The Value of an Emergency Medicine Virtual Observation Unit.

STUDY OBJECTIVE: We implemented a virtual observation unit in which emergency department (ED) patients receive observation-level care at home. Our primary aim was to compare this new care model to in-person observation care in terms of brick-and-mortar ED length of stay (inclusive of ED observation unit time) as well as secondarily on inpatient admission and 72-hour return visits (overall and with admission). METHODS: In a retrospective analysis of electronic health record data on ED observation patients from January 1, 2022 to December 29, 2022 from an academic urban ED, we used propensity matching to compare virtual to in-person observation patients on outcomes of interest. Patients were matched 1:1 based on age, sex, Charlson Comorbidity Index, and reason for observation. We also conducted real-time review of all virtual observation cases for potential safety concerns. RESULTS: Of 8,218 observation stays, 361 virtual observation patients were matched with 361 in-person observation patients. Virtual observation patients experienced lower median brick-and-mortar ED + EDOU LOS [14.6 (IQR 10.2, 18.9) versus 33.3 (IQR 28.1, 38.1) hours] and lower inpatient admission rates (10.2% [SD 5.0] versus 24.7% [SD 11.3]). The 72-hour return rate was higher for virtual observation patients (3.6% [SD 3.0] versus 2.5% [SD 3.0]). Among those with return visits, the rate of inpatient admission was higher among virtual observation patients (53.8% [SD 3.2] versus 11.1% [13.0]). There were no significant patient safety events recorded. CONCLUSION: Virtual observation unit patients used fewer hours in ED and ED observation relative to on-site observation patients. This new care delivery model warrants further study because it has the potential to positively impact ED capacity.

Development of a predictive model for identifying women vulnerable to HIV in Chicago.

INTRODUCTION: Researchers in the United States have created several models to predict persons most at risk for HIV. Many of these predictive models use data from all persons newly diagnosed with HIV, the majority of whom are men, and specifically men who have sex with men (MSM). Consequently, risk factors identified by these models are biased toward features that apply only to men or capture sexual behaviours of MSM. We sought to create a predictive model for women using cohort data from two major hospitals in Chicago with large opt-out HIV screening programs. METHODS: We matched 48 newly diagnosed women to 192 HIV-negative women based on number of previous encounters at University of Chicago or Rush University hospitals. We examined data for each woman for the two years prior to either their HIV diagnosis or their last encounter. We assessed risk factors including demographic characteristics and clinical diagnoses taken from patient electronic medical records (EMR) using odds ratios and 95% confidence intervals. We created a multivariable logistic regression model and measured predictive power with the area under the curve (AUC). In the multivariable model, age group, race, and ethnicity were included a priori due to increased risk for HIV among specific demographic groups. RESULTS: The following clinical diagnoses were significant at the bivariate level and were included in the model: pregnancy (OR 1.96 (1.00, 3.84)), hepatitis C (OR 5.73 (1.24, 26.51)), substance use (OR 3.12 (1.12, 8.65)) and sexually transmitted infections (STIs) chlamydia, gonorrhoea, or syphilis. We also a priori included demographic factors that are associated with HIV. Our final model had an AUC of 0.74 and included healthcare site, age group, race, ethnicity, pregnancy, hepatitis C, substance use, and STI diagnosis. CONCLUSIONS: Our predictive model showed acceptable discrimination between those who were and were not newly diagnosed with HIV. We identified risk factors such as recent pregnancy, recent hepatitis C diagnosis, and substance use in addition to the traditionally used recent STI diagnosis that can be incorporated by health systems to detect women who are vulnerable to HIV and would benefit from preexposure prophylaxis (PrEP).

COVID-19 Outcomes in Hospitalized Patients With Neurodegenerative Disease: A Retrospective Cohort Study.

Background and Objectives: COVID-19 outcomes in patients with neurodegenerative disorders (NDs) are not well understood, and we hypothesize that there may be increased morbidity and mortality in this group. Methods: This was a retrospective cohort study performed at 3 hospitals in the Chicagoland area. All patients hospitalized with COVID-19 infection with ND during a 3-month period (March 15, 2020-June 15, 2020) were included and compared with age-matched controls (CL) at 1:1 ratio. Primary outcomes were death, intensive care unit (ICU) admission, and invasive ventilation. Secondary outcomes included presenting COVID-19 symptoms, development of encephalopathy, supplementary oxygen use, discharge disposition, and risk factors for mortality. Results: The study included 132 patients with neurodegenerative disorders and 132 age-matched CL. Ninety-day mortality (ND 19.7% vs CL 23.5%, p = 0.45) and ICU admission (ND 31.5% vs CL 35.9%, p = 0.43) rates were not significantly different between the 2 groups. Patients with ND had a lower rate of invasive ventilation (ND 11.4% vs CL 23.2%, p = 0.0075) and supplementary oxygen use (ND 83.2% vs CL 95.1%, p = 0.0012). Patients with ND were also more likely to have altered mental status or confusion as their presenting COVID-19 symptom and less likely to present with respiratory symptoms. Patients with ND were discharged to nursing home or hospice at higher rates compared with CL. Discussion: We found that there was no difference in short-term mortality of patients with ND hospitalized for COVID-19 compared with CL, but they may have higher rates of neurologic complications and disability. Future studies should address long-term outcomes.

The Association of an Alpha-2 Adrenergic Receptor Agonist and Mortality in Patients With COVID-19.

There is a need for treatments to reduce coronavirus disease 2019 (COVID-19) mortality. Alpha-2 adrenergic receptor (α2 AR) agonists can dampen immune cell and inflammatory responses as well as improve oxygenation through physiologic respiratory parameters. Therefore, α2 AR agonists may be effective in reducing mortality related to hyperinflammation and acute respiratory failure in COVID-19. Dexmedetomidine (DEX) is an α2 AR agonist used for sedation. We performed a retrospective analysis of adults at Rush University System for Health hospitals between March 1, 2020 and July 30, 2020 with COVID-19 requiring invasive mechanical ventilation and sedation (n = 214). We evaluated the association of DEX use and 28-day mortality from time of intubation. Overall, 28-day mortality in the cohort receiving DEX was 27.0% as compared to 64.5% in the cohort that did not receive DEX (relative risk reduction 58.2%; 95% CI 42.4-69.6). Use of DEX was associated with reduced 28-day mortality on multivariable Cox regression analysis (aHR 0.19; 95% CI 0.10-0.33; p < 0.001). Adjusting for time-varying exposure to DEX also demonstrated that DEX was associated with reduced 28-day mortality (aHR 0.51; 95% CI 0.28-0.95; p = 0.03). Earlier DEX use, initiated <3.4 days from intubation, was associated with reduced 28-day mortality (aHR 0.25; 95% CI 0.13-0.50; p < 0.001) while later DEX use was not (aHR 0.64; 95% CI 0.27-1.50; p = 0.30). These results suggest an α2 AR agonist might reduce mortality in patients with COVID-19. Randomized controlled trials are needed to confirm this observation.