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Our retrospective study aimed to evaluate the effectiveness of monoclonal antibodies (casirivimab and imdevimab) on mild cases of coronavirus disease 2019 patients admitted to the tertiary care center. A total of 161 patients were evaluated of which the test group consisted of 79 and the control group of 82. In the test group the patients had been administered with diluted 250 ml of 0.9 % sodium chloride along with co-formulated casirivimab (600 mg) and imdevimab (600 mg) solution intravenously and in the control group the patients were administered standard coronavirus disease 2019 treatment protocol. The monitoring of patients in both groups was done at least 1 h after drug infusion in the designated room. Post-treatment designed interviews were taken to evaluate the effectiveness of treatment. This retrospective analysis discovered a significant association of symptoms with the group at 48 h for injected and non-injected patients and 1 mo from the chi-square test after injecting monoclonal antibodies. There is no significant association of symptoms with the groups at 3 mo. A significant difference in the symptom distribution through different time points in the injected group and not injected group was observed. From the pairwise McNemar's test, a significant difference in the symptoms between each time in 48 h, the difference was p=0.0075 and after 1 mo, p<0.001 points in both groups. The combination of casirivimab and imdevimab could be considered a treatment of choice for vaccinated, non-vaccinated and mild to highrisk coronavirus disease 2019 patients.
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The research community has paid great attention to the prediction of air traffic flows. Nonetheless, research examining the prediction of air traffic patterns for unmanned aircraft traffic management (UTM) is relatively sparse at present. Thus, this paper proposes a one-dimensional convolutional neural network and encoder-decoder LSTM framework to integrate air traffic flow prediction with the intrinsic complexity metric. This adapted complexity metric takes into account the important differences between ATM and UTM operations, such as dynamic flow structures and airspace density. Additionally, the proposed methodology has been evaluated and verified in a simulation scenario environment, in which a drone delivery system that is considered essential in the delivery of COVID-19 sample tests, package delivery services from multiple post offices, an inspection of the railway infrastructure and fire-surveillance tasks. Moreover, the prediction model also considers the impacts of other significant factors, including emergency UTM operations, static no-fly zones (NFZs), and variations in weather conditions. The results show that the proposed model achieves the smallest RMSE value in all scenarios compared to other approaches. Specifically, the prediction error of the proposed model is 8.34% lower than the shallow neural network (on average) and 19.87% lower than the regression model on average. © 2023 by the authors.
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Nowadays, the COVID-19 virus disease is spreading rampantly. There are some testing tools and kits available for diagnosing the virus, but it is in a limited count. To diagnose the presence of disease from radiological images, automated COVID-19 diagnosis techniques are needed. The enhancement of AI (Artificial Intelligence) has been focused in previous research, which uses X-ray images for detecting COVID-19. The most common symptoms of COVID-19 are fever, dry cough and sore throat. These symptoms may lead to an increase in the rigorous type of pneumonia with a severe barrier. Since medical imaging is not suggested recently in Canada for critical COVID-19 diagnosis, computer-aided systems are implemented for the early identification of COVID-19, which aids in noticing the disease progression and thus decreases the death rate. Here, a deep learning-based automated method for the extraction of features and classification is enhanced for the detection of COVID-19 from the images of computer tomography (CT). The suggested method functions on the basis of three main processes: data preprocessing, the extraction of features and classification. This approach integrates the union of deep features with the help of Inception 14 and VGG-16 models. At last, a classifier of Multi-scale Improved ResNet (MSI-ResNet) is developed to detect and classify the CT images into unique labels of class. With the support of available open-source COVID-CT datasets that consists of 760 CT pictures, the investigational validation of the suggested method is estimated. The experimental results reveal that the proposed approach offers greater performance with high specificity, accuracy and sensitivity. © 2023 CRL Publishing. All rights reserved.
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Several instances of pneumonia with no clear etiology were recorded in Wuhan, China, on December 31, 2019. The world health organization (WHO) called it COVID-19 that stands for "Coronavirus Disease 2019," which is the second version of the previously known severe acute respiratory syndrome (SARS) Coronavirus and identified in short as (SARSCoV-2). There have been regular restrictions to avoid the infection spread in all countries, including Saudi Arabia. The prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus spread. Methodology: Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory (LSTM). The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius (BER) algorithm. Results: To evaluate the effectiveness of the proposed methodology, a dataset is collected based on the recorded cases in Saudi Arabia between March 7th, 2020 and July 13th, 2022. In addition, six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed approach. The achieved results show that the proposed approach could reduce the mean square error (MSE), mean absolute error (MAE), and R2 by 5.92%, 3.66%, and 39.44%, respectively, when compared with the six base models. On the other hand, a statistical analysis is performed to measure the significance of the proposed approach. Conclusions: The achieved results confirm the effectiveness, superiority, and significance of the proposed approach in predicting the infection cases of COVID-19. © 2023 CRL Publishing. All rights reserved.
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Pityriasis rosea (PR) is frequently proposed to result from a viral etiology. In line with the current pandemic, COVID-19 vaccines are noticed to trigger PR development. Our patient is a 23-year-old female who developed an itchy skin rash following the Pfizer-BioNTech COVID-19 vaccine. Examination showed one erythematous plaque on the left shoulder and multiple small scaly plaques of similar appearance distributed over the trunk and proximal extremities. The patient was clinically diagnosed, educated, reassured, prescribed topical mometasone ointment and oral chlorpheniramine, and was given a follow-up appointment. We report this case to increase awareness on COVID-19 vaccines as potential triggers of PR. Copyright © 2022 Journal of Dermatology and Dermatologic Surgery.
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This study was conducted to determine the objective role of antiviral drugs such as arbidol, lopinavir/ritonavir, and others in improving clinical symptoms, decreasing duration of hospitalization, and decreasing duration of viral shedding in patients with mild and moderate COVID-19 infection. A systematic literature search was carried out on Google Scholar and PubMed databases, using the keywords "COVID-19”, "Antiviral”, "Treatment”, and "Symptomatic” in various combinations. Observational studies, cohort and case control studies, and clinical trials published in English with full-text available were included in the study. Data extraction was carried out from selected studies, and all statistical analysis for the study was carried out using Microsoft Excel. The key outcomes studied were time to negative PCR, duration of clinical stay, time to clinical improvement, and occurrence of adverse events. Seven studies were selected for final review after rigorous selection process. Data of total 4734 participants was analyzed, the majority of which were females (n=2810, 59.3%). The majority of participants had mild disease (n=4197, 88.65%). Average time for negative RT-PCR in the included treatment groups was 13.5 days, whereas the average duration of hospitalization was 14.9 days for the treatment groups. Adverse reactions such as ECG changes, gastrointestinal symptoms, secondary bacterial infections, and hepatic and renal dysfunction were scarcely reported in the included studies. There is no clear benefit in terms of duration of hospitalization and time to negative PCR with the use of various antiviral regimens in mild disease;however, these drugs did play a role in limiting disease progression in the participant population. Pending further evidence, the use of these drugs for the management of COVID-19 is not recommend in patients with mild disease. © 2022, The Running Line. All rights reserved.
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BACKGROUND AND AIM: The novel coronavirus disease 2019 (COVID-19) can be transmitted to clinicians involved in their care, in spite centers for disease control and prevention (CDC) had put standards for precaution but unfortunately several health care providers had lost their lives around the world. OBJECTIVE(S): To Evaluate virtual/ in-person medical simulation training about airway management of suspected/ confirmed COVID-19 pediatric patients on pediatric health care provider in KFMC METHOD: cross section study done on health care providers at King Fahad Medical City (KFMC), Riyadh, Saudi Arabia through google form questioner. Inclusion criteria: health care providers involved in pediatric airway management for confirmed/suspected Covid 19 patients, whether they attended virtual/ in-person simulation training courses. So we decided to transmit the guideline on airway management into simulation training courses to be run into in-situ simulation, then when in situ area was converted into covid 19 care area we video taped it and added as QR barcode to the guideline. RESULT(S): 85 responders, 55.4% nurses, 12.3% consultant, 14% fellows and asistant consultants, 2% medical residents, and 2% respiratory therapist. 91% used proper PPE, 80% followed learned precautions during intubation while 91% during extubation, 75.8% used video laryngoscope. 91.3% confirmed that simulation training/video demonstration had helped them in airway management. CONCLUSION(S): Simulation training either hands on or video demonstration on proper PPE precautions and Airway management for confirmed/suspected COVID-19 Plus Adding the video demonstration barcode to the guideline of institute, had safely improved the knowledge and the skills for medical practitioner. further larger studies are recommended to measure sustainability.
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Introduction: Ever since COVID-19 became a pandemic much responsibility has been put on healthcare providers, and since medical students are future healthcare workers, it is necessary to study their response and perceptions on the current pandemic. This study's objective is to evaluate the knowledge, attitude, and preventive practices (KAP) of medical students in King Saud bin Abdulaziz University for Health Sciences (KSAU-HS) Riyadh branch towards COVID-19. Methods: This cross-sectional study was conducted from 26th of August 2021 to 15th of February 2022 using an online questionnaire. The questionnaire was composed of 34 questions: 7 on demographics, 13 on knowledge about COVID-19, 5 on attitude towards COVID-19, and 9 on preventive behaviors against COVID-19. This study included all undergraduate medical students of KSAU-HS, Riyadh branch. The sample size was calculated to be 370. Results: In this study, the 378 participants who responded were mostly males (51.06%), and more than half (56.51%) were in their basic years. The percentage of stream I students was 89.95%. The average correct response rate of knowledge questions was 81.40%. Most of the participants adopted positive behaviors over the course of the pandemic. In addition, 55.29% had high adherence to precautionary practices. When comparing the variables, clinical year students had higher knowledge, but basic year students had better preventive measures. Furthermore, stream II students exhibited better knowledge. Conclusion: Overall, medical students had excellent knowledge levels, adequate positive attitude, and high adherence to preventive measures. Although clinical year students showed high knowledge their lower performance in preventive behaviors should be investigated.
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Background: Corona virus disease 2019 pandemic had a major impact on the general wellbeing of people. Hypertension patients are more liable to psychological stress. This study aims to assess the prevalence of psychological stress in hypertensive patients affected by Covid-19 in Madinah. Methods: Hypertension patients in Al Madinah were invited to participate in an online questionnaire in the period from December 2020 to May 2021. It included the personal data, questions assessing hypertension and psychological health status using the General Health Questionnaire. Results: Total number of participants in our study was 588. 30.8% of participants were mildly distressed and 6.8% were severely distressed. Females are being more at risk of severe distress. Regarding taking prescribed medications there was a significant relationship between groups. Conclusion: The prevalence was found to be 0.376. Hypertensive patients in Al Madinah are at more risk of psychological stress especially females, students, unemployed, and those who are not adherent to their medications. More psychological care should be provided to them in pandemics. Objectives: To evaluate the prevalence of psychological stress after Covid-19 in hypertensive patients in Madinah.
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Lack of knowledge about the type and prevalence of gastrointestinal symptoms as a clinical manifestation is one of the reasons for delayed diagnosis and treatment of COVID-19 patients. This review study aimed to systematically review the type and prevalence of gastrointestinal symptoms in COVID-19 patients. To study the gastrointestinal manifestations of COVID-19, we used the 06- PRISMA registered in the CAMARADES-NC3Rs Preclinical Systematic Review and Meta-Analysis Facility (SyRF) database. PubMed, Embase, Web of Science, Google Scholar, and Scopus databases were searched for publications on the gastrointestinal manifestations of COVID-19 with no publication time frame. Articles were found using the following terms and search strategy: ["COVID-19, Coronavirus, 2019-nCoV, Clinical SymptomsGastrointestinal or gastric or intestinal manifestations"]. Out of 27652 papers, 35 papers on a total of 6730 COVID-19 patients up to 2022 met the inclusion criteria. Remarkably, most articles (28 papers, 77.8%) were from China (77.8%). The most common gastrointestinal manifestations were nausea or vomiting (13.1%), diarrhea (11.05%), anorexia (8.7%), and abdominal pain (2.4%), respectively. The findings of the present review revealed that contrary to what was initially assumed in the COVID-19 outbreak, this infection does not manifest only as respiratory symptoms but also as gastrointestinal symptoms. Therefore, clinicians and gastroenterologists must be alert to these unusual cases and fecal-oral transmission during the COVID-19 pandemic and implement preventive strategies.
Subject(s)
COVID-19 , Gastrointestinal Diseases , COVID-19/complications , Gastrointestinal Diseases/epidemiology , Gastrointestinal Diseases/virology , Humans , Pandemics , SARS-CoV-2ABSTRACT
OBJECTIVE: Healthcare outbreaks, especially infectious disease pandemics, often stretch the healthcare systems to its limits. Healthcare systems have no option other than being supported by the participation of young and motivated healthcare providers (HCPs) in their undergraduate medical studies during their prevention and control internship program during the outbreak. Understanding key motivation factors influencing HCPs are vital to ensure their effective participation in such situations. SUBJECTS AND METHODS: A cross-sectional study was conducted on 410 undergraduate medical students at Qassim University in Saudi Arabia with the aim to describe the motivation factors that affect their willingness to volunteer during a pandemic. An online survey questionnaire was conducted. RESULTS: 410 participants of which 239 (58.29%) were female, 108 (26.34%) were in their third academic year and 129 (31.46%) were between 21-22 years of age. More than 70% of participants showed willingness to volunteer during a pandemic. Their willingness to volunteer was motivated by distance of workplace to home, availability of transportation, being vaccinated, access to health care for self and family if affected, and provision of specialized training. CONCLUSIONS: Healthcare administrators and policy makers need to address these factors effectively to ensure the availability of skilled and motivated healthcare providers during a pandemic.
Subject(s)
Communicable Diseases , Students, Medical , Attitude of Health Personnel , Cross-Sectional Studies , Female , Humans , Male , Motivation , Pandemics , Saudi Arabia/epidemiology , VolunteersABSTRACT
Celiac disease is an autoimmune enteropathy disease caused by an immune reaction to gliadin which is a component of gluten that affects the intestinal lamina and leads to its atrophy, which occurs when a celiac patient consumes gluten products. The symptoms are different from diarrhea, vomiting, or abdominal pain after eating gluten, however, most of them are asymptomatic. Due to the low frequency of studies regarding celiac disease among youngsters in Saudi Arabia, thegoal of this study was to screen anti-gliadin IgA among students at the College of Applied Medical Sciences at Taif University. A cross-sectional study was conducted on 182 healthy participants from students at the College of Applied Medical Sciences at Taif University from March 3, 2022, to March 26, 2022. Some participants have confirmed to have food allergy or an immune disorder such as nut allergy, systemic lupus erythema, and wheat sensitivity. The anti-gliadin IgA test was performed by ELISA to assess anti-gliadin IgA titer on the serum of the students. 9 out of 182 were anti-gliadin IgA positive test. Most of the positive participants were females, and one was male, and all were healthy and confirmed to be undiagnosed previously with celiac disease neither their relatives. Moreover, they are not shown symptoms that are associated with their gluten intake. We found an association with many parameters of AGA positivity of the participants such as gender, BMI or COVID-19 infection and vaccine. This study provides a screening analysis of anti-gliadin IgA among students at College of Applied Medical Sciences at Taif University, and our results are similar to the prevalence of celiac disorder in Saudi Arabia. However, seropositivity for anti-gliadin IgA can be a marker for other enteropathies therefore other confirmatory tests should be performed.
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Objectives: To assess the prevalence of coronavirus disease 2019 (COVID-19) infection among sickle cell disease (SCD) patients in Jazan region and to determine the impact of COVID-19 on the SCD population. Methods: This was an observational, descriptive, cross-sectional study using a self-administrated questionnaire directed to SCD patients in Jazan to assess the prevalence of COVID-19. The data were analyzed using a t-test and Chi-square test. Results: A total of 188 responses were received and only 96 SCD patients were included (mean age is 24 years). About half of the study samples (53%) of the study population were male. About 11% of patients with SCD were diagnosed with COVID-19. Vaso-occlusive crisis was reported in 73% and a single patient presented with acute chest syndrome. About three-fourths of patients (73%) were admitted to the hospital and most of them experienced mild symptoms and one patient was treated in the intensive care unit. Conclusion: SCD patients are at risk of SARS-CoV-2 infection. In the absence of comorbidities, patients with SCD are not at increased risk of COVID-19 mortality, but a higher admission rate is reported. SCD patients with COVID-19 may have a milder clinical course, compared to other populations with comorbidities such as diabetes and hypertension, and this may be due to proinflammatory adaptation of the immune system. Larger studies including epidemiological and molecular details are needed to enhance our understanding of how SARS-CoV-2 could affect patients with SCD. © 2022 Journal of Nature and Science of Medicine. All rights reserved.
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Emerging global infections, such as coronavirus disease (COVID-19), pose serious public health threats, especially for vulnerable groups, including pregnant women. Knowledge about the disease, attitudes toward disease prevention, and preventative practices can help curb the spread of disease and limit mortality as well. To determine knowledge, attitudes, and practices (KAP) among a cohort of Saudi women who were either pregnant during the pandemic or pregnant at the time of data collection. A cross-sectional, prospective observational study using data collected via an online self-reported questionnaire was carried out between February 3 and March 14, 2021. The questionnaire ascertained the levels of knowledge, attitude, and practice of pregnant women. An ANOVA and t-test were used to determine significant associations between levels of KAP and sociodemographic variables. The average knowledge score was 10.4 +/- 2.85 out of 19 (54.7%);for attitudes, the average score was 3.4 +/- 1.61 out of 5 (68%);and for practices, the average score was 5.9 +/- 1.21 out of 7 (84.2%). Higher educational status and healthcare as a profession were significantly associated with improved KAP scores among pregnant women. Participants from the Western region of Saudi Arabia were heavily represented in our study. Pregnant women, especially those subgroups with low KAP scores, should be provided with adequate and updated information regarding COVID-19. This can help prevent the spread of disease and increase their knowledge, especially regarding breastfeeding practices during infection.
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Objectives: The study was performed to identify the clinical manifestation of Covid-19 infection during pregnancy its impact on the pregnancy outcomes, and its presentation in completely/incompletely vaccinated women. Material and Methods: We conducted this cross-sectional study at Ha`il, a northern city in Saudi Arabia, starting from 15th Dec. 2021 till 15th Jan. 2022. The mean differences of background variables were computed by using the Independent-Sample t-test. A Chi-square test was applied to assess the presentation of the disease in pregnant/non–pregnant and vaccinated/ non-vaccinated women. P-value <0.05 was taken as statistically significant. Results: Fatigue followed by fever and cough (65, 42, and 38% respectively) were the most common presentations of infection during pregnancy. Hospitalization (15.4%) and ICU (9.4%) admissions were more in pregnant than in non-pregnant women. Clinical manifestations were the same in the completely and incompletely vaccinated women. The incompletely vaccinated women were at increased risk of hospitalization (p-value 0.01), and pneumonia (p-value 0.05). The covid-19 infection has no significant association with age of the participants, body mass index, and parity. Covid-positive women during pregnancy underwent fewer cesarean- sections than Covid negative (20% vs. 80%, p <0.05). The mean gestational age at delivery, preterm birth, and neonatal weight at birth were the same in both groups. The rate of transmission of the infection to the neonates remained extremely low. Conclusion: Covid disease during pregnancy doesn’t increase the risk of preterm birth, cesarean delivery, or low birth weight of the babies. Complete vaccination against tcovid-19 declines the risk of hospital admission for severe disease and pneumonia in women.
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Background and Objectives: Self-medication is defined as using drugs without doctor prescription, whether it is modern or traditional treatment through different sources that allowed them to take these medications individually. The World Health Organization (WHO) considers self-medication as a serious problem. This study aimed to explore the prevalence and the association of self-medication among the population in Medina. The study also aimed to know the resources, reasons, knowledge, and other aspects of self-medication. Methods: This is a community-based cross-sectional study has been conducted in Medina, Saudi Arabia. The duration of study was one year. The sample includes 281 participants. An online questionnaire has been designed to reach the research goals. Statistical Package for the Social Sciences (SPSS) 22.0 has been used to analyze the collected data. The research used texts, tables, and graphs to present the statistical data. Results: The study showed that (58%) of the participants practiced self-medication. The most common reasons for using self-medications are having an old recipe (33.1%), or to save time (33.1%). The most common symptom for using self-medication is headache (70.6%). The most used medicine in self-medication is analgesics (42.9%). Most of the participants received information about the medicines from the drug leaflet (45.4%). Conclusion: Self-medication is a serious problem. The prevalence of self-medication is less in this study comparing to other studies around the world. More attention and protocols may help to reduce the prevalence.
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People are required to wear masks in many countries, now a days with the Covid-19 pandemic. Automated mask detection is very crucial to help identify people who do not wear masks. Other important applications is for surveillance issues to be able to detect concealed faces that might be a safety threat. However, automated mask wearing detection might be difficult in complex scenes such as hospitals and shopping malls where many people are at present. In this paper, we present analysis of several detection techniques and their performances. We are facing different face sizes and orientation, therefore, we propose one technique to detect faces of different sizes and orientations. In this research, we propose a framework to incorporate two deep learning procedures to develop a technique for mask-wearing recognition especially in complex scenes and various resolution images. A regional convolutional neural network (R-CNN) is used to detect regions of faces, which is further enhanced by introducing a different size face detection even for smaller targets. We combined that by an algorithm that can detect faces even in low resolution images. We propose a mask-wearing detection algorithms in complex situations under different resolution and face sizes. We use a convolutional neural network (CNN) to detect the presence of the mask around the detected face. Experimental results prove our process enhances the precision and recall for the combined detection algorithm. The proposed technique achieves Precision of 94.5%, and is better than other techniques under comparison.
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COVID-19, being the virus of fear and anxiety, is one of the most recent and emergent of various respiratory disorders. It is similar to the MERS-COV and SARS-COV, the viruses that affected a large population of different countries in the year 2012 and 2002, respectively. Various standard models have been used for COVID-19 epidemic prediction but they suffered from low accuracy due to lesser data availability and a high level of uncertainty. The proposed approach used a machine learning-based time-series Facebook NeuralProphet model for prediction of the number of death as well as confirmed cases and compared it with Poisson Distribution, and Random Forest Model. The analysis upon dataset has been performed considering the time duration from January 1st 2020 to16th July 2021. The model has been developed to obtain the forecast values till September 2021. This study aimed to determine the pandemic prediction of COVID-19 in the second wave of coronavirus in India using the latest Time-Series model to observe and predict the coronavirus pandemic situation across the country. In India, the cases are rapidly increasing day-by-day since mid of Feb 2021. The prediction of death rate using the proposed model has a good ability to forecast the COVID-19 dataset essentially in the second wave. To empower the prediction for future validation, the proposed model works effectively. © 2022 Tech Science Press. All rights reserved.
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COVID-19 pandemic outbreak became one of the serious threats to humans. As there is no cure yet for this virus, we have to control the spread of Coronavirus through precautions. One of the effective precautions as announced by the World Health Organization is mask wearing. Surveillance systems in crowded places can lead to detection of people wearing masks. Therefore, it is highly urgent for computerized mask detection methods that can operate in real-time. As for now, most countries demand mask-wearing in public places to avoid the spreading of this virus. In this paper, we are presenting an object detection technique using a single camera, which presents real-time mask detection in closed places. Our contributions are as follows: 1) presenting a real time feature extraction module to improve the detection computational time;2) enhancing the extracted features learned from the deep convolutional neural network models to improve small objects detection. The proposed model is a lightweight backbone CNN which ensures real time mask detection. The accuracy is also enhanced by utilizing the feature enhancement module after some of the convolution layers in the CNN. We performed extensive experiments comparing our model to the single-shot detector (SDD) and YoloV3 neural network models, which are the state-of-the-art models in the literature. The comparison shows that the result of our proposed model achieves 95.9% accuracy which is 21% higher than SSD and 17.7% higher than YoloV3 accuracy. We also conducted experiments testing the mask detection speed. It was found that our model achieves average detection time of 0.85s for images of size 1024 x 1024 pixels, which is better than the speed achieved by SSD but slightly less than the speed of YoloV3.
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TOPIC: Palliative Care and End of Life Issues TYPE: Original Investigations PURPOSE: The end-of-life resuscitation status and therapeutic interventions in critically ill Muslim patients who succumb to their illness is not well reported. We describe our experience in such patients who were admitted to our tertiary care hospital Intensive Care Unit (ICU). METHODS: Our hospital is a tertiary care center accredited by Joint Commission International and Nurses Magnet Programs and runs active organ transplantation services. The patient population and treating ICU physicians are all Muslim. We collected twelve-month data from the year 2020 of patients who died in our ICU. Coronavirus Disease 2019 infected patients were treated separately and were not included in the study to give true reflection of the end-of-life care in Muslim patients under ordinary circumstances. Patient demographics, characteristics before and at ICU admission, cardiopulmonary resuscitation and DNAR details in ICU, and therapies administered in last 24 hours before death were recorded. Descriptive statistics were used to organize the collected data. Continuous variables were described as median with Interquartile Range Q1-Q3 (IQR), and categorical variables were described as number and percentages, as appropriate. RESULTS: 104 Muslim patients died during the study period. Their median age was 64 years and 51% were male. These patients had a median of 5 underlying comorbidities and a Charlson Comorbidity Index of 6 at baseline, highlighting their moribund status. 56% had underlying illness that would have qualified them for hospice before admission. Patients spent a median of 10 days (IQR 6-15) in the ward before ICU admission, had a high APACHE II score of 23 (IQR 20-33) and lactic acid of 3.7 (IQR 2.2-4.8) upon ICU admission. Their duration of mechanical ventilation (6 days;IQR 4-9), ICU stay (6 days;IQR 2-13) and hospital length of stay (10 days;IQR 6-15) were relatively long. 92% were "Full Code" at ICU admission and the status was changed to 'do-not-attempt resuscitation' (DNAR) in about 67% of the cohort before death. 42 patients had CPR done and 8 were made DNAR after one CPR. DNAR decision was made after median of 13 days (IQR 7-22 days) of hospital admission and 5 days (IQR 2.5-9 days) before death. DNAR discussions were led by Intensivists in 89% of the cases. Until the very end, patients in both groups were on tube feeds, underwent blood draws, had few limitations on therapy or withdrawal of care. There was hardly any involvement of Muslim chaplain and palliative care service. CONCLUSIONS: The concept of DNAR is accepted in Muslim patients even though decision is made near end of life. Many patients with terminal disease ended up in the ICU and role of hospice and palliative care needs to be increased in this population. CLINICAL IMPLICATIONS: DNAR is acceptable in Muslim patients, however, active mechanisms need to be developed to avoid terminal patients suffering undue ICU course at end of life. DISCLOSURES: No relevant relationships by Azhar Alharbi, source=Web Response No relevant relationships by Mohammed Alzahrani, source=Web Response No relevant relationships by MANSOR BINHASHR, source=Web Response No relevant relationships by Maryam Imran, source=Web Response No relevant relationships by Manahil Imran, source=Web Response No relevant relationships by Imran Khalid, source=Web Response No relevant relationships by Tabindeh Khalid, source=Web Response No relevant relationships by Murad Mawlawi, source=Web Response No relevant relationships by Nahid Mulla, source=Web Response No relevant relationships by Renad Nadhreen, source=Web Response No relevant relationships by Ahmed Qadah, source=Web Response No relevant relationships by Romaysaa Yamani, source=Web Response