Browsing by Author "Newgard, Craig"
Now showing 1 - 4 of 4
Results Per Page
Sort Options
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 A Comparison of Scoring Systems for Predicting Short‐ and Long‐term Survival After Trauma in Older Adults(Wiley, 2019) Meagher, Ashley D.; Lin, Amber; Mandell, Samuel P.; Bulger, Eileen; Newgard, Craig; Surgery, School of MedicineObjectives Early identification of geriatric patients at high risk for mortality is important to guide clinical care, medical decision making, palliative discussions, quality assurance, and research. We sought to identify injured older adults at highest risk for 30‐day mortality using an empirically derived scoring system from available data and to compare it with current prognostic scoring systems. Methods This was a retrospective cohort study of injured adults ≥ 65 years transported by 44 emergency medical services (EMS) agencies to 49 emergency departments in Oregon and Washington from January 1, 2011, through December 31, 2011, with follow‐up through December 31, 2012. We matched data from EMS to Medicare, inpatient, trauma registries, and vital statistics. Using a primary outcome of 30‐day mortality, we empirically derived a new risk score using binary recursive partitioning and compared it to the Charlson Comorbidity Index (CCI), modified frailty index, geriatric trauma outcome score (GTOS), GTOS II, and Injury Severity Score (ISS). Results There were 4,849 patients, of whom 234 (4.8%) died within 30 days and 1,040 (21.5%) died within 1 year. The derived score, the geriatric trauma risk indicator (GTRI; emergent airway or CCI ≥ 2), had 87.2% sensitivity (95% confidence interval [CI] = 83.0% to 91.5%) and 30.6% specificity (95% CI = 29.3% to 31.9%) for 30‐day mortality (area under the receiving operating characteristic curve [AUROC] = 0.589, 95% CI = 0.566 to 0.611). AUROC values for other scoring systems ranged from 0.592 to 0.678. When the sensitivity for each existing score was held at 90%, specificity values ranged from 7.5% (ISS) to 30.6% (GTRI). Conclusions Older, injured adults transported by EMS to a large variety of trauma and nontrauma hospitals were more likely to die within 30 days if they required emergent airway management or had a higher comorbidity burden. When compared to other risk measures and holding sensitivity constant near 90%, the GTRI had higher specificity, despite a lower AUROC. Using GTOS II or the GTRI may better identify high‐risk older adults than traditional scores, such as ISS, but identification of an ideal prognostic tool remains elusive.Item The Effect of Trauma Center Verification on Outcomes of Traumatic Brain Injury Patients Undergoing Interfacility Transfer(Wiley, 2021) Jenkins, Peter C.; Newgard, Craig; Surgery, School of MedicineItem Extending Trauma Quality Improvement Beyond Trauma Centers: Hospital Variation in Outcomes Among Nontrauma Hospitals(Wolters Kluwer, 2022) Jenkins, Peter C.; Timsina, Lava; Murphy, Patrick; Tignanelli, Christopher; Holena, Daniel N.; Hemmila, Mark R.; Newgard, Craig; Surgery, School of MedicineObjective: The American College of Surgeons (ACS) conducts a robust quality improvement program for ACS-verified trauma centers, yet many injured patients receive care at non-accredited facilities. This study tested for variation in outcomes across non-trauma hospitals and characterized hospitals associated with increased mortality. Summary background data: The study included state trauma registry data of 37,670 patients treated between January 1, 2013, and December 31, 2015. Clinical data were supplemented with data from the American Hospital Association and US Department of Agriculture, allowing comparisons among 100 nontrauma hospitals. Methods: Using Bayesian techniques, risk-adjusted and reliability-adjusted rates of mortality and interfacility transfer, as well as Emergency Departments length-of-stay (ED-LOS) among patients transferred from EDs were calculated for each hospital. Subgroup analyses were performed for patients ages >55 years and those with decreased Glasgow coma scores (GCS). Multiple imputation was used to address missing data. Results: Mortality varied 3-fold (0.9%-3.1%); interfacility transfer rates varied 46-fold (2.1%-95.6%); and mean ED-LOS varied 3-fold (81-231 minutes). Hospitals that were high and low statistical outliers were identified for each outcome, and subgroup analyses demonstrated comparable hospital variation. Metropolitan hospitals were associated increased mortality [odds ratio (OR) 1.7, P = 0.004], decreased likelihood of interfacility transfer (OR 0.7, P ≤ 0.001), and increased ED-LOS (coef. 0.1, P ≤ 0.001) when compared with nonmetropolitan hospitals and risk-adjusted. Conclusions: Wide variation in trauma outcomes exists across nontrauma hospitals. Efforts to improve trauma quality should include engagement of nontrauma hospitals to reduce variation in outcomes of injured patients treated at those facilities.