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1.
Advances in Human Biology ; 12(3):329-332, 2022.
Article in English | Web of Science | ID: covidwho-2110431

ABSTRACT

Obesity is widely reported to be associated with a higher risk of the severity and worse clinical outcome of COVID-19. With the global prevalence of obesity, exploring the relationship between obesity and the severity of COVID-19 disease is of major clinical importance, thus requiring increased attention to preventive measures in susceptible individuals. Studies have shown that obesity is associated with increased risk of hospitalisation, intensive care unit admission, integrated motivational-volitional requirement and mortality among patients with COVID-19. The pathophysiological mechanisms which cause disease severity and adverse outcomes among obese subjects remain unclear. Recently, it was shown that elevated leptin levels correlate positively with the severity and progression of disease in COVID-19 patients. Leptin modulates both the innate and adaptive immune responses in cells. Elevated leptin levels in obese individuals may contribute to worse symptoms and outcomes in COVID-19 disease. Emerging evidence suggests that alpha-1 (alpha 1)-adrenergic receptor stimulation increases leptin secretion, while the administration of alpha 1-adrenergic receptor antagonists is reported to reduce plasma leptin levels in human subjects. Therefore, alpha 1-adrenergic receptor antagonists may improve clinical outcomes in obesity patients with COVID-19 infection through modulation of hyperinflammation and reduction of plasma leptin levels. The aim of this minireview is to delineate the potential beneficial therapeutic effects of alpha 1-adrenergic receptor antagonists in preventing adverse outcomes of coronavirus infection in obese patients. Large, randomised trials are needed to confirm the beneficial effects and safety profile of the use of alpha 1-adrenergic receptor antagonists in obese patients with COVID-19.

3.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2005718

ABSTRACT

Background: Patients (pts) with cancer are at a higher risk of COVID-19 (C19) severe disease. However, our group and others have demonstrated a low prevalence of C19 infection among asymptomatic pts with cancer on active systemic treatment. We hypothesized this phenomenon was due to increased adherence of pts with cancer to anti-C19 protective measures. This study compares adherence and the perceived importance of such measures in oncologic and non-oncologic populations. Methods: This is a cross-sectional study conducted between June and September 2021. A questionnaire was developed to assess how participants perceived and adhered to masking, handwashing, and other anti-C19 protective measures. Demographic information, educational level, and monthly income were also collected. Three groups were included: A) pts with cancer treated at Hospital de Base (HB);B) pts without cancer treated at HB for other medical conditions;C) a healthy outpatient population. Data were summarized in means, medians, and proportions. Chi-squared or Fisher's exact test was used to compare categories;ANOVA was employed to compare means. A multivariable analysis assessing factors associated with adherence to anti-C19 protective measures was performed. Results: A total of 607 people were interrogated (200 in groups A and B, and 207 in C). The mean age of groups A, B, C was significantly different: 60 vs. 52 vs. 35 years old (p < 0.001). Group C had a higher educational level and a higher monthly income than groups A and B (p < 0.001). In cohort A, gastrointestinal, breast, and genitourinary were the most frequent tumors (33%, 31%, 15%);75% of pts had active disease. Pts with cancer were more adherent to anti-C19 protective measures: of 33 points, the mean score of groups A, B, C was respectively 27.8 vs. 25.5 vs. 21.9 (p < 0.001). Regarding the importance of anti-C19 protective measures, pts with cancer also perceived those as more relevant: of 21 points, the mean score of groups A, B, C was respectively 17.8 vs. 17 vs. 16.9 (p < 0.001). For instance, in group A, 95% report consistently wearing a mask when leaving home compared to 90% and 58.2% of groups B and C. In line with our findings, 20.5% vs. 32.5% vs. 35.3% (p < 0.003) of groups A, B, and C reported having C19 before the questionnaire. In multivariable analysis, groups B and C were less likely to adhere to anti-C19 protective measures than group A. Conclusions: Pts with cancer are more adherent to anti- C19 protective measures and perceive them as more important than non-oncologic populations. Our results shed light on the accumulating literature of a low incidence of C19 amongst asymptomatic pts with cancer on systemic treatment even during the surges. Such findings are possibly related to the fact that cancer pts are more vulnerable to hospitalizations and unfavorable outcomes than the general population, prompting a more risk-averse behavior.

4.
Egyptian Journal of Medical Human Genetics ; 23(1), 2022.
Article in English | EMBASE | ID: covidwho-1869113

ABSTRACT

Background: The angiotensin-converting enzyme-2 (ACE2) is recognized to be the fundamental receptor of severe acute respiratory syndrome coronavirus-2 (SARS-CoV2), responsible for the worldwide Coronavirus Disease-2019 (COVID-19) epidemic. However, genetic differences between people besides racial considerations and their relation to disease susceptibility are still not fully elucidated. Main body: To uncover the role of ACE2 in COVID-19 infection, we reviewed the published studies that explore the association of COVID-19 with the functional characteristics of ACE2 and its genetic variations. Notably, emerging studies tried to determine whether the ACE2 variants and/or expression could be associated with SARS-CoV/SARS-CoV2 have conflicting results. Some researchers investigated the potential of “population-specific” ACE2 genetic variations to impact the SARS-CoV2 vulnerability and suggested no ethnicity enrichment for ACE2 polymorphisms that could influence SARS-CoV2 S-protein binding. At the same time, some studies use data mining to predict several ACE2 variants that could enhance or decline susceptibility to SARS-CoV. On the other hand, fewer studies revealed an association of ACE2 expression with COVID-19 outcome reporting higher expression levels of ACE2 in East Asians. Conclusions: ACE2 gene variants and expression may modify the deleterious consequences of SARS-CoV2 to the host cells. It is worth noting that apart from the differences in gene expression and the genetic variations of ACE2, many other environmental and/or genetic factors could modify the disease outcome, including the genes for the innate and the adaptive immune response.

5.
Clinical Cancer Research ; 27(6 SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1816940

ABSTRACT

Background: The COVID-19 pandemic had enormous consequences in Brazil and worldwide. Patients with cancer affected by COVID-19 are at a higher risk of developing complications and worse outcomes compared to a non-cancer population, particularly the ones on active systemic treatment. Considering the COVID-19 high transmissibility in asymptomatic and presymptomatic patients, we sought to determine the prevalence of COVID-19 infection in patients with solid cancers receiving systemic therapy in a Brazilian public health hospital. Furthermore, we interrogated if socioeconomic status (SES) was associated with prevalence. Methods: Consecutive asymptomatic patients undergoing treatment for solid tumors at the chemotherapy and infusion center of Hospital de Base were enrolled. Patients were prospectively tested for SARS-CoV2 RNA real-time polymerase chain reaction with nasal and oropharyngeal swabs immediately prior to treatment. A socioeconomic survey was performed prior to testing. Demographic and socioeconomic characteristics were summarized in means, medians, and proportions. Results: From October 6 to 13, 2020, 148 asymptomatic patients were identified. Of those, 41 were excluded (16 had hematological malignancies, 15 declined testing, 10 were not on active systemic treatment) leaving 107 eligible patients. The mean age of the population was 58 years-old (SD± 12.6);55% were female and 90% were self-identified as White. The most common cancer sites were gastrointestinal tract (37%) and breast (25%). Most patients had metastatic disease (62.9%) and were on a anticancer treatment involving chemotherapy (62.9%). Regarding to SES, 70% of our population had either primary school or were illiterate as their highest educational level. In terms of monthly income, 88% had a personal income inferior to U$390 and 92% a household income inferior to U$585. Of 107 patients tested, only one (0.9%) was positive for COVID-19. This is a 48 years-old man living in an urban area, with primary school educational level and a monthly personal income inferior to U$390. Conclusion: Despite a high prevalence of COVID19 in Brazil, our cohort demonstrated a low prevalence of COVID19 (0.9%) amongst asymptomatic patients with cancer. We hypothesize that patients with cancer, independently of their SES, are aware of the increased risk of developing severe disease and are adherent to physical distancing, masking, and hygiene measures. LF and BB are co-senior authors.

6.
Clinical Cancer Research ; 27(6 SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1816902

ABSTRACT

Background: Patients with cancer, both active and previously treated, are at a higher risk of developing severe outcomes from COVID-19. During the pandemic, health care systems (HCS) have adapted the delivery of care, and disparities between private and public systems became even more striking. In Brazil, where 70% of the population depends on the public system, ICU demands largely exceed the capacity in most public centers, whereas in private centers the situation is less challenging. Herein we compare outcomes of patients with cancer and COVID-19 treated in the public and private HCS in Brazil. Methods: We used data from adult patients with solid malignancies who tested positive for COVID-19 and were admitted to two tertiary centers in the state of São Paulo. Patients who tested positive for SARS-CoV2 RNA real-time polymerase chain reaction (RT-PCR) were included. We collected data on baseline clinical conditions, cancer and treatment. Patients were classified by HCS: public system (public) versus (vs) private insurance coverage (private). The co-primary endpoints were all-cause mortality and a composite endpoint consisting of intensive-care-unit (ICU) admission, mechanical ventilation or death (ICU-MV-D). Chi-square, Fisher's exact test and Mann-Whitney U test were used when appropriate. We assessed the association between outcomes and HCS using logistic regression analyses, adjusting for age, sex, current anticancer treatment and comorbidities. Results: From March 16 to October 20 2020, 124 patients were identified. Of those, 90 (72%) were from the public and 34 (28%) from the private HCS. There were no statistical differences in sex, smoking, primary tumor siteand staging between patients from both HCS. Conversely, patients treated in the private system were older [66 (SD 13.8) vs 74 (SD 15.1), p=0.004], had more comorbidities (64.7% vs 37.8% p=0.009), and were on anticancer treatment more frequently (64.7% vs 34.4% p=0.004) compared to public patients. There were no differences in all-cause mortality (public 40% vs private 44.1% p=0.69) between patients treated at the different HCS. Nevertheless, in the composite outcome, private system was significantly associated with increased risk of ICU-MV-D compared to the public system (79.4% and 57.8% p=0.030, respectively). The median time from COVID-19 diagnosis to ICU-MV-D was 13 vs 8 days (p=0.031) and to death was 25 vs 24 days (p=0.24), respectively for public and private HCS patients. In the multivariable logistic regression, HCS was not associated with death [adjusted odds ratio (aOR)=1.16 p=0.75] or ICU-MV-D (aOR=0.55, p=0.27). Conclusion: While patients in the private system were older and had more comorbidities, there were no differences in inpatients all-cause mortality between private and public systems. However, private patients were associated with increased ICU-MV-D. We hypothesize that these findings may reflect disparities in ICU availability, known to be higher in the private system. Further studies investigating this hypothesis are warranted. EDR and DVA co-senior authors.

7.
7th International Conference on Contemporary Information Technology and Mathematics, ICCITM 2021 ; : 13-18, 2021.
Article in English | Scopus | ID: covidwho-1730930

ABSTRACT

As the Covid-19 outbreak spreads across the globe and has killed many lives, many applications have been created to track patients and fight this pandemic. However, several applications lack safety and privacy. This paper designs and develops a mobile app to track patients with the Covid-19 or any other pandemic disease through using GPS in Iraq. Moreover, the app maintains a privacy for users by encrypting their personal data before sending them to the cloud using a MODE CBC AES block encryption algorithm. The app keeps the identity and location of the users, supports two language interfaces English and Arabic, and works in Android and iOS environments. Only the health care providers can decrypt these data and know about the patient's location. Also, to make the patient trusts the application, his/her information will be deleted after sending his/her negative test after 21 days. In addition, the app provides users with information regarding healthcare places in the case of emergency. For the evaluation of this app, a data was collected from 20 users, including males and females and their ages were between (20-50) in Mosul city. The results showed that the app works properly and the users are notified when they are in close with other registered infected people. In addition, the users found that the app was simple, easy to use, and useful to do contact safely. To convince the users to utilize this app, the app is provided with button trial option to try it. © 2021 IEEE.

8.
ASAIO Journal ; 66(SUPPL 3):39, 2020.
Article in English | EMBASE | ID: covidwho-984359

ABSTRACT

Background: Although commonly seen as a respiratory causing disease, COVID-19 is associated with increased coagulopathy and thrombus formation. Venovenous extracorporeal membrane oxygenation (VV-ECMO), a rescue therapy for severe acute respiratory distress syndrome (ARDS) usually requires anticoagulation. We present three patients with suspected oxygenator thrombosis that were successfully treated with a protocolized tissue plasminogen activator (Alteplase). Case Presentation: All three cases were male patients, with a median age of 42, that tested positive for SARS-CoV-2 requiring mechanical ventilation and subsequently VV-ECMO (Maquet Cardiohelp HLS HIT 7.0, Getinge, Sweden) for severe ARDS. In all patients, heparin infusion was the anticoagulation of choice. During the first 24-48 hours of starting ECMO, transmembrane pressure (delta-P) elevation started and was sustained in the range 70-100 mmHg. This was associated with a drop in blood flow rate, elevated fibrinogen, fibrinogen degradation products, and hypercoagulable state on rotational thromboelastometry (ROTEM, TEM Ltd, Germany), raising the possibility of oxygenator thrombosis. After determining low risk of bleeding, Alteplase was administered following the K-ECLS protocol, mitigating the need to change the ECMO circuit. Two patients were successfully decannulated and discharged home in good condition. Whilst, one of the patients remains on ECMO. Conclusions: Protocolized t-PA for ECMO oxygenators with suspected thrombosis is feasible and cost-effective in mitigating circuit change for patients on VV-ECMO for ARDS due to COVID-19. Such protocol might be generalizable to all ECMO patients who have low risk of bleeding. To our knowledge, this is the first case series of such therapy and protocol.

9.
2020 International Conference on Intelligent Systems and Computer Vision, ISCV 2020 ; 2020.
Article in English | Scopus | ID: covidwho-900836

ABSTRACT

To control the spread of the COVID-19 virus and to gain critical time in controlling the spread of the disease, rapid and accurate diagnostic methods based on artificial intelligence are urgently needed. In this article, we propose a clinical decision support system for the early detection of COVID 19 using deep learning based on chest radiographic images. For this we will develop an in-depth learning method which could extract the graphical characteristics of COVID-19 in order to provide a clinical diagnosis before the test of the pathogen. For this, we collected 100 images of cases of COVID-19 confirmed by pathogens, 100 images diagnosed with typical viral pneumonia and 100 images of normal cases. The architecture of the proposed model first goes through a preprocessing of the input images followed by an increase in data. Then the model begins a step to extract the characteristics followed by the learning step. Finally, the model begins a classification and prediction process with a fully connected network formed of several classifiers. Deep learning and classification were carried out using the VGG convolutional neural network. The proposed model achieved an accuracy of 92.5% in internal validation and 87.5% in external validation. For the AUC criterion we obtained a value of 97% in internal validation and 95% in external validation. Regarding the sensitivity criterion, we obtained a value of 92% in internal validation and 87% in external validation. The results obtained by our model in the test phase show that our model is very effective in detecting COVID-19 and can be offered to health communities as a precise, rapid and effective clinical decision support system in COVID-19 detection. © 2020 IEEE.

10.
2020 International Conference on Intelligent Systems and Computer Vision, ISCV 2020 ; 2020.
Article in English | Scopus | ID: covidwho-900835

ABSTRACT

To combat the spread of COVID 19, the World Health Organization suggests a large-scale implementation of COVID 19 tests. Unfortunately, these tests are expensive and cannot be provided and available for people in rural and remote areas. To remedy this problem, we will develop an intelligent clinical decision support system (SADC) for the early diagnosis of COVID 19 from chest X-rays which are more accessible for people in rural areas. Thus, we collected a total of 566 radiological images classified into 3 classes: a class of COVID19 type, a Class of Pneumonia type and a class of Normal type. In the experimental analysis, 70% of the data set was used as training set and 30% was used as the test set. After preprocessing process, we use some augmentation using a rotation, a horizontal flip, a channel shift and rescale. Our finale classifier achieved the best performance with test accuracy of 99%, f1score 98%, precision of 98.60% and sensitivity 98.30%. © 2020 IEEE.

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