Monitoring and Management of Home-Quarantined Patients With COVID-19 Using a WeChat-Based Telemedicine System: Retrospective Cohort Study.

BACKGROUND: Most patients with coronavirus disease (COVID-19) who show mild symptoms are sent home by physicians to recover. However, the condition of some of these patients becomes severe or critical as the disease progresses. OBJECTIVE: The aim of this study was to evaluate a telemedicine model that was developed to address the challenges of treating patients with progressive COVID-19 who are home-quarantined and shortages in the medical workforce. METHODS: A telemedicine system was developed to continuously monitor the progression of home-quarantined patients with COVID-19. The system was built based on a popular social media smartphone app called WeChat; the app was used to establish two-way communication between a multidisciplinary team consisting of 7 medical workers and 188 home-quarantined individuals (including 74 confirmed patients with COVID-19). The system helped patients self-assess their conditions and update the multidisciplinary team through a telemedicine form stored on a cloud service, based on which the multidisciplinary team made treatment decisions. We evaluated this telemedicine system via a single-center retrospective study conducted at Tongji Hospital in Wuhan, China, in January 2020. RESULTS: Among 188 individuals using the telemedicine system, 114 (60.6%) were not infected with COVID-19 and were dismissed. Of the 74 confirmed patients with COVID-19, 26 (35%) recovered during the study period and voluntarily stopped using the system. The remaining 48/76 confirmed patients with COVID-19 (63%) used the system until the end of the study, including 6 patients whose conditions progressed to severe or critical. These 6 patients were admitted to hospital and were stabilized (one received extracorporeal membrane oxygenation support for 17 days). All 74 patients with COVID-19 eventually recovered. Through a comparison of the monitored symptoms between hospitalized and nonhospitalized patients, we found prolonged persistence and deterioration of fever, dyspnea, lack of strength, and muscle soreness to be diagnostic of need for hospitalization. CONCLUSIONS: By continuously monitoring the changes in several key symptoms, the telemedicine system reduces the risks of delayed hospitalization due to disease progression for patients with COVID-19 quarantined at home. The system uses a set of scales for quarantine management assessment that enables patients to self-assess their conditions. The results are useful for medical staff to identify disease progression and, hence, make appropriate and timely treatment decisions. The system requires few staff to manage a large cohort of patients. In addition, the system can solicit help from recovered but self-quarantined medical workers to alleviate shortages in the medical workforce and free healthy medical workers to fight COVID-19 on the front line. Thus, it optimizes the usage of local medical resources and prevents cross-infections among medical workers and patients.

The Distance Teaching Practice of Combined Mode of Massive Open Online Course Micro-Video for Interns in Emergency Department During the COVID-19 Epidemic Period.

Objective:To observe and analyze the application effect of the combined mode of Massive Open Online Course (MOOC) micro-video during the COVID-19 epidemic period in the distance teaching practice of interns in the emergency department.Materials and Methods:The subjects of this study were 60 trainee nurses who conducted emergency nursing practice in Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology from January 1 to February 29, 2020. At the time of the COVID-19 outbreak in Wuhan, they were divided into two groups: (1) the experimental group (combined mode of MOOC micro-video) and (2) the control group (traditional theory teaching combined with clinical practice teaching). The differences of theoretical and practical examination scores and teaching satisfaction between the two groups were compared.Results:There was no significant difference in theoretical, practical, and total examination scores between the two groups, but in terms of teaching satisfaction, the overall satisfaction, the degree of easy understanding, the evaluation of teachers and learning results in the experimental group were higher than those in the control group, with statistical difference (p < 0.05).Conclusion:Compared with the traditional teaching methods, the effect of combined mode of MOOC micro-video in emergency nursing practice is the same as that of traditional teaching methods, but the satisfaction is higher, so it is more suitable to be used in nursing practice during the COVID-19 epidemic period, so as to effectively reduce the cross-infection between doctors, nurses, and teaching staff.

Implications for Online Management: Two Cases with COVID-19.

Satisfactory outcome was observed in one mild case and one severe case of COVID-19 pneumonia after the use of the online/offline multidisciplinary quarantine observation form, online monitoring, and classified diagnosis and treatment, as well as strict compliance with quarantine measures. Conditions of both patients were improved, and cross-infection and disease onset clustering were not observed. The multidisciplinary self-quarantine model provides early judgment, identification, and treatment of disease, improves compliance with early rehabilitation, increases confidence in recovery, and enhances self-management capabilities. This model is applicable to the current novel coronavirus pneumonia epidemic and can actively promote the management of suspected or confirmed mild cases, monitoring of critical cases, and self-management of discharged patients. The application of this new management model is worthy of being promoted in our specialized treatment facilities and in countries with severe epidemics.

Discomfort of postoperative patients with aortic dissection after discharge: telephone follow-up analysis of a cross-sectional study.

BACKGROUND: Postoperative discomfort is one of the important manifestations of disease changes, but few studies have reported detailed description of postoperative discomfort in patients with aortic dissection after discharge. The aim of this study is to investigate the discomfort symptoms and to explore the possible influencing factors of discomfort symptoms. METHOD: This cross-sectional study based on convenience sampling collected medical records from 999 patients hospitalized in Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of science and technology, Wuhan, Hubei, China from January 1, 2019 to December 31, 2019. Postoperative patients with first onset and confirmed aortic dissection were eligible for follow-up. Telephone follow-up was conducted from July 20, 2020 to August 20, 2020. Symptoms of discomfort were reported by patients or their immediate family members. Univariate and multivariable logistic regression analysis were performed to identify factors associated with symptoms of discomfort. RESULTS: A total of 675 patients were followed up, 185 patients (27.4%) were lost to follow-up, and the remaining 490 patients were divided into survival group (N = 428) and death group (N = 62) and were included in the study. There was no difference in gender and age among the three groups. 152 of 428 patients reported discomfort. The uncomfortable symptoms of postoperative patients were diverse, and mainly manifested as back and chest pain (32.24%, 49/152), chest tightness (15.79%, 24/152), dizzy (10.53%, 16/152) and weakness (10.53%, 16/152). Multivariable logistic regression analysis of postoperative discomfort showed length of discharge (OR 0.995; P 0.018; 95% CI 0.990-0.999) and positive history of drinking (OR 3.519; P 0.018; 95% CI 1.236-10.022) were significant among patients with Stanford A AD, and diagnosis was made in the first visiting hospital (OR 0.395; P 0.001; 95% CI 0.230-0.677) was a protective factor for patients. CONCLUSIONS: The incidence of postoperative discomfort in patients with aortic dissection was high and the symptoms were diverse and not single. In order to reduce the possibility of postoperative discomfort, it is important to formulate effective public policies to limit the public to drink alcohol and timely diagnose aortic dissection. Long term follow-up is necessary for patients with aortic dissection to observe the recovery process of aortic dissection.

Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China.

Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic. Hospitalized patients of COVID-19 suffer from a high mortality rate, motivating the development of convenient and practical methods that allow clinicians to promptly identify high-risk patients. Here, we have developed a risk score using clinical data from 1479 inpatients admitted to Tongji Hospital, Wuhan, China (development cohort) and externally validated with data from two other centers: 141 inpatients from Jinyintan Hospital, Wuhan, China (validation cohort 1) and 432 inpatients from The Third People's Hospital of Shenzhen, Shenzhen, China (validation cohort 2). The risk score is based on three biomarkers that are readily available in routine blood samples and can easily be translated into a probability of death. The risk score can predict the mortality of individual patients more than 12 d in advance with more than 90% accuracy across all cohorts. Moreover, the Kaplan-Meier score shows that patients can be clearly differentiated upon admission as low, intermediate, or high risk, with an area under the curve (AUC) score of 0.9551. In summary, a simple risk score has been validated to predict death in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); it has also been validated in independent cohorts.

[Development and validation on death risk model of Stanford type A aortic dissection based on Cox regression].

OBJECTIVE: To construct the prediction model of death risk of Stanford type A aortic dissection (AAD) based on Cox proportional risk regression model. METHODS: AAD patients who were diagnosed and received surgical treatment admitted to the department of cardiothoracic surgery of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology from January 1st, 2019 to April 30th, 2020 were enrolled. The general situation, clinical manifestations, pre-hospital data, laboratory examination and imaging examination results of the patients were collected. The observation period was up to the death of the patients or ended on April 30th, 2021. They were divided into the model group and the verification group according to the ratio of 7:3. Lasso method was used to screen prognostic variables from the data of the modeling group, and multivariate Cox regression analysis was included to construct the AAD death risk prediction model, which was displayed by nomogram. The receiver operator characteristic curve (ROC curve) was used to evaluate the discrimination of the model, the calibration curve to evaluate the accuracy of the model, and the clinical decision curve (DCA) to evaluate the effectiveness of the model. RESULTS: A total of 454 patients with AAD were finally included, and the mortality was 19.4% (88/454). Lasso regression analysis was used to screen out 10 variables from the data of 317 patients in the model group, and the prediction model of death risk was constructed: 0.511×abdominal pain+1.061×syncope+0.428×lower limb pain/numbness-0.365×emergency admission-1.933×direct admission-1.493×diagnosis before referral+0.662×preoperative systolic blood pressure (SBP) < 100 mmHg (1 mmHg = 0.133 kPa)+0.632×hypersensitivity cardiac troponin I (hs-cTnI) > 34.2 ng/L+1.402×De Bakey type+0.641× pulmonary infection+1.472×postoperative delirium. The area under the ROC curve (AUC) and 95% confidence interval (95%CI) of the AAD death risk prediction model were 0.873 (0.817-0.928), and that of the verification group was 0.828 (0.740-0.916). DCA showed that the net benefit value of the model was higher. The calibration curve showed that there was a good correlation between the actual observation results and the model prediction results. CONCLUSIONS: The AAD death risk prediction model based on abdominal pain, syncope, lower limb pain/numbness, mode of admission, diagnosis before referral, preoperative SBP < 100 mmHg, hs-cTnI > 34.2 ng/L, De Bakey type , pulmonary infection, and postoperative delirium can effectively help clinicians identify patients at high risk for AAD, evaluate their postoperative survival and timely adjust treatment strategies.

Reflections on the Cluster Epidemic of COVID-19; Lessons Learned from Wuhan's Experience: A Brief Review.

At present, new coronavirus pneumonia (COVID-19) is circulating worldwide. The pathogen of this coronavirus pneumonia is named SARS-CoV-2. The virus has a long incubation period and is highly contagious. There is currently no specific targeted drug treatment. The focus of anti-epidemic work should be more on prevention and control while cutting off the virus transmission route while treating infected patients, and protecting healthy people. In order to protect the safety and health of the Chinese citizens and to maintain the safety of world public health, the Chinese government and people have made unprecedented efforts to control the epidemic. Many people in the international community have joined in limiting the spread of COVID-19. This article combines the development of COVID-19 epidemic situation in Wuhan, the relevant prevention and control measures of the Wuhan government and local health authorities to share Wuhan's experience on control the cluster epidemic and provide new suggestions and ideas for epidemic prevention and control.

Clinical characteristics of diarrhea in 90 cases with COVID-19: A descriptive study.

BACKGROUND: The novel coronavirus disease (COVID-19) has spread worldwide. Herein, we aimed to clarify the epidemiological and clinical characteristics of patients presenting with diarrhea. METHODS: A descriptive design was adopted from Jan 10 to Feb 17, 2020. All the cases included were diagnosed with COVID-19 under the interim guidance of the WHO. RESULTS: 912 patients with COVID-19 were admitted to hospital, in which, 90 cases (9.87%) presented with diarrhea. Among the 90 cases, 8 cases (9%) presented with diarrhea as the initial symptom, and 24%, 17%, and 24% of the patients complained of nausea, vomiting, and poor appetite, respectively. The most common fecal characteristics on admission were watery stool (64%) and mushy stool (28%). For the defecation frequency, 37% of the cases defecated over three times a day. The median time from illness onset to diarrhea was 3.0 days (IQR 0.0-5.0) and the median duration of diarrhea was 5.0 days (IQR 2.0-9.3). CONCLUSION: Clinicians are required to promptly identify the patients with initial diarrhea symptoms and pay adequate attention to the nutrient requirements of the patients with diarrhea during hospitalization. Standardized management is also recommended for the discharge of the patients to avoid potential fecal-oral transmission.