SARS-CoV-2 molecular diagnostic point-of-care testing based on loop-mediated isothermal amplification: A prospective, single-center validation study

Objectives Rapid and accurate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic tests are crucial for controlling the spread of infections in emergency settings. This study evaluated the diagnostic accuracy of a point-of-care (POC) test based on loop-mediated isothermal amplification (LAMP) that produces rapid results within 30 min. Methods We prospectively included adult patients (age >19 years) who were diagnosed with SARS-CoV-2 infection within the last 3 days and symptomatic patients who had visited the emergency room. Posterior nasopharyngeal (PNP) swabs and throat swabs collected by physicians were used to test the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and Cohen's Kappa coefficient (k) of the POC index and reference reverse transcription quantitative polymerase chain reaction (RT-qPCR) test devices. Results Of the 352 participants, 102 (29.0%) tested positive via the RT-PCR-based reference test device;the RT-LAMP-based POC test had a sensitivity of 70.6% and specificity of 98.0%, with 93.5% PPV, 89.1% NPV, 35.5% PLR, and 3.4% NLR. Cohen's k correlation of results from the two devices was 0.74. The cycle threshold value between the positive and negative POC test results differed (17.6 vs. 24.6, p < 0.001). Conclusions The RT-LAMP POC test in the emergency medical setting has a fair predictive value in high viral load cases in terms of infectivity.

Predicting medical specialty from text based on a domain-specific pre-trained BERT.

BACKGROUND: Owing to the prevalence of the coronavirus disease (COVID-19), coping with clinical issues at the individual level has become important to the healthcare system. Accordingly, precise initiation of treatment after a hospital visit is required for expedited processes and effective diagnoses of outpatients. To achieve this, artificial intelligence in medical natural language processing (NLP), such as a healthcare chatbot or a clinical decision support system, can be suitable tools for an advanced clinical system. Furthermore, support for decisions on the medical specialty from the initial visit can be helpful. MATERIALS AND METHODS: In this study, we propose a medical specialty prediction model from patient-side medical question text based on pre-trained bidirectional encoder representations from transformers (BERT). The dataset comprised pairs of medical question texts and labeled specialties scraped from a website for the medical question-and-answer service. The model was fine-tuned for predicting the required medical specialty labels among 27 labels from medical question texts. To demonstrate the feasibility, we conducted experiments on a real-world dataset and elaborately evaluated the predictive performance compared with four deep learning NLP models through cross-validation and test set evaluation. RESULTS: The proposed model showed improved performance compared with competitive models in terms of overall specialties. In addition, we demonstrate the usefulness of the proposed model by performing case studies for visualization applications. CONCLUSION: The proposed model can benefit hospital patient management and reasonable recommendations for specialties for patients.

Assessment of novel ICT-EMS systems to improve emergency patient transportation during the COVID-19 pandemic.

OBJECTIVES: This study aimed to examine the usability, feasibility, acceptability, and appropriateness of the information and communication technology for emergency medical services (ICT-EMS) systems to improve the transportation of emergency patients during the COVID-19 pandemic. METHODS: Emergency medical technicians (EMTs) (n = 229) employed at 7 fire stations operated by the North Chungcheong Fire Service Headquarters, South Korea were trained to use ICT-EMS devices prior to a 1-month implementation period. System Usability Scale (SUS), Feasibility of Intervention Measure (FIM), Acceptability of Intervention Measure (AIM), and Intervention Appropriateness Measure (IAM) questionnaires were conducted in the 4th week of the 1-month implementation period to assess the perceived usability, feasibility, acceptability, and appropriateness of the ICT-EMS systems. RESULTS: Among a total of 229 EMTs, 187 EMTs (81.7%) completed the survey. The overall SUS score was significantly low (score of 35.6) indicating an overall negative perception of the ICT-EMS systems. With regard to the feasibility, acceptability, and intervention appropriateness of ICT-EMS, roughly 50 (26.7%) participants agreed that ICT-EMS implementation was possible, appealing, and suitable. CONCLUSION: Many potential areas of improvement were identified within the ICT-EMS systems. System alterations regarding usability, feasibility, acceptability, and appropriateness may be necessary to successfully implement the ICT-EMS systems.

Burnout and Resilience among Emergency Physicians at Korean University Hospitals during the COVID-19 Pandemic: A Cross-Sectional Analysis.

PURPOSE: This study aimed to investigate burnout and resilience among emergency physicians (EPs) at university teaching hospitals during the coronavirus disease (COVID-19) pandemic. MATERIALS AND METHODS: In April to May 2021, a survey was administered to 331 and 309 emergency medicine specialists and residents, respectively, from 31 university teaching hospitals in Korea. Data on the respondents' age, sex, designation, working area, experience with treating COVID-19 patients, and personal experience with COVID-19 were collected. Based on the participants' characteristics, quality of life (compassion satisfaction, burnout, and secondary traumatic stress), resilience, emotional content, and self-image were analyzed. RESULTS: A total of 247 responses were analyzed. Compared to specialists, compassion satisfaction and resilience in residents were not good, burnout was severe, and emotional content and self-image were less positive. Experiences with treating COVID-19 patients did not cause any difference in quality of life, resilience, emotional content, and self-image among participant subgroups. Personal COVID-19 experiences were associated with poor compassion satisfaction, resilience, less positive emotional content and self-image, and severe burnout. Compassion satisfaction, secondary traumatic stress, and resilience can definitively affect burnout. CONCLUSION: The quality of life and resilience of EPs in university teaching hospitals in Korea during the COVID-19 pandemic have been low. Supportive measures to improve resilience can prevent burnout among emergency staff, particularly residents and EPs, with personal experiences related to COVID-19.

Valorization of hazardous COVID-19 mask waste while minimizing hazardous byproducts using catalytic gasification.

This study proposes a method to valorize hazardous waste such as used COVID-19 face mask via catalytic gasification over Ni-loaded ZSM-5 type zeolites. The 25% Ni was found as an optimal loading on ZSM-5 in terms of H2 production. Among different zeolites (ZSM-5(30), ZSM-5(80), ZSM-5(280), mesoporous (m)-ZSM-5(30), and HY(30)), 25% Ni/m-ZSM-5(30) led to the highest H2 selectivity (45.04 vol%), most likely because of the highest Ni dispersion on the m-ZSM-5(30) surface, high porosity, and acid site density of the m-ZSM-5(30). The content of N-containing species (e.g., caprolactum and nitriles) in the gasification product was also reduced, when steam was used as gasifying agent, which is the source of potentially hazardous air pollutants (e.g., NOx). The increase in the SiO2/Al2O3 ratio resulted in lower tar conversion and lower H2 generation. At comparable conditions, steam gasification of the mask led to ~15 vol% higher H2 selectivity than air gasification. Overall, the Ni-loaded zeolite catalyst can not only suppress the formation of hazardous substances but also enhance the production of hydrogen from the hazardous waste material such as COVID-19 mask waste.

Production of value-added aromatics from wasted COVID-19 mask via catalytic pyrolysis.

In this study, wasted mask is chosen as a pyrolysis feedstock whose generation has incredibly increased these days due to COVID-19. We suggest a way to produce value-added chemicals (e.g., aromatic compounds) from the mask with high amounts through catalytic fast pyrolysis (CFP). To this end, the effects of zeolite catalyst properties on the upgradation efficiency of pyrolytic products produced from pyrolysis of wasted mask were investigated. The compositions and yields of pyrolytic gases and oils were characterized as functions of pyrolysis temperature and the type of zeolite catalyst (HBeta, HY, and HZSM-5), including the mesoporous catalyst of Al-MCM-41. The mask was pyrolyzed in a fixed bed reactor, and the pyrolysis gases evolved in the reactor was routed to a secondary reactor inside which the zeolite catalyst was loaded. It was chosen 550 °C as the CFP temperature to compare the catalyst performance for the production of benzene, toluene, ethylbenzene, and xylene (BTEX) because this temperature gave the highest oil yield (80.7 wt%) during the non-catalytic pyrolysis process. The large pore zeolite group of HBeta and HY led to 134% and 67% higher BTEX concentrations than HZSM-5, respectively, likely because they had larger pores, higher surface areas, and higher acid site density than the HZSM-5. This is the first report of the effect of zeolite characteristics on BTEX production via CFP.

Impact of Personal Protective Equipment on the First-Pass Success of Endotracheal Intubation in the ED: A Propensity-Score-Matching Analysis.

Various types and levels of personal protective equipment (PPE) are currently available to protect health-care workers against infectious diseases. However, wearing cumbersome PPE may negatively affect their performance in life-saving procedures. This study aimed to evaluate the impact of wearing extensive PPE, including a powered air-purifying respirator with a loose-fitting hood or an N95 filtering facepiece respirator, on the first-pass success (FPS) rate of endotracheal intubation (ETI) in the emergency department (ED). This study was a single-center, observational before-and-after study of 934 adult (≥18 years old) patients who underwent ETI in the academic ED. The study period was divided into a control period (from 20 January 2019, to 30 September 2019, and from 20 January 2018, to 30 September 2018) and an intervention period (from 20 January 2020, to 30 September 2020). Extensive PPE was not donned during the control period (control group, n = 687) but was donned during the intervention period (PPE group, n = 247). The primary outcome was the FPS rate. We used propensity score matching between the PPE and control groups to reduce potential confounding. Propensity score matching identified 247 cases in the PPE group and 492 cases in the control group. In the matched cohort, no significant difference was found in the FPS rate between the PPE and control groups (83.8% (n = 207) vs. 81.9% (n = 403); p = 0.522). In multivariable analysis, wearing PPE was not associated with the FPS rate (adjusted odds ratio, 0.90; 95% confidence interval, 0.57-1.40; p = 0.629) after adjusting for the level of the intubator (junior resident, senior resident, or emergency medicine (EM) specialist). In conclusion, the FPS rate is not significantly affected by wearing extensive PPE in the ED.

Understanding the Host Innate Immune Responses against SARS-CoV-2 Infection and COVID-19 Pathogenesis.

The emergence of a new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has become a significant health concern worldwide. Undoubtedly, a better understanding of the innate and adaptive immune responses against SARS-CoV-2 and its relationship with the coronavirus disease 2019 (COVID-19) pathogenesis will be the sole basis for developing and applying therapeutics. This review will summarize the published results that relate to innate immune responses against infections with human coronaviruses including SARS-CoV-1 and SARS-CoV-2 in both humans and animal models. The topics encompass the innate immune sensing of the virus to the dysregulation of various innate immune cells during infection and disease progression.