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1.
Medical Visualization ; 25(1):14-26, 2021.
Article in Russian | EMBASE | ID: covidwho-20245198

ABSTRACT

Research goal. Comparative characteristics of the dynamics of CT semiotics and biochemical parameters of two groups of patients: with positive RT-PCR and with triple negative RT-PCR. Reflection of the results by comparing them with the data already available in the literature. The aim of the study is to compare the dynamics of CT semiotics and biochemical parameters of blood tests in two groups of patients: with positive RT-PCR and with triple negative RT-PCR. We also reflect the results by comparing them with the data already available in the literature. Materials and methods. We have performed a retrospective analysis of CT images of 66 patients: group I (n1 = 33) consists of patients who had three- time negative RT-PCR (nasopharyngeal swab for SARS-CoV-2 RNA) during hospitalization, and group II (n2 = 33) includes patients with triple positive RT-PCR. An important selection criterion is the presence of three CT examinations (primary, 1st CT and two dynamic examinations - 2nd CT and 3rd CT) and at least two results of biochemistry (C-reactive protein (CRP), fibrinogen, prothrombin time, procalcitonin) performed in a single time interval of +/- 5 days from 1st CT, upon admission, and +/- 5 days from 3st CT. A total of 198 CT examinations of the lungs were analyzed (3 examinations per patient). Results. The average age of patients in the first group was 58 +/- 14.4 years, in the second - 64.9 +/- 15.7 years. The number of days from the moment of illness to the primary CT scan 6.21 +/- 3.74 in group I, 7.0 (5.0-8.0) in group II, until the 2nd CT scan - 12.5 +/- 4, 87 and 12.0 (10.0-15.0), before the 3rd CT scan - 22.0 (19.0-26.0) and 22.0 (16.0-26.0), respectively. In both groups, all 66 patients (100%), the primary study identified the double-sided ground-glass opacity symptom and 36 of 66 (55%) patients showed consolidation of the lung tissue. Later on, a first follow-up CT defined GGO not in all the cases: it was presented in 22 of 33 (67%) patients with negative RT-PCR (group I) and in 28 of 33 (85%) patients with the positive one (group II). The percentage of studies showing consolidation increased significantly: up to 30 of 33 (91%) patients in group I, and up to 32 of 33 (97%) patients in group II. For the first time, radiological symptoms of "involutional changes" appeared: in 17 (52%) patients of the first group and in 5 (15%) patients of the second one. On second follow-up CT, GGO and consolidations were detected less often than on previous CT: in 1 and 27 patients of group I (3% and 82%, respectively) and in 6 and 30 patients of group II (18% and 91%, respectively), although the consolidation symptom still prevailed significantly . The peak of "involutional changes" occurred on last CT: 31 (94%) and 25 (76%) patients of groups I and II, respectively.So, in the groups studied, the dynamics of changes in lung CT were almost equal. After analyzing the biochemistry parameters, we found out that CRP significantly decreased in 93% of patients (p < 0.001) in group I;in group II, there was a statistically significant decrease in the values of C-reactive protein in 81% of patients (p = 0.005). With an increase in CT severity of coronavirus infection by one degree, an increase in CRP by 41.8 mg/ml should be expected. In group I, a statistically significant (p = 0.001) decrease in fibrinogen was recorded in 77% of patients;and a similar dynamic of this indicator was observed in group II: fibrinogen values decreased in 66% of patients (p = 0.002). Such parameters as procalcitonin and prothrombin time did not significantly change during inpatient treatment of the patients of the studied groups (p = 0.879 and p = 0.135), which may indicate that it is inappropriate to use these parameters in assessing dynamics of patients with a similar course of the disease. When comparing the outcomes of the studied groups, there was a statistically significant higher mortality in group II - 30.3%, in group I - 21.2% (p = 0.043). Conclusion. According to our data, a course of the disease does not significantly differ in the groups o patients with positive RT-PCR and three-time negative RT-PCR. A negative RT-PCR analysis may be associated with an individual peculiarity of a patient such as a low viral load of SARS-CoV-2 in the upper respiratory tract. Therefore, with repeated negative results on the RNA of the virus in the oro- and nasopharynx, one should take into account the clinic, the X-ray picture and biochemical indicators in dynamics and not be afraid to make a diagnosis of COVID-19.Copyright © 2021 ALIES. All rights reserved.

2.
Archives of Pediatric Infectious Diseases ; 11(2) (no pagination), 2023.
Article in English | EMBASE | ID: covidwho-20242270

ABSTRACT

Introduction: Spontaneous pneumothorax is a rare complication of coronavirus disease 2019 (COVID-19), primarily reported in adults. Pediatric cases with bilateral pneumothorax are much less reported. Case Presentation: We presented the case of a five-year-old previously healthy boy who developed persistent fever, abdominal pain, generalized maculopapular rash, and dyspnea before admission. His chest computed tomography (CT) showed a viral involvement pattern of pneumonia suggestive of COVID-19. Subsequently, he was confirmed with multisystem inflammatory syndrome in children (MIS-C). While he responded well to the therapies, on the fifth day of admission, he developed respiratory distress again. A chest roentgenogram showed bilateral spontaneous pneumothorax. Bilateral chest tubes were inserted, and his condition improved sig-nificantly after five days of admission to the intensive care unit. Two weeks later, he was discharged in good condition. Conclusion(s): Children with MIS-C associated with COVID-19 may develop primary spontaneous pneumothorax. Owing to the clinical picture overlapping with MIS-C associated with COVID-19, the timely diagnosis of pneumothorax may be challenging in such patients.Copyright © 2022, Author(s).

3.
Shiraz E Medical Journal ; 24(4) (no pagination), 2023.
Article in English | EMBASE | ID: covidwho-20241778

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) pandemic and its associated morbidities are a great global concern. Diabetes mellitus (DM) is associated with adverse clinical outcomes and high mortality in patients with COVID-19. Objective(s): This study examined the frequency of BM, newly diagnosed hyperglycemia, and their impacts on hospitalized patients with COVID-19. Method(s): This retrospective study examined 810 medical records of PCR-confirmed COVID-19 patients admitted to Razi Hospital, Ahvaz, Iran. The clinical presentations, severity, and impacts of COVID-19 were compared between patients with and without DM. Disease severity was determined based on the NEWS2 scoring system. Result(s): This study included 810 medical records of COVID-19 patients, of whom 326 had pre-existing DM, and 484 were non-DM. The rates of diabetes and newly diagnosed hyperglycemia were 40.2% and 11.2%, respectively. The most common underlying diseases were hypertension (35.3%), ischemic heart disease (17.9%), and chronic kidney disease (11.9%), which were higher in people with diabetes than non-diabetics. The rate of acute kidney injury was higher in patients with diabetes than in non-diabetics (30.7% vs. 19.2%;P < 0.001) and in patients with severe COVID-19 than in those whose disease was not severe (27.8% vs. 21.5%;P = 0.04). The rates of severe COVID-19 (46.3% vs. 34.7%;P = 0.093), ICU admission (40.7% vs. 27.4%;P = 0.012), and mortality (18.5% vs. 10.5%;P = 0.079) were higher in patients with newly diagnosed hyperglycemia than in euglycemic patients. Conclusion(s): This study showed that COVID-19 infection is linked with newly diagnosed hyperglycemia and pre-existing DM, both associated with severe COVID-19, more need for ICU admission, and mortality.Copyright © 2023, Author(s).

4.
Pharmaceutical and Biomedical Research ; 6(SpecialIssue1):17-26, 2020.
Article in English | EMBASE | ID: covidwho-20241664

ABSTRACT

Coronavirus Disease 2019 (COVID-19) is an emerging disease with a rapid increase in cases and deaths since its first discovery in December 2019, in Wuhan, China. Limited data are available on COVID-19 effects during pregnancy;however, information on diseases associated with other highly pathogenic coronaviruses (i.e. Severe Acute Respiratory Syndrome [SARS] and the Middle East respiratory syndrome [MERS]) may provide insight into the effects of COVID-19 during pregnancy. Coronaviruses cause illnesses ranging from the common cold to severe respiratory disease and death. The data indicate an average of 5 days incubation period (range: 2-14 days). The average age range of the hospitalized patients was 49-56 years, and a third to half of them have an underlying illness. Children were rarely mentioned. Within hospitalized cases, men were more frequent (54%-73%). Fever, cough, myalgia, vomiting, and diarrhea are common symptoms. This review aims at giving an in-depth understanding of COVID-19 by comparing its effects with SARS and MERS to evaluate its severity in pregnant women1. The results of varied studies show that COVID-19 affects pregnant women seriously and there is an alarming need to look into this aspect to prevent its harmful effects on the fetus.Copyright © 2020

5.
Acta Medica Iranica ; 61(3):194-195, 2023.
Article in English | EMBASE | ID: covidwho-20239991
6.
Cancer Research, Statistics, and Treatment ; 5(1):19-25, 2022.
Article in English | EMBASE | ID: covidwho-20239094

ABSTRACT

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.

7.
Cancer Research, Statistics, and Treatment ; 5(2):361-362, 2022.
Article in English | EMBASE | ID: covidwho-20238218
8.
Cancer Research, Statistics, and Treatment ; 5(1):116-118, 2022.
Article in English | EMBASE | ID: covidwho-20237640
9.
Annals of Clinical and Analytical Medicine ; 13(1):25-29, 2022.
Article in English | EMBASE | ID: covidwho-20235095

ABSTRACT

Aim: The gold standard diagnostic method for the diagnosis of COVID-19 is based on the demonstration of viral RNA in samples taken from the upper respiratory tract in reverse transcriptase-polymerase chain reaction (RT-PCR). However, in emergencies, the World Health Organization (WHO) also recommends to use computed tomography (CT) in order to reduce the loss of time and to provide rapid diagnosis, treatment and isolation of suspicious cases. In our study, we aimed to compare the laboratory values of patients with PCR negative CT findings and PCR positive patients. Material(s) and Method(s): The medical records of 1280 COVID-19 patients registered at our Family Medicine Center were reviewed retrospectively. Result(s): In our study, it was found that 66,70 % of PCR-negative patients with CT findings were aged 60 years and older, and 50.70% of PCR-positive COVID-19 patients were between the ages of 40-59 years;61.30% of the patients with CT findings and 48% of the PCR-positive patients were male;73% of PCR-positive patients had lung involvement. When CRP, fibrinogen and D-dimer values were examined, it was found that in PCR-negative COVID-19 patients with CT findings these values were statistically significantly higher. Discussion(s): Although the definitive diagnosis of the disease is made using a PCR test, it should not be overlooked that the patients may remain PCR negative, and it should not be forgotten that thoracic tomography findings are a good diagnostic method for this group.Copyright © 2022, Derman Medical Publishing. All rights reserved.

10.
Open Access Macedonian Journal of Medical Sciences ; 11(B):314-319, 2023.
Article in English | EMBASE | ID: covidwho-20232646

ABSTRACT

BACKGROUND: Thoracic computed tomography (CT) scan plays a role in detecting and assessing the progression of COVID-19. It can evaluate the response to the therapy given. In diagnosis, the CT scan of the chest may complement the limitations of reverse transcription polymerase chain reaction (RT-PCR). Several recent studies have discussed the importance of CT scans in COVID-19 patients with false-negative RT-PCR results. The sensitivity of chest CT scan in the diagnosis of COVID-19 is reportedly around 98%. AIM: This study aimed to determine the compatibility of CT scan of the thorax with RT-PCR in suspected COVID-19 patients. MATERIALS AND METHODS: This research was conducted in the Radiology Department of the Wahidin Sudirohusodo Hospital Makassar from April to December 2020 with 350 patients. The method used was a 2 x 2 table diagnostic test. RESULT(S): The study included 188 male patients (53.7%) and 162 female patients (46.2%). The most common age group was 46-65 years (35.4%). The most common types of lesions were ground-glass opacity (163 cases), consolidation (128 cases), and fibrosis (124 cases), mostly found in the inferior lobe with a predominantly peripheral or subpleural distribution. The sensitivity of the CT scan to the PCR examination was 86%, and the specificity was 91%. CONCLUSION(S): Thoracic CT scan was a good modality in establishing the diagnosis of COVID-19. CT scan of the chest with abnormalities could confirm the diagnosis in 88% of cases based on RT-PCR examination. It excluded the diagnosis in 91% based on the RT-PCR examination. The accuracy of the thoracic CT scan was 88% with RT-PCR as the reference value.Copyright © 2023 Sri Asriyani, Albert Alexander Alfonso, Mirna Muis, Andi Alfian Zainuddin, Irawaty Djaharuddin, Muhammad Ilyas.

11.
AIP Conference Proceedings ; 2776, 2023.
Article in English | Scopus | ID: covidwho-20231983

ABSTRACT

The coronavirus has spread fast resulting in a worldwide pandemic. Early discovery of positive patients is critical in preventing the pandemic from spreading further, leading to the development of diagnostic technologies that provide rapid and reliable responses for COVID-19 detection. Previous research has shown that chest x-rays are an essential tool for the detection and diagnosis of sirivanoroC (COVID-19) patients. A radiological finding known as ground-glass opacity (GGO), which causes color and texture changes, was discovered in the lung of a person with COVID-19 as a consequence of x-ray tests. An automatic method to assist radiologists is required due to the carelessness of radiologists who work a long time and misdiagnosis resulting in the confusion of findings with different diseases, in this study, were described a new technique to help us with the early diagnosis of COVID-19 using x-rays that is based on fuzzy classification. The skewness, kurtosis, and average statistical features of x-rays of patients in two classes, COVID and Normal, are calculated in the suggested method, and the value ranges for both classes are identified. In the building of a fuzzy logic classifier, three statistical characteristics and value ranges are used as membership functions. The suggested solution, which uses a user-friendly interface, allows for quick and accurate COVID vs Normal (binary classification). Experiments show that our method has a lot of promise for radiologists to validate their initial screening and enhance early diagnosis, isolation, and therapy, which helps prevent infection and contain the pandemic. © 2023 Author(s).

12.
Front Med (Lausanne) ; 10: 1125530, 2023.
Article in English | MEDLINE | ID: covidwho-20243521

ABSTRACT

Introduction: Chest computed tomography (CT) is suitable to assess morphological changes in the lungs. Chest CT scoring systems (CCTS) have been developed and use in order to quantify the severity of pulmonary involvement in COVID-19. CCTS has also been correlated with clinical outcomes. Here we wished to use a validated, relatively simple CTSS to assess chest CT patterns and to correlate CTSS with clinical outcomes in COVID-19. Patients and methods: Altogether 227 COVID-19 cases underwent chest CT scanning using a 128 multi-detector CT scanner (SOMATOM Go Top, Siemens Healthineers, Germany). Specific pathological features, such as ground-glass opacity (GGO), crazy-paving pattern, consolidation, fibrosis, subpleural lines, pleural effusion, lymphadenopathy and pulmonary embolism were evaluated. CTSS developed by Pan et al. (CTSS-Pan) was applied. CTSS and specific pathologies were correlated with demographic, clinical and laboratory data, A-DROP scores, as well as outcome measures. We compared CTSS-Pan to two other CT scoring systems. Results: The mean CTSS-Pan in the 227 COVID-19 patients was 14.6 ± 6.7. The need for ICU admission (p < 0.001) and death (p < 0.001) were significantly associated with higher CTSS. With respect to chest CT patterns, crazy-paving pattern was significantly associated with ICU admission. Subpleural lines exerted significant inverse associations with ICU admission and ventilation. Lymphadenopathy was associated with all three outcome parameters. Pulmonary embolism led to ICU admission. In the ROC analysis, CTSS>18.5 significantly predicted admission to ICU (p = 0.026) and CTSS>19.5 was the cutoff for increased mortality (p < 0.001). CTSS-Pan and the two other CTSS systems exerted similar performance. With respect to clinical outcomes, CTSS-Pan might have the best performance. Conclusion: CTSS may be suitable to assess severity and prognosis of COVID-19-associated pneumonia. CTSS and specific chest CT patterns may predict the need for ventilation, as well as mortality in COVID-19. This can help the physician to guide treatment strategies in COVID-19, as well as other pulmonary infections.

13.
Int J Gen Med ; 16: 2337-2348, 2023.
Article in English | MEDLINE | ID: covidwho-20242882

ABSTRACT

Introduction: Currently, infection control measures for SARS-COV2 are being relaxed, and it is important in daily clinical practice to decide which findings to focus on when managing patients with similar background factors. Methods: We retrospectively evaluated 66 patients who underwent blood tests (complete blood count, blood chemistry tests, and coagulation tests) and thin slice CT between January 1 and May 31, 2020, and performed a propensity score-matched case-control study. Cases and controls were a severe respiratory failure group (non-rebreather mask, nasal high-flow, and positive-pressure ventilation) and a non-severe respiratory failure group, matched at a ratio of 1:3 by propensity scores constructed by age, sex, and medical history. We compared groups for maximum body temperature up to diagnosis, blood test findings, and CT findings in the matched cohort. Two-tailed P-values <0.05 were considered statistically significant. Results: Nine cases and 27 controls were included in the matched cohort. Significant differences were seen in maximum body temperature up to diagnosis (p=0.0043), the number of shaded lobes (p=0.0434), amount of ground-glass opacity (GGO) in the total lung field (p=0.0071), amounts of GGO (p=0.0001), and consolidation (p=0.0036) in the upper lung field, and pleural effusion (p=0.0117). Conclusion: High fever, the wide distribution of viral pneumonia, and pleural effusion may be prognostic indicators that can be easily measured at diagnosis in COVID-19 patients with similar backgrounds.

14.
Cureus ; 15(5): e38437, 2023 May.
Article in English | MEDLINE | ID: covidwho-20236634

ABSTRACT

Introduction Despite the fact that smoking has been identified as a risk factor for respiratory diseases and lung infections, the relationship between smoking and coronavirus severity remains ambiguous. It is believed that smoking is a risk factor for pulmonary infections. However, the effect of smoking on COVID-19 patients is still controversial. Objective The aim of the study was to identify and analyze the distinct radiological features in COVID-19 patients with different smoking statuses. Additionally, the study sought to examine the association between smoking and the severity of pulmonary changes. Methods A retrospective cohort study of 111 patients who were referred to Al-Salt/Hussein Hospital, Al-Salt, Jordan, from January to June 2021, with a confirmed COVID-19 diagnosis and smoking status recorded. Patients' demographics, medical history, age, gender, comorbidity, and length of hospitalization were obtained from their medical records. Results Study groups were similar in median age, prevalence of chosen chronic diseases, and median length of hospital stay. Based on the median scores of the radiological findings in each lung lobe, no statistically significant differences were found between the scores and smoking status (p-values of >0.05; Mann-Whitney test). Conclusion Smoking is an independent risk factor for the severity of COVID-19. Smoking has no noticeable impact on interstitial manifestation in COVID-19 patients.

15.
Canadian Journal of Respiratory, Critical Care, and Sleep Medicine ; 7(1):36-40, 2023.
Article in English | EMBASE | ID: covidwho-2324856

ABSTRACT

Autoimmune pulmonary alveolar proteinosis (PAP) is a rare disease, especially in pediatrics, but important to consider, as it may avoid unnecessary and/or invasive investigations and delayed diagnosis. This case report highlights an adolescent girl with rapid onset dyspnea but an unremarkable physical exam and initial testing. However, due to a high index of suspicion, a chest computed tomography (CT) scan was done, revealing a "crazy paving" pattern, which then prompted expedited assessment. This finding, however, is not as specific as often discussed and has a broad differential diagnosis, which will be reviewed in detail as part of this case. Furthermore, this report demonstrates a diagnostic approach for PAP that avoids lung biopsy, previously considered to be required for diagnosis of PAP, but is increasingly becoming unnecessary with more advanced blood tests and understanding of their sensitivity and specificity. Additionally, management strategies for PAP will be briefly discussed.Copyright © 2022 Canadian Thoracic Society.

16.
China Tropical Medicine ; 21(3):255-258, 2021.
Article in Chinese | EMBASE | ID: covidwho-2327351

ABSTRACT

Objective To analyze the clinical features of patients with coronavirus disease 2019COVID-19in Wuhan, and we provide reference for further prevention and control of the disease. Methods We collected the clinical data of patients with COVID-19 in Dongxihu Shelter Hospital of Wuhan from February 7 to March 6, 2020. The main symptoms, blood test results, lung CT results, and nucleic acid negative conversion were analyzed. Results A total of 654 patients were included, 17526.76%were mild, and 47973.24%were general. There were 344 males (52.60%), and 310 females (47.40%). The patients were with a mean age of49.36+/-10.30years, and 97 patients (14.83%) with a history of hypertension, 51 patients (7.80%) had a history of diabetes. The main clinical symptoms were fever with 547(83.64%) patients, 186 cases (28.44%) had chills, 15 cases (2.29%) had shiver, 342(52.29%) had fatigue symptoms, 413(63.15%) had cough, 137(20.95%) had chest tightness, and 109(16.67%) had diarrhea during the course of the disease. Blood routine tests of 395 patients, the white blood cell count (WBC) was (4.12+/-1.46)x109/L. The total white blood cell count was normal in 378 cases(95.70%), increased in 7(1.77%), and decreased in 10(2.53%). The lymphocyte percentage was (23.10+/-10.02)%, lymphocyte1.06+/-0.37x109/L. The percentage and count of lymphocyte were low. All the 654 cases were examined by CT, 175 cases (26.76%) showed normal lung CT, 422 cases (64.52%) showed patchy or segmental ground-glass opacity, and 57 cases (8.72%) showed multilobar consolidation, ground-glass shadow coexisted with consolidation or streak shadow. The interval between positive nucleic acid test before admission and negative test after admission was as short as 5 days and as long as 24 days, the average was (12.35+/-3.73) days. Conclusion Fever, coughing, and fatigue are the main symptoms in patients with COVID-19. The typical lung CT findings can be used as the basis for clinical diagnosis and disease evaluation. Patients with mild and common type had better prognosis.Copyright © 2021 Editorial Office of Chinese Journal of Schistosomiasis Control. All rights reserved.

17.
The Egyptian Journal of Radiology and Nuclear Medicine ; 51(1):105, 2020.
Article in English | ProQuest Central | ID: covidwho-2319631

ABSTRACT

BackgroundCoronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Chest computed tomography (CT) plays an essential role in the evaluation of COVID-19. This retrospective study aims to determine and compare the pulmonary changes in Iraqi patients with COVID-19 disease across the first two weeks after onset of symptoms using computerized tomography (CT) scan.Ninety-six patients with COVID-19 disease were enrolled in this study. Patients were divided into two groups according to the duration of symptoms (the first group has been scanned within the first week of presentation while the second group has been scanned in the second week).ResultsThe CT findings in the first and second group were as follows: ground glass opacity (GGO) were 94.3% vs. 88.5%, consolidation were 25.7% vs. 34.6%, broncho vascular thickening were 18.6% vs. 7.7%, crazy paving appearance were 15.7% vs. 3.8%, tree-in-bud appearance were 4.3% vs. 10.7%, pulmonary nodules were 5.1% vs. 7.7%, and bronchiectasis were 5.5% vs. 7.7%. Pleural effusion and cavitation were seen only in the first group (2.9% and 1.4% respectively).The distribution of CT changes across the two groups were as follows: bilateral changes were 85.7% vs. 100%;central distribution were 11.4% vs. 11.5%;peripheral distribution were 64.3% vs. 42.3%, and diffuse (central and peripheral) distribution were 24.3% vs. 46.2% while multilobar distribution were 70% vs. 80.8%.ConclusionThe type, extent, and distributions of pulmonary manifestations associated with COVID-19 infection are significantly different between the two groups who have been scanned in different stages of the disease.

18.
Annals of African Surgery ; 20(1):32-36, 2023.
Article in English | EMBASE | ID: covidwho-2318875

ABSTRACT

Coronavirus 2019 (COVID-19) is a predominantly respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It creates a hypercoagulable milieu, manifesting at varied extrapulmonary sites as pulmonary embolism, deep venous thrombosis, stroke, myocardial infarction, and mesenteric ischemia. The pathophysiology behind this hypercoagulability is still not entirely understood, although a heightened systemic inflammatory response to the virus is deemed responsible. We herein report a case of a 36-year-old healthy male who presented with an acute abdomen and was found to have extensive mesenteric and portal venous thrombosis with bowel gangrene. The patient underwent emergency exploration with ileal resection and end-ileostomy. The hypercoagulability panel was negative, but a postoperative chest radiograph revealed suspicious ground-glass opacities. Given the ongoing global COVID-19 pandemic, we considered testing for SARSCoV-2. A positive test for SARS-CoV-2 led us to attribute the thrombotic event to COVID-19. With anticoagulation and supportive therapy, the patient went on to make a steady recovery. A non-specific clinical manifestation of COVID-19 necessitates considering mesenteric venous thrombosis as a differential diagnosis in patients with acute abdomen.Copyright © 2023 Author.

19.
International Journal of Cancer Management ; 16(1) (no pagination), 2023.
Article in English | EMBASE | ID: covidwho-2317270

ABSTRACT

Introduction: The coronavirus disease 2019 (COVID-19) mainly causes pulmonary disease. However, extrapulmonary manifesta-tions, which affect the gastrointestinal tract and hepatobiliary system, have been reported. Case Presentation: Here we reported a 4-year-old boy with acute lymphoblastic leukemia and abdominal pain who had acute necrotic pancreatitis secondary to COVID-19. Conclusion(s): According to the COVID-19 epidemic, if drug-induced pancreatitis is ruled out, viral causes, especially COVID-19, should be considered.Copyright © 2023, Author(s).

20.
2023 International Conference on Intelligent Systems, Advanced Computing and Communication, ISACC 2023 ; 2023.
Article in English | Scopus | ID: covidwho-2293183

ABSTRACT

The severity of the nCOVID infection relies on the presence of Ground Glass Opacities (GGO) present in the patient's chest CT scan images. Although, detecting and delineating the precise boundaries of GGO in the chest CT images is challenging. Here, we proposed a fast and novel technique to automatically segment the regions containing GGO in lung CT images using mathematical morphology. We have tested our algorithm on the chest CT images of 145 Covid-positive cases. This unique segmentation approach correctly segments the lung field from chest CT images and identifies GGO with average sensitivity, specificity, and accuracy of 96.89%, 95.23%, and 97.22%, respectively. We used expert radiologists' hand-curated segmentation of GGO as ground truth for quantificational performance analysis. Our research results indicate that this algorithm performs well found in the literature. © 2023 IEEE.

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