Autonomous Oropharyngeal-Swab Robot System for COVID-19 Pandemic

The outbreak of COVID-19 has led to the shortage of medical personnel and the increasing need for nucleic acid testing. Manual oropharyngeal sampling is susceptible to inconsistency caused by fatigue and close contact could also cause healthcare personnel exposure and cross infection. The innate deficiency calls for a safer and more consistent way to collect the oropharyngeal samples. Therefore a fully autonomous oropharyngeal-swab robot system is proposed in this paper. The system is installed in a negative pressure chamber and carrying out a standardized sampling process to minimize individual sampling differences. A hierarchical throat detection algorithm is presented and multiple modality sensory information are fused to safely and accurately localize the optimum sampling location. Also, a force/position hybrid control method is adopted to ensure both accurate sampling and subject comfort. The robot system described in this paper can safely and efficiently collect the oropharyngeal sample, providing a scalable solution for large-scale Polymerase Chain Reaction (PCR) Molecular sample collection for various respiratory diseases. Note to Practitioners-During the COVID-19 pandemic, pre-diagnostic is essential for both prevention and treatment. Existing approaches, including nasal swab and oropharyngeal-swab, require extensive medical worker training and increase the chance of cross-infection. The robot system introduced in this paper can take oropharyngeal-swab samples from subjects with minimum human intervention, reducing medical worker exposure, alleviating the work pressure of medical staff, and speed up large quantity of sampling plan. The robot will first guide the subject into position with vocal commands, and automatically detect the optimum sampling location with a real-time machine learning algorithm. A dedicated control strategy aiming at minimizing discomfort and uniforming sample quantity is then applied to safely collect nucleic samples from the throat. Eventually, while the swab is being stored in the culture medium, a disinfection process is carried out simultaneously to prepare the robot for the next subject. Preliminary clinical trials show that our robot system can safely and accurately collect samples from subjects.

Smart Bracelet System for Temperature Monitoring and Movement Tracking Analysis.

In several epidemic diseases, one of the main symptoms exhibited by people is abnormal body temperature. Therefore, monitoring body temperature is crucial for preventing the spread of infectious diseases and facilitating timely responses. This study presents a wearable bracelet that can be used as a temperature monitoring and trajectory analysis system. The temperature sensor in the bracelet can effectively monitor the body temperature of the wearer in the target scene, and the data transmission between the bracelet and the data collector can effectively detect the movement range and trajectory of the wearer. Through these, the whole set can also detect the direct and indirect contact of the wearer in any period of time, which is very helpful for the prevention and control of infectious diseases and the isolation of potentially infected persons.

Longitudinal Chest CT Features in Severe/Critical COVID-19 Cases and the Predictive Value of the Initial CT for Mortality.

PURPOSE: To evaluate longitudinal computed tomography (CT) features and the predictive value of the initial CT and clinical characteristics for mortality in patients with severe/critical coronavirus disease 2019 (COVID-19) pneumonia. METHODS: A retrospective analysis was performed on patients with COVID-19 pneumonia confirmed by laboratory. By excluding mild and common patients, 155 severe/critical patients with definite outcome were finally enrolled. A total of 516 CTs of 147 patients were divided into four stages according to the time after onset (stage 1, 1-7 days; stage 2, 8-14 days; stage 3, 15-21 days, and stage 4, >21 days). The evolving imaging features between the survival and non-survival groups were compared by using Chi-square, Fisher's exact test, student's t-test or Mann-Whitney U-test, as appropriate. The predictive value of clinical and CT features at admission for mortality was analysed through logistic regression analysis. To avoid overfitting caused by CT scores, CT scores were divided into two parts, which were combined with clinical variables, respectively, to construct the models. RESULTS: Ground-glass opacities (GGO) patterns were predominant for stages 1 and 2 for both groups (both P>0.05). The numbers of consolidation lesions increased in stage 3 in both groups (P=0.857), whereas the linear opacity increased in the survival group but decreased in the non-survival group (P=0.0049). In stage 4, the survival group predominantly presented linear opacity patterns, whereas the non-survival group mainly showed consolidation patterns (P=0.007). Clinical and imaging characteristics correlated with mortality; multivariate analyses revealed age >71 years, neutrophil count >6.38 × 109/L, aspartate aminotransferase (AST) >58 IU/L, and CT score (total lesions score >17 in model 1, GGO score >14 and consolidation score >2 in model 2) as independent risk factors (all P<0.05). The areas under the curve of the six independent risk factors alone ranged from 0.65 to 0.75 and were 0.87 for model 2, 0.89 for model 1, and 0.92 for the six variables combined. Statistical differences were observed between Kaplan Meier curves of groups separated by cut-off values of these six variables (all P<0.01). CONCLUSION: Longitudinal imaging features demonstrated differences between the two groups, which may help determine the patient's prognosis. The initial CT score combined with age, AST, and neutrophil count is an excellent predictor for mortality in COVID-19 patients.

Clinical characteristics and longitudinal chest CT features of healthcare workers hospitalized with coronavirus disease 2019 (COVID-19).

Rationale: The clinical data and corresponding dynamic CT findings were investigated in detail to describe the clinical and imaging profiles of COVID-19 pneumonia disease progression. Methods: Forty HCWs with COVID-19 were included in this study and 30 enrolled for imaging assessment. Disease was divided into four stages based on time from onset: stage 1 (1-6 days), stage 2 (7-13 days), stage 3 (14-22 days), and stage 4 (> 22 days). Clinical wand imaging data were analyzed retrospectively. Results: The cohort included 33 female and 7 male cases, with a median age of 40 years. Six had underlying comorbidities. More than half of the cases were nurses (22, 55%). Each stage included 39, 37, 34 and 32 CTs, respectively. Bilateral lesions, multifocal lesions and lesions with GGO pattern occurred in both lower lobes at all stages. The crazy-paving pattern (20, 54%), air bronchogram (13, 35%), and pleural effusion (2, 5%) were the most common CT features in stage 2. Consolidation score peaked in stage 2 whereas total lesions score peaked in stage 3. Conclusions: COVID-19 pneumonia in HCWs has a potential predilection for younger female workers. Stage 2 of COVID-19 pneumonia may be the key period for controlling progression of the disease, and consolidation scores may be an objective reflection of the severity of lung involvement.

Chest CT Features of 182 Patients with Mild Coronavirus Disease 2019 (COVID-19) Pneumonia: A Longitudinal, Retrospective and Descriptive Study.

INTRODUCTION: The evolution of computed tomography (CT) findings in patients with mild coronavirus disease 2019 (COVID-19) pneumonia has not been described in detail. A large-scale longitudinal study is urgently required. METHODS: We analyzed 606 CT scans of 182 patients. The dynamic evolution of CT scores was evaluated using two staging methods: one was divided into 10 periods based on decile intervals, and the other was one stage per week. Moreover, the latter was used to evaluate the dynamic evolution of imaging performance. A published severity scoring system was used to compare findings of the two methods. RESULTS: In the dynamic evolution of 10 stages, the total lesion CT score peaked during stage 3 (9-11 days) and stage 6 (17-18 days), with scores = 7.19 ± 3.66 and 8.00 ± 4.57, respectively. The consolidation score peaked during stage 6 (17-18 days; score = 2.72 ± 3.07). In contrast, when a 1-week interval was used and time was divided into five stages, the total lesion score peaked during week 3 (score = 7.3 ± 4.15). The consolidation score peaked during week 2 (score = 2.54 ± 3.25). The predominant CT patterns differed significantly during each stage (P < 0.01). Ground-glass opacities (GGO), with an increased trend during week 3 and beyond, was the most common pattern in each stage (33-46%). The second most common patterns during week 1 were GGO and consolidation (24%). The linear opacity pattern with an increased trend was the second most common pattern during week 2 and beyond (21-32%). CONCLUSIONS: The total lesion score of mild COVID-19 pneumonia peaked 17-18 days after disease onset. The consolidation scores objectively reflected the severity of the lung involvement compared with total lesion scores. Each temporal stage of mild COVID-19 pneumonia mainly manifested as GGO pattern. Moreover, good prognosis may be associated with increases in the proportions of the GGO and linear opacity patterns during the later stage of disease.

Response to the COVID-19 Outbreak in Urban Settings in China.

The COVID-19 outbreak in China was devastating, and spread throughout the country before being contained. Stringent physical distancing recommendations and shelter-in-place were first introduced in the hardest-hit provinces, and by March, these recommendations were uniform throughout the country. In the presence of an evolving and deadly pandemic, we sought to investigate the impact of this pandemic on individual well-being and prevention practices among Chinese urban residents. From March 2-11, 2020, 4,607 individuals were recruited from 11 provinces with varying numbers of COVID-19 casers using the social networking app WeChat to complete a brief, anonymous, online survey. The analytical sample was restricted to 2,551 urban residents. Standardized scales measured generalized anxiety disorder (GAD), the primary outcome. Multiple logistic regression was conducted to identify correlates of GAD alongside assessment of community practices in response to the COVID-19 pandemic. We found that during the COVID-19 pandemic, recommended public health practices significantly (p <0.001) increased, including wearing facial mask, practicing physical distancing, handwashing, decreased public spitting, and going outside in urban communities. Overall, 40.3% of participants met screening criteria for GAD and 49.3%, 62.6%, and 55.4% reported that their work, social life, and family life were interrupted by anxious feelings, respectively. Independent correlates of having anxiety symptoms included being a healthcare provider (aOR=1.58, p <0.01), living in regions with a higher density of COVID-19 cases (aOR=2.13, p <0.01), having completed college (aOR=1.38, p =0.03), meeting screening criteria for depression (aOR=6.03, p <0.01) and poorer perceived health status (aOR=1.54, p <0.01). COVID-19 had a profound impact on the health of urban dwellers throughout China. Not only did they markedly increase their self- and community-protective behaviors, but they also experienced high levels of anxiety associated with a heightened vulnerability like depression, having poor perceived health, and the potential of increased exposure to COVID-19 such as living closer to the epicenter of the pandemic.