MALIGNANT HYPERTENSION AFTER COVD-19 VACCINE INJECTION

Case;40 y/o male. Clinical course;The patient was transferred to our university hospital because of DOE and severe headache. He had been well and had no history of hypertension or obesity. He had experienced the COVID-19 vaccine injection two week before this visit. After the injection he had been experienced high fever and general fatigue as well as 7 kg of weight loss. On examnation, it was found that he had severe hypertension (190/110 mmHg) and hypertensive optic fundi. On chest X-ray, cardiomegaly and bilateral lung infiltrations was evident and biochemical data indicated renal dysfunction (serum creatinine 2.35 mg/dl), high levels of plasma renin activity (39.1 ng/ml/hour normal;0.6-3.9) and aldosterone concentration (176 pg/ml normal;4.0-82.1), and inflammatory changes (CRP = 23 mg/dl). We also found that increased levels of LDH and decreased levels of hemoglobin which indicated hemolytic anemia and thrombotic microangiopathy. After the control of high blood pressure by intravenous administration of Calcium channel blockades, We performed renal biopsy, which had a finding of diffuse findings of onion skin lesion and global glomerular sclerosis compatible with the diagnosis of malignant hypertension. Any secondary etiologies including renal artery disease or collagen disease had not been identified. Seven days after the admission, we started hemodialysis for this patient because of the renal failure was not resolved. We also had startred ACE inhibitors. We stopped the diuretics and minimized the ultrafiltration. Twenty-five days after the admission the patients was withdrawn from dialysis with the urine volume around 2000 ml/day and the serum creatinine concentration 5.29 mg/dl. He was discharged without any aid of dialysis and with small number of anti-hypertensives. Four months after the discharge, his serum creatinine concentration was 3.36 mg/dl and his blood pressure was 139/85 mmHg with the ACE inhibitor and calcium channel blockades. Conclusions;The case suggested that the malignant hypertension might be triggered by COVID-19 vaccine injection, which is of clinical importance.

PREVALENCE AND HOSPITAL OUTCOME OF BACTERIAL CO-INFECTION IN RESPIRATORY TRACT SPECIMEN AMONG COVID 19 PATIENTS WITH SARS-COV-2 PNEUMONIA

Introduction: COVID-19, a zoonotic disease caused by the novel coronavirus SARS-CoV-2, is a highly transmittable pathogenic viral infection, infecting millions of people globally. Guidelines recommendthe use of empiric antimicrobials based on clinical judgment, patient host factors and local epidemiology in patients suspected or confirmed severe COVID-19. However, current evidence does not support a high rate of bacterial respiratory co-infections in patients with SARSCOV- 2 infection. At present, there is no known study regarding the prevalence of bacterial co-infection in COVID-19 patients in the Philippines Methods: This research is a cross-sectional hospital-based study that utilized hospital electronic and printed medical records, chest radiograph and microbiologic results. All respiratory specimen bacteriologic results for the year 2020 and 2021 were collected from the hospital laboratory unit followed by review of the hospital electronic records, printed medical records and chest radiograph results. Data were analyzed using Two-tailed Z-test for significance test for proportions and Chi-square test. Results: Among 100 subjects, only 22% (n = 22) of the subjects were found to have bacterial isolates. the only demographic that is dependent with presence of bacterial infection is gender. The three most common bacterial isolate among COVID confirmed patients are Klebsiella pneumoniae (n = 9), Pseudomonas aeruginosa (n = 5), and Acinetobacter baumannii (n = 3). Although the most common bacterial isolate is Klebsiella pneumoniae, the most common bacterial co-infection in patients who died are Acinetobacter baumannii (n = 2, 29%)and Pseudomonas aeruginosa (n = 2, 29%). Conclusion: The prevalence of bacterial co-infection among COVID confirmed patients is relatively low, hence appropriate guidelines regarding antibiotic use should be formed taking into consideration local data on antimicrobial resistance.

Outcomes of elective cancer surgery in COVID-19 survivors: An observational study

Background and Objectives: Guidelines recommend deferral of elective surgery after COVID-19. Delays in cancer surgeries may affect outcomes. We examined perioperative outcomes of elective cancer surgery in COVID-19 survivors. The primary objective was 30-day all-cause postoperative mortality. The secondary objectives were 30-day morbidity, and its association with COVID-19 severity, and duration between COVID-19 and surgery. Methods: We collected data on age, gender, comorbidities, COVID-19 severity, preoperative investigations, surgery performed, and intra and postoperative outcomes in COVID-19 survivors who underwent elective cancer surgery at a tertiary-referral cancer center. Results: Three hundred and forty-eight COVID-19 survivors presented for elective cancer surgery. Of these, 332/348 (95%) patients had mild COVID-19 and 311 (89%) patients underwent surgery. Among patients with repeat investigations, computerized tomography scan of the thorax showed the maximum new abnormalities (30/157, 19%). The 30-day all-cause mortality was 0.03% (1/311) and 30-day morbidity was 17% (54/311). On multivariable analysis, moderate versus mild COVID-19 (odds ratio [OR]: 1.95;95% confidence interval [CI]: 0.52–7.30;p = 0.32) and surgery within 7 weeks of COVID-19 (OR: 0.61;95% CI: 0.33–1.11;p = 0.10) were not associated with postoperative morbidity. Conclusions: In patients who recover from mild to moderate COVID-19, elective cancer surgery can proceed safely even within 7 weeks. Additional preoperative tests may not be indicated in these patients. © 2022 Wiley Periodicals LLC.

Potential Cardiac Tamponade Development Secondary to SARS-CoV-2 Infection

Upon initial discovery in late 2019, severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, has managed to spread across the planet. A plethora of symptoms affecting multiple organ systems have been described, with the most common being nonspecific upper respiratory symptoms: cough, dyspnea, and wheezing. However, the cardiovascular system is also at risk following COVID-19 infection. Numerous cardiovascular complications have been reported by physicians globally, in particular cardiac tamponade Physicians must hold a high index of suspicion in identifying and treating patients with cardiac tamponade who may have contracted the novel coronavirus. This review will describe the current epidemiology and pathophysiology of SARS-CoV-2 and cardiac tamponade, highlighting their clinical course progression and the implications it may have for the severity of both illnesses. The paper will also review published case reports of cardiac tamponade, clinical presentation, and treatment of this complication, as well as the disease as a whole. © 2022 Elsevier Inc.

Rapid detection of COVID-19 from chest X-ray images using deep convolutional neural networks

The entire world is suffering from the corona pandemic (COVID-19) since December 2019. Deep convolutional neural networks (deep CNN) can be used to develop a rapid detection system of COVID-19. Among all the existing literature, ResNet50 is showing better performance, but with three main limitations, i.e.: 1) overfitting;2) computation cost;3) loss of feature information. To overcome these problems authors have proposed four different modifications on ResNet50, naming it as LightWeightResNet50. An image dataset containing chest X-ray images of coronavirus patients and normal persons is used for evaluation. Five-fold cross-validation is applied with transfer learning. Ten different performance measures (true positive, false negative, false positive, true negative, accuracy, recall, specificity, precision, F1-score and area under curve) are used for evaluation along with fold-wise performance measures comparison. The four proposed methods have an accuracy improvement of 4%, 13%, 14% and 7% respectively when compared with ResNet50.

Applications of deep learning in disease diagnosis of chest radiographs: A survey on materials and methods

Recent advances in deep learning have given rise to high performance in image analysis operations in healthcare. Lung diseases are of particular interest, as most can be identified using non-invasive image modalities. Deep learning techniques such as convolutional neural networks, convolution autoencoders, and graph convolutional networks have been implemented in several pulmonary disease identification applications, e.g., lung nodule classification, Covid-19, and pneumonia detection. Various sources of medical images such as X-rays, computed tomography scans, magnetic resonance imaging, and positron emission tomography scans make deep learning techniques favorable to identify lung diseases with great accuracy. This paper discusses state-of-the-art methods that use deep learning on various medical imaging modalities to detect and classify diseases in the lungs. A description of a few publicly available databases is included in this study, along with some distinct deep learning techniques developed in recent times. Furthermore, several challenges and open research areas for pulmonary disease diagnosis using deep learning are discussed. The objective of this work is to direct researchers in the field of diagnosis of lung diseases.

Lung disease detection using Self-Attention Generative Adversarial Capsule network optimized with sun flower Optimization Algorithm

Lung cancer is the uncontrolled growth of abnormal cells in one or both lungs. This is one of the dangerous diseases. A lot of feature extraction with classification methods were discussed previously regarding this disease, but none of the methods give sufficient results, not only that, those methods have high over fitting problem, as a result, the detection accuracy was minimizing. Therefore, to overcome these issues, a Lung Disease Detection using Self-Attention Generative Adversarial Capsule Network optimized with Sun flower Optimization Algorithm (SA-Caps GAN-SFOA-LDC) is proposed in this manuscript. Initially, NIH chest X-ray image dataset is gathered through Kaggle repository to diagnose the lung disease. Then, the chests X-ray images are pre-processed by using the contrast limited adaptive histogram equalization (CLAHE) filtering method to eliminate the noise and to enhance the image quality. These pre-processed outputs are fed to feature extraction process. In the feature extraction process, the empirical wavelet transform method is used. These extracted features are given into Self-Attention based Generative Adversarial Capsule classifier for detecting the lung disease. The hyper parameters of SA-Caps GAN classifier is optimized using Sun flower Optimization Algorithm. The simulation is implemented in MATLAB. The proposed SA-Caps GAN-SFOA-LDC method attains higher accuracy 21.05%, 33.28%, 30.27%, 29.68%, 32.57% and 44.28%, Higher Precision 30.24%, 35.68%, 32.08%, 41.27%, 28.57% and 34.20%, Higher F-Score 32.05%, 31.05%, 36.24%, 30.27%, 37.59% and 22.05% analyzed with the existing methods, SVM-SMO-LDC, CNN-MOSHO-LDC, XGboost-PSO-LDC respectively. © 2022 Elsevier Ltd

Clinical and Laboratory Evaluations of Patients Diagnosed as Having Multisystem Inflammatory Syndrome Associated with Coronavirus Disease 2019 in Children: A Single Center Experience from Konya

Objective Multisystem inflammatory syndrome in children (MIS-C), characterized by fever, inflammation, and multiorgan dysfunction, was newly defined after severe acute respiratory syndrome coronavirus 2 infection. The clinical spectrum of MIS-C can be classified as mild, moderate, and severe. We aimed to evaluate demographics, clinical presentations, laboratory findings, and treatment modalities of patients with MIS-C according to clinical severity. Methods We performed a retrospective study of patients who were diagnosed as having MIS-C between September 2020 and October 2021 in the Necmettin Erbakan University Meram Faculty of Medicine, Türkiye. Results A total of 48 patients (24 females and 24 males) with a median age at diagnosis of 10.3 years (range: 42 months-17 years) were enrolled, the most common clinical severity of MIS-C was moderate. The common presentations of patients were fever (97%), nonpurulent conjunctivitis (89.6%), rashes (81.3%), fatigue (81.3%), strawberry tongue (79.2%), and myalgia (68.8%). The most common laboratory findings were lymphopenia (81.2%), thrombocytopenia (54.1%), elevated D-dimer levels (89.5%), C-reactive protein (CRP;100%), procalcitonin (97%), erythrocyte sedimentation rate (87.5%), ferritin (95.8%), interleukin 6 (IL-6) (86.1%), and probrain natriuretic peptide (pro-BNP) (97%). High levels of CRP, procalcitonin, pro-BNP, and urea were associated with the severity of MIS-C (p < 0.05). Fifteen of the patients were found to have pulmonary involvement. Ascites were the most common finding on abdominal ultrasonography (11 patients) and were not seen in a mild form of the disease. During the study period, two patients died. Conclusion It is important to make patient-based decisions and apply a stepwise approach in treating patients with MIS-C due to the increased risk of complications and mortality. © 2022. Thieme. All rights reserved.

Isolated tracheobronchial mucormycosis: Report of a case and systematic review of literature

Background: Isolated tracheobronchial mucormycosis (ITBM) is an uncommonly reported entity. Herein, we report a case of ITBM following coronavirus disease 2019 (COVID-19) and perform a systematic review of the literature. Case description and systematic review: A 45-year-old gentleman with poorly controlled diabetes mellitus presented with cough, streaky haemoptysis, and hoarseness of voice 2 weeks after mild COVID-19 illness. Computed tomography and flexible bronchoscopy suggested the presence of a tracheal mass, which was spontaneously expectorated. Histopathological examination of the mass confirmed invasive ITBM. The patient had complete clinical and radiological resolution with glycaemic control, posaconazole, and inhaled amphotericin B (8 weeks). Our systematic review of the literature identified 25 additional cases of isolated airway invasive mucormycosis. The median age of the 26 subjects (58.3% men) was 46 years. Diabetes mellitus (79.2%) was the most common risk factor. Uncommon conditions such as anastomosis site mucormycosis (in two lung transplant recipients), post-viral illness (post-COVID-19 [n = 3], and influenza [n = 1]), and post-intubation mucormycosis (n = 1) were noted in a few. Three patients died before treatment initiation. Systemic antifungals were used in most patients (commonly amphotericin B). Inhalation (5/26;19.2%) or bronchoscopic instillation (1/26;3.8%) of amphotericin B and surgery (6/26;23.1%) were performed in some patients. The case-fatality rate was 50%, primarily attributed to massive haemoptysis. Conclusion: Isolated tracheobronchial mucormycosis is a rare disease. Bronchoscopy helps in early diagnosis. Management with antifungals and control of risk factors is required since surgery may not be feasible. © 2022 Wiley-VCH GmbH.

Role of Chest Radiography as the Imaging Tool in COVID Pandemic Era

Background: The present radiological COVID literature is mainly confined to the CT findings. Using High Resolution Computed tomography (HRCT) as a regular 1st line investigation put a large burden on radiology department and constitute a huge challenge for the infection control in CT suite. Materials and Methods: A prospective study of 700 consecutive COVID positive cases who underwent Chest Xray (CXR) and HRCT thorax were included in the study. Many of these CXR were repeated and followed up over a duration of time to see the progression of disease. Results: 392/700 (56%) were found to be negative for radiological thoracic involvement. 147/700 (21%) COVID positive patients showed lung consolidations, 115/700 (16.5%) presented with GGO, 40/700 (5.7%) with nodules and 42/700 (6%) with reticular–nodular opacities. 150/700 patients (21.4 %) had mild findings with total RALE severity score of 1-2. More extensive involvement was seen in 104/700 (14.8 %) and 43/700 (6.2%) patients, who had severity scores of 3-4 and 5-6 respectively. 11/700 patients had a severity score of >6 on their baseline CXR. Those with severity score of 5 or more than 5 (54/700, 7.7%) required aggressive treatment with mean duration of stay of 14 days, many of them died also (23/54, 42.5%). Conclusion: In cases of high clinical suspicion for COVID-19, a positive CXR may obviate the need for CT. Additionally, CXR utilization for early disease detection and followup may also play a vital role in areas around the world with limited access to CT and RT-PCR test.

Characteristics of fever in patients with COVID-19 at presentation and after initiation of treatment

Coronavirus-19 (COVID-19) infection presents in a many ways, from asymptomatic or mild symptoms to death or serious illness. Coughing, shortness of breath, and fever are the common symptoms. Other symptoms include weakness, muscle discomfort, lethargy, sore throat, breathing problems, and loss of smell and/or taste. COVID-19 is diagnosed using clinical indicators, CT scans or chest x-rays, serological tests, and molecular diagnostics of the viral genome using reverse transcription polymerase chain reaction. This study analyzes the duration of fever, the most important symptom of the disease, and its association with other patient characteristics. The cross-sectional study was conducted in Iraq's Al-Diwaniyah Province, located in the Mid-Euphrates region. The study included 99 COVID-19 cases, 50 males and 49 females aged 16–81 years. Age, gender, white blood cell (WBC) count, lymphocyte percent, lung involvement assessed by CT scan, duration of fever at the time of presentation, and duration until the fever subsides following initiation of treatment were the main variables studied, in addition to the presence of chronic medical illnesses such as diabetes mellitus, systemic hypertension, asthma, and pulmonary tuberculosis. The mean age of all patients was 50.38 ± 16.27 years, with no significant difference between males and females (P = 0.924). There was also no significant difference in mean WBC count and lymphocyte percent between males and females (P > 0.05). Lung involvement from CT scan ranged from 0 to 80% and the mean was 26.77 ± 21.43%, with no significant difference between males and females (P = 0.770). The mean duration of fever at the time of presentation was 6.61 ± 3.60 days and it ranged from 1 to 21 days. The duration of subsiding fever ranged between 2 and 25 days in all patients with a mean of 5.82 ± 3.53 days, with no significant difference between males and females (P = 0.214). The duration needed for the fever to subside was positively and significantly correlated to the WBC count, the duration of fever at presentation, and the presence of diabetes mellitus (P < 0.05). Longer duration of fever after diagnosis and treatment of COVID-19 can be predicted with a high WBC count. Patients with diabetes having a longer duration of fever are at high risk of developing severe complications and death.

The value of case reports in diagnostic radiography.

OBJECTIVE: - This paper sought to explore the value of case reports in diagnostic radiography with regards to current usage, relevance to evidence-based radiography, and educational benefits. KEY FINDINGS: Case reports are short accounts of novel pathologies, trauma or treatment with a critical review of relevant literature. Examples within diagnostic radiography include the appearances of COVID-19 alongside examination-level scenarios involving image artefacts, equipment failure and patient incidents in radiology. With greatest risk of bias and lowest generalisability, they are considered as low-quality evidence with generally poor citation rates. Despite this, there are examples of significant discoveries or developments initiated with case reports with important patient care implications. Furthermore, they offer educational development for both reader and author alike. Whereas the former learns about an unusual clinical scenario, the latter develops scholarly writing skills, reflective practice and may generate further, more complex, research. Radiography-specific case reports could capture the diverse imaging skills and technological expertise currently under-represented in traditional case reports. Potential avenues for cases are broad and may include any imaging modality where patient care or safety of other persons may illicit a teaching point. This encapsulates all stages of the imaging process, before, during and after patient interaction. CONCLUSION: Despite being low-quality evidence, case reports contribute to evidence-based radiography, add to the knowledge base, and foster a research culture. However, this is contingent upon rigorous peer-review and adherence to ethical treatment of patient data. IMPLICATIONS FOR PRACTICE: With the drive to increase research engagement and output at all levels in radiography (student to consultant), case reports may act as a realistic grass-root activity for a burdened workforce with limited time and resources.

A study on changes in lung function, neutralizing antibodies, and symptoms of adult patients hospitalized with COVID-19.

Background/Aims: To identify changes in symptoms and pulmonary sequelae in patients with coronavirus disease 2019 (COVID-19). Methods: Patients with COVID-19 hospitalized at seven university hospitals in Korea between February 2020 and February 2021 were enrolled, provided they had ≥ 1 outpatient follow-up visit. Between January 11 and March 9, 2021 (study period), residual symptom investigations, chest computed tomography (CT) scans, pulmonary function tests (PFT), and neutralizing antibody tests (NAb) were performed at the outpatient visit (cross-sectional design). Additionally, data from patients who already had follow-up outpatient visits before the study period were collected retrospectively. Results: Investigation of residual symptoms, chest CT scans, PFT, and NAb were performed in 84, 35, 31, and 27 patients, respectively. After 6 months, chest discomfort and dyspnea persisted in 26.7% (4/15) and 33.3% (5/15) patients, respectively, and 40.0% (6/15) and 26.7% (4/15) patients experienced financial loss and emotional distress, respectively. When the ratio of later CT score to previous ones was calculated for each patient between three different time intervals (1-14, 15-60, and 61-365 days), the median values were 0.65 (the second interval to the first), 0.39 (the third to the second), and 0.20 (the third to the first), indicating that CT score decreases with time. In the high-severity group, the ratio was lower than in the low-severity group. Conclusions: In COVID-19 survivors, chest CT score recovers over time, but recovery is slower in severely ill patients. Subjects complained of various ongoing symptoms and socioeconomic problems for several months after recovery.

Not all shortness of breath and throat pain is COVID

Case Report: A previously, healthy 18-year-old female presents to a Pediatric Emergency Medicine Department with shortness of breath, fever, and worsening throat and abdominal pain for 3 days. She had a sick contact, a teacher that tested positive for COVID-19 2 weeks prior to presentation. She denies runny/stuffy nose, cough, loss of taste/smell, or rashes/lesions. She denies any significant past medical history including allergies, as well as any history of smoking or any illicit drug use. Upon arrival to the ED, the patient was noted to be tachycardic, hypotensive and febrile. There were no desaturations. Initial physical examination revealed a generally uncomfortable female that was alert and oriented, with noted tenderness over the right anterior neck region, diffuse cervical lymphadenopathy, and painful neck range of motion. Her pharynx was noted to be erythematous without exudates or any unilateral tonsillar swelling. In the ED patient received IV fluid resuscitation and was started on norepinephrine drip, broad spectrum antibiotics. Initial lab workup revealed an anion gap metabolic acidosis, likely secondary to uremia or lactic acidosis from poor perfusion in setting of sepsis and hypovolemia. BUN and creatinine were elevated, likely due to an acute kidney injury (AKI) secondary to hypovolemia. The patient was also found to have an elevated LDH, fibrinogen, and mild elevation of AST. D-Dimer was elevated at 29 000. Covid PCR, Rapid Strep, and respiratory PCR panel were negative. Her chest X-ray (CXR) was negative and ECG showed sinus tachycardia. Given the patient's history of throat and neck pain with shortness of breath, in the setting of a septic picture, a CT scan of neck, chest, abdomen was ordered prior to transferring the patient to the PICU. CT scan of the chest revealed small patches of consolidation with ground glass opacities in the right lung apex, as well as an nearly occlusive, acute thrombosis of the anterior right facial vein. The patient's initial blood cultures grew gram negative bacilli which later were revealed to be Fusobacterium necrophorum. These findings are consistent with Lemierre's syndrome. The patient was treated in the PICU on vasopressors, heparin anticoagulation, and antibiotics for 6 days and discharged with a course of Augmentin. Lemierre's syndrome is an infectious thrombophlebitis of the internal jugular vein. First described by Andre Lemierre in 1936, it begins as a bacterial pharyngitis, generally developing into a peritonsillar abscess or other deep space neck infection with progressive erosion into the internal jugular vein. Diagnostic criteria for Lemierre's syndrome includes radiographically evidence of thrombophlebitis of the internal vein and positive blood cultures. CT and MRI can help make the diagnosis, but are not always required. Treatment is prompt intravenous antibiotics with beta-lactamase penicillins, metronidazole, clindamycin, and third generation cephalosporins. [Figure presented] Copyright © 2023 Southern Society for Clinical Investigation.

A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron

The Coronavirus (COVID-19) outbreak in December 2019 has drastically affected humans worldwide, creating a health crisis that has infected millions of lives and devastated the global economy. COVID-19 is ongoing, with the emergence of many new strains. Deep learning (DL) techniques have proven helpful in efficiently analysing and delineating infectious regions in radiological images. This survey paper draws a taxonomy of deep learning techniques for detecting COVID-19 infection in radiographic imaging modalities Chest X-Ray, and Computer Tomography. DL techniques are broadly categorised into classification, segmentation, and multi-stage approaches for COVID-19 diagnosis at the image and region-level analysis. These techniques are further classified as pre-trained and custom-made Convolutional Neural Network architectures. Furthermore, a discussion is drawn on radiographic datasets, evaluation metrics, and commercial platforms provided for detection. In the end, a brief look is paid to emerging ideas, gaps in existing research, and challenges in developing diagnostic techniques. This survey provides insight into the promising areas of research in DL and is likely to guide the research community on the upcoming development of deep learning techniques for COVID-19. This will pave the way to accelerate the research in designing customised DL-based diagnostic tools for effectively dealing with new variants of COVID-19 and emerging challenges. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

An efficient lung disease classification from X-ray images using hybrid Mask-RCNN and BiDLSTM

Lung diseases mainly affect the inner lining of the lungs causing complications in breathing, airway obstruction, and exhalation. Identifying lung diseases such as COVID-19, pneumonia, fibrosis, and tuberculosis at the earlier stage is a great challenge due to the availability of insufficient laboratory kits and image modalities. The rapid progression of the lung disease can be easily identified via Chest X-rays and this serves as a major boon for the terminally ill patients admitted to Intensive Care Units (ICU). To enhance the decision-making capability of the clinicians, a novel lung disease prediction framework is proposed using a hybrid bidirectional Long-Short-Term-Memory (BiDLSTM)-Mask Region-Based Convolutional Neural Network (Mask-RCNN) model. The Crystal algorithm is used to optimize the scalability and convergence issues in the Mask-RCNN model by hyperparameter tuning. The long-range dependencies for lung disease prediction are done using the BiDLSTM architecture which is connected to the fully connected layer of the Mask RCNN model. The efficiency of the proposed methodology is evaluated using three publicly accessible lung disease datasets namely the COVID-19 radiography dataset, Tuberculosis (TB) Chest X-ray Database, and National Institute of Health Chest X-ray Dataset which consists of the images of infected lung disease patients. The efficiency of the proposed technique is evaluated using different performance metrics such as Accuracy, Precision, Recall, F-measure, Specificity, confusion matrix, and sensitivity. The high accuracy obtained when comparing the proposed methodology with conventional techniques shows its efficiency of it in improving lung disease diagnosis. Copyright © 2022 Elsevier Ltd

More Than Meets the Eye: Orbital Swelling in an Adolescent with Sickle Cell Disease

Periorbital swelling is a clinical presentation with a broad differential and potentially deleterious consequence. Causes range from benign, including allergic reaction, to vision-and life-threatening, including orbital cellulitis and orbital infarction. The recent climate of SARS-CoV-2 has further complicated this differential, as the virus poses broad clinical presentations with new manifestations reported frequently. Rapid identification of the underlying etiology is crucial, as treatment approaches diverge greatly. Here, we report the case of an African American adolescent male with a history of homozygous sickle cell anemia presenting to an inner city hospital with bilateral periorbital swelling amid the coronavirus pandemic. Differentials including orbital cellulitis, COVID-MIS-C, orbital inflammatory syndrome, Hoagland sign, and orbital infarction secondary to sickle cell crisis are contrasted. We contrast our case with 12 case reports of orbital infarction in the setting of sickle cell crisis within the past 10 years, highlighting how these presentations, along with commonly reported findings of orbital infarction, compare with our patient. Copyright © 2022 Tehran University of Medical Sciences.

Study of Haematological Profile in Covid-19 Patients

Introduction: Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 recognized on 31st December 2019 in Wuhan, China which was declared a worldwide pandemic by the World Health Organization on 11 March 2020. Haematological and inflammatory test results are found to be peculiar in COVID-19 patients. Aim(s): This study was conducted to add to the knowledge database of haematological values in Covid patients and to correlate with clinical findings wherever possible to carry out timely intervention. Method(s): This was a prospective cohort study conducted from July 2020 to December 2021 in a tertiary care centre at Pune in Western Maharashtra region. The study included 603 RTPCR Covid positive patients. The patients were grouped clinically according to the severity score based on the CT/chest x-ray and SpO2 findings and their blood samples were analyzed at the Central Clinical Laboratory of our hospital for complete haematological profile. Result(s): The haematological parameters were tabulated and statistically analyzed. The mean Hb, PCV, Eosinophil, Basophil, Lymphocyte and Monocyte counts were significantly low in severe category. The mean MCV, MCH, NLR, PLR, ESR and D-dimer was high in severe category. Leucocytosis and Neutrophilia were seen in severe category patients. The mean PT was prolonged in severe category patients. Overall, there were 15% deaths. Significantly, more deaths were found in severe category. Conclusion(s): Hematological and coagulation parameters are closely related to the covid-19 disease severity. Among various parameters, some like ESR, D-Dimer, NLR/PLR Ratio can be used as a reliable predictor of severity. Copyright © 2022 Authors. All rights reserved.