Confirmed Coronavirus Disease 2019 Patients Research Articles

Development and Validation of a Deep Learning-Based Model Using Computed Tomography Imaging for Predicting Disease Severity of Coronavirus Disease 2019.

ObjectivesCoronavirus disease 2019 (COVID-19) is sweeping the globe and has resulted in infections in millions of people. Patients with COVID-19 face a high fatality risk once symptoms worsen; therefore, early identification of severely ill patients can enable early intervention, prevent disease progression, and help reduce mortality. This study aims to develop an artificial intelligence-assisted tool using computed tomography (CT) imaging to predict disease severity and further estimate the risk of developing severe disease in patients suffering from COVID-19.Materials and MethodsInitial CT images of 408 confirmed COVID-19 patients were retrospectively collected between January 1, 2020 and March 18, 2020 from hospitals in Honghu and Nanchang. The data of 303 patients in the People’s Hospital of Honghu were assigned as the training data, and those of 105 patients in The First Affiliated Hospital of Nanchang University were assigned as the test dataset. A deep learning based-model using multiple instance learning and residual convolutional neural network (ResNet34) was developed and validated. The discrimination ability and prediction accuracy of the model were evaluated using the receiver operating characteristic curve and confusion matrix, respectively.ResultsThe deep learning-based model had an area under the curve (AUC) of 0.987 (95% confidence interval [CI]: 0.968–1.00) and an accuracy of 97.4% in the training set, whereas it had an AUC of 0.892 (0.828–0.955) and an accuracy of 81.9% in the test set. In the subgroup analysis of patients who had non-severe COVID-19 on admission, the model achieved AUCs of 0.955 (0.884–1.00) and 0.923 (0.864–0.983) and accuracies of 97.0 and 81.6% in the Honghu and Nanchang subgroups, respectively.ConclusionOur deep learning-based model can accurately predict disease severity as well as disease progression in COVID-19 patients using CT imaging, offering promise for guiding clinical treatment.

Outbreak investigation: transmission of COVID-19 started from a spa facility in a local community in Korea.

OBJECTIVESIn Korea, there have been 10,480 confirmed cases of coronavirus disease 2019 (COVID-19) as of April 11, 2020. We investigated the transmission of COVID-19 in a cluster of cases.METHODSWe analyzed the epidemiological characteristics of 10 confirmed COVID-19 patients in an outbreak that started at Spa facility A in a local community in Korea on March 28, 2020 and traced them through April 8, 2020. Epidemiological surveys and diagnostic tests were conducted for each contact, and the secondary attack rate was estimated.RESULTSThere were 3 male confirmed patients (30.0%) and 7 female confirmed patients (70.0%), and their mean age was 53.5 years (range, 2.0 to 73.0). Two patients (20.0%) were asymptomatic. The incubation period was between 3 days and 12 days. Three confirmed patients were infected at female’s Spa facility A and 7 confirmed patients were second, third, and fourth generations of transmission. Seven confirmed patients contracted COVID-19 through presymptomatic contact. In total, 192 contacts were identified, with a secondary attack rate of 3.6%. Eighty-three contacts (43.2%) were aged 40-59 years, and the secondary attack rate was the highest (12.1%) in those aged ≥60 years. Most exposures (n=156, 81.3%) involved casual contact. The number of visitors using the female’s spa facility was 58, including 3 confirmed patients, resulting in a secondary outbreak rate of 5.9%.CONCLUSIONSThis study presents a cluster of cases occurring in a setting with high temperature and humidity. The second, third, and fourth generations were transmitted through presymptomatic contact.

An Analysis of High-Resolution Computed Tomography Chest Manifestations of COVID-19 Patients in Pakistan.

ObjectiveThe objective of the present study is to describe high-resolution CT (HRCT) chest manifestations of coronavirus disease 2019 (COVID-19) patients presenting to a tertiary healthcare facility in Punjab, Pakistan, and to analyze the distribution of the disease in lung fields. Additionally, we assess the role of chest CT severity scoring (CT-SS) in determining the severity of pneumonia.MethodsIn this cross-sectional descriptive study conducted from March 30, 2020, to May 30, 2020, 87 confirmed COVID-19 patients undergoing HRCT scan in a tertiary care facility in Punjab, Pakistan were included. The HRCT chest was performed on the patients using a standard protocol. Each study was evaluated for the presence of ground-glass opacities (GGOs), consolidation, mixed pattern, distribution, crazy paving, reverse halo sign, nodules, pleural effusion, and other findings. Additionally, CT-SS was calculated by dividing each lung into 20 zones. Each zone was scored as 0, 1, and 2, representing no involvement, <50% involvement, and >50% involvement of one zone respectively (total score: 0-40 for each patient). The patients were classified into mild, moderate, and severe cases (mild: CT-SS of <20, moderate: CT-SS of 20-30, and severe: CT-SS of >30).ResultsGGO was the most common finding, as seen in 88.5% of the patients, followed by consolidations (52.8%) and crazy paving (33.3%). The majority of the patients showed the bilateral and peripheral distribution of the disease process. Vascular dilatation and bronchiectasis were seen in 10 patients; pleural effusions were observed in only two study patients, while no patient exhibited reverse halo sign or pulmonary nodules. The superior segment of lower lobes was the most commonly involved segment bilaterally. According to CT-SS, 78 (89.6%), six (6.9%), and three (3.45%) patients had mild, moderate, and severe disease respectively.ConclusionThe typical imaging findings of COVID-19 on HRCT are GGOs with multilobe involvement and bilateral, peripheral, and basal predominance. CT-SS is helpful in categorizing pneumonia into mild, moderate, and severe types, thereby helping to identify patients with severe disease. This is particularly helpful in settings where fast triage is required.

Evaluation of the exposure risk of SARS-CoV-2 in different hospital environment

The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has imposed a significant impact on social and economic activities. As a high infectious pathogen, the existence of SARS-CoV-2 in public space is very important for its transmission. During the COVID-19 pandemic, hospitals are the main places to deal with the diseases. In this work, we evaluated the exposure risk of SARS-CoV-2 in hospital environment in order to protect healthcare workers (HCWs). Briefly, air and surface samples from 6 different sites of 3 hospitals with different protection levels were collected and tested for the SARS-CoV-2 nucleic acid by reverse transcription real-time fluorescence PCR method during the COVID-19 epidemic. We found that the positive rate of SARS-CoV-2 nucleic acid was 7.7 % in a COVID-19 respiratory investigation wards and 82.6 % in a ICUs with confirmed COVID-19 patients. These results indicated that in some wards of the hospital, such as ICUs occupied by COVID-19 patients, the nucleic acid of SARS-CoV-2 existed in the air and surface, which indicates the potential occupational exposure risk of HCWs. This study has clarified retention of SARS-CoV-2 in different sites of hospital, suggesting that it is necessary to monitor and disinfect the SARS-CoV-2 in hospital environment during COVID-19 pandemic, and will help to prevent the iatrogenic infection and nosocomial transmission of SARS-CoV-2 and to better protect the HCWs.

Clinical Characteristics and Immune Injury Mechanisms in 71 Patients with COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19), caused by the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a threat to global health. The mortality rate of severely ill patients in the early stage is 32.5%. The exacerbation of the condition and death of patients are closely associated with inflammatory cytokine storms, which are caused by excessive activation of the immune and complement systems as well as the coinfection of other pathogens. However, the immunological characteristics and the mechanisms underlying inflammatory storms have not been well elucidated. Here, we analyzed the clinical and immunological characteristics of 71 confirmed COVID-19 patients. Based on the National Health Commission of China (NHCC) guidelines, patients were stratified into mild and severe types. We compared the clinical and laboratory data obtained from electronic medical records between the two types. In regard to the hematological parameters, COVID-19 patients showed decreased erythrocyte count, hemoglobin, hematocrit, lymphocyte count, eosinophil count, and complement C1q, whereas neutrophils, C-reactive protein, and procalcitonin were significantly increased, especially in severe cases. We also found that CD3+ CD4+ T lymphocytes, CD3+ CD8+ T lymphocytes, CD19+ B lymphocytes, and CD16+ CD56+ NK cells in the peripheral blood of all patients were decreased. In addition, CD3+ CD8+ T lymphocytes, CD16+ CD56+ NK cells, and complement C1q in severely ill patients decreased more significantly. Additionally, interleukin 6 (IL-6) elevation was particularly prominent in all patients, especially in severe cases. These results suggest that CD3+ CD8+ T lymphocytes, CD16+ CD56+ NK cells, C1q as well as IL-6 may play critical roles in the inflammatory cytokine storm. The dysregulation of these aforementioned immune parameters, along with bacterial coinfection, were the important causes of exacerbation of the patients' condition and death. This study improves our understanding of the immune dysregulation of COVID-19 and provides potential immunotherapeutic strategies.IMPORTANCE The dysregulation of CD3+ CD8+ T lymphocytes, CD16+ CD56+ NK cells, C1q as well as IL-6, along with bacterial coinfection, were important causes of exacerbation of the patients' condition and death.

Hemodialysis vascular access care during the COVID-19 pandemic.

Dialysis patients are more vulnerable and susceptible to the severe coronavirus disease 2019 (COVID-19) infection due to multiple comorbidities. Since Taiwan has the highest incidence and prevalence of treated end-stage kidney disease worldwide, it is crucial to act in advance to prevent a potential disaster. In the face of the COVID-19 pandemic, we implement proactive infection control measures to prevent it from spreading without sacrificing the dialysis care quality. In this article, we focused on hemodialysis vascular access (HVA) care in particular. As a life-line of hemodialysis (HD) patients, HVA care has a profound impact on the patient’s quality of dialysis and life. Specifically, in our facility, the working and office areas of the HD units are separated to reduce cross-infection. All elective procedures for HVA are postponed, and operating rooms equipped with a negative-pressure anteroom are used for the suspected or confirmed COVID-19 patients. Herein, we share how we modified our HVA care policy not only to prevent our patients from COVID-19 infection but also to maintain the quality of HVA care.

A predictive model and scoring system combining clinical and CT characteristics for the diagnosis of COVID-19.

ObjectivesTo develop a predictive model and scoring system to enhance the diagnostic efficiency for coronavirus disease 2019 (COVID-19).MethodsFrom January 19 to February 6, 2020, 88 confirmed COVID-19 patients presenting with pneumonia and 80 non-COVID-19 patients suffering from pneumonia of other origins were retrospectively enrolled. Clinical data and laboratory results were collected. CT features and scores were evaluated at the segmental level according to the lesions’ position, attenuation, and form. Scores were calculated based on the size of the pneumonia lesion, which graded at the range of 1 to 4. Air bronchogram, tree-in-bud sign, crazy-paving pattern, subpleural curvilinear line, bronchiectasis, air space, pleural effusion, and mediastinal and/or hilar lymphadenopathy were also evaluated.ResultsMultivariate logistic regression analysis showed that history of exposure (β = 3.095, odds ratio (OR) = 22.088), leukocyte count (β = − 1.495, OR = 0.224), number of segments with peripheral lesions (β = 1.604, OR = 1.604), and crazy-paving pattern (β = 2.836, OR = 2.836) were used for establishing the predictive model to identify COVID-19-positive patients (p < 0.05). In this model, values of area under curve (AUC) in the training and testing groups were 0.910 and 0.914, respectively (p < 0.001). A predicted score for COVID-19 (PSC-19) was calculated based on the predictive model by the following formula: PSC-19 = 2 × history of exposure (0–1 point) − 1 × leukocyte count (0–2 points) + 1 × peripheral lesions (0–1 point) + 2 × crazy-paving pattern (0–1 point), with an optimal cutoff point of 1 (sensitivity, 88.5%; specificity, 91.7%).ConclusionsOur predictive model and PSC-19 can be applied for identification of COVID-19-positive cases, assisting physicians and radiologists until receiving the results of reverse transcription–polymerase chain reaction (RT-PCR) tests.Key Points • Prediction of RT-PCR positivity is crucial for fast diagnosis of patients suspected of having coronavirus disease 2019 (COVID-19). • Typical CT manifestations are advantageous for diagnosing COVID-19 and differentiation of COVID-19 from other types of pneumonia. • A predictive model and scoring system combining both clinical and CT features were herein developed to enable high diagnostic efficiency for COVID-19.

Cohort study of chest CT and clinical changes in 29 patients with coronavirus disease 2019 (COVID-19).

ObjectivesTo investigate the imaging findings and clinical time course of COVID-19 pneumonia.MethodsA total of 113 baseline and follow-up CT scans from 24 January 2020 to 18 February 2020 were longitudinally collected from 29 confirmed COVID-19 patients in a single center. The changes in the clinical and laboratory characteristics, imaging features, lesion-to-muscle ratio (LMR), and pulmonary inflammation index (PII) at baseline, 1–6 days, 7–13 days, and ≥ 14 days were compared.ResultsOf the 29 COVID-19 patients enrolled, the baseline chest CT scan was obtained 3 ± 2 (0–9) days after the onset of symptoms, and each patient had an average of 4 ± 1 (3–5) CT scans with a mean interval of 5 ± 2 (1–14) days. The percentage of patients with fever, cough, shortness of breath, and myalgia obviously decreased at 7–13 days with regular treatment (p < 0.05). The lymphocyte count, C-reactive protein, interleukin-6, and oxygenation index worsened within 1–6 days but improved sharply at 7–13 days. Compared with those at the other three time points, the LMR, PII, and number of involved lobes at 1–6 days were the highest, and gradually improved after 7–13 days.ConclusionsLung lesion development on chest CT reflects the clinical time course of COVID-19 progression over 1–6 days, followed by clinical improvement and the resorption of lesions. CT imaging may be indicated when patients fail to improve within a week of treatment, but repeated chest CT may be unnecessary when the patients show improvements clinically.Key Points • Chest CT reflects the development of coronavirus disease 2019 pneumonia (COVID-19). • COVID-19 usually shows progressive lesions over up to 9 days with subsequent resorption. • Unusual clinical time course of COVID-19 may indicate repeated chest CT.

Asymptomatic patients and asymptomatic phases of Coronavirus Disease 2019 (COVID-19): a population-based surveillance study.

In this population-based study, we identified 307 confirmed COVID-19 cases from massive surveillance, including 129 551 individuals screened at fever clinics or returning from Hubei and 3710 close contacts of confirmed COVID-19 patients. Among them, 17 patients were asymptomatic at initial clinical assessment. These asymptomatic patients on admission accounted for a small proportion of all patients (5.54%) with relatively weak transmissibility, and the detection rate was 0.35 per 100 close contacts. Moreover, the dynamics of symptoms of the 307 patients showed that the interval from symptom remission to the final negativity of viral nucleic acid was 5.0 days (interquartile range 2.0 to 11.0 days), with 14 patients (4.56%) having re-detectable viral RNA after discharge. Overall, our findings suggested asymptomatic carriers and presymptomatic patients only accounted for a small proportion of COVID-19 patients. Also, the asymptomatic phase during recovery from COVID-19 implied that negativity in viral RNA is necessary as a de-isolation criterion and follow-up is recommended.

Detection of Unsuspected Coronavirus Disease 2019 Cases by Computed Tomography and Retrospective Implementation of the Radiological Society of North America/Society of Thoracic Radiology/American College of Radiology Consensus Guidelines.

The purpose of this article was to report the utility of computed tomography (CT) for detecting unsuspected cases of Coronavirus disease 2019 (COVID-19) and the utility of the Radiological Society of North America (RSNA)/Society of Thoracic Radiology (STR)/American College of Radiology (ACR) consensus guidelines for COVID-19 reporting. A total of 22 patients of the 156 reverse transcriptase polymerase chain reaction confirmed COVID-19 patients who were hospitalized between March 27, 2020 and March 31, 2020 at our quaternary care academic medical center and who underwent CT imaging within 1 week of admission were included in this retrospective study. Demographics and clinical data were extracted from the electronic medical record system. Two thoracic radiologists independently categorized each CT study on the basis of RSNA/STR/ACR consensus guidelines. Disagreement in categorization was resolved by consensus discussion with a third thoracic radiologist. At the time of imaging, 16 patients (73%) were suspected of COVID-19, and 6 patients (27%) were not. Common symptoms at presentation were fever (73%), cough (77%), and gastrointestinal symptoms (59%). An overall 63% of suspected COVID-19 patients exhibited shortness of breath, whereas 0 unsuspected COVID-19 patients did (P=0.02). On the basis of the RSNA consensus guidelines, 68%, 18%, 9%, and 5% of studies were categorized as "typical appearance," "indeterminate appearance," "atypical appearance," and "negative for pneumonia," respectively. There was no difference of category distribution between suspected and unsuspected COVID-19 patients (P=0.20), with "typical appearance" being the most prevalent in both (69% vs. 67%, respectively). It is important to recognize imaging features of COVID-19 pneumonia even in unsuspected patients. Implementation of the RSNA/STR/ACR consensus guidelines may increase consistency of reporting and convey the level of suspicion for COVID-19 to other health care providers, with "typical appearance" especially warranting further attention.

Rational perspectives on risk and certainty for dentistry during the COVID-19 pandemic

Rational perspectives on risk and certainty for dentistry during the COVID-19 pandemic

Cardiovascular Health in the COVID-19 Era: A Call for Action and Education

Cardiovascular Health in the COVID-19 Era: A Call for Action and Education

Ocular manifestations of coronavirus disease 2019.

PurposeCoronavirus disease 2019 (COVID-19) is an ongoing global public health problem, and most of the COVID-19 research is focused mainly on the respiratory system because of life-threatening results. However, manifestations in other organs should not be ignored since they can also be a mode of transmission. We sought to describe the ocular manifestations of COVID-19 and investigate the association between ocular involvement and clinical presentation and laboratory outcomes.MethodsThis cross-sectional study was conducted between March 1, 2020, and April 30, 2020. Ninety-three sequentially hospitalized and clinically confirmed COVID-19 patients were included in the study. The systemic and ocular symptoms, clinical findings, and laboratory outcomes were recorded.ResultsOf the 93 COVID-19 patients, 54 (58.1%) were male, and 39 (41.9%) were female. Mean age of the patients was 39.4 ± 21.9 (min 7, max 88) years. Twenty patients (n 21.5%) had at least one ocular abnormality. Most common findings included hyperemia (n = 20), epiphora (n = 9), increased secretion (n = 6), chemosis (n = 3), follicular conjunctivitis (n = 2), and episcleritis (n = 2). The most common symptom was photophobia (n 15). Patients with ocular involvement were more likely to have higher neutrophil counts (p = 0.001), and increased CRP (p < 0.001), PCT (p = 0.001), and ESR levels (p < 0.001). Mean lymphocyte count was statistically lower in patients with ocular manifestations (p = 0.001). Mean age and number of patients with fever over 37.3 °C in the ocular involvement group was found to be higher (p < 0.001, p = 0.006, respectively).ConclusionOlder age, high fever, increased neutrophil/lymphocyte ratio, and high levels of acute phase reactants seemed to be risk factors for ocular involvement.

A Retrospective Analysis of the Clinical and Epidemiological Characteristics of COVID-19 Patients in Henan Provincial People's Hospital, Zhengzhou, China.

Objective: This study evaluated the clinical and epidemiological characteristics of patients with confirmed coronavirus disease 2019 (COVID-19).Methods: This retrospective study evaluated 29 patients with confirmed COVID-19 infection admitted to Henan Provincial People's Hospital between January 27 and February 27, 2020, with follow-up until April 01, 2020.Results: The median age of the patients was 56 years. Nineteen (19/29; 65.5%) had underlying conditions including cardiovascular disease, digestive disease, or type 2 diabetes mellitus. Twenty-two (22/29; 76%) had close contact with acquaintances or family members who were confirmed or probable COVID-19 cases. Many patients had white blood cell counts with abnormal neutrophil and lymphocyte numbers, abnormal hemoglobin concentration, coagulation profiles, and blood biochemistry, and increased infection markers. Mottling and multiple ground-glass opacities were seen in X-ray images of 19 patients (19/29; 65.5%). Most patients (23/29; 79.8%) received supplemental oxygen therapy and antibiotics (23/29; 79.8%) in addition to traditional Chinese medicines (26/29; 89.7%). The most frequent presenting symptoms were fever, cough, and sputum production. One patient, an 86-years-old woman with more than one underlying disease, died during follow-up. Patients with severe disease were significantly older and more likely to have been transferred from other healthcare facilities than those with mild disease. Anemia, decreased activated partial thromboplastin time, calcium, and albumin, and increased D-dimer and interleukin-6 were more frequent in severe disease. Need of oxygen therapy, mechanical ventilation, intravascular immunoglobulin, and duration of antibiotic therapy were increased in those with severe disease.Conclusions: Significant differences in demographical and clinical characteristics were observed in patients with moderate and severe COVID-19.

Covering the Cover

Covering the Cover

Using Mind-Body Modalities via Telemedicine during the COVID-19 Crisis: Cases in the Republic of Korea.

The coronavirus disease 2019 (COVID-19) pandemic affected the world, and its deleterious effects on human domestic life, society, economics, and especially on human mental health are expected to continue. Mental health experts highlighted health issues this pandemic may cause, such as depression, anxiety, obsessive compulsive disorder, and post-traumatic stress disorder. Mind–body intervention, such as mindfulness meditation, has accumulated sufficient empirical evidence supporting the efficacy in improving human mental health states and the use for this purpose has been increasing. Notably, some of these interventions have already been tried in the form of telemedicine or eHealth. Korea, located adjacent to China, was exposed to COVID-19 from a relatively early stage, and today it is evaluated to have been successful in controlling this disease. “The COVID-19 telemedicine center of Korean medicine” has treated more than 20% of the confirmed COVID-19 patients in Korea with telemedicine since 9 March 2020. The center used telemedicine and mind–body modalities (including mindfulness meditation) to improve the mental health of patients diagnosed with COVID-19. In this paper, the telemedicine manual is introduced to provide insights into the development of mental health interventions for COVID-19 and other large-scale disasters in the upcoming new-normal era.

Changes in Pediatric Endoscopic Practice During the Coronavirus Disease 2019 Pandemic: Results From an International Survey

Changes in Pediatric Endoscopic Practice During the Coronavirus Disease 2019 Pandemic: Results From an International Survey

Epidemic features of coronavirus disease 2019 in Hunan Province.

To explore and analyze the epidemic features of coronavirus disease 2019 (COVID-19) in Hunan Province from January 21, 2020 to March 14, 2020, as well as to investigate the COVID-19 epidemics in each city of Hunan Province. The epidemic data was obtained from the official website of Hunan Province's Health Commission. The data of each city of Hunan Province was analyzed separately. Spatial distribution of cumulative confirmed COVID-19 patients and the cumulative occurrence rate was drawn by ArcGIS software for each city in Hunan Province. Some regional indexes were also compared with that in the whole country. The first patient was diagnosed in January 21, sustained patient growth reached its plateau in around February 17. Up to March 14, the cumulative confirmed COVID-19 patients stopped at 1 018. The cumulative occurrence rate of COVID-19 patients was 0.48 per 0.1 million person. The number of cumulative severe patients was 150 and the number of cumulative dead patients was 4. The mortality rate (0.39%) and the cure rate (99.6%) in Hunan Province was significantly lower and higher respectively than the corresponding average rate in the whole country (0.90% and 96.2%, Hubei excluded). The first 3 cities in numbers of the confirmed patients were Changsha, Yueyang, and Shaoyang. While sorted by the cumulative occurrence rate, the first 3 cities in incidence were Changsha, Yueyang, and Zhuzhou. The epidemic of COVID-19 spread out smoothly in Hunan Province. The cities in Hunan Province implement anti-disease strategies based on specific situations on their own and keep the epidemic in the range of controllable.

Roles of multidisciplinary team in diagnosis and treatment of suspected cases of COVID-19

To analyze the roles of multidisciplinary team (MDT) in the diagnosis and treatment of suspected cases of coronavirus disease 2019 (COVID-19). The clinical data of 48 patients with suspected COVID-19 admitted in Jinhua Municipal Central Hospital from January 21, 2020 to March 20, 2020 were retrospectively analyzed. In the 48 suspected cases, 18 were diagnosed with COVID-19, and 30 were excluded. Each of the confirmed cases were discussed among MDT for 2 to 12 times with an average of (4.7±3.2) times; while for non-COVID-19 patients were discussed for 2 to 4 times with an average of (2.3±0.6) times. With the guidance of MDT, one COVID-19 patient was transferred to designated provincial hospital after effective treatment; one patient complicated with acute cholecystitis underwent gallbladder puncture and drainage; and COVID-19 was excluded in a highly suspected patient after alveolar lavage fluid examination. Except one transferred patient, all 17 confirmed COVID-19 patients were cured and discharged. There was no cross-infection occurred in suspected patients during the hospitalization. There were no deaths and no medical staff infections. The efficiency of diagnosis and treatment for suspected COVID-19 patients can be improved with MDT, particularly for complicated cases.

Characterization of an Asymptomatic Cohort of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infected Individuals Outside of Wuhan, China.

PurposeWe aimed to further clarify the epidemiological and clinical characteristics of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections.MethodsWe identified close contacts of confirmed coronavirus disease 2019 (COVID-19) cases in northeast Chongqing, China, who were confirmed by real-time reverse transcription polymerase chain reaction-positive (RT-PCR+). We stratified this cohort by normal vs abnormal findings on chest computed tomography (CT) and compared the strata regarding comorbidities, demographics, laboratory findings, viral transmission and other factors.ResultsBetween January 2020 and March 2020, we identified and hospitalized 279 RT-PCR+ contacts of COVID-19 patients. 63 (23%) remained asymptomatic until discharge; 29 had abnormal and 34 had normal chest CT findings. The mean cohort age was 39.3 years, and 87.3% had no comorbidities. Mean time to diagnosis after close contact with a COVID-19 index patient was 16.0 days, and it was 13.4 days and 18.7 days for those with abnormal and normal CT findings, respectively (P < .05). Nine patients (14.3%) transmitted the virus to others; 4 and 5 were in the abnormal and normal CT strata, respectively. The median length of time for nucleic acid to turn negative was 13 days compared with 10.4 days in those with normal chest CT scans (P < .05).ConclusionsA portion of asymptomatic individuals were capable of transmitting the virus to others. Given the frequency and potential infectiousness of asymptomatic infections, testing of traced contacts is essential. Studies of the impact of treatment of asymptomatic RT-PCR+ individuals on disease progression and transmission should be undertaken.