Suspected COVID-19 Research Articles

The Symptomatic Expression in Chinese Patients with Suspected COVID-19 Omicron Variant Infection: A Clinical Case Registry Study

Little systematic research has been conducted into the symptomatic expression of COVID-19 infections in patients. It is known that symptomatic expression varies between patients, but the nature and extent of this variability is poorly understood. This paper elaborates on the symptoms reported by Chinese patients infected with COVID-19 during the Omicron wave, and compares this with available data from other countries. This was an observational clinical case registry study of Chinese patients with suspected Omicron variant COVID-19 infection. Symptoms were prospectively collected via a 171-item questionnaire and entered into the Clificol COVID-19 Clinical Case Registry. Two types of symptoms were distinguished: A) common clinical symptoms as identified by a search of available/published data, and B) homeopathic symptoms, used for the selection of the most suitable homeopathic medicine. Data were mainly analysed descriptively. Additionally, we compared the prevalence of the reported symptoms with available symptom data from the UK and France. Twenty one Chinese practitioners collected questionnaires on 388 cases that received a first homeopathic prescription between 5 December 2021 and 8 April 2022. With respect to A), the most frequently reported clinical symptoms were respectively cough (71%), fever (65%), extreme tiredness (58%), headache (51%), sore throat (46%), runny nose (34%), unusual muscle pains (31%), hoarseness (21%), eye soreness (8%) and brain fog (6%). With respect to B), homeopathic symptoms related to cough and fever were particularly prevalent. This study identified the reported symptoms of Chinese COVID-19 patients with suspected Omicron variant infection. A more detailed understanding of the clinical presentation of COVID-19 variants in different countries is important for the selection of test-triggering symptoms.

Spot Diagnosis for Suspected COVID-19 Cases: Is there a Place for a Traditional Weapon in Modern Combat?

Spot Diagnosis for Suspected COVID-19 Cases: Is there a Place for a Traditional Weapon in Modern Combat?

The Relation of Polymerase Chain Reaction and Computed Tomography Infiltrations of Suspected Covid-19 Patients in Emergency Department

Aims: In the context of the persistent global challenge posed by COVID-19, effective diagnostic methods are crucial. Considering the limitations of Polymerase Chain Reaction (PCR) in the Emergency Department (ED), alternative confirmation methods for assessing Covid-19 are needed. This study aimed to evaluate the performance of Thorax-Computed Tomography (T-CT), following Radiological Society of North America (RSNA) recommendations, for suspected Covid-19 patients with pulmonary infiltrations. Materials and Methods: From March to August 2020, 324 ED patients with suspected Covid-19 underwent T-CT scans. Blinded radiologists independently assessed T-CT scans based on RSNA guidelines. Reverse-transcriptase polymerase chain reaction (RT-PCR) served as the reference test. Results: Of 324 patients, 35% tested positive via RT-PCR. T-CT categories were typical (35.2%), indeterminate (47.5%), and atypical (11.1%). Using a typical T-CT category threshold resulted in 66% sensitivity, 81% specificity, 65% positive predictive value (PPV), 82% negative predictive value (NPV), and 76% accuracy. Subgroup analysis of repeat RT-PCR tests improved performance: 80% sensitivity, 79% specificity, 76% PPV, 83% NPV, and 79% accuracy. Combining RT-PCR and T-CT in the ED achieved 95.5% sensitivity, 79% PPV, and 86.4% accuracy. Conclusion: Following RSNA guidelines, T-CT exhibits moderate sensitivity and high specificity for detecting Covid-19. In ED settings with suspected cases, T-CT aids in recommending retesting after an initial negative RT-PCR result, facilitating early management and enabling timely isolation measures. The combined use of RT-PCR and T-CT enhances diagnostic performance, emphasizing the potential benefits of integrating these methods.

Knowledge and Confidence Level among Emergency Healthcare Workers in Airway Management and Resuscitation of Suspected Covid-19 Patients: A Cross-Sectional Study in Penang and Kelantan

INTRODUCTION: COVID-19 cases in Malaysia have followed a never-ending course of spike and fall since it was first detected. Though the prominent role of infection control standard precautions were strictly applied, cases among emergency healthcare workers (EHCW) contracting the disease continue to rise. Our study aims to evaluate the knowledge and confidence level and the factors that may influence the knowledge and confidence level among EHCW in airway management and resuscitation of suspected COVID-19 patients. MATERIALS AND METHODS: This was a cross-sectional study conducted in tertiary hospitals in Penang and Kelantan using a validated questionnaire. The territories evaluated include the possible method of transmission, proper steps during resuscitation, airway management and intubation, intensive care management, and etiquette of personal protective equipment. RESULTS: Out of 543 EHCW eligible for the study, only 300 participants responded to the questionnaire. Our study showed only 15.3% of respondents had good knowledge and 62.3% had high confidence in airway management and resuscitation of suspected COVID-19 patients. Significant associations were seen in knowledge and confidence level among respondents with previous experience attending continuing medical education (F=7.041, P=0.008 and F=19.398, P<0.001 respectively). Significant associations were also demonstrated in confidence level among respondents with previous simulation training experience (F=13.905, P<0.001). CONCLUSION: Our study revealed that most EHCW had poor knowledge and moderately adequate confidence in the airway management and resuscitation of suspected COVID-19 patients. A more comprehensive and strategized training program needs to be conducted to help in improvement of the knowledge and confidence level among EHCW.

Pandemic phase-related racial and ethnic disparities in COVID-19 positivity and outcomes among patients presenting to emergency departments during the first two pandemic waves in the USA

BackgroundIn many countries including the USA, the UK and Canada, the impact of COVID-19 on people of colour has been disproportionately high but examination of disparities in patients presenting to...

Evaluation of Non-COVID-19 CT Scan Findings Detected on CT Images Performed due to Suspected COVID-19 Pneumonia: A Retrospective Analysis of 6669 Cases

Evaluation of Non-COVID-19 CT Scan Findings Detected on CT Images Performed due to Suspected COVID-19 Pneumonia: A Retrospective Analysis of 6669 Cases

Internalized stigma related to COVID-19 and its psychosocial and mental health correlates: a multicentric health facility based observational study from Nepal.

The COVID-19 pandemic has led to physical and psychological complications and social consequences in the form of illness-related stigma. This study aimed (1) to assess the sociodemographic and clinical variable, as well as COVID-19 related knowledge and perception of persons admitted for COVID-19/Suspected COVID-19 in Nepal, (2) to determine their levels of COVID-19- related internalized stigma, depression, and anxiety symptoms, and (3) to evaluate the correlates of COVID-19- related internalized stigma. It was a cross-sectional exploratory study with a convenience sample of 395 participants (306 confirmed cases, 89 suspected cases) conducted between July-October 2020 in four health facilities in Madhesh and Lumbini provinces of Nepal. We used a semi-structured questionnaire to assess sociodemographic details, clinical information, COVID-19-related knowledge, perception, COVID-19-related internalized stigma, and the Hamilton Anxiety Depression Scale (HADS) in Nepali language. Descriptive statistics, correlation analyses, and linear regression analyses were performed. The level of statistical significance was considered at p < 0.05. Around 23.3% of the patients had anxiety symptoms, 32.9% had depressive symptoms, and 20.3% had high COVID-19-related internalized stigma (mean ISMI score: 2.51-4.00). Linear regression analyses showed a significant positive association of COVID-19-related internalized stigma total score, with the following eight factors, i.e., no income in the past one month (p = 0.013), below average socioeconomic status (p = 0.004), anxiety symptoms (p = <0.001), depressive symptoms (p = <0.001), recent testing positive for COVID-19 (p = <0.001), involuntary admission (p = <0.001), prior experience of being in isolation and quarantine (p = 0.045), and those who blame others for COVID-19 (p = 0.025). COVID-19 survivors and suspects are vulnerable to symptoms of depression, anxiety, and COVID-19-related internalized stigma. For the first time from Nepal, our data suggests that COVID-19-related internalized stigma is associated with anxiety and depression symptoms, perceived below-average socioeconomic status, involuntary admission, prior experience of being in isolation and quarantine, recent COVID-19 positive report, self-blame, below-average socioeconomic status and no income in the past one month. Mitigating and preventing internalized stigma associated with a public health crisis such as COVID-19 is imperative by diagnosing and treating such mental health issues early and designing interventions and policies especially targeting vulnerable populations focusing on their economic background and socio-cultural beliefs.

Comparison of Clinic and Demographic Characteristics of Children with Laboratory-Confirmed and Suspected COVID-19 who Admitted to Pediatric Emergency Clinic

Aim: To determine the frequency of COVID-19 infection in children and to compare the parameters of laboratory-confirmed and suspected cases.&#x0D; &#x0D; Material and Methods: Medical records collected with a prospective design of 1300 pediatric patients who applied to COVID-19 triage of pediatric emergency service. Clinic and demographic characteristics of children with laboratory-confirmed and suspected COVID-19 were compared. Nasopharyngeal swab sample was taken from all pediatric patients in accordance with the possible case definition determined by the national Ministry of Health.&#x0D; &#x0D; Results: The COVID-19 test was found positive in 94 (7.2%) children. Of those, 34.5% children had a history of contact, and 31.9% of all cases were asymptomatic. The mean age of children who were positive for COVID-19 was higher than those who were negative (p

MSTAC: A Multi-Stage Automated Classification of COVID-19 Chest X-ray Images Using Stacked CNN Models.

This study introduces a Multi-Stage Automated Classification (MSTAC) system for COVID-19 chest X-ray (CXR) images, utilizing stacked Convolutional Neural Network (CNN) models. Suspected COVID-19 patients often undergo CXR imaging, making it valuable for disease classification. The study collected CXR images from public datasets and aimed to differentiate between COVID-19, non-COVID-19, and healthy cases. MSTAC employs two classification stages: the first distinguishes healthy from unhealthy cases, and the second further classifies COVID-19 and non-COVID-19 cases. Compared to a single CNN-Multiclass model, MSTAC demonstrated superior classification performance, achieving 97.30% accuracy and sensitivity. In contrast, the CNN-Multiclass model showed 94.76% accuracy and sensitivity. MSTAC's effectiveness is highlighted in its promising results over the CNN-Multiclass model, suggesting its potential to assist healthcare professionals in efficiently diagnosing COVID-19 cases. The system outperformed similar techniques, emphasizing its accuracy and efficiency in COVID-19 diagnosis. This research underscores MSTAC as a valuable tool in medical image analysis for enhanced disease classification.

Correlation between Chest Computed Tomography Severity Scores and Age of Adult Patients with Suspected Covid-19 Pneumonia Admitted in Intensive Care Unit of a Tertiary Care Hospital, Bangladesh

In Bangladesh, the second wave of Covid-19 was devastating. Mostly RT-PCR is used to determine the Covid-19 infection. But when test results are delayed, or when there is a clinical suspicion of Covid-19 despite initial negative RT-PCR testing, CT scan of chest was used to detect Covid-19 and Covid-19 severity. This observational cross-sectional study was carried out at Corona dedicated ICU of Bangabandhu Sheikh Mujib Medical College Hospital, Faridpur during February to June, 2021 to observe the HRCT severity score of the patient and its correlation with different ages. A total of 50 patients with clinically suspected Covid-19 cases who were admitted to the Corona dedicated ICU were included in the study. The chest HRCT images of study participants was gathered, CT severity score was calculated by a particular assignment radiologist. Based on this score; Severe disease was mainly seen in the &gt;60 year age group (50%). A significant moderate positive correlation was observed between age and CT chest severity score. With the increasing age the patients were suffering more and being male may increase the risk and put the patient to get admitted in the ICU, and as an alternative of the RT-PCR, CT scan of chest could be useful. Bangabandhu Sheikh Mujib Med. Coll. J. 2023;2(2):77-82

Investigation of the Frequency of Respiratory Viral Co-Infection in Respiratory Samples of Suspected COVID-19 Patients

Investigation of the Frequency of Respiratory Viral Co-Infection in Respiratory Samples of Suspected COVID-19 Patients

(010) Catatonia in the Setting of Suspected COVID-19 Associated Autoimmune Rhombencephalitis in a Patient With No Known Psychiatric History

(010) Catatonia in the Setting of Suspected COVID-19 Associated Autoimmune Rhombencephalitis in a Patient With No Known Psychiatric History

Primary care gatekeeping during the COVID-19 pandemic: a survey of 1234 Norwegian regular GPs.

In the Nordic healthcare systems, GPs regulate access to secondary health services as gatekeepers. Limited knowledge exists about the gatekeeper role of GPs during public health crises seen from the perspective of GPs. To document GPs' gatekeeper role and organisational changes during the initial COVID-19 lockdown in Norway. A cross-sectional online survey was addressed to all regular Norwegian GPs (n = 4858) during pandemic lockdown in spring 2020. Each GP documented how patients with potential COVID-19 disease were triaged and handled during a full regular workday. The survey also covered workload, organisational changes, and views on advice given by the authorities. A total of 1234 (25.4%) of Norway's GPs participated. Together, they documented nearly 18 000 consultations, of which 65% were performed digitally (video, text, and telephone). Suspected COVID-19 symptoms were reported in 11% of the consultations. Nearly all these patients were managed in primary care, either in regular GP offices (55.7%) or GP-run municipal respiratory clinics (40.7%), while 3.7% (n = 73) were admitted to hospitals. The GPs proactively contacted an average of 0.8 at-risk patients per day. While 84% were satisfied with the information provided by the medical authorities, only 20% were able to reorganise their practice in accordance with national recommendations. During the early stage of the COVID-19 pandemic in Norway, the vast majority of patients with COVID-19-suspected symptoms were handled in primary care. This is likely to have protected secondary health services from potentially detrimental exposure to contagion and breakdown of capacity limits.

Web-based Non-contact Edge Computing Solution for Suspected COVID-19 Infection Classification Model

The recent outbreak of the COVID-19 coronavirus pandemic has necessitated the development of web-based, non-contact edge analytics solutions. Non-contact sensors serve as the interface between web servers and edge analytics through web engineering technology. The need for an edge device classification model that can identify COVID-19 patients based on early symptoms has become evident. In particular a non-contact implementation of such a classification model is required to efficiently prevent viral infection and minimize cross-infection. In this work, we investigate the use of diverse non-contact biosensors (e.g., remote photoplethysmography, radar, and infrared sensors) for reducing effective physical contact with patients and for measuring their biometric data and vital signs. We further explain a classification method for suspected COVID-19 infection based on the measured vital signs and symptoms. The results of this study can be applied in patient classification by mobile-based edge computing applications. The correlation between symptoms comprising cough, sore throat, fever, headache, myalgia, and arthralgia are analyzed in the model. We implement a machine learning classification model using vital signs for performance evaluation, and propose an ensemble model realized by fine-tuning the high-performing classification models. The proposed ensemble model successfully distinguishes suspected patients with an accuracy, area under curve, and F1 scores of 94.4%, 98.4%, and 94.4%, respectively.

Evaluating the Triage of Suspected COVID-19 Cases in Sudan's Emergency Settings: A Clinical Audit.

The inevitable coronavirus disease 2019 global pandemic has severely affected Sudan's fragile healthcare system. The authors share the experience of COVID-19 triage in the emergency departments of five public hospitals in Khartoum state, Sudan. A clinical audit was conducted in December 2020 using the Centers for Disease Control and Prevention Checklist and Monitoring Tool for Triage of Suspected COVID-19 Cases. The tool was categorised into 5 domains and 38 indicators. Only three hospitals had hand hygiene stations in their triage areas: Ibrahim Malik, Omdurman, and Al-Nau. Omdurman Teaching Hospital was the sole hospital with a designated respiratory waiting area. At Al-Nau and Omdurman Hospitals, all respiratory symptomatic patients wore a facemask or alternative. Ibrahim Malik and Bahri Teaching Hospitals had 60% and 50% compliance, respectively, while none at El-Tamayouz Hospital did. No posters or job aids were present in donning and doffing areas. Heavy duty gloves were worn only at Ibrahim Malik (50%) and Omdurman (20%). 100% of staff wore closed-toe footwear at Ibrahim Malik and Omdurman, 75% at El-Tamayouz, 63% at Bahri, and none at Al-Nau. The healthcare facilities displayed significant shortcomings in preparedness and response to COVID-19, with variations across hospitals in infrastructure, human resources, and procedures. To better combat future outbreaks, systemic improvements and a focused approach on consistent staff training, standard triage algorithms, and adequate PPE availability are imperative.

Epidemiological and Demographic Analysis of Suspected Covid-19 Cases Confirmed by PCR at Medical Center ISSEMyM Toluca from March 2019 to December 2022

Objective: To describe the prevalence and incidence of suspected COVID-19 cases confirmed by PCR at Medical Center ISSEMyM Toluca from March 2019 to December 2022. Materials and Methods: 3226 PCR tests for suspected COVID-19 cases were analyzed to obtain epidemiological and demographic data of the population, descriptive and inferential statistics analyses were carried out to find differences between population parameters. Results: No differences between female and male respect to COVID-19 positivity were found (p-value = 0.9302). Age mean was 49 years old and the probability to get COVID-19 increase with age (p-value = 0.000). Hospitalization was the medical service with more frequency in patients with COVID-19 positive. Conclusion: Age but no gender is a risk factor hospitalization due COVID-19., nonetheless vaccination appear to an efficient method to prevent hospitalization. Moreover, the dynamic pandemic in Mexico is no homogeneous across the territory.

A New HRCT Score for Diagnosing SARS-CoV-2 Pneumonia: A Single-Center Study with 1153 Suspected COVID-19 Patients in the Emergency Department

The 2019 coronavirus disease (COVID-19) pandemic is affecting millions of people worldwide. Chest high-resolution computed tomography (HRCT) is commonly used as a diagnostic test for suspected COVID-19; however, despite numerous attempts, there is no single scoring system that is widely accepted and used in clinical practice to estimate the probability of SARS-CoV-2 pneumonia. The aim of this single-center retrospective study is to develop a radiological score to predict the probability of COVID-19 with HRCT. Patients admitted to the emergency department with symptoms suggestive of COVID-19 who underwent both HRCT and RT-PCR on nasopharyngeal swab to detect SARS-CoV-2 infection between 1 March and 30 April 2020 were included. A multivariable regression analysis was conducted to identify all HRCT signs independently associated with a positive RT-PCR assay for SARS-CoV-2 and build the HRCT score. A total of 1153 patients were enrolled in this study. The number of segments with ground glass opacities (OR 1.18, 95% CI 1.11–1.26), number of segments with linear opacities (OR 1.21, 95% CI 1.05–1.42), crazy paving patterns (OR 6, 95% CI 3.79–9.76), and vascular ectasia in each segment (OR 2.46, 95% CI 1.1.5–5.8) were included in the score. The HRCT score showed high discriminatory power (area under the ROC curve of 0.8267 [95% CI 0.8–0.85]) with 72.2% sensitivity, 86.6% specificity, 78% PPV, and 83% NPV for its best cut-off. In summary, the HRCT score has good diagnostic and discriminatory accuracy for COVID-19 and is easy and quick to perform.

Incidental Thorax CT Findings in Patients with Suspected COVID-19 Pneumonia

Incidental Thorax CT Findings in Patients with Suspected COVID-19 Pneumonia

SARS-CoV-2-Specific Immune Responses in Patients With Postviral Syndrome After Suspected COVID-19.

Millions of Americans were exposed to SARS-CoV-2 early in the pandemic but could not get diagnosed with COVID-19 due to testing limitations. Many have developed a postviral syndrome (PVS) including neurologic manifestations similar to those with postacute sequelae of SARS-CoV-2 infection (Neuro-PASC). Owing to those circumstances, proof of SARS-CoV-2 infection was not required for evaluation at Northwestern Medicine's Neuro COVID-19 clinic. We sought to investigate clinical and immunologic findings suggestive of SARS-CoV-2 exposure in patients with PVS. We measured SARS-CoV-2-specific humoral and cell-mediated immune responses against Nucleocapsid and Spike proteins in 29 patients with PVS after suspected COVID-19, 32 confirmed age-matched/sex-matched Neuro-PASC (NP) patients, and 18 unexposed healthy controls. Neurologic symptoms and signs, comorbidities, quality of life, and cognitive testing data collected during clinic visits were studied retrospectively. Of 29 patients with PVS, 12 (41%) had detectable humoral or cellular immune responses consistent with prior exposure to SARS-CoV-2. Of 12 PVS responders (PVS+), 75% harbored anti-Nucleocapsid and 50% harbored anti-Spike responses. Patients with PVS+ had similar neurologic symptoms as patients with NP, but clinic evaluation occurred 5.3 months later from the time of symptom onset (10.7 vs 5.4 months; p = 0.0006). Patients with PVS+ and NP had similar subjective impairments in quality of life measures including cognitive function and fatigue. Patients with PVS+ had similar results in objective cognitive measures of processing speed, attention, and executive function and better results in working memory than patients with NP. Antibody and T-cell assays showed evidence of prior SARS-CoV-2 exposure in approximately 40% of the PVS group. Three-quarters of patients with PVS+ had detectable anti-Nucleocapsid and one-half anti-Spike responses, highlighting the importance of multitargeted COVID-19 immunologic evaluation and the limitations of commercially available diagnostic tests. Despite their persistent symptoms, lack of COVID-19 diagnosis likely delayed clinical care in patients with PVS. Our data suggest that millions of Americans presenting with PVS resembling Neuro-PASC were indeed exposed to SARS-CoV-2 at the beginning of the pandemic, and they deserve the same access to care and inclusion in research studies as patients with NP with confirmed COVID-19 diagnosis.

Rapid Triage of Children with Suspected COVID-19 Using Laboratory-Based Machine-Learning Algorithms

In order to limit the spread of the novel betacoronavirus (SARS-CoV-2), it is necessary to detect positive cases as soon as possible and isolate them. For this purpose, machine-learning algorithms, as a field of artificial intelligence, have been recognized as a promising tool. The aim of this study was to assess the utility of the most common machine-learning algorithms in the rapid triage of children with suspected COVID-19 using easily accessible and inexpensive laboratory parameters. A cross-sectional study was conducted on 566 children treated for respiratory diseases: 280 children with PCR-confirmed SARS-CoV-2 infection and 286 children with respiratory symptoms who were SARS-CoV-2 PCR-negative (control group). Six machine-learning algorithms, based on the blood laboratory data, were tested: random forest, support vector machine, linear discriminant analysis, artificial neural network, k-nearest neighbors, and decision tree. The training set was validated through stratified cross-validation, while the performance of each algorithm was confirmed by an independent test set. Random forest and support vector machine models demonstrated the highest accuracy of 85% and 82.1%, respectively. The models demonstrated better sensitivity than specificity and better negative predictive value than positive predictive value. The F1 score was higher for the random forest than for the support vector machine model, 85.2% and 82.3%, respectively. This study might have significant clinical applications, helping healthcare providers identify children with COVID-19 in the early stage, prior to PCR and/or antigen testing. Additionally, machine-learning algorithms could improve overall testing efficiency with no extra costs for the healthcare facility.