COVID-19 Symptoms Research Articles

Diagnostic accuracy of chest x-ray in covid -19, taking high resolution computed tomography as gold standard

ABSTRACT Objective: To determine sensitivity & specificity of chest X-ray in COVID-19, taking High-Resolution Computed Tomography as gold standard. Study Design: Cross-sectional study. Place and Duration of Study: Radiology Deptt, Margalla Hospital, Taxila and Islamabad Diagnostic Centre, Wah. Two years (February 2020 to February 2022). Patients and Methods: The sample comprised 100 COVID-19 patients (Positive Polymerase chain reaction (PCR) test). Their HighResolution Computed Tomography (HRCT) was done which was considered a gold standard for diagnosing COVID-19. Their Chest X-rays (CXR) were performed, and findings of both modalities were compared. Patients having respiratory tract symptoms but PCR negative for COVID-19 were excluded. Results: The research had 49 males & 51 females having a median (IQR) age of 46.50(35-55.75) years. The minimum & maximum ages were 6 years and 83 years respectively. Among 100 PCR-positive patients, 29 were found normal on HRCT and 30 on CXR. For moderate cases, the chest X-rays were 72% sensitive & 90.67% specific, with Positive Predictive Value (PPV), Negative Predictive Value (NPV) & diagnostic efficacy of 72%,90.67% & 86% respectively. Similarly, other severity levels were assessed. Conclusion: CXR has acceptable diagnostic accuracy for COVID-19 patients, especially with good sensitivity for moderate cases and better specificity for severe cases. A portable chest radiograph might be regarded as an initial alternative imaging modality for patients with COVID-19 signs and symptoms in remote areas. Key words: COVID-19, CXR , HRCT

Medical oxygen production, supply, and infrastructure augmentation during the COVID-19 pandemic in India: A narrative review

According to the World Health Organization, the primary symptoms of COVID-19 include fever, cough, and fatigue, while more serious cases present with dyspnea (difficulty breathing) and chest pain. The medical use of oxygen therapy is a common life support treatment for numerous diseases at multiple levels of health care in India. An abrupt spike in medical oxygen demand (nearly 100 – 200 fold) has been observed in regions such as South America, Africa, and Asia, including India. Governments of the respective countries have implemented policy decisions to tackle medical oxygen shortage during the pandemic. In this narrative review, we describe and summarize the actions taken by the Indian government to manage the medical oxygen requirement during the deadly COVID-19 waves in India. Searches were conducted on PubMed, Scopus, Google Scholar databases, and websites of various ministries and departments of the Government of India, covering the period from January 2020 to January 31, 2023. Qualitative data were extracted using pre-defined themes from published documents related to medical oxygen supply during the COVID-19 pandemic in the Indian context. This narrative review summarizes the state of medical oxygen during the COVID-19 pandemic, focusing on medical oxygen production, supply, infrastructure augmentation, pressure swing adsorption plants, capacity building, web application, and monitoring mechanisms. The 76th World Health Assembly has also adopted the Access to Medical Oxygen Resolution to prevent deaths and ensure that no country faces an oxygen shortage, as seen during the COVID-19 pandemic.

COVID-19 Infection in Ultramarathon Runners: Findings of the Ultrarunners Longitudinal TRAcking Study.

Ultramarathon runners are a unique patient population who have been shown to have a lower rate of severe chronic medical conditions. This study aimed to determine the effect that COVID-19 infection has had on this population and their running behavior. The Ultrarunners Longitudinal TRAcking (ULTRA) Study is a large longitudinal study of ultramarathon runners. Questions on health status, running behavior, and COVID-19 infection were included in the most recent survey. Community survey. Seven hundred thirty-four ultramarathon runners participated in the study. None. Personal, exercise, and COVID-19 infection history. 52.7% of study participants reported having been symptomatic from a COVID-19 infection, with 6.7% testing positive multiple times. Participants required a total of 4 days of hospitalization. The most common symptoms included fever (73.6%), fatigue (68.5%), sore throat (68.2%), runny nose (67.7%), and cough (67.4%). Cardiovascular symptoms, which are of particular interest in the running population, included shortness of breath (46.3%), tachycardia (44.7%), chest pain (36.2%), and wheezing (33.3%). A total of 50 subjects (6.8%) reported long COVID (symptoms lasting more than 12 weeks). Severe COVID-19 infection has been rare in this population of ultramarathon runners, although symptomatic infection that affects running is common. To support the well-being of this group of highly active athletes, clinicians should appreciate that cardiovascular symptoms are common and the long-term significance of these symptoms in runners is unknown. Level 2 prospective study.

COVID-19 and Pneumonia detection and web deployment from CT scan and X-ray images using deep learning.

During the COVID-19 pandemic, pneumonia was the leading cause of respiratory failure and death. In addition to SARS-COV-2, it can be caused by several other bacterial and viral agents. Even today, variants of SARS-COV-2 are endemic and COVID-19 cases are common in many places. The symptoms of COVID-19 are highly diverse and robust, ranging from invisible to severe respiratory failure. Current detection methods for the disease are time-consuming and expensive with low accuracy and precision. To address such situations, we have designed a framework for COVID-19 and Pneumonia detection using multiple deep learning algorithms further accompanied by a deployment scheme. In this study, we have utilized four prominent deep learning models, which are VGG-19, ResNet-50, Inception V3 and Xception, on two separate datasets of CT scan and X-ray images (COVID/Non-COVID) to identify the best models for the detection of COVID-19. We achieved accuracies ranging from 86% to 99% depending on the model and dataset. To further validate our findings, we have applied the four distinct models on two more supplementary datasets of X-ray images of bacterial pneumonia and viral pneumonia. Additionally, we have implemented a flask app to visualize the outcome of our framework to show the identified COVID and Non-COVID images. The findings of this study will be helpful to develop an AI-driven automated tool for the cost effective and faster detection and better management of COVID-19 patients.

Investigating fear, depressive symptoms and coping mechanisms among Egyptian nursing students amidst the covid-19 pandemic: a cross-sectional study

BackgroundAmidst the ongoing COVID-19 pandemic, nursing students' contribution to combating this global health crisis is becoming more significant. However, we need a more comprehensive understanding of the psychological impact of this crisis on these students. Therefore, this study holds immense importance as it offers valuable insights into the connection between COVID-19 pandemic fear, coping strategies, and depressive symptoms among nursing students.MethodsA cross-sectional survey was conducted to collect and analyze data from 319 undergraduate nursing students. They participated in the study by responding to an online questionnaire. The questionnaire consisted of the Fear of the Coronavirus Questionnaire, Brief Coping Orientation to Problems Experienced, and the Beck Depression Inventory-II.ResultsThe study revealed that 45.5% of the participants had a severe fear of COVID-19, 21.9% showed severe depressive symptoms, and 64.6% used moderate coping mechanisms. A positive correlation (r = 0.160, p = 0.01) was found between the fear of COVID-19 and depressive symptoms. Interestingly, this correlation turned negative (r = -0.074, p = 0.01) when adaptive coping strategies such as religion, acceptance, planning, positive reframing, instrumental support, emotional support, active coping, and humor were used. However, when participants resorted to maladaptive coping strategies like venting, self-distraction, self-blame, behavioral disengagement, denial, and substance abuse, the correlation between high fear levels and depressive symptoms became positive (r = 0.352, p = 0.01).ConclusionThe study demonstrated that the fear of COVID-19 and depressive symptoms among nursing students are significantly correlated. However, the nature of this correlation is influenced by the type of coping strategies employed. Adaptive coping mechanisms can mitigate the impact of fear on depressive symptoms. In contrast, maladaptive coping can exacerbate the relationship between fear and depressive symptoms. Therefore, promoting adaptive coping strategies could be a crucial approach to managing the psychological impact of the COVID-19 pandemic.

Evaluation of diseases complicating long COVID: A retrospective chart review

AbstractBackgroundEvidence for the pathogenesis and treatment of postacute coronavirus disease 2019 (COVID‐19) (long COVID) is lacking. As long COVID symptoms are predicted to have an impact on the global economy, clarification of the pathogenesis is urgently needed. Our experiences indicated that some symptoms were complicated by diseases established before the COVID‐19 pandemic.MethodsUsing a retrospective, cross‐sectional study, we aimed to evaluate the diseases complicating long COVID. Using the medical records of patients with confirmed COVID‐19 exhibiting residual symptoms lasting ≥60 days postinfection who visited our clinic in January 2021–February 2023, we investigated the symptoms and diseases observed. We identified diseases that occurred after COVID‐19 and excluded those that were exacerbations of existing diseases.ResultsDuring the first visit, the most common symptoms reported in a total of 798 patients were fatigue (523 patients), anxiety (349 patients), and lack of motivation (344 patients). Complicating diseases were observed in 452 patients (57%). There were 115, 65, and 60 patients with postural tachycardia syndrome, postural syndrome without tachycardia, and mood disorders, respectively. Some diseases requiring immediate treatment included pulmonary thromboembolism, purulent shoulder arthritis, cerebellopontine angle tumors, myasthenia gravis, and cervical myelopathy.ConclusionNot all symptoms that occur after COVID‐19 should be treated as long COVID. Similar to normal medical treatment, a list of differential diagnoses should be maintained based on symptoms to obtain definitive diagnoses.

The depression and anxiety status and influencing factors survey of international students during COVID-19 outbreak period in Hunan, China: A cross-sectional study

International students are susceptible to several mental health disorders, including anxiety and depression amid the COVID-19 pandemic due to the implementation of epidemic control measures such as lockdown, quarantine, etc. The study aimed to investigate the depression and anxiety status as well as influencing factors of international students in Hunan, China during the COVID-19 outbreak lockdown. An online cross-sectional survey was conducted between May and June 2020. A snowball sampling technique was used to recruit participants. Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) were used to assess depression and anxiety status, respectively. 450 participants completed the online survey. The overall prevalence of depression and anxiety was 28.7 % and 36.9 %, respectively. Multivariate logistic regression analyses showed that having suspected symptoms of COVID-19 (aOR = 3.54, 95 %CI = 1.30–9.64) and having family members or friends infected with COVID-19 (aOR = 1.51, 95 %CI = 1.31–3.84) were positively associated with depression. Being single was positively associated with anxiety (aOR = 3.10, 95 %CI = 1.46–6.57). Also, obtaining news or updates about the COVID-19 daily (aOR = 1.76, 95 %CI = 1.13–3.75), and using electronic devices for 5–6 h every day (aOR = 2.21, 95 %CI = 1.17–4.17) showed a positive association with anxiety. Furthermore, having a high coping strategy was negatively associated with anxiety (aOR = 0.33, 95 %CI = 0.12–0.92). Although implementing lockdown was an excellent measure, it resulted in a high prevalence of depression and anxiety symptoms. The findings support previous studies that reported an increased in depression and anxiety status due to the COVID-19 pandemic. Therefore, mental health education and psychological support should be provided to this population during the pandemic or future epidemic diseases.

Relationship between acute SARS-CoV-2 viral clearance with Long COVID Symptoms: a cohort study.

The relationship between SARS-CoV-2 viral dynamics during acute infection and the development of long COVID is largely unknown. A total of 7361 asymptomatic community-dwelling people enrolled in the Test Us at Home parent study between October 2021 and February 2022. Participants self-collected anterior nasal swabs for SARS-CoV-2 RT-PCR testing every 24-48 hours for 10-14 days, regardless of symptom or infection status. Participants who had no history of COVID-19 at enrollment and who were subsequently found to have ≥1 positive SARS-CoV-2 RT-PCR test during the parent study were recontacted in August 2023 and asked whether they had experienced long COVID, defined as the development of new symptoms lasting 3 months or longer following SARS-CoV-2 infection. Participant's cycle threshold values were converted into viral loads, and slopes of viral clearance were modeled using post-nadir viral loads. Using a log binomial model with the modeled slopes as the exposure, we calculated the relative risk of subsequently developing long COVID with 1-2 symptoms, 3-4 symptoms, or 5+ symptoms, adjusting for age, number of symptoms, and SARS-CoV-2 variant. Adjusted relative risk (aRR) of individual long COVID symptoms based on viral clearance was also calculated. 172 participants were eligible for analyses, and 59 (34.3%) reported experiencing long COVID. The risk of long COVID with 3-4 symptoms and 5+ symptoms increased by 2.44 times (aRR: 2.44; 95% CI: 0.88-6.82) and 4.97 times (aRR: 4.97; 95% CI: 1.90-13.0) per viral load slope-unit increase, respectively. Participants who developed long COVID had significantly longer times from peak viral load to viral clearance during acute disease than those who never developed long COVID (8.65 [95% CI: 8.28-9.01] vs. 10.0 [95% CI: 9.25-10.8]). The slope of viral clearance was significantly positively associated with long COVID symptoms of fatigue (aRR: 2.86; 95% CI: 1.22-6.69), brain fog (aRR: 4.94; 95% CI: 2.21-11.0), shortness of breath (aRR: 5.05; 95% CI: 1.24-20.6), and gastrointestinal symptoms (aRR: 5.46; 95% CI: 1.54-19.3). We observed that longer time from peak viral load to viral RNA clearance during acute COVID-19 was associated with an increased risk of developing long COVID. Further, slower clearance rates were associated with greater number of symptoms of long COVID. These findings suggest that early viral-host dynamics are mechanistically important in the subsequent development of long COVID.

Prevalence and Predictors of Long COVID-19 and the Average Time to Diagnosis in the General Population: A Systematic Review, Meta-Analysis and Meta-Regression

Objectives: We aimed to assess the prevalence of long COVID-19 and estimate the average time to its diagnosis and meta-regression for covariates. Methods: We conducted a systematic review, meta-analysis, and meta-regression from 43 studies (367,236 patients) (June 2020–August 2022). With the random-effects model, the pooled prevalence of long COVID-19 was measured. Publication bias was ascertained, and meta-regression analysis was performed on predetermined covariates. The trial was registered with PROSPERO (CRD42022328509). Results: The pooled prevalence of long COVID-19 was 42.5% (95% CI 36% to 49.3%), with 25% and 66% at four and two months, respectively. Mostly, long COVID-19 signs and symptoms occurred at three (54.3%) to six (57%) months (p < 0.0001), further increasing at 12 months (57.9%, p = 0.0148). Hypertension was significantly associated with long COVID-19 at 32% (0.322 (95% CI 0.166, 0.532) (p < 0.001) and hospital re-admission contributed to 17% (Q = 8.70, df = 1, p = 0.0032) (R2 = 0.17). All the covariates explained at least some of the variance in effect size on long COVID-19 at 53% (Q = 38.81, df = 19, p = 0.0047) (R2 analog = 0.53). Conclusion: The prevalence of long COVID-19 was 42.5% when linked with a cardiovascular disorder. Hospital re-admission majorly predicted the incidence of long COVID-19. Clinical and methodological characteristics in a specific study contributed to over 50% of long COVID-19 events, with most signs and symptoms occurring between 3 and 6 months and increasing at 12 months.

Hospital outcomes for young adults with COVID-19

BackgroundOlder adults are at higher risk of severe outcomes from COVID-19 with comorbidities increasing such risk. Much less is known about the outcomes of young adults with COVID-19 despite their having had high infection rates. ObjectivesOur objective was to determine outcomes of hospitalized young adults with COVID-19 infection including rates of oxygen use, mortality, ICU admission, intubation, duration of hospitalization, and factors associated with adverse outcomes. Study designThis retrospective cohort study included EHR data from 21 health systems in the United States on 18–29-year-olds hospitalized with COVID-19 from March 1, 2020 – January 31, 2022. Oxygen need was used to identify symptomatic COVID-19. Rates for mortality, ICU admission, and intubation were calculated for the symptomatic and asymptomatic groups. Effects of demographic and health characteristics on outcomes were assessed as were changes in hospital outcomes over time. ResultsOur sample included 9871 young adults hospitalized with COVID-19; 35% required oxygen. Of those who required oxygen, 53.5% were female, 23.7% had an anxiety disorder, 2.6% died (n = 89), 27.7% were admitted to the ICU (n = 955), and 15.8% were intubated (n = 547). A past-year history of any cancer was associated with a 2.1 times increased odds of death. Vaccination was associated with a >40% reduction in the odds of ICU admission. Mortality rates did not change significantly across the study period. ConclusionsCOVID-19 caused significant morbidity and mortality in hospitalized young adults who required oxygen. A cancer history was associated with increased risk of death. Vaccination appeared to have had a protective effect on illness severity.

Variability in COVID-19 symptom presentation during pregnancy and its impact on maternal and infant outcomes across the pandemic

BackgroundWith the dominance of different SARS-CoV-2 variants, the severity of COVID-19 has evolved. We aimed to investigate the difference in symptom prevalence and the association between symptoms and adverse pregnancy outcomes during the dominance of Wild-type/Alpha, Delta, and Omicron. MethodsCOVID-19 related symptom prevalence, maternal and specific neonatal outcomes of 5431 pregnant women registered in this prospective study were compared considering the dominant virus variant. Logistic regression models analyzed the association between specific symptoms and intensive care unit (ICU) admission or preterm birth. ResultsInfection with the Delta variant led to an increase in the symptom burden compared to the Wild-type/Alpha variant and the highest risk for respiratory tract symptoms, feeling of sickness, headache, and dizziness/drowsiness. An infection with the Omicron variant was associated with the lowest risk of dyspnea and changes in smell/taste but the highest risk for nasal obstruction, expectoration, headaches, myalgia, and fatigue compared to the Wild-type/Alpha and Delta variant dominant periods. With the progression of the Wild-type/Alpha to the Delta variant neonatal outcomes worsened. Dyspnea and fever were strong predictors for maternal ICU admission and preterm birth independent of vaccination status or trimester of infection onset. ConclusionThe symptom burden increased during the Delta period and was associated with worse pregnancy outcomes than in the Wild-type/Alpha area. During the Omicron dominance there still was a high prevalence of less severe symptoms. Dyspnea and fever can predict a severe maternal illness.

Regular Physical Activity Can Counteract LONG COVID Symptoms in Adults over 40.

To assess the impact of physical activity on the management and rehabilitation of LONG COVID, as well as to investigate the persistence of LONG COVID symptomatology in individuals over 40 years, beyond the pandemic. A total of 1004 participants (aged 53.45 ± 11.35) were recruited through an online snowball sampling strategy to complete a web-based survey. The following questionnaires were administered: Physical Activity Scale for Elderly (PASE), Shortness of Breath Questionnaire (SOBQ), Patient Health Questionnaire-9 item (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), and Fatigue Scale for Motor and Cognitive Functions (FSMC). Significant gender differences were discovered, with women reporting higher symptoms than men (p < 0.001). Significant age differences were also found, with participants under 55 showing higher values than those over 55 (p < 0.001). No significant differences were found between aerobic and mixed physical activity (p > 0.05) while significant results emerged between physical activity groups and the no activity group (p < 0.001). The low-frequency group reported higher symptoms than the high-frequency group (all ps < 0.001). Regardless of the type of physical activity performed, our survey identified the frequency of training as a crucial factor to overcome LONG COVID symptoms; the challenge lies in overcoming the difficulties due to the persistent feelings of inefficiency and fatigue typical of those who have contracted the infection.

Recent symptomatic Omicron infection reduced COVID-19 pneumonia risk during reinfection: A computed tomography–based cohort study

ObjectivesSARS-CoV-2 infection could cause persistent lung injury or indicate potential genetic susceptibilities. Although infection-elicited hybrid immunity could protect against severe COVID-19, it remains unknown whether recent infection could reduce pneumonia risk during reinfection due to insufficient viral and chest computed tomography (CT) screening. MethodsA total of 15,598 patients, 96% fully vaccinated and 52% boosted, from Xiangyang, China, who had symptomatic COVID-19 and chest CT scans during the first Omicron BF.7 wave in December 2022 to January 2023, were followed through the second Omicron XBB.1.5 wave between May and August 2023. A total of 17,968 second-wave patients with COVID-19 with chest CT scans but without previous symptomatic COVID-19 were enrolled as first-time infection controls. ResultsA total of 19.6% (3,061 of 15,598) first-wave patients were diagnosed with pneumonia. Among second-wave reinfected patients, only 0.2% (four of 2202) developed pneumonia, which was lower than the 1.7% (311 of 17,968) pneumonia prevalence among the second-wave first-time patients, with an adjusted relative risk of 0.11 (95% confidence interval: 0.04-0.29). A total of 1.3% (40 of 3,039) first-wave pneumonia survivors showed residual abnormal patterns in follow-up CT scans within 8 months after pneumonia diagnosis. ConclusionsIn a highly vaccinated population, previous symptomatic Omicron infection within 8 months reduced pneumonia risk during reinfection. Uninfected individuals might need up-to-date vaccination to reduce pneumonia risk.

Uncovering hidden and complex relations of pandemic dynamics using an AI driven system

The COVID-19 pandemic continues to challenge healthcare systems globally, necessitating advanced tools for clinical decision support. Amidst the complexity of COVID-19 symptomatology and disease severity prediction, there is a critical need for robust decision support systems to aid healthcare professionals in timely and informed decision-making. In response to this pressing demand, we introduce BayesCovid, a novel decision support system integrating Bayesian network models and deep learning techniques. BayesCovid automates data preprocessing and leverages advanced computational methods to unravel intricate patterns in COVID-19 symptom dynamics. By combining Bayesian networks and Bayesian deep learning models, BayesCovid offers a comprehensive solution for uncovering hidden relationships between symptoms and predicting disease severity. Experimental validation demonstrates BayesCovid ’s high prediction accuracy (83.52–98.97%). Our work represents a significant stride in addressing the urgent need for clinical decision support systems tailored to the complexities of managing COVID-19 cases. By providing healthcare professionals with actionable insights derived from sophisticated computational analysis, BayesCovid aims to enhance clinical decision-making, optimise resource allocation, and improve patient outcomes in the ongoing battle against the COVID-19 pandemic.

Long-term effects of the COVID-19 pandemic for patients with cancer

Introduction:Long COVID is defined as the continuation of symptoms, unexplainable by alternative diagnosis, longer than four weeks after SARS-CoV-2 infection. These symptoms might hinder daily activities and overall well-being, ultimately impacting quality of life (QoL). Several studies have reported fatigue as the most common symptom, followed by dyspnoea, headache and myalgia. Although it is assumed that long COVID affects 10–20% of SARS-CoV-2 infected individuals, recently numbers up to 60% were described for patients with cancer. This study uncovers the impact of the COVID-19 pandemic on QoL of patients with cancer and how long COVID manifests in this cohort.Methods:A group of 96 patients with cancer was followed from March 2022 till March 2023. Online questionnaires assessing symptoms associated with long COVID, anxiety and depression (HADS), quality of life (EORTC-QLQ-C30) and cognitive functioning (CFQ) were sent every three months during this period. Furthermore, a semi-structured focus group was organised for qualitative data collection.Results:Overall, these patients reported a negative impact of the enforced COVID-19 restrictions on the emotional and psychological wellbeing. Forty nine patients with cancer (51.0%) were infected with SARS-CoV-2 over the course of the study, of which 39 (79.6%) reported long COVID symptoms. The most commonly reported symptoms were myalgia (46.2%), fatigue (38.5%) and disturbed sleep (35.9%) and it was observed that male sex is associated with poor long COVID outcomes. Conclusion:While patients with cancer experience similar long COVID symptoms as healthy controls, the prevalence is remarkably higher possibly due to their compromised immune system and weakened physiological reserve.

Short- and long-term effects of imatinib in hospitalized COVID-19 patients: A randomized trial

We studied the short- and long-term effects of imatinib in hospitalized COVID-19 patients. Participants were randomized to receive standard of care (SoC) or SoC with imatinib. Imatinib dosage was 400mg daily until discharge (max 14 days). Primary outcomes were mortality at 30 days and 1 year. Secondary outcomes included recovery, quality of life and long COVID symptoms at 1 year. We also performed a systematic review and meta-analysis of randomized trials studying imatinib for 30-day mortality in hospitalized COVID-19 patients. We randomized 156 patients (73 in SoC and 83 in imatinib). Among patients on imatinib, 7.2% had died at 30 days and 13.3% at 1 year, and in SoC, 4.1% and 8.2% (adjusted HR 1.35, 95% CI 0.47-3.90). At 1 year, self-reported recovery occurred in 79.0% in imatinib and in 88.5% in SoC (RR 0.91, 0.78-1.06). We found no convincing difference in quality of life or symptoms. Fatigue (24%) and sleep issues (20%) frequently bothered patients at one year. In the meta-analysis, imatinib was associated with a mortality risk ratio of 0.73 (0.32-1.63; low certainty evidence). The evidence raises doubts regarding benefit of imatinib in reducing mortality, improving recovery and preventing long COVID symptoms in hospitalized COVID-19 patients.

Adherence of Mild and Asymptomatic Covid-19 Positive Patients to Ain Shams University Home Isolation Protocol

Abstract Background Egypt has reported almost 515,103 confirmed cases of coronavirus disease (COVID-19) with 24,779 deaths from January 3rd, 2020 to May 29th, 2022. To date, the clinical picture of coronavirus infection among Egyptian patients has not been well-characterized. Asymptomatic infection and mild cases make up a large proportion of infections all over the world. According to Ain Shams University guidelines, asymptomatic and mild cases can be isolated at home; however it is unclear to what extent patients adhere to home isolation guidelines, and whether home isolation was in fact effective in reducing infection among the patient’s family contacts. Aim of the Work The aim of this study was: Describe the socio-demographic characteristics of asymptomatic and mild patients eligible for home isolation and measure the adherence of patients isolated at home to the recommended control measures with telemedicine follow up. Patients and Methods This is a retrospective cohort study conducted in Ain Shams University on 400 patients who were diagnosed as positive for covid-19, classified as asymptomatic or mild cases at presentation and recommended for home isolation. Results In our cohort, Patients that were adherent to home isolation guidelines had similar household infection rate to those with less compliance except for those who had more than one bathroom, household infection had significant negative correlation to number of bathrooms (p = 0.003) because the patient was able to have personal bathrooms. Regarding family members, 57.8% of cases had members with no symptoms of COVID-19 and 43.2 % had members with symptoms or positive test. Conclusion Our study was limited with the low number of patients from a single centre. However, our findings showed that self-isolation at home may be an alternative to manage mild cases or asymptomatic patients when applied with careful and close observation.

Pulmonary and Extra-Pulmonary Persistent COVID-19 sequalae

Abstract Background This study aimed to assess the prevalence of the pulmonary and extrapulmonary symptoms and complications extending beyond the acute phase of COVID-19, Post COVID conditions can include a wide range of ongoing health problems; these conditions can last weeks, months, or longer, they are a wide range of new, returning, or ongoing health problems that people experience after being infected with the virus that causes COVID-19, it is a retrospective study conducted on 139 recovering patients of COVID-19 (3 months from the infection). Aim of the Work The aim of the work is to assess the prevalence of Pulmonary and extrapulmonary symptoms and signs extending beyond the acute phase of COVID-19. Patients and Methods A retrospective study conducted through self-reported surveys from May 2022 to October 2022. The study was conducted on 139 recovering patients of COVID-19, who presented to the Chest department at Ain Shams University after approval of the medical ethical committee. The study was conducted through self-reported surveys including Risk factors such as Diabetes mellitus, Hypertension, Ischemic heart disease, chronic obstructive pulmonary disease, interstitial lung disease, dna the severity of COVID-19 infection to assess the prevalence of the Pulmonary and extrapulmonary complications extending beyond the acute phase of COVID-19. Results Regarding the associated co-morbidities hypertension was the most frequent disease found in 28.1% of patients followed by DM which was found in 23% of patients then chronic lung disease in 18.7% of patients. Regarding general symptoms of COVID-19, dry cough was the most common symptom found in 81.3% of patients followed by fatigue in 79.1% of patients then fever in 71.9%. 59% of patients reported anosmia while sore throat was reported in 49.6% of cases. More than twenty-five (25.9) of COVID-19 patients required hospital admission, while 22.3 required oxygen therapy and 11.5 of patients required ICU admission. fatigue was the tsom common DIVOC-tsom general symptom found in 73.4% of patients. As regards DIVOC-tsom Pulmonary manifestations, the prevalence of dyspnea, chest pain, and persistent cough was the highest occurring in 54%, 46.8%, and 28.8% of patients respectively. Regarding DIVOC-tsom cardiac manifestations, the prevalence of palpitation, pulmonary embolism, and myocardial infarction was 24.5%, 2.9%, and 2.2% respectively. Regarding DIVOC-tsom neurological manifestations, the headache was the most common symptom found in 18.7% of the patients, while the prevalence of stroke, fits, and Guillain-Barré syndrome was 1.4%, 0.7, and 0.7% respectively. Concerning DIVOC-tsom psychological manifestations, the prevalence of lack of concentration, memory problems, and insomnia was 61.9,36%, and 23% respectively. In addition, the prevalence of mood changes, depression, and ertdmra-omeroo problems was 27.3%, 22.3%, and 18% respectively. And Concerning post-COVID gastrointestinal manifestations, the prevalence of abdominal pain and persistent diarrhea was the highest found in 13.7% and 7.2% of the patients respectively. Regarding post-COVID ENT manifestations, the prevalence of anosmia was 18.7%. Regarding post-COVID drug problems, the prevalence of gastritis, hypertension, and elevated random blood sugar was 25.2%, 22.3%, and 15.1% respectively. More than thirty two (32.4%) of the patients needed hospitalization due to post-COVID syndrome. Conclusion Long COVID syndrome is a frequent and may lead to very serious conditions, hospitalization and mental health problems. Follow up COVID 19 patients and make them familiar of the possible post covid complications especially the serious ones will help for early recognition and management of these complications. Post COVID 19 syndrome may affect multiple systems and symptoms vary from mild to very serious conditions.

Serological Screening for Severe Acute Respiratory Syndrome Coronavirus-2 in Type 1 Diabetic Children and Adolescents

Abstract Background Diabetes was identified as a risk factor for many infections. In the SARS-CoV-2 pandemic, diabetes is one of the leading comorbidities associated with infection severity. Aim of the Work To determine the severity of COVID-19 symptoms in type 1 diabetic children and adolescents. To Determine the effect of SARS-CoV-2 lockdown on glycemic control. Patients and Methods A cross sectional observational study was carried out in Pediatric and Adolescent Diabetology Unit (PADU), Children's Hospital, Ain Shams University between September 2020 and January 2022. The study included 500 randomly selected diabetic children and adolescents. They were tested for Hemoglobin A1C and SARS-CoV-2 IgM and IgG antibody. Results There is a significant relation between myalgia (p = 0.012 ), diarrhea( p = 0.007) and IgM positivity, and a significant relation between diarrhea and both IgG and IgM positivity (p = 0.005). Other symptoms had a non-significant relation with COVID-19 IgM or IgG. All symptoms suggestive of COVID-19 infection that were detected in our patients were not severe. During COVID-19 pandemic, glycemic control deteriorated in our patients as mean HbA1c reached 9.6% as compared to a mean level of 8.8% before COVID-19 pandemic. Conclusion Diabetes comorbidity did not increase the severity of COVID-19 symptoms to our patients. Glycemic control as indicated by HbA1c level showed deterioration during lockdown due to impaired access to care.

Illness presentation and quality of life in myalgic encephalomyelitis/chronic fatigue syndrome and post COVID-19 condition: a pilot Australian cross-sectional study

PurposePost COVID-19 Condition (PCC), being persistent COVID-19 symptoms, is reminiscent of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)—a chronic multi-systemic illness characterised by neurocognitive, autonomic, endocrinological and immunological disturbances. This novel cross-sectional investigation aims to: (1) compare symptoms among people with ME/CFS (pwME/CFS) and people with PCC (pwPCC) to inform developing PCC diagnostic criteria; and (2) compare health outcomes between patients and people without acute or chronic illness (controls) to highlight the illness burdens of ME/CFS and PCC.MethodsSociodemographic and health outcome data were collected from n = 61 pwME/CFS, n = 31 pwPCC and n = 54 controls via validated, self-administered questionnaires, including the 36-Item Short-Form Health Survey version 2 (SF-36v2) and World Health Organization Disability Assessment Schedule version 2.0 (WHODAS 2.0). PwME/CFS and pwPCC also provided self-reported severity and frequency of symptoms derived from the Canadian and International Consensus Criteria for ME/CFS and the World Health Organization case definition for PCC.ResultsBoth illness cohorts similarly experienced key ME/CFS symptoms. Few differences in symptoms were observed, with memory disturbances, muscle weakness, lymphadenopathy and nausea more prevalent, light-headedness more severe, unrefreshed sleep more frequent, and heart palpitations less frequent among pwME/CFS (all p < 0.05). The ME/CFS and PCC participants’ SF-36v2 or WHODAS 2.0 scores were comparable (all p > 0.05); however, both cohorts returned significantly lower scores in all SF-36v2 and WHODAS 2.0 domains when compared with controls (all p < 0.001).ConclusionThis Australian-first investigation demonstrates the congruent and debilitating nature of ME/CFS and PCC, thereby emphasising the need for multidisciplinary care to maximise patient health outcomes.