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With the emergence of several new epidemics of viral infections - SARS, MERS, EBOLA, ZIKA, Influenza A (H1N1) pandemic,Covid-2019 - over the past 3 decades we suggest that a world-wide programme of stratospheric surveillance and space weather monitoring should be urgently put in place without further delay.

To evaluate the first-attempt success rates and complications of endotracheal intubation of coronavirus disease 2019 (COVID-19) patients by emergency physicians.

This prospective observational study was conducted from March 24, 2020 through May 28, 2020 at the emergency department (ED) of an urban, academic trauma center. We enrolled patients consecutively admitted to the ED with suspected or confirmed COVID-19 submitted to endotracheal intubation. No patients were excluded. The primary outcome was first-attempt intubation success, defined as successful endotracheal tube placement with the first device passed (endotracheal tube) during the first laryngoscope insertion confirmed with capnography. Secondary outcomes included the following complications hypotension, hypoxemia, aspiration, and esophageal intubation.

A total of 112 patients with confirmed or suspected COVID-19 were enrolled. Median age was 61 years and 61 patients (54%) were men. The primary outcome, first-attempt intubation success, was achieved in 82% of patients. Among the 20 patients who were not intubated on the first attempt, 75% were intubated on the second attempt and 20% on the third attempt; cricothyrotomy was performed in 1 patient. Forty-eight (42%) patients were hypotensive and required norepinephrine immediately post-intubation. Fifty-eight (52%) experienced peri-intubation hypoxemia, and 2 patients (2%) had cardiac arrest. There were no cases of failed intubation resulting in death up to 24hours after the procedure.

Emergency physicians achieve high success rates when intubating COVID19 patients, although complications are frequent. However, these findings should be considered provisional until their generalizability is assessed in their institutions and setting.

Emergency physicians achieve high success rates when intubating COVID19 patients, although complications are frequent. However, these findings should be considered provisional until their generalizability is assessed in their institutions and setting.

The impact of public health interventions during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic on critical illness in children has not been studied. We seek to determine the impact of SARS-CoV-2 related public health interventions on emergency healthcare utilization and frequency of critical illness in children.

This was an interrupted time series analysis conducted at a single tertiary pediatric emergency department (PED). All patients evaluated by a provider from December 31 through May 14 of 6 consecutive years (2015-2020) were included. Total patient visits (ED and urgent care), shock trauma suite (STS) volume, and measures of critical illness were compared between the SARS-CoV-2 period (December 31, 2019 to May 14, 2020) and the same period for the previous 5 years combined. A segmented regression model was used to explore differences in the 3 outcomes between the study and control period.

Total visits, STS volume, and volume of critical illness were all significantly lower during the SARS-CoV-2 period. During the height of public health interventions, per day there were 151 fewer total visits and 7 fewer patients evaluated in the STS. The odds of having a 24-hour period without a single critical patient were >5 times higher. Trends appeared to start before the statewide shelter-in-place order and lasted for at least 8weeks.

In a metropolitan area without significant SARS-CoV-2 seeding, the pandemic was associated with a marked reduction in PED visits for critical pediatric illness.

In a metropolitan area without significant SARS-CoV-2 seeding, the pandemic was associated with a marked reduction in PED visits for critical pediatric illness.The novel coronavirus disease 2019 (COVID-19) pandemic, with its public health implications, high case fatality rate, and strain on hospital resources, will continue to challenge clinicians and researchers alike for months to come. Accurate triage of patients during the pandemic will assign patients to the appropriate level of care, provide the best care for the maximum number of patients, rationally limit personal protective equipment (PPE) usage, and mitigate nosocomial exposures. The authors describe an adapted COVID-19 pandemic triage algorithm for emergency departments (EDs) guided by the best available evidence and responses to prior pandemics, with recommendations for clinician PPE use for each level of encounter in the setting of an ongoing PPE shortage. Our algorithm adheres to Centers for Disease Control and Prevention guidelines and supports discharge of patients with mild symptoms coupled with explicit and strict return precautions and infection control education.

There is minimal evidence describing outcomes for emergency department (ED) patients with suspected coronavirus disease 2019 (COVID-19) infection who are not hospitalized. The study objective was to assess 30-day outcomes (ED revisit, admission, ICU admission, and death) for low-risk patients discharged after ED evaluation for COVID-19.

This was a retrospective cohort study of patients triaged to a COVID-19 surge area within an urban ED and discharged between March 12 and April 6. Physicians were encouraged to discharge patients if they were well-appearing with few comorbidities. click here Data were collected from review of medical records and phone follow-up, and the analysis was descriptive.

Of 452 patients, the median age was 38, and 61.7% had no comorbidities. Chest radiographs were performed for 50.4% of patients and showed infiltrates in 14% of those tested. Polymerase chain reaction testing was performed for 28.3% of patients during the index ED visit and was positive in 35.9% of those tested. Follow-up wak is warranted to develop and validate ED disposition guidelines.

The large number of clinical variables associated with coronavirus disease 2019 (COVID-19) infection makes it challenging for frontline physicians to effectively triage COVID-19 patients during the pandemic. This study aimed to develop an efficient deep-learning artificial intelligence algorithm to identify top clinical variable predictors and derive a risk stratification score system to help clinicians triage COVID-19 patients.

This retrospective study consisted of 181 hospitalized patients with confirmed COVID-19 infection from January 29, 2020 to March 21, 2020 from a major hospital in Wuhan, China. The primary outcome was mortality. Demographics, comorbidities, vital signs, symptoms, and laboratory tests were collected at initial presentation, totaling 78 clinical variables. A deep-learning algorithm and a risk stratification score system were developed to predict mortality. Data were split into 85% training and 15% testing. Prediction performance were compared with those using COVID-19 severity score, CURB-65 score and pneumonia severity index (PSI).