Objectives
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.
Introduction:The American College of Emergency Physicians (ACEP) endorses emergency medicine (EM) residency training as the only legitimate pathway to practicing EM, yet the economic reality of Iowa’s rural population will continue to require the hiring of non-EM trained physicians. The objective of our study is to better understand the current staffing practices of Iowa emergency departments (EDs). Specifically, we seek to determine the Iowa community size required to support hiring an emergency physician (EP), identify the number of EDs staffed by advanced practice providers (APPs) in solo coverage in EDs, determine the changes in staffing over a 4-year period, and understand the market forces that contribute to staffing decisions.Methods:Researchers surveyed all 119 hospitals throughout the state of Iowa regarding their ED hiring practices, both in 2008 and 2012. From these data, we determined the mean population that supports hiring EPs and performed a qualitative examination of the reasons given for hiring preferences.Results:We found that a mean population of approximately 85,000 is needed to support EP-only staffing practices. In 2012, only 14 (11.8%) of Iowa’s EDs were staffed exclusively with EPs. Seventy-two (60.5%) staff with a combination of EPs and FPs, 33 (27.7%) staff with FPs alone, and 72 (60.5%) have physician assistants or nurse practitioners working in solo coverage for at least part of the week. Comparing the data from 2008 and 2012, there is no statistical change in the hiring of EPs versus FPs over the 4 years (Chi-square 0.68, p=0.7118), although there is a significant increase in the number of APPs in solo practice (Chi-square 11.36, p= 0.0008). Administrators at hospitals cited several factors for preferring to hire EPs: quality of care provided by EPs, availability of EPs, high patient acuity, and high patient volume.Conclusion:Many EDs in Iowa remain staffed by family medicine-trained physicians and are being increasingly staffed by APPs. Without the contribution of family physicians, large areas of the state would be unable to provide adequate emergency care. Board-certified emergency physicians remain concentrated in urban areas of the state, where patient volumes and acuity support their hiring.
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