Predicting Progression of COVID-19 Infection to Prioritize Medical Resource Allocation: A Novel Triage Model Based on Patient Characteristics and Symptoms at Presentation.

Background: The COVID-19 global pandemic has posed unprecedented challenges to health care systems all over the world. The speed of the viral spread results in a tsunami of patients, which begs for a reliable screening tool using readily available data to predict disease progression. Methods: Multicenter retrospective cohort study was performed to develop and validate a triage model. Patient demographic and non-laboratory clinical data were recorded. Using only the data from Zhongnan Hospital, step-wise multivariable logistic regression was performed, and a prognostic nomogram was constructed based on the independent variables identifies. The discrimination and calibration of the model were validated. External independent validation was performed to further address the utility of this model using data from Jinyintan Hospital. Results: A total of 716 confirmed COVID-19 cases from Zhongnan Hospital were included for model construction. Men, increased age, fever, hypertension, cardio-cerebrovascular disease, dyspnea, cough, and myalgia are independent risk factors for disease progression. External independent validation was carried out in a cohort with 201 cases from Jinyintan Hospital. The area under the curve (AUC) was 0.787 (95% confidence interval [CI]: 0.747-0.827) in the training group and 0.704 (95% CI: 0.632-0.777) in the validation group. Conclusions: We developed a novel triage model based on basic and clinical data. Our model could be used as a pragmatic screening aid to allow for cost efficient screening to be carried out such as over the phone, which may reduce disease propagation through limiting unnecessary contact. This may help allocation of limited medical resources.

Feasibility of a 5G-Based Robot-Assisted Remote Ultrasound System for Cardiopulmonary Assessment of Patients With Coronavirus Disease 2019.

BACKGROUND: Traditional methods for cardiopulmonary assessment of patients with coronavirus disease 2019 (COVID-19) pose risks to both patients and examiners. This necessitates a remote examination of such patients without sacrificing information quality. RESEARCH QUESTION: The goal of this study was to assess the feasibility of a 5G-based robot-assisted remote ultrasound system in examining patients with COVID-19 and to establish an examination protocol for telerobotic ultrasound scanning. STUDY DESIGN AND METHODS: Twenty-three patients with COVID-19 were included and divided into two groups. Twelve were nonsevere cases, and 11 were severe cases. All patients underwent a 5G-based robot-assisted remote ultrasound system examination of the lungs and heart following an established protocol. Distribution characteristics and morphology of the lung and surrounding tissue lesions, left ventricular ejection fraction, ventricular area ratio, pericardial effusion, and examination-related complications were recorded. Bilateral lung lesions were evaluated by using a lung ultrasound score. RESULTS: The remote ultrasound system successfully and safely performed cardiopulmonary examinations of all patients. Peripheral lung lesions were clearly evaluated. Severe cases of COVID-19 had significantly more diseased regions (median [interquartile range], 6.0 [2.0-11.0] vs 1.0 [0.0-2.8]) and higher lung ultrasound scores (12.0 [4.0-24.0] vs 2.0 [0.0-4.0]) than nonsevere cases of COVID-19 (both, P < .05). One nonsevere case (8.3%; 95% CI, 1.5-35.4) and three severe cases (27.3%; 95% CI, 9.7-56.6) were complicated by pleural effusions. Four severe cases (36.4%; 95% CI, 15.2-64.6) were complicated by pericardial effusions (vs 0% of nonsevere cases, P < .05). No patients had significant examination-related complications. INTERPRETATION: Use of the 5G-based robot-assisted remote ultrasound system is feasible and effectively obtains ultrasound characteristics for cardiopulmonary assessment of patients with COVID-19. By following established protocols and considering medical history, clinical manifestations, and laboratory markers, this system might help to evaluate the severity of COVID-19 remotely.

Cancer patients in SARS-CoV-2 infection: a single-center experience from Wuhan.

Background: The Coronavirus disease 2019 (COVID-19) global pandemic has posed unprecedented challenges to the health-care systems all over the world. Among the booming literatures about COVID-19, there is yet a paucity of study addressing the association between COVID-19 and cancer, which is a rare comorbidity of COVID-19, as well as consensus for treatment of cancer in this pandemic. Methods: In this retrospective, single-center cohort study, information of all inpatient cases with laboratory-confirmed COVID-19 who had treatment outcome were collected from the designated departments in Zhongnan Hospital of Wuhan University, Wuhan, China on March 10, 2020. Demographic data, clinical information, and treatment outcomes were extracted from electronic medical records. Severe events were defined as admission to intensive care unit (ICU), the use of mechanical ventilation, or death. Result: A total of 716 patients with laboratory-confirmed COVID-19 infection were identified. Among them, a total of 12 cases (1.7%, 95% CI: 0.7%-2.6%) had history of cancer with 4 cases (33%) experienced severe events. Compared with cases without cancer, patients with cancer have higher risks of severe events (33% vs 7.7%, p=0.012) and deaths (25% vs 3.6%, p=0.009). Multivariable logistic regression model showed that cancer was independently associated with increased odds of severe events after adjusting for other risk factors (OR 6.51, 95% CI 1.72-24.64; p=0.006). Among COVID-19 patients with cancer, we found that patients older than 60 years (75%), with other comorbidities (50%), or experiencing anticancer treatment in past month (42.9%) had a numerically higher incidence of severe events. Conclusion: Cancer is a rare comorbidity of patients with COVID-19; however, it cannot be overemphasized due to its poorer outcomes. We propose that personalized treatment recommendation for cancer patients should be addressed during COVID-19 pandemic, along with meticulous personal protective protocols for them to mitigate the risk of SARS-CoV-2 infection.

Application of a Robotic Tele-Echography System for COVID-19 Pneumonia.

To date, coronavirus disease 2019 (COVID-19) has infected millions of people worldwide. Ultrasound plays an indispensable role in the diagnosis, monitoring, and follow-up of patients with COVID-19. In this study, we used a robotic tele-echography system based on a 5G communication network for remote diagnosis. The system has great potential for lung, heart, and vasculature information, medical staff protection, and resource sharing, can be a valuable tool for treating patients during the pandemic, and can be expected to expand to more specialized fields.