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Item Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021(PloS, 2021-03) Kline, Jeffrey A.; Camargo, Carlos A.; Courtney, D. Mark; Kabrhel, Christopher; Nordenholz, Kristen E.; Aufderheide, Thomas; Baugh, Joshua J.; Beiser, David G.; Bennett, Christopher L.; Bledsoe, Joseph; Castillo, Edward; Chisolm-Straker, Makini; Goldberg, Elizabeth M.; House, Hans; House, Stacey; Jang, Timothy; Lim, Stephen C.; Madsen, Troy E.; McCarthy, Danielle M.; Meltzer, Andrew; Moore, Stephen; Newgard, Craig; Pagenhardt, Justine; Pettit, Katherine L.; Pulia, Michael S.; Puskarich, Michael A.; Southerland, Lauren T.; Sparks, Scott; Turner-Lawrence, Danielle; Vrablik, Marie; Wang, Alfred; Weekes, Anthony J.; Westafer, Lauren; Wilburn, John; Emergency Medicine, School of MedicineObjectives Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. Methods Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. Results Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5°C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n = 9,975), the probability from logistic regression score produced an area under the receiver operating characteristic curve of 0.80 (95% CI: 0.79–0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified score, a score of zero produced a sensitivity of 95.6% (94.8–96.3%), specificity of 20.0% (19.0–21.0%), negative likelihood ratio of 0.22 (0.19–0.26). Increasing points on the simplified score predicted higher probability of infection (e.g., >75% probability with +5 or more points). Conclusion Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints.Item Establishing a Low-Resource Simulation Emergency Medicine Curriculum in Nepal(Association of American Medical Colleges, 2020-07-15) Wang, Alfred; Saltarelli, Nicholas; Cooper, Dylan; Amatya, Yogendra; House, Darlene R.; Emergency Medicine, School of MedicineIntroduction High-fidelity medical simulation is widely used in emergency medicine training because it mirrors the fast-paced environment of the emergency department (ED). However, simulation is not common in emergency medicine training programs in lower-resourced countries as cost, availability of resources, and faculty experience are potential limitations. We initiated a simulation curriculum in a low-resource environment. Methods We created a simulation lab for medical officers and students on their emergency medicine rotation at a teaching hospital in Patan, Nepal, with 48,000 ED patient visits per year. We set up a simulation lab consisting of a room with one manikin, an intubation trainer, and a projector displaying a simulation cardiac monitor. In this environment, we ran a total of eight cases over 4 simulation days. Debriefing was done at the end of each case. At the end of the curriculum, an electronic survey was delivered to the medical officers to seek improvement for future cases. Results All eight cases were well received, and learners appreciated the safe learning space and teamwork. Of note, the first simulation case that was run (the airway lab) was more difficult for learners due to lack of experience. Survey feedback included improving the debriefing content and adding further procedural skills training. Discussion Simulation is a valuable experience for learners in any environment. Although resources may be limited abroad, a sustainable simulation lab can be constructed and potItem First-time Diabetic Ketoacidosis in Type 2 Diabetics with COVID-19 Infection: A Novel Case Series(Elsevier, 2020-07-08) Croft, Alexander; Bucca, Antonino; Jansen, Jaclyn H.; Motzkus, Christine; Herbert, Audrey; Wang, Alfred; Hunter, Benton R.; Emergency Medicine, School of MedicineBackground: SARS-CoV-2 is a novel coronavirus first diagnosed in US hospitals in January 2020. Typical presenting symptoms include fever, dry cough, dyspnea, and hypoxia. However, several other symptoms have been reported, including fatigue, weakness, diarrhea, and abdominal pain. We have identified a series of patients with diabetic ketoacidosis (DKA) likely precipitated by COVID-19. Case Series: We describe five patients with previously known type 2 diabetes and no history of DKA, who presented to the emergency department with new-onset DKA and COVID-19. Why should an emergency physician be aware of this?: Diabetes mellitus is a known risk factor for poor outcomes in viral respiratory illnesses, including COVID-19. Infection may precipitate DKA in patients with type 2 diabetes. Aggressive management of these patients is recommended; however, management guidelines have not yet been put forth for this unique subset of patients.Item Risk factors associated with hospital admission in COVID-19 patients initially admitted to an observation unit(Elsevier, 2020) Russell, Frances M.; Wang, Alfred; Ehrman, Robert R.; Jacobs, Jake; Croft, Alex; Larsen, Caleb; Emergency Medicine, School of MedicineBackground No set guidelines to guide disposition decisions from the emergency department (ED) in patients with COVID-19 exist. Our goal was to determine characteristics that identify patients at high risk for adverse outcomes who may need admission to the hospital instead of an observation unit. Methods We retrospectively enrolled 116 adult patients with COVID-19 admitted to an ED observation unit. We included patients with bilateral infiltrates on chest imaging, COVID-19 testing performed, and/or COVID-19 suspected as the primary diagnosis. The primary outcome was hospital admission. We assessed risk factors associated with this outcome using univariate and multivariable logistic regression. Results Of 116 patients, 33 or 28% (95% confidence interval [CI] 20–37%) required admission from the observation unit. On multivariable logistic regression analysis, we found that hypoxia defined as room-air oxygen saturation < 95% (OR 3.11, CI 1.23–7.88) and bilateral infiltrates on chest radiography (OR 5.57, CI 1.66–18.96) were independently associated with hospital admission, after adjusting for age. Two three-factor composite predictor models, age > 48 years, bilateral infiltrates, hypoxia, and Hispanic race, bilateral infiltrates, hypoxia yield an OR for admission of 4.99 (CI 1.50–16.65) with an AUC of 0.59 (CI 0.51–0.67) and 6.78 (CI 2.11–21.85) with an AUC of 0.62 (CI 0.54–0.71), respectively. Conclusions Over 1/4 of suspected COVID-19 patients admitted to an ED observation unit ultimately required admission to the hospital. Risk factors associated with admission include hypoxia, bilateral infiltrates on chest radiography, or the combination of these two factors plus either age > 48 years or Hispanic race.