the basic metabolic panel including sodium level of 142 mmol/L and normal complete blood count. Due to her prolonged and worsening headache, she underwent a brain MRI which revealed a 4 mm round shape of thickening pituitary stalk and partial empty sella. The polydipsia, polyuria, and the thickening of the pituitary stalk led to further pituitary work-up. She underwent the overnight water deprivation test followed by the desmopressin challenge test. Her overnight water deprivation test revealed hypernatremia (Na 147 mmol/L), elevated serum osmolarity (309 mmol/kg), and low urinary osmolarity (83 mmol/kg) which were compatible with diabetes insipidus. Her IGF1 level revealed low normal range (66 ng/mL). Her 250 mcg cosyntropin test showed appropriate response without adrenal insufficiency. DDAVP was started. 3 months after the vaccination, her symptoms have partially improved, and on repeating the MRI brain she has persistent pituitary stalk thickening. Discussion: We report a rare case of diabetes insipidus from hypophysitis associated with SARS-CoV2 vaccine. Mechanisms of SARS-CoV2 vaccination-associated endocrinopathy is unknown. From our literature search, we found increasing numbers of the cases of endocrinopathy reported after the SARS- CoV2 vaccination. The thyroid seems the most frequently reported endocrine organ (83%), followed by the pituitary (11%) and adrenal (6%). Average onset is 1-5 days after the vaccinations and reported with all types of SARS-CoV2 vaccines. More mid-age (average age 46) female (78%) cases have been reported. Although associations are not confirmed, endocrinopathies may be underestimated in the post vaccinated population. Further studies are warranted to better understand SARS-CoV2 vaccinations and potential associations of endocrinopathy.Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.
ABSTRACT
Our study aims to investigate the best performing Convolutional Neural Networks (CNN) suitable for COVID-19 detection on Chest X-Ray (CXR) images. We applied five state-of-art CNN models in this study: DarkNet-19, ResNet-101, SqueezeNet, VGG-16, and VGG-19. These CNN models were pre-trained with natural images for classification. Therefore, we used transfer learning to modify the fully connected layer and output layer for a binary classification between COVID-19 and normal lungs. The models were trained using our combined dataset of CXR images obtained from the public domain, COVIDx, and private domain, University of Malaya (UM). The CXR images were pre-processed with reflection along the horizontal and vertical axis before being fed into the CNN models. Then another combined dataset from both COVIDx and UM was used to test the performance of the models. The numbers of correctly and wrongly predicted classes were tallied and represented with a confusion matrix. Then, the specificity, sensitivity, precision, F1-score, and accuracy were measured to evaluate the performance of each model. Our study demonstrated an accuracy above 90% for all five models. Gradient-weighted Class Activation Mapping (Grad-CAM) was used to visualize the significant activation regions that contributed to the model's decision. We have also applied the COVID-Net-CXR-Large model to our combined dataset for testing to evaluate its performance in multiclass classification. The current CNN models require further improvement and modification before they can be applied clinically as a secondary tool for the diagnosis of COVID-19 cases. © 2021 IEEE.
ABSTRACT
Background The 2012 Neonatal Early Onset Infection Guideline by National Institute for Clinical Excellent (NICE) [CG149], led to an increase in antibiotic use in well newborns. The Kaiser Permanente Sepsis Risk Calculator (KP-SRC) uses the population's background incidence of EOS, objective information at birth and the infant's clinical presentation to evaluate risk of neonatal EOS in infants >34 weeks gestation. This has safely shown to reduce the use of antibiotics. During the COVID-19 pandemic, the local Operational Delivery Network endorsed the use of the KP-SRC. Objectives To show implementation of KP-SRC can safely and effectively reduce the incidence of antibiotic use in well babies over 34 weeks gestation without an increase in missed cases of sepsis. Methods KP-SRC was implemented in 4 neonatal units. KPSRC is used on all babies with risk factors for infection in accordance with the NICE EOS guideline [CG149] and antibiotics are started according to the recommended outcome. There was slight variation in the parameters used by the units in the calculation of KP-SRC (i.e. Infection incidence rate of 0.8/1000 in 2 units and 0.6/1000 in the other 2 units). Blood culture data during the first seven days of life was provided on a monthly basis by the laboratories. Babies < 34 weeks gestation were excluded and clinical details of the remaining babies were reviewed, particularly with respect to positive blood cultures and readmissions following discharge home. Data was reviewed over a consecutive 5 month period prior to implementation of the KP-SRC (1 Sept 2019 - 31 Jan 2020), and post implementation (1 Sept 2020 - 31 Jan 2021). Results There was a percentage reduction in blood cultures taken in the post KP-SRC implementation period between the 4 units of 52 to 85% (mean 60%). There were 5 positive blood cultures, all babies were commenced on antibiotics at birth in accordance with the KP-SRC recommendation. Twenty babies were started on antibiotics after 24 hours of age and received 5 days of antibiotics. Twelve had no risk factors for infection and would not have been picked up by NICE. Of the eight assessed by KP-SRC, two were admitted to the neonatal unit on day 2 with tachypnea but did not require respiratory support. Only one baby was readmitted following discharge and received 5 days of antibiotics. This baby was readmitted on day 7 with apnoea requiring ventilation. There was a history of maternal prolonged rupture of membranes and mild maternal pyrexia but the baby was well in the immediate postnatal period. Blood cultures were negative with normal CRP's. Conclusions The KP-SRC can lead to a safe and consistent reduction in the number of well babies receiving antibiotics post-delivery. All babies with positive blood cultures were on antibiotics as guided by the KP-SRC and there were no missed cases of sepsis.
ABSTRACT
Rationale: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, has led to a global health crisis unlike any our contemporaries have witnessed before. SUNY Downstate Health Sciences University was designated as one of three COVID-19-only hospitals on March 28, 2020. This retrospective, single-center observational study grants a unique perspective surrounding the experience of the critical care service at a public institution serving a predominantly Afro-Caribbean, inner city population. Methods: Between March 11 and April 30, 2020, the critical care service was consulted for a total of 271 COVID-19 patients. We queried the electronic medical record for patient visits with critical care consult notes and collected data on demographics, comorbidities, ICU acceptance, treatment strategies, and clinical outcomes. Non-COVIDrelated consults were excluded. Chi-squared tests compared categorical variables, and independent samples ttest assessed differences in continuous variables based on mortality and ICU admission status. Logistic regression models determined if various factors independently predicted the odds of mortality. We conducted retrospective analyses to identify factors associated with survival and ICU acceptance. Results: Of the 271 patients with critical care consults, 33% (n=89) survived and 67% (n=182) expired. At the bivariate level, age, BUN, and neutrophil percentage were significantly associated with mortality, with age showing the strongest correlation (age: survivors, 61.62±1.50 vs. non-survivors, 68.98±0.85, p<0.001). There was a significant association between neutrophil percentage and mortality in the univariate logistic regression model (Q4 vs. Q1, OR 2.73, 95% CI (1.28-5.82), p trend = 0.044). In the multivariate analyses, procalcitonin exhibited a positive correlation with the odds of mortality, adjusting for age, sex, and race/ethnicity (procalcitonin: Q4 vs. Q1, OR 5.65, 95% CI (2.14-14.9), p trend <0.001). Adjusting for the same covariates, platelets exhibited a negative correlation with the odds of mortality (Q4 vs. Q1, OR 0.47, 95% CI (0.22-0.998), p trend = 0.010). Interestingly, of these factors, only elevated procalcitonin levels were associated with an increased likelihood of ICU acceptance. Conclusions: This retrospective, observational study during the first peak of the COVID-19 pandemic identified key factors linked to disease severity and outcomes. Of note, procalcitonin was the factor most strongly associated with both mortality and likelihood of ICU acceptance at the bivariate level. Respiratory failure is the primary cause of death in COVID-19, and our data suggests that procalcitonin is a useful marker that accurately reflects the severity of lung involvement during SARS-CoV-2 infection.
ABSTRACT
Background: Triple-negativebreast cancer (TNBC) has the highest rate of distant metastasis and poorestoverallsurvival among all breast cancer subtypes. Adagloxad simolenin (AS;OBI-822)is a therapeutic vaccine comprisingthe synthetically manufactured tumor-associatedantigen Globo H linked to the carrier protein keyhole limpethemocyanin (KLH).The KLH provides antigenic immune recognition and T-cell responses. AS isco-administered witha saponin-based adjuvant OBI-821 to induce a humoralresponse. A phase 2 trial showed that AS/OBI-821exhibiteda trend for superior progression-free survival vs placebo in patientswhose breast cancers had higher GloboHexpression. Administrationof AS/OBI-821 resulted in IgM and IgG anti-Globo H humoral response and atrendtowards improved PFS in patients with metastatic breast cancer overexpressingGlobo H. We describe therationale and design of GLORIA, an ongoing Phase III,randomized, open-label study to evaluate efficacy, safety, and quality of life(QoL) of AS plus standard of care (SOC) versus SOC alone in patients with high-risk, early-stage TNBC. The primary endpoint is invasive progression-freesurvival;secondary endpoints include overall survival, QoL, breastcancer-freeinterval, distant disease-free survival, safety, and tolerability. Trial Design: A phase 3 trial was initiated inDecember 2018 and had been slowly enrolling until being put on holddue to theCovid-19 pandemic. While the study wason hold the design waschanged from a placebo-control to astandard-of-care control trial based onfeedback from investigators and leading breast cancer advisers, that thenumberof placebo injections was a serious burden on patients. Furthermore, it wasapparent that blinding wasquestionable given the expected and frequent localskin inflammation and low-grade fevers that accompany theAS/OBI-821 vaccineadministration and the absence of these obvious clinical signs and symptoms with the normalsaline placebo control.The main changes to the protocol are as follows:Methods: Eligibility includes patients with TNBC (estrogen receptor/progesterone receptor <5%,and HER2-negative) with nonmetastatic disease and 1) either residual invasive disease of ≥1 cm in breast or ≥1 positiveaxillary node following neoadjuvantchemotherapy;Pathological Stage IIB or III disease treated with adequateadjuvant chemotherapy alone;received ≥4 cycles of standard taxane- and/oranthracycline-basedchemotherapy;randomized within 12 weeks of surgery, adjuvant multi-agent chemotherapy,or radiation therapy.Inaddition, tumors must express Globo H (H-score of ≥15 by central laboratory analysis using a validatedimmunohistochemical assay). Subjects in the AS/OBI-821 group will receive 30 μg of AS in combination with 100 μgofOBI-821.This revised study will start re-enrolling patients as soon as Covid-19 restrictions are lifted with the firstcountry being South Korea with an anticipated start date in Q4/2020.