Critical pediatric neurological illness associated with COVID-19 (Omicron BA.2.3.7 variant) infection in Taiwan: immunological assessment and viral genome analysis in tertiary medical center.

OBJECTIVES: Since April 2022, another wave of the Omicron epidemic has struck Taiwanese society, and children with severe neurological complications have been reported frequently. A few cases even developed acute fulminant encephalitis. To investigate the possible causes of the increased incidence of such complications in Taiwan, we reviewed several cases of pediatric patients with severe neurological symptoms. METHODS: We collected the medical records of pediatric patients with COVID-19 infection who presented with severe neurological symptoms. The COVID-19 infection was diagnosed by nasal swab reverse transcriptase-polymerase chain reaction. The remaining samples were sent for whole genome sequencing and spike (S) protein amino acid variation mapping. RESULTS: The increase of several inflammatory markers was observed in all patients included in this study. However, none of the cerebrospinal fluid samples tested positive for SARS-CoV-2. The result of whole genome sequencing showed that all the sequences belonged to the lineage BA.2.3.7. However, the sequences had a K97E mutation in the S protein that differed from other BA.2.3.7 lineage strains, which was located at the S protein N-terminal domain. CONCLUSION: The new mutation in the S protein, which had not previously been observed but was discovered in this study, potentially explains the sudden increase in incidence of extremely adverse neurological symptoms in pediatric patients.

Curbing COVID-19 progression and mortality with traditional Chinese medicine among hospitalized patients with COVID-19: A propensity score-matched analysis.

BACKGROUND: Viral- and host-targeted traditional Chinese medicine (TCM) formulae NRICM101 and NRICM102 were administered to hospitalized patients with COVID-19 during the mid-2021 outbreak in Taiwan. We report the outcomes by measuring the risks of intubation or admission to intensive care unit (ICU) for patients requiring no oxygen support, and death for those requiring oxygen therapy. METHODS: This multicenter retrospective study retrieved data of 840 patients admitted to 9 hospitals between May 1 and July 26, 2021. After propensity score matching, 302 patients (151 received NRICM101 and 151 did not) and 246 patients (123 received NRICM102 and 123 did not) were included in the analysis to assess relative risks. RESULTS: During the 30-day observation period, no endpoint occurred in the patients receiving NRICM101 plus usual care while 14 (9.27%) in the group receiving only usual care were intubated or admitted to ICU. The numbers of deceased patients were 7 (5.69%) in the group receiving NRICM102 plus usual care and 27 (21.95%) in the usual care group. No patients receiving NRICM101 transitioned to a more severe status; NRICM102 users were 74.07% less likely to die than non-users (relative risk= 25.93%, 95% confidence interval 11.73%-57.29%). CONCLUSION: NRICM101 and NRICM102 were significantly associated with a lower risk of intubation/ICU admission or death among patients with mild-to-severe COVID-19. This study provides real-world evidence of adopting broad-spectrum oral therapeutics and shortening the gap between outbreak and effective response. It offers a new vision in our preparation for future pandemics.

Electromagnetically-driven integrated microfluidic platform using reverse transcription loop-mediated isothermal amplification for detection of severe acute respiratory syndrome coronavirus 2.

Rapid, sensitive and accurate diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of great need for effective quarantining and treatment. Real-time reverse-transcription polymerase chain reaction requiring thermocyling has been commonly used for diagnosis of SARS-CoV-2 though it may take two to 4 h before lengthy sample pretreatment process and require bulky apparatus and well-trained personnel. Since multiple reverse transcription loop-mediated isothermal amplification (multiple RT-LAMP) process without thermocycling is sensitive, specific and fast, an electromagnetically-driven microfluidic chip (EMC) was developed herein to lyse SARS-CoV-2 viruses, extract their RNAs, and perform qualitative analysis of three marker genes by on-chip multiple RT-LAMP in an automatic format within 82 min at a limit of detection of only ∼5000 copies per reaction (i.e. 200 virus/ µL). This compact EMC may be especially promising for SARS-CoV-2 diagnostics in resource-limited countries.

Guidelines for COVID-19 Laboratory Testing for Emergency Departments From the New Diagnostic Technology Team of the Taiwan Society of Emergency Medicine

COVID-19 tests have different turnaround times (TATs), accuracy levels, and limitations, which emergency physicians should be aware of. Nucleic acid amplification tests (NAATs) can be divided into standard high throughput tests and rapid molecular diagnostic tests at the point of care (POC). The standard NAAT has the advantages of high throughput and high accuracy with a TAT of 3–4 hours. The POC molecular test has the same advantages of high accuracy as standard high throughput PCR, but can be done in 13–45 minutes. Roche cobas Liat is the most commonly used machine in Taiwan, displaying 99%–100% sensitivity and 100% specificity, respectively. Abbott ID NOW is an isothermal PCR-based POC machine with a sensitivity of 79% and a specificity of 100%. A high rate of false positives and false negatives is associated with rapid antigen testing. Antibody testing is mostly used as part of public health surveys and for testing for immunity.

Clinical Characteristics of Patients Returning to Emergency Department With Initial False-Negative Reverse Transcriptase Polymerase Chain Reaction (RT-PCR)-Based COVID-19 Test.

Background: The coronavirus disease 2019 (COVID-19) outbreak is an international public health emergency. Early identification of COVID-19 patients with false-negative RT-PCR tests is paramount in the ED to prevent both nosocomial and community transmission. This study aimed to compare clinical characteristics of repeat emergency department (ED) visits among coronavirus disease 2019 (COVID-19) patients with initial false-negative reverse transcriptase-polymerase chain reaction (RT-PCR)-based COVID-19 test. Methods: This is a retrospective, multi-center, cohort study conducted at 12 hospitals affiliated with Baylor Scott & White Health system. Patients visiting the EDs of these hospitals between June and August 2020 were screened. Patients tested negative for viral RNA by quantitative RT-PCR in the first ED visit and positive in the second ED visit were included. The primary outcome was the comparison of clinical characteristics between two consecutive ED visits including the clinical symptoms, triage vital signs, laboratory, and chest X-ray (CXR) results. Results: A total of 88 confirmed COVID-19 patients with initial false-negative RT-PCR COVID-19 test in the ED were included in the final analyses. The mean duration of symptoms in the second ED visit was significantly higher (3.6 ± 0.4 vs. 2.6 ± 0.3 days, p = 0.020). In the first ED visit, lymphocytopenia (35.2%), fever (32.6%), nausea (29.5%), and dyspnea (27.9%) are the most common signs of COVID-19 infection during the window period. There were significant increases in the rate of hypoxia (13.6% vs. 4.6%, p = 0.005), abnormal infiltrate on CXR (59.7% vs. 25.9%, p < 0.001), and aspartate aminotransferase (AST) elevation (26.1% vs. 9.1%, p < 0.001) in the second ED visit. Conclusions: Early COVID-19 testing (less than 3 days of symptom duration) could be associated with a false-negative result. In this window period, lymphocytopenia, fever, nausea, and dyspnea are the most common early signs that can potentially be clinical hints for COVID-19 diagnosis.

Effect of the Nintendo Ring Fit Adventure Exergame on Running Completion Time and Psychological Factors Among University Students Engaging in Distance Learning During the COVID-19 Pandemic: Randomized Controlled Trial.

BACKGROUND: The COVID-19 outbreak has not only changed the lifestyles of people globally but has also resulted in other challenges, such as the requirement of self-isolation and distance learning. Moreover, people are unable to venture out to exercise, leading to reduced movement, and therefore, the demand for exercise at home has increased. OBJECTIVE: We intended to investigate the relationships between a Nintendo Ring Fit Adventure (RFA) intervention and improvements in running time, cardiac force index (CFI), sleep quality (Chinese version of the Pittsburgh Sleep Quality Index score), and mood disorders (5-item Brief Symptom Rating Scale score). METHODS: This was a randomized prospective study and included 80 students who were required to complete a 1600-meter outdoor run before and after the intervention, the completion times of which were recorded in seconds. They were also required to fill out a lifestyle questionnaire. During the study, 40 participants (16 males and 24 females, with an average age of 23.75 years) were assigned to the RFA group and were required to exercise for 30 minutes 3 times per week (in the adventure mode) over 4 weeks. The exercise intensity was set according to the instructions given by the virtual coach during the first game. The remaining 40 participants (30 males and 10 females, with an average age of 22.65 years) were assigned to the control group and maintained their regular habits during the study period. RESULTS: The study was completed by 80 participants aged 20 to 36 years (mean 23.20, SD 2.96 years). The results showed that the running time in the RFA group was significantly reduced. After 4 weeks of physical training, it took females in the RFA group 19.79 seconds (P=.03) and males 22.56 seconds (P=.03) less than the baseline to complete the 1600-meter run. In contrast, there were no significant differences in the performance of the control group in the run before and after the fourth week of intervention. In terms of mood disorders, the average score of the RFA group increased from 1.81 to 3.31 for males (difference=1.50, P=.04) and from 3.17 to 4.54 for females (difference=1.38, P=.06). In addition, no significant differences between the RFA and control groups were observed for the CFI peak acceleration (CFIPA)_walk, CFIPA_run, or sleep quality. CONCLUSIONS: RFA could either maintain or improve an individual's physical fitness, thereby providing a good solution for people involved in distance learning or those who have not exercised for an extended period. TRIAL REGISTRATION: ClinicalTrials.gov NCT05227040; https://clinicaltrials.gov/ct2/show/NCT05227040.

Emergency SARS-CoV-2 Variants of Concern: Novel Multiplex Real-Time RT-PCR Assay for Rapid Detection and Surveillance.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread worldwide. Many variants of SARS-CoV-2 have been reported, some of which have increased transmissibility and/or reduced susceptibility to vaccines. There is an urgent need for variant phenotyping for epidemiological surveillance of circulating lineages. Whole-genome sequencing is the gold standard for identifying SARS-CoV-2 variants, which constitutes a major bottleneck in developing countries. Methodological simplification could increase epidemiological surveillance feasibility and efficiency. We designed a novel multiplex real-time reverse transcriptase PCR (RT-PCR) to detect SARS-CoV-2 variants with S gene mutations. This multiplex PCR typing method was established to detect 9 mutations with specific primers and probes (ΔHV 69/70, K417T, K417N, L452R, E484K, E484Q, N501Y, P681H, and P681R) against the receptor-binding domain of the spike protein of SARS-CoV-2 variants. In silico analyses showed high specificity of the assays. Variants of concern (VOC) typing results were found to be highly specific for our intended targets, with no cross-reactivity observed with other upper respiratory viruses. The PCR-based typing methods were further validated using whole-genome sequencing and a commercial kit that was applied to clinical samples of 250 COVID-19 patients from Taiwan. The screening of these samples allowed the identification of epidemic trends by time intervals, including B.1.617.2 in the third Taiwan wave outbreak. This PCR typing strategy allowed the detection of five major variants of concern and also provided an open-source PCR assay which could rapidly be deployed in laboratories around the world to enhance surveillance for the local emergence and spread of B.1.1.7, B.1.351, P.1, and B.1.617.2 variants and of four Omicron mutations on the spike protein (ΔHV 69/70, K417N, N501Y, P681H). IMPORTANCE COVID-19 has spread globally. SARS-CoV-2 variants of concern (VOCs) are leading the next waves of the COVID-19 pandemic. Previous studies have pointed out that these VOCs may have increased infectivity, have reduced vaccine susceptibility, change treatment regimens, and increase the difficulty of epidemic prevention policy. Understanding SARS-CoV-2 variants remains an issue of concern for all local government authorities and is critical for establishing and implementing effective public health measures. A novel SARS-CoV-2 variant identification method based on a multiplex real-time RT-PCR was developed in this study. Five SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, and Omicron) were identified simultaneously using this method. PCR typing can provide rapid testing results with lower cost and higher feasibility, which is well within the capacity for any diagnostic laboratory. Characterizing these variants and their mutations is important for tracking SAR-CoV-2 evolution and is conducive to public infection control and policy formulation strategies.

An integrated microfluidic platform featuring real-time reverse transcription loop-mediated isothermal amplification for detection of COVID-19.

An integrated microfluidic platform (IMP) utilizing real-time reverse-transcription loop-mediated isothermal amplification (RT-LAMP) was developed here for detection and quantification of three genes of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; i.e., coronavirus diseases 2019 (COVID-19)): RNA-dependent RNA polymerase, the envelope gene, and the nucleocapsid gene for molecular diagnosis. The IMP comprised a microfluidic chip, a temperature control module, a fluidic control module that collectively carried out viral lysis, RNA extraction, RT-LAMP, and the real-time detection within 90 min in an automatic format. A limit of detection of 5 × 103 copies/reaction for each gene was determined with three samples including synthesized RNAs, inactive viruses, and RNAs extracted from clinical samples; this compact platform could be a useful tool for COVID-19 diagnostics.

Prospective Pilot Study Evaluating SARS-CoV-2 Transmission-Limiting Measures in an On-Site School.

OBJECTIVES: The purpose of our study is to evaluate the feasibility and reliability of a comprehensive set of preventive measures in limiting secondary transmission of COVID-19 in schools. METHODS: A prospective cohort study was conducted to evaluate SARS-CoV-2 transmission in an independent K-8 school in San Mateo County, California. The research was conducted between September 14, 2020 through March 22, 2021 and consisted of: 1) demographic and epidemiological questionnaires; 2) daily symptom reporting; 3) weekly RT-PCR testing; and 4) periodic on-site qualitative observations. RESULTS: One hundred eighty (79%) students and 63 (74%) on-site staff/contractors were enrolled. Participants reported symptoms in 144 (<1%) daily surveys of the 19,409 collected. Among those who reported symptoms and exposures, none tested positive during the 22-week study period. Of all participants, a total of 6 tested positive for SARS-CoV-2 at least once by RT-PCR; all were asymptomatic at time of testing. No in-school transmission occurred. Mask adherence was high among all grades, and incidents of improper mask use mostly occurred during noninstruction time. Physical distancing was well-enforced during class time and snack breaks, although adherence during noninstruction time waned as the school year progressed. CONCLUSIONS: Our comprehensive, prospective study following COVID-19 transmission over 22 weeks in a K-8 school demonstrates that: 1) surveillance testing is important for detecting asymptomatic infections in schools; 2) monitoring symptoms may not be necessary and/or sufficient for COVID-19; and 3) younger children can adhere to key mitigation measures (eg, masking) which have the potential to limit transmission.

Development and validation of a prediction model for estimating one-month mortality of adult COVID-19 patients presenting at emergency department with suspected pneumonia: a multicenter analysis.

There are only a few models developed for risk-stratifying COVID-19 patients with suspected pneumonia in the emergency department (ED). We aimed to develop and validate a model, the COVID-19 ED pneumonia mortality index (CoV-ED-PMI), for predicting mortality in this population. We retrospectively included adult COVID-19 patients who visited EDs of five study hospitals in Texas and who were diagnosed with suspected pneumonia between March and November 2020. The primary outcome was 1-month mortality after the index ED visit. In the derivation cohort, multivariable logistic regression was used to develop the CoV-ED-PMI model. In the chronologically split validation cohort, the discriminative performance of the CoV-ED-PMI was assessed by the area under the receiver operating characteristic curve (AUC) and compared with other existing models. A total of 1678 adult ED records were included for analysis. Of them, 180 patients sustained 1-month mortality. There were 1174 and 504 patients in the derivation and validation cohorts, respectively. Age, body mass index, chronic kidney disease, congestive heart failure, hepatitis, history of transplant, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, and national early warning score were included in the CoV-ED-PMI. The model was validated with good discriminative performance (AUC: 0.83, 95% confidence interval [CI]: 0.79-0.87), which was significantly better than the CURB-65 (AUC: 0.74, 95% CI: 0.69-0.79, p-value: < 0.001). The CoV-ED-PMI had a good predictive performance for 1-month mortality in COVID-19 patients with suspected pneumonia presenting at ED. This free tool is accessible online, and could be useful for clinical decision-making in the ED.

Federated learning for predicting clinical outcomes in patients with COVID-19.

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.92 for predicting outcomes at 24 and 72 h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site's data. For prediction of mechanical ventilation treatment or death at 24 h at the largest independent test site, EXAM achieved a sensitivity of 0.950 and specificity of 0.882. In this study, FL facilitated rapid data science collaboration without data exchange and generated a model that generalized across heterogeneous, unharmonized datasets for prediction of clinical outcomes in patients with COVID-19, setting the stage for the broader use of FL in healthcare.

Mortality Variations of COVID-19 from Different Hospital Settings During Different Pandemic Phases: A Multicenter Retrospective Study.

INTRODUCTION: Diverse coronavirus disease 2019 (COVID-19) mortalities have been reported but focused on identifying susceptible patients at risk of more severe disease or death. This study aims to investigate the mortality variations of COVID-19 from different hospital settings during different pandemic phases. METHODS: We retrospectively included adult (≥18 years) patients who visited emergency departments (ED) of five hospitals in the state of Texas and who were diagnosed with COVID-19 between March-November 2020. The included hospitals were dichotomized into urban and suburban based on their geographic location. The primary outcome was mortality that occurred either during hospital admission or within 30 days after the index ED visit. We used multivariable logistic regression to investigate the associations between independent variables and outcome. Generalized additive models were employed to explore the mortality variation during different pandemic phases. RESULTS: A total of 1,788 adult patients who tested positive for COVID-19 were included in the study. The median patient age was 54.6 years, and 897 (50%) patients were male. Urban hospitals saw approximately 59.5% of the total patients. A total of 197 patients died after the index ED visit. The analysis indicated visits to the urban hospitals (odds ratio [OR] 2.14, 95% confidence interval [CI], 1.41, 3.23), from March to April (OR 2.04, 95% CI, 1.08, 3.86), and from August to November (OR 2.15, 95% CI, 1.37, 3.38) were positively associated with mortality. CONCLUSION: Visits to the urban hospitals were associated with a higher risk of mortality in patients with COVID-19 when compared to visits to the suburban hospitals. The mortality risk rebounded and showed significant difference between urban and suburban hospitals since August 2020. Optimal allocation of medical resources may be necessary to bridge this gap in the foreseeable future.

Clinical Features of Emergency Department Patients from Early COVID-19 Pandemic that Predict SARS-CoV-2 Infection: Machine-learning Approach.

INTRODUCTION: Within a few months coronavirus disease 2019 (COVID-19) evolved into a pandemic causing millions of cases worldwide, but it remains challenging to diagnose the disease in a timely fashion in the emergency department (ED). In this study we aimed to construct machine-learning (ML) models to predict severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection based on the clinical features of patients visiting an ED during the early COVID-19 pandemic. METHODS: We retrospectively collected the data of all patients who received reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 at the ED of Baylor Scott & White All Saints Medical Center, Fort Worth, from February 23-May 12, 2020. The variables collected included patient demographics, ED triage data, clinical symptoms, and past medical history. The primary outcome was the confirmed diagnosis of COVID-19 (or SARS-CoV-2 infection) by a positive RT-PCR test result for SARS-CoV-2, and was used as the label for ML tasks. We used univariate analyses for feature selection, and variables with P<0.1 were selected for model construction. Samples were split into training and testing cohorts on a 60:40 ratio chronologically. We tried various ML algorithms to construct the best predictive model, and we evaluated performances with the area under the receiver operating characteristic curve (AUC) in the testing cohort. RESULTS: A total of 580 ED patients were tested for SARS-CoV-2 during the study periods, and 98 (16.9%) were identified as having the SARS-CoV-2 infection based on the RT-PCR results. Univariate analyses selected 21 features for model construction. We assessed three ML methods for performance: of the three methods, random forest outperformed the others with the best AUC result (0.86), followed by gradient boosting (0.83) and extra trees classifier (0.82). CONCLUSION: This study shows that it is feasible to use ML models as an initial screening tool for identifying patients with SARS-CoV-2 infection. Further validation will be necessary to determine how effectively this prediction model can be used prospectively in clinical practice.

Impact of the COVID-19 Pandemic on the Loading and Quality of an Emergency Department in Taiwan: Enlightenment from a Low-Risk Country in a Public Health Crisis.

The impact of the coronavirus disease 2019 (COVID-19) pandemic on health-care quality in the emergency department (ED) in countries with a low risk is unclear. This study aimed to explore the effects of the COVID-19 pandemic on ED loading, quality of care, and patient prognosis. Data were retrospectively collected from 1 January 2018 to 30 September 2020 at the ED of Tri-service general hospital. Analyses included day-based ED loading, quality of care, and patient prognosis. Data on triage assessment, physiological states, disease history, and results of laboratory tests were collected and analyzed. The number of daily visits significantly decreased after the pandemic, leading to a reduction in the time to examination. Admitted patients benefitted from the pandemic with a reduction of 0.80 h in the length of stay in the ED, faster discharge without death, and reduced re-admission. However, non-admitted visits with chest pain increased the risk of mortality after the pandemic. In conclusion, the COVID-19 pandemic led to a significant reduction in low-acuity ED visits and improved prognoses for hospitalized patients. However, clinicians should be alert about patients with chest pain due to their increased risk of mortality in subsequent admission.