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1.
Advances and Trends in Artificial Intelligence: Theory and Practices in Artificial Intelligence ; 13343:112-123, 2022.
Article in English | Web of Science | ID: covidwho-2103799

ABSTRACT

Computer Vision, as an area of Artificial Intelligence, has recently achieved success in tackling numerous difficult challenges in health care and has the potential to contribute to the fight against several lung diseases, including COVID-19. In fact, a chest X-ray is one of the most frequent radiological procedures used to diagnose a variety of lung illnesses. Therefore, deep learning researchers have recommended that deep learning techniques can be used to build computer-aided diagnostic systems. According to the literature, there are a variety of CNN structures. Unfortunately, there are no guidelines for compressing these architectural designs for any particular task. For these reasons, this design is still very subjective and hugely dependent on data scientists' expertise. Deep convolution neural networks have recently proven their capacity to perform well in classification and dimension reduction tasks. However, the problem of selecting hyper-parameters is essential for these networks. This is due to the fact that the size of the search space rises exponentially with the number of layers, and the large number of parameters requires extensive calculations and storage, which makes it unsuitable for application in low-capacity devices. In this paper, we present a system based on a genetic method for compressing CNNs to classify radiographic images and detect the possible thoracic anomalies and infections, including the case of COVID-19. This system uses pruning, quantization, and compression approaches to minimize the network complexity of various CNNs while maintaining good accuracy. The suggested technique combines the use of genetic algorithms (GAs) to execute convolutional layer pruning selection criteria. Our suggested system is validated by a series of comparison experiments and tests with regard to relevant state-of-the-art architectures used for thoracic X-ray image classification.

2.
Computational Collective Intelligence, Iccci 2022 ; 13501:283-296, 2022.
Article in English | Web of Science | ID: covidwho-2094416

ABSTRACT

Computer Vision has lately shown progress in addressing a variety of complex health care difficulties and has the potential to aid in the battle against certain lung illnesses, including COVID-19. Indeed, chest X-rays are one of the most commonly performed radiological techniques for diagnosing a range of lung diseases. Therefore, deep learning researchers have suggested that computer-aided diagnostic systems be built using deep learning methods. In fact, there are several CNN structures described in the literature. However, there are no guidelines for designing and compressing a specific architecture for a specific purpose;thus, such design remains highly subjective and heavily dependent on data scientists' knowledge and expertise. While deep convolutional neural networks have lately shown their ability to perform well in classification and dimension reduction tasks, the challenge of parameter selection is critical for these networks. However, since a CNN has a high number of parameters, its implementation in storage devices is difficult. This is due to the fact that the search space grows exponentially in size as the number of layers increases, and the large number of parameters necessitates extensive computation and storage, making it impractical for use on low-capacity devices. Motivated by these observations, we propose an automated method for CNN design and compression based on an evolutionary algorithm (EA) for X-Ray image classification that is capable of classifying radiography images and detecting possible chest abnormalities and infections, including COVID-19.Our evolutionary method is validated through a series of comparative experiments against relevant state-of-the-art architectures.

3.
J Clin Med ; 11(21)2022 Oct 29.
Article in English | MEDLINE | ID: covidwho-2090234

ABSTRACT

BACKGROUND: Polytrauma patients with SARS-CoV-2 infections may be associated with an increased complication rate. The main goal of this study was to analyze the clinical course of trauma patients with COVID infection and a positive CT finding. METHODS: This was a retrospective in-hospital study. Polytrauma patients diagnosed with SARS-CoV-2 infections were included in our analysis. The outcome parameters were pulmonary complication during admission, pulmonary embolism, pleural effusion, pneumonia, mortality, length of stay and readmission < 30 days. RESULTS: 48 patients were included in the study. Trauma patients in the age-adjusted matched-pair analysis with typical changes in SARS-CoV-2 infection in CT findings showed significantly more pulmonary complications in general and significantly more cases of pneumonia (complications: 56% vs. 11%, p = 0.046; pneumonia 44% vs. 0%, p = 0.023). In addition, the clinical course of polytrauma patients with SARS-CoV-2 infection showed a high rate of pulmonary complications in the inpatient course (53%). CONCLUSION: The results of our study show that the changes in the CT findings of trauma patients with SARS-CoV-2 infection are a good indicator of further inpatient outcomes. Similarly, polytrauma patients with a SARS-CoV-2 infection and positive CT findings are shown to have increased risk for pulmonary complications.

4.
Pakistan Journal of Medical and Health Sciences ; 16(8):192-195, 2022.
Article in English | EMBASE | ID: covidwho-2067748

ABSTRACT

Aim: To evaluate the pattern of surgical emergencies and surgical care provided during COIVD 19 pandemic. Study design: Cross-sectional Study Place and duration of study: Department of Surgery, CMH, Lahore from 15th March - 15 June 2020. Methodology: Data was collected retrospectively, of all the patients who were admitted in department of surgery over the duration of 3 months. Demographic variables, diagnosis, work up related to COVID-19, specialty of admission and surgical vs conservative management was recorded. Results: A total of 312 patients were included. Majority were male 216(69.2%). Most of the patients 191(61.2%) were admitted via clinic, predominantly in month of May 148(41%). COVID-19 PCR was done on 210 patients (67.3%), chest x-ray was done on 271(87.9%), HRCT chest was done on 113 patients (29.20%). Although general surgery was the busiest service line with a total patient admission of 89(43.1%), Orthopedic surgery top the operative interventions list with 85.1% of admissions underwent operative management. Conclusion: The current local guidelines about patient flow and management of patients in COVID crisis are practical and can be implemented. In the wake of the later waves of COVID 19 hospitals should prepare to divert their resources to high volume specialties like General and orthopedic surgery. Simple, but important procedures like arteriovenous fistula creation should only be stopped it there is shortage of manpower.

5.
Pakistan Journal of Medical and Health Sciences ; 16(8):88-91, 2022.
Article in English | EMBASE | ID: covidwho-2067739

ABSTRACT

Background: The COVID-19 first surfaced when cluster of pneumonia patients arose in Wuhan, Hubei Province, China. Although the current gold standard for COVID-19 diagnosis is reverse transcriptase-polymerase chain reaction (RT-PCR), chest x-ray (CXR) and computed tomography (CT) play a vital role in sickness diagnosis due to their limited sensitivity and availability. Aim: To evaluate retrospectively the role of CXR, the main radiological findings in it and its diagnostic accuracy in COVID-19 pneumonia. Methods: This is a cross sectional study involving 264 PCR positive COVID-19 patients with their clinical-epidemiological findings admitted at Ziauddin Hospital from May-July 2020. CXRs were taken as digital radiographs in our emergency department's isolation wards using the same portable X-ray device, according to local norms. CXRs were taken in two directions: antero-posterior (AP) and postero-anterior (PA). The hospitals' database had all of the images. To determine the number of radiological findings, multiple radiologists on duty completed an independent and retrospective examination of each CXR. In the event of disagreement, a mutual agreement was reached. SPSS version 20 was used for statistical analysis. Results: We were able to find 264 patients who met our criteria. With a mean age of 56.4214.89, the majority of individuals were determined to be males 189(71.6%) and females 75(28.4%). (Range of 16 to 87 years). 127 patients (48.1%) had severe illness symptoms and were admitted to the ICU, while the remaining 102(38.6%) had mild to moderate disease 35(13.3%). Diffuse (29.2%) and middle and lower co-existing distribution (25.8%) whereas just lower lobe (13.3%) were the most common predominance in severity. Peripheral involvement was also seen in (8.7%) cases. Conclusion: Both lungs are equally affected with the disease having the consolidation and opacifications while the effusion is the major complication in the severe cases. Diffuse involvement of the lung lobes is seen in the study followed by the middle and lower lobe involvement.

6.
Indian Journal of Forensic Medicine and Toxicology ; 16(3):63-68, 2022.
Article in English | EMBASE | ID: covidwho-2067687

ABSTRACT

Background: COVID-19 is a pandemic disease caused by droplet infection from SARS-CoV-2. Due to its rapid transmission and high case fatality rate, the identification of risk factors and prognostic factors is important. Obesity is a risk factor for poor outcomes in COVID-19. It is associated with chronic inflammation, disorders of the immune system. Obesity can be determined based on BMI. Chest X-Ray is supported in establishing the diagnosis and prognosis of COVID-19 patients. Assessment of the severity index of Chest X-Ray radiographs can use the Modified Chest X-Ray Scoring System of RSUP Dr. Soetomo. This study was conducted to analyze the relationship between BMI and chest radiography severity index in hospitalized COVID-19 patients at dr. Mohammad Hoesin Palembang in 2021. Methods: This research used a cross-sectional analytic observational design. Sampling was done using a consecutive sampling technique with 70 samples and obtained from the patient's medical record. The data were analyzed by univariate and bivariate (Chi-Square) using IBM SPSS Statistics 26 software. Results: Patients with BMI Overweight-Obesity had more in Moderate-Severe (18.6%) radiographic severity index scores (18.6%) than Normal-Mild (15.7%). Chi-Square bivariate analysis, BMI (p=0.033;p-value <0.05) had a significant relationship with the chest radiographic severity index with Odds Ratio 3,00, 95% CI (1,073–8,386). Conclusion: There is a significant relationship between body mass index and chest radiography severity index in COVID-19 patients. Overweight-Obesity BMI patients have a 3-fold chance of having a Moderate-Severe category of radiographic severity index compared to Underweight-Normal BMI patients.

7.
Italian Journal of Gynaecology and Obstetrics ; 34(3):172-179, 2022.
Article in English | EMBASE | ID: covidwho-2067679

ABSTRACT

Radiologic imaging in the evaluation of pregnant patients has significantly grown with the outbreak of the severe acute respiratory syndrome related to SARS-CoV-2 pandemic. Lung ultrasound is an emerging non-invasive bedside technique used to diag-nose interstitial lung syndrome through evaluation and quantitation of the number of B-lines, pleural irregularities and nodules or consolidations. In pregnant COVID-19 patients, lung ultrasound should be considered on ac-count of its various strengths, such as its being easily carried out bedside by trained sonographers for the monitoring of lung involvement in follow-ups, and its repeatability and affordability. However, pregnant patients could need chest radiography or computed tomo-graphic (CT) examinations for the diagnosis of pneumonia. Concerns and mis-conceptions about potential radiation-related risks for the embryo or fetus are still widespread among clinicians and can lead to excessive anxiety among pa-tients. Several well-recognized guidance documents were published in the last years as to the safety of a single-phase CT or an X-ray chest and related carcino-genic and teratogenic risk. This paper summarizes the safety of radiological examination for pneumonia in pregnant women affected by COVID 19, based on the estimated embryo-fetal radiation absorption per procedure (mGy).

8.
Journal of Pure and Applied Microbiology ; 16(3):1622-1627, 2022.
Article in English | EMBASE | ID: covidwho-2067515

ABSTRACT

Methicillin-resistant Staphylococcus aureus (MRSA) infections are a primary health concern. They are commonly differentiated as hospital-acquired methicillin-resistant Staphylococcus aureus (HA-MRSA) and community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) infections, based on their epidemiology, susceptibility findings, and molecular typing patterns. Therefore, appropriate contact precautions and isolation measures should be implemented. CA-MRSA mostly causes skin and soft-tissue infections, but the probability and incidence of it causing sepsis and invasive infections have increased dramatically in recent years. In this study, we report a case of CA-MRSA pneumonia with pan-pneumonic effusion in a 59-year-old male diabetic patient with preexisting comorbidities such as diabetic ketoacidosis and non-ST elevated myocardial infarction. The early reporting of the organism's identity and its antimicrobial susceptibility, as well as timely initiation of antibiotic therapy, aided in the successful management and cure of the patient.

9.
Iranian Journal of Neurology ; 19(4):122-130, 2020.
Article in English | EMBASE | ID: covidwho-2067436

ABSTRACT

Background: Few studies have reported the association of Guillain-Barre syndrome (GBS) and coronavirus disease-2019 (COVID-19) infection. In this study, we reported GBS in six patients infected with COVID-19 and reviewed all existing literature about GBS in association with COVID-19. Method(s): This study was performed in three referral centers of COVID-19 in Iran, and six patients with the diagnosis of GBS were enrolled. Patients enrolled in the study with acute progressive weakness according to the demyelinating or axonal variant of GBS, according to Uncini's criteria. Result(s): Four of our patients had axonal polyneuropathy, two patients had demyelinating polyneuropathy, and one patient required mechanical ventilation. All our patients had a favorable response to treatment. In one patient, the GBS symptoms recurred four months after the first episode. Conclusion(s): Limited case reports suggest a possible association between GBS and COVID-19. Such associations may be an incidental concurrence or a real cause-and-effect linkage;however, more patients with epidemiological studies are necessary to support a causal relationship. Copyright © 2020 Iranian Neurological Association, and Tehran University of Medical Sciences.

10.
NeuroQuantology ; 20(11):4357-4363, 2022.
Article in English | EMBASE | ID: covidwho-2067344

ABSTRACT

Background The entire world is combating COVID-19;however, a significant proportion of patients demonstrate the persistence of some COVID-19 symptoms, new symptom development, or exaggeration of pre-existing disease after a negative viral load. They are referred to as a post-COVID-19 syndrome. According to various researches, COVID-19 has a wide range of long-term effects on virtually all systems, including the respiratory, cardiovascular, gastrointestinal, neurological, mental, and dermatological systems. Finding the various symptoms of post-acute and chronic is critical since they might have a significant impact on the patients' everyday functioning. As a result, we aimed to distinguish the symptoms immediately after the initial phase in which the symptoms affected them for more than three weeks.The symptoms prolonged for a few weeks in post covid time are referred to as acute COVID-19 and the symptoms that persist with the affected individuals for more than three months are referred to as chronic COVID - 19. This paper was written as a review report to provide an overview of the nature and frequency of symptoms observed by patients with mild COVID-19 after the first three weeks. We also envisionedlooking at the various incidences and factors that contribute to the development of post-COVID-19 syndrome in different patient groups, as well as the chances of overcoming it. Objective The objective of this review paper is as follows: To establish the prevalence and characteristics of the post-COVID 19 syndrome in COVID-19 survivors, as well as the factors associated with persistent symptoms. To increase community knowledge about the type and frequency of persistent symptoms experienced by patients post serious and moderate COVID-19 infection. Methods The three-session questionnaire, which includes patient demographic data, vaccination status, and patient status during COVID-19, and post-COVID-19 syndrome, was provided to the public who recovered from COVID-19 and received their responses as primary data. The responses were evaluated to show the relationship between numerous factors that induce post-COVID-19 syndrome. Results A total of 136 responses were obtained and evaluated. This literature review comprised ten publications. As a result, the frequency of persistent symptoms in individuals following mild COVID-19 infection ranged from 15% to 45%. Symptoms reported in mild COVID-19 infected people can be classified as physical, mental, or social. Weakness was the most frequently mentioned consistent symptom. Dyspnea, cough, chest pain, headache, poor mental and cognitive state, and olfactory impairment were also reported as persistent symptoms. There was a significant impact seen in their employment and the daily functioning of the patients. Copyright © 2022, Anka Publishers. All rights reserved.

11.
NeuroQuantology ; 20(11):4252-4263, 2022.
Article in English | EMBASE | ID: covidwho-2067343

ABSTRACT

There is a huge the spread of Covid-19 pandemic (Corona) in large areas of the country, including modern and rural areas, and due to the scarcity of medical tools and supplies, especially in rural areas. Therefore, artificial intelligence researchers are using technologies to help detect disease early by using chest X-rays to classify whether or not the disease is present. Note that doctors have agreed in more than one scientific article that the initial examination to detect this disease is carried out through chest x-rays, the devices of which are available in most places.Because the Internet is available in most rural areas and in order to reduce the spread of this pandemic, in this paper we built a project by deep transfer learning using an application in Keras called "InceptionV3" on cloud, this model trained and tested 10 thousand images of people with the disease and others where the data distribution was equal to avoid From imbalanced data, and this model will be used across the cloud by web framework so that we can get proactive decisions and avoid spread. This model has been applied in the Department of Respiratory Medicine at Dr. ShankarraoChavan Government Hospital, Nanded, under the supervision of a medical staff headed by Dr. V. R. Kapse, associate professor and head of the department of pulmonary, we have obtained results after training and evaluating the model are training accuracy 97.6%, testing accuracy 97.5%, precision 97.8%, sensitivity 100% and specificity 99.9%. Copyright © 2022, Anka Publishers. All rights reserved.

12.
NeuroQuantology ; 20(11):684-699, 2022.
Article in English | EMBASE | ID: covidwho-2067331

ABSTRACT

Lung cancer (LC) is one of the most common malignant tumors, with rapid growth and early spread. LC is one of the most common malignant tumors. Lung cancer is a deadly disease, and early detection is essential. To achieve more precise diagnoses, cancer segmentation aids clinicians in determining the extent and location of cancer. But manually segmenting lung tumors from large medical images is a time-consuming and difficult task. A convolutional neural network (CNN)-based encoding network with position awareness is proposed in this study for automatically segmenting LC from computed tomography images. It is our model's design philosophy to change the usual link net architecture so that we can properly identify cancer. Our innovation resides in the manner we connect each encoder with decoder, in contrast to previous neural network topologies used for segmenting. During the encoder's many downsampling processes, spatial information is lost. By employing simply the encoder's down sampled output, it is impossible to retrieve this lost information Through the use of untrainable indices, the encoder and decoder are connected together. The output of an encoder may also be sent straight into a decoder, which can then execute segmentation on it.To conduct this study, a spatial attention-based encoder and a decoder that bypasses each encoder's input to the output of its related decoder were employed. Decoding and upsampling procedures will benefit from the spatial information that is recovered in this manner. With each layer of encoded information, the decoding process may require less parameter space, making it more efficient. Lung Image Database Consortium image collecting dataset obtained 98.5 percent accuracy in verifying the suggested system's performance. According to the study mentioned, a subjective comparison between the suggested approach and certain current methodologies is also carried out. Experiments have shown that the suggested method outperformed current technologies, allowing radiologist to more precisely locate a lung tumour while using it.

13.
NeuroQuantology ; 20(10):8436-8442, 2022.
Article in English | EMBASE | ID: covidwho-2067321

ABSTRACT

Covid-19 is a deadly viral infection disease that is affected in globally and causing large number of deaths. So, early treatment will possible to reduce the risk and death cases. In this paper, using deep learning technique to predict covid-19 based on using chest x-ray images. In this case using four CNN models as VGG16, Resnet50, Inception-V3, and Exception to predict and classify the covid infection. Create a web application using flask framework and user can upload the images and get the result of infection possibility covid or non-covid-19 case.

14.
NeuroQuantology ; 20(10):7542-7549, 2022.
Article in English | EMBASE | ID: covidwho-2067317

ABSTRACT

Background: CT is based on the fundamental principle that the density of the tissue passed by the x-ray beam can be measured from the calculation of the attenuation coefficient. Using this principle, CT allows the reconstruction of the density of the body, by a two-dimensional section perpendicular to the axis of the acquisition systemThe role of chest CT imaging in the management of patients with COVID-19 has evolved since the onset of the pandemic. Specifically, the description of CT scan findings, use of chest CT imaging in various acute and subacute settings, and its usefulness in predicting chronic disease have been defined better.In April 2020, the Fleischner Society released a multinational expert consensus statement that offered guidance to physicians on the use of thoracic imaging in various health care environments. The Society of Thoracic Radiology, the American College of Radiology, and the Radiological Society of North America offered additional guidance for the use of both plain chest radiography and CT imaging for patients suspected to have COVID-19. The GGO often lacks a rounded configuration. These opacities may lack a peripheral distribution. An atypical appearance is uncommonly associated with COVID-19 pneumonia and is more indicative of an alternate diagnosis, including bacterial pneumonia with or without cavitation, and tree-in-bud branching centrilobular nodules. The indeterminate pattern is observed mainly in elderly patients and is the most challenging.

15.
NeuroQuantology ; 20(9):1751-1763, 2022.
Article in English | EMBASE | ID: covidwho-2067287

ABSTRACT

Infectious disease Covid-19 is a fast-spreading virus that infects both human beings and animals. As a result of this condition, animals may get infected with the virus. This fatal viral illness has an impact on not only the day-to-day lives of people but also their health and the economy of the nation in which they live. There is currently no vaccination available for COVID-19, regardless of the fact it is a global epidemic that is growing rapidly across the globe. Since then, the virus has swiftly spread over the globe, turning into a pandemic (WHO, 2020), with the number of reported cases and fatalities connected with them continuing to rise on a daily basis. At the moment, more research on an efficient screening technique is necessary in order to diagnose instances of the virus and separate those who have been infected from the rest of the population. To limit the spread of the fatal virus and defend themselves from it, medical practitioners and specialists in many nations across the world are introducing multifunction testingto improve their treatment regimen and testing capacity. This is currently being done to enhance their capacity to detect the infection. When COVID-19-infected patients were studied in a clinical area, it was observed that they were often infected with respiratory illnesses. This conclusion was reached as a result of the findings of the study. Imaging techniques such as chest x- rays (also known as radiography) and chest CT scans are more accurate than other methods when it comes to detecting issues that are connected to the lungs. A thorough chest x-ray is less expensive than a chest CT, albeit. The most successful method of machine learning uses deep learning technologies. This is a great tool for analysing a large number of chest x-ray images, which could significantly affect the Covid-19 screening process. Copyright © 2022, Anka Publishers. All rights reserved.

16.
Journal of Clinical and Diagnostic Research ; 16(9):KD01-KD03, 2022.
Article in English | EMBASE | ID: covidwho-2067200

ABSTRACT

Being a highly contagious disease, Coronavirus Disease-2019 (COVID-19) has shown its impact throughout the world. Clinical manifestations are seen primarily involving the respiratory system. Fever, cough, fatigue, and breathlessness are the commonly seen symptoms. Several cases of COVID-19 manifest as viral pneumonia-induced Acute Respiratory Distress Syndrome (ARDS). COVID-19 symptoms appear not only during the course of the illness but also as its after effects. Long COVID-19 is said to be multisystem syndrome, categorised as postacute or chronic depending upon the time frame. It is characterized by the presence of symptoms beyond four weeks of the actual disease. Change in structural components in the lung leads to having a functional consequence on the body, affecting the cognitive, psychosocial, mental and physical well-being of the patients. Studies have shown alveolar damage same as ARDS. The most common pulmonary sequences seen are dyspnoea, cough (dry/with expectoration) and decreased diffusion capacity leading to reduced endurance. The present case report was of a 45-year-old nurse, who presented with the symptoms of postacute long COVID-19. Her previous scan of thorax showed a severity score of 11/25 after being tested COVID-19 positive. In view of the presenting complaints, a tailor-made pulmonary rehabilitation program was administered which showed great improvement in overall health condition. This case had been reported to document the effects of post COVID rehabilitation program on aspects such as functional capacity, quality of life, anxiety and depression using novel measures such as Incremental Shuttle Walk Test (ISWT), World Health Organisation Quality of Life-Brief Version (WHOQOL-BREF), and Depression, Anxiety and Stress Scale - 21 Items (DASS-21). Rehabilitation has been proven to be effective and safe in improving the exercise performance, quality of life affected due to COVID-19 and psychological function of the patients. Copyright © 2022 Journal of Clinical and Diagnostic Research. All rights reserved.

17.
Journal of Clinical and Diagnostic Research ; 16(9):OC21-OC24, 2022.
Article in English | EMBASE | ID: covidwho-2067195

ABSTRACT

Introduction: The clinical diagnosis of COVID-19 is supplemented by clinical severity indices. These indices are the National Early Warning Score (NEWS, which aids in risk stratification), CT severity score (radiological severity score), and Reverse Transcription-Polymerase Chain Reaction (RT-PCR) cycle threshold (Ct value, which provides a semi-quantitative measure of viral load). Aim(s): To assess the correlation between NEWS at admission, RT-PCR Ct value and CT severity score in mild and moderate COVID-19 patients. Methods and Materials: This prospective cohort study was conducted in Maulana Azad Medical College and Lok Nayak hospital, New Delhi, from January to June 2021. The study included 50 subjects (25 with mild COVID-19 and 25 with moderate COVID-19). NEWS was calculated at admission and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Ct value was estimated using real-time RT-PCR. CT severity score was calculated based on High Resolution Computed Tomography (HRCT) chest findings. The correlation among the parameters was determined using Pearson correlation formula. Result(s): The mean age of subjects in the mild and moderate COVID-19 groups were 49.52 years and 51.84 years, respectively. The mean RT-PCR Ct value of E gene was 24.48 and Rdrp gene was 24.56 in the mild COVID-19 group;while in the moderate group it was 23.72 for both E gene and Rdrp genes. The correlation between NEWS and Ct value of E gene (r-value=-0.06, p-value=0.68), Ct value of Rdrp gene (r-value=-0.03, p-value=0.79) and the correlation between CT severity score and Ct value of E gene (r-value=-0.05, p-value=0.73), Ct value of Rdrp gene (r-value=-0.06, p-value=0.68) was negative and insignificant. The mean CT severity score in mild COVID-19 group was 3.92, and in moderate COVID-19 group was 9.88. A significant positive correlation was found between the CT severity score and NEWS at admission. Conclusion(s): The clinical severity of COVID-19 as estimated by NEWS corroborates with CT severity score while the relationship between RT-PCR Ct value and clinicoradiological severity needs to be ascertained by further research. Copyright © 2022 Journal of Clinical and Diagnostic Research. All rights reserved.

18.
Open Access Macedonian Journal of Medical Sciences ; 10:1914-1921, 2022.
Article in English | EMBASE | ID: covidwho-2066688

ABSTRACT

BACKGROUND: The fluctuating COVID-19 cases among the pregnant women’s population encountered increased of cases and maternal mortality. AIM: This research aimed to describe the case of maternal deaths caused by COVID-19. CASE REPORT: We present nine serial cases of maternal death caused by COVID-19 who were admitted to Dr. Soetomo General Academic Hospital for 14 days in June. We found 32 positive COVID-19 obstetric cases and reported nine maternal deaths with a fatality rate of up to 28%. Seven of nine patients had reverse transcription-polymerase chain reaction–confirmed SARS-CoV-2 infection, while two had a positive antigen swab. Half of the patients ≥35 years old, and five of nine patients had Class I obesity as preexisting comorbidity. This study reported the death of pregnant woman at their 2nd trimester and 3rd trimester presenting infected by severe COVID-19. The usual symptoms are dyspnea, cough, fever, and decreased consciousness. The result of chest X-ray examination among eight patients showed bilateral pneumonia. Most of cases were referrals from a secondary hospital due to overload hospital capacity. Three patients were directly transferred to the tertiary hospital without receiving initial treatment. Eight of 9 patients (88.9%) were transferred to intensive care unit and intubated due to low oxygen saturation. CONCLUSION: In conclusion, the limited hospital facility and lack of intensive care capacity for obstetric cases during the second wave of the COVID-19 pandemic may enhance the probability of mortality and morbidity in pregnant women infected by COVID-19.

19.
Open Access Macedonian Journal of Medical Sciences ; 10:217-221, 2022.
Article in English | EMBASE | ID: covidwho-2066680

ABSTRACT

INTRODUCTION: The first data for COVID-19 in pregnancy showed mild-to-moderate forms of the disease while the current data speak of severe forms in these subjects. Here, we present a case of a severe form of COVID-19 in a gemelar pregnant woman complicated with pneumomediastinum and pneumothorax, during her hospital stay, in a late stage of disease. CASE PRESENTATION: A 38-year-old multiparous woman was referred to university hospital at 25 weeks of gemelar pregnancy. On admission, the patient presented with signs of moderate respiratory insufficiency, which after 12 h progressed further to severe ARDS. She tested positive for SARS-CoV-2 on quantitative real-time polymerase chain reaction. Under these conditions, it was decided that the patient undergoes a cesarean section for termination of pregnancy. Remdesivir 200 mg/day and tocilizumab 8 mg/kg were administered, based on national guidelines. The patient’s fever subsided, but her SpO2 remained at 94%, even with a 15 L/min oxygen mask. After 12 days, the patient complains of a severe back pain and her respiratory condition rapidly worsened and reduced saturations up to 80% being under O2 therapy with facial mask with 15 l/min. Chest CT findings confirmed pneumomediastinum and pneumothorax, which deteriorated the patient’s status. Thereafter, tube thoracostomy was performed. There was a clinical and ABG analysis parameter’s improvement. The patient was discharged 34 days after cesarean delivery with a proper general health. CONCLUSION: Our case highlights even more convincingly the fact that, in pregnancy, can be severe to life-threating forms of COVID-19. Pneumothorax and pneumomediastinum are complications that can be encountered even in the late stages of severe forms cases with COVID-19 in pregnancy. Early diagnosis of these complications is essential in adequate management and treatment to avoid fatal outcome.

20.
Open Access Macedonian Journal of Medical Sciences ; 10(C):246-251, 2022.
Article in English | EMBASE | ID: covidwho-2066676

ABSTRACT

BACKGROUND: Pregnancy state affects the immune regulation including physical barrier, innate, and adaptive immunity-related to susceptibility of infections and increasing risk for severe to critical case of COVID-19. Further, high risk of thrombosis becomes a challenge in the management of COVID19 in pregnancy due to the strong association with worse outcome. CASE REPORT: Here, we present three cases of pregnant women infected with COVID-19 pneumonia with different outcomes in maternal and fetal condition related to high-risk thrombosis. Serial inflammatory markers were needed to the early detect the disease progressivity in pregnant women with COVID-19. Further, complete assessment of fetus including reverse transcriptase-polymerase chain reaction and chest X-ray must be performed to the early diagnosis of COVID-19 in neonatal whose mother was infected by SARS-CoV-2. CONCLUSION: Pregnancy state affects the immune regulation including physical barrier, innate, and adaptive immunity-related to susceptibility of infections and increasing risk for severe to critical case of COVID-19. Further, high risk of thrombosis becomes a challenge in the management of COVID19 in pregnancy due to the strong association with worse outcome. Although fetal transmission of COVID-19 to fetus remains unclear, complete assessment of fetus including RT-PCR, and chest X-ray must be performed to the early diagnosis of COVID-19 in neonatal whose mother was infected by SARS-CoV-2.

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