No abstract

Importance The Coronavirus Disease (COVID-19) pandemic has significantly impacted mental health outcomes. While the frequency of anxiety and depressive symptoms has increased in the whole population, the relationship between COVID-19 and new psychiatric diagnoses remains unclear. Objective To compare the population incidence rate of emergence of de novo psychiatric disorders in 2020 compared to the previous years, and to compare the incidence rate of new psychiatric disorder diagnoses between people with vs without COVID-19. Design, setting, and participants This study utilized administrative claims data from the Clinformatics® Data Mart database, licensed from Optum®. The study is a cross-sectional analysis that compared the incidence rate of new psychiatric disorders in 2020 vs. 2018 and 2019 in the entire insured population database. Subsequently, the incidence of new psychiatric disorders in people with vs. without COVID-19 during 2020 was analyzed. Exposure The exposures included diagnosis and severity of COVID-19 infection. Main outcomes measures The dependent variables of interest were the incidence rates of new psychiatric disorders, specifically schizophrenia spectrum disorders, mood disorders, anxiety disorders, and obsessive-compulsive disorder. Results The population studied included 10,463,672 US adults (mean age 52.83, 52% female) who were unique people for the year of 2020. Incidence of newly diagnosed psychiatric disorders per 1,000 individuals in the 2020 whole population were 28.81 (CI: 28.71, 28.92) for anxiety disorders, 1.04 (CI: 1.02, 1.06) for schizophrenia disorders, 0.42 (CI: 0.41, 0.43) for OCD and 28.85 (CI: 28.75, 28.95) for mood disorders. These rates were not significantly higher than 2018 or 2019. When comparing incidence rates between COVID-19 vs. non-COVID-19 populations in 2020, the rates were significantly higher in the COVID-19 population: 46.89 (CI: 46.24, 47.53) for anxiety, 49.31 (CI: 48.66, 49.97) for mood disorders, 0.57 (CI: 0.50, 0.65) for OCD, and 3.52 (CI: 3.34, 3.70) for schizophrenia. COVID-19 severity was significantly associated with new diagnoses of schizophrenia, anxiety and mood disorders in multivariate analyses. Conclusions Compared to 2018 and 2019, in 2020 there was no increased incidence of new psychiatric disorders in the general population based on insurance claims data. Importantly, people with COVID-19 were more likely to be diagnosed with a new psychiatric disorder, most notably disorders with psychosis, indicating a potential association between COVID-19 and mental/brain health.

Background: Although developments in computational big data methods have enhanced the ability to meaningfully extract information from hospital EMRs, there are inherent gaps in understanding care utilization and long-term patient outcomes outside of in-patient milieu, particularly across hospital systems. Methods: Utilizing registry data from a 7-hospital stroke certified healthcare system serving a large metropolitan, cohorts were identified for Medicare-insured patients with primary discharge diagnoses of acute ischemic stroke (AIS), intracerebral hemorrhage (ICH), or cerebral amyloid angiopathy (CAA). In collaboration with a CMS Qualified Entity which houses health care utilization data for over 80% of the state population (including 100% of Medicare Fee-for-Service), patient records were securely matched and linked. Socio-demographic and enrollment characteristics for matched cohorts are reported. Results: Medical records and claims data were matched for 98.4% of patients (n=6,531) admitted between 05/2016 and 12/2020 (n=5,789 AIS; 696 ICH; 46 CAA). Across all matched patients, the median (IQR) age at hospital admission was 76.0 (69.0-84.0) (54% female; 56% non-Hispanic White; 24% non-Hispanic Black; 13% Hispanic/Latino; median [IQR] Area Deprivation Index: 4 [2-6]). Age-based standard enrollment represented 86% of patients, with the remainder enrolled due to disability or health complications. Median (IQR) number of total years for patients with Part AB and D coverage was 6.9 (5.0-7.0) and 5.4 (2.9-7.0) years, respectively. At the time of reporting, all-cause death rates among Medicare enrollees who sought care are: 33% (AIS), 55% (ICH), and 41% (CAA). Conclusion: In the absence of systematically captured long-term outcomes data, health informatic pipelines that create linkages across multimodal sources provide a valuable framework for enabling longitudinal research on patients throughout and after stroke hospitalizations.

No abstract

Background: Good collateral flow has been shown to have better outcomes after acute ischemic stroke (AIS), including for patients receiving IV thrombolysis (IVT) and mechanical thrombectomy (MT). Hypothesis: In patients with AIS who undergo MT, good collateral flow is associated with better functional independence measure (FIM) change. Design/Methods: Data was collected retrospectively for patients who presented with AIS and were treated with MT. A total of 54 patients from 4 inpatient rehabilitation facility (IRF) locations between April 2017 and August 2019 were included. Collateral score was collected from angiograms and CT angiogram (CTA) in cases where an angiogram was not available. FIM change was defined as the difference in FIM at admission to IRF and discharge from IRF. Regression analyses were conducted to estimate the relationship between collateral score and FIM change. The predictors in the model included collateral score, FIM at admission to IRF, age at onset, and gender. Logistic regression was used for categorical variables and linear regression was applied for continuous variables. Statistical significance level was set at 0.05. Collaterals were scored from 0 to 4, with 0 to 2 being poor and good collateral flow defined as scores 3 and 4. The primary outcome of this study was FIM change. Results: The mean age was 70.4 years, and 54.5% was female. Regression analyses did not show any significant differences in FIM change in patients with collaterals ranging from poor to good p = 0.807 (Table 1), when adjusted for age, gender, and severity as represented by FIM at admission to IRF. Conclusion: In this patient cohort, good collateral flow was not associated with improvement in FIM change.