Risk of COVID-19 Hospitalization and Protection Associated With mRNA Vaccination Among US Adults With Psychiatric Disorders.

BACKGROUND: Although psychiatric disorders have been associated with reduced immune responses to other vaccines, it remains unknown whether they influence COVID-19 vaccine effectiveness (VE). This study evaluated risk of COVID-19 hospitalization and estimated mRNA VE stratified by psychiatric disorder status. METHODS: In a retrospective cohort analysis of the VISION Network in four US states, the rate of laboratory-confirmed COVID-19-associated hospitalization between December 2021 and August 2022 was compared across psychiatric diagnoses and by monovalent mRNA COVID-19 vaccination status using Cox proportional hazards regression. RESULTS: Among 2,436,999 adults, 22.1% had ≥1 psychiatric disorder. The incidence of COVID-19-associated hospitalization was higher among patients with any versus no psychiatric disorder (394 vs. 156 per 100,000 person-years, p < 0.001). Any psychiatric disorder (adjusted hazard ratio [aHR], 1.27; 95% CI, 1.18-1.37) and mood (aHR, 1.25; 95% CI, 1.15-1.36), anxiety (aHR, 1.33, 95% CI, 1.22-1.45), and psychotic (aHR, 1.41; 95% CI, 1.14-1.74) disorders were each significant independent predictors of hospitalization. Among patients with any psychiatric disorder, aHRs for the association between vaccination and hospitalization were 0.35 (95% CI, 0.25-0.49) after a recent second dose, 0.08 (95% CI, 0.06-0.11) after a recent third dose, and 0.33 (95% CI, 0.17-0.66) after a recent fourth dose, compared to unvaccinated patients. Corresponding VE estimates were 65%, 92%, and 67%, respectively, and were similar among patients with no psychiatric disorder (68%, 92%, and 79%). CONCLUSION: Psychiatric disorders were associated with increased risk of COVID-19-associated hospitalization. However, mRNA vaccination provided similar protection regardless of psychiatric disorder status, highlighting its benefit for individuals with psychiatric disorders.

Clinical Epidemiology and Risk Factors for Critical Outcomes Among Vaccinated and Unvaccinated Adults Hospitalized With COVID-19-VISION Network, 10 States, June 2021-March 2023.

BACKGROUND: The epidemiology of coronavirus disease 2019 (COVID-19) continues to develop with emerging variants, expanding population-level immunity, and advances in clinical care. We describe changes in the clinical epidemiology of COVID-19 hospitalizations and risk factors for critical outcomes over time. METHODS: We included adults aged ≥18 years from 10 states hospitalized with COVID-19 June 2021-March 2023. We evaluated changes in demographics, clinical characteristics, and critical outcomes (intensive care unit admission and/or death) and evaluated critical outcomes risk factors (risk ratios [RRs]), stratified by COVID-19 vaccination status. RESULTS: A total of 60 488 COVID-19-associated hospitalizations were included in the analysis. Among those hospitalized, median age increased from 60 to 75 years, proportion vaccinated increased from 18.2% to 70.1%, and critical outcomes declined from 24.8% to 19.4% (all P < .001) between the Delta (June-December, 2021) and post-BA.4/BA.5 (September 2022-March 2023) periods. Hospitalization events with critical outcomes had a higher proportion of ≥4 categories of medical condition categories assessed (32.8%) compared to all hospitalizations (23.0%). Critical outcome risk factors were similar for unvaccinated and vaccinated populations; presence of ≥4 medical condition categories was most strongly associated with risk of critical outcomes regardless of vaccine status (unvaccinated: adjusted RR, 2.27 [95% confidence interval {CI}, 2.14-2.41]; vaccinated: adjusted RR, 1.73 [95% CI, 1.56-1.92]) across periods. CONCLUSIONS: The proportion of adults hospitalized with COVID-19 who experienced critical outcomes decreased with time, and median patient age increased with time. Multimorbidity was most strongly associated with critical outcomes.

Specificity, frequency, and intent: Multiple characteristics of adolescents' suicide plan correlate with their history of suicidal behavior.

BACKGROUND: Suicide plans (SP) can be a common precipitant to suicidal behavior (SB) during adolescence, and SPs can vary in how specific they are, how frequently they are thought about, and how strongly they are intended to be enacted. To date, we have limited understanding of how discrete SP characteristics (i.e., specificity, frequency, and intent to act) present among adolescents, and whether they relate to SB. In the current study, we investigated SP characteristics and their association with SB history among adolescents who had previously considered suicide. METHODS: Participants were 142 community-based adolescents (14-19 years; M = 17.6, SD = 1.4) who reported a history of suicidal ideation. Adolescents provided responses pertaining to their SP history, SP characteristics, and SB history, via the Self-Injurious Thoughts and Behaviors Interview-Revised (SITBI-R). RESULTS: Greater specificity, frequency, and intent were each associated with modestly increased odds of reporting an SB history. The associations between plan specificity and SB history, as well as between frequency of thinking about one's SP and SB history, were mediated by adolescents' intent to act on their SP. CONCLUSIONS: It may not only be whether, but how, adolescents plan for suicide that relates to their tendency to engage in SB.

Relationships Between Social Vulnerability and Coronavirus Disease 2019 Vaccination Coverage and Vaccine Effectiveness.

BACKGROUND: Coronavirus disease 2019 (COVID-19) vaccination coverage remains lower in communities with higher social vulnerability. Factors such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure risk and access to healthcare are often correlated with social vulnerability and may therefore contribute to a relationship between vulnerability and observed vaccine effectiveness (VE). Understanding whether these factors impact VE could contribute to our understanding of real-world VE. METHODS: We used electronic health record data from 7 health systems to assess vaccination coverage among patients with medically attended COVID-19-like illness. We then used a test-negative design to assess VE for 2- and 3-dose messenger RNA (mRNA) adult (≥18 years) vaccine recipients across Social Vulnerability Index (SVI) quartiles. SVI rankings were determined by geocoding patient addresses to census tracts; rankings were grouped into quartiles for analysis. RESULTS: In July 2021, primary series vaccination coverage was higher in the least vulnerable quartile than in the most vulnerable quartile (56% vs 36%, respectively). In February 2022, booster dose coverage among persons who had completed a primary series was higher in the least vulnerable quartile than in the most vulnerable quartile (43% vs 30%). VE among 2-dose and 3-dose recipients during the Delta and Omicron BA.1 periods of predominance was similar across SVI quartiles. CONCLUSIONS: COVID-19 vaccination coverage varied substantially by SVI. Differences in VE estimates by SVI were minimal across groups after adjusting for baseline patient factors. However, lower vaccination coverage among more socially vulnerable groups means that the burden of illness is still disproportionately borne by the most socially vulnerable populations.

EHR Data Quality Assessment Tools and Issue Reporting Workflows for the 'All of Us' Research Program Clinical Data Research Network.

The All of Us (AoU) Research Program aggregates electronic health records (EHR) data from 300,00+ participants spanning 50+ distinct data sites. The diversity and size of AoU's data network result in multifaceted obstacles to data integration that may undermine the usability of patient EHR. Consequently, the AoU team implemented data quality tools to regularly evaluate and communicate EHR data quality issues at scale. The use of systematic feedback and educational tools ultimately increased site engagement and led to quantitative improvements in EHR quality as measured by program- and externally-defined metrics. These improvements enabled the AoU team to save time on troubleshooting EHR and focus on the development of alternate mechanisms to improve the quality of future EHR submissions. While this framework has proven effective, further efforts to automate and centralize communication channels are needed to deepen the program's efforts while retaining its scalability.

Feasibility of Linking Area Deprivation Index Data to the OMOP Common Data Model.

Linking Area Deprivation Index (ADI) scores to observational data offers the opportunity to characterize healthcare treatment and outcomes that are driven by socioeconomic deprivation. The current study aims to assess the feasibility of creating an analysis package to link ADI rankings to multiple patient-level EHR datasets transformed into the OMOP CDM. Patients within two cancer cohorts (breast cancer and multiple myeloma) were identified within two OMOP datasets and their records were linked with ADI scores using address information in the OMOP location table. With ADI linked to patient addresses, we generated visualizations showing the geographic distribution of each cohort based on ADI scores. Additionally, further assessment showed that over 89% of patient addresses could successfully be linked with ADI rankings. In conducting this assessment, we have demonstrated that developing a package to link ADI scores with multiple OMOP datasets is feasible.

Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study.

Many patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. It is unknown whether MDD is a comorbidity of BD or its earlier stage, and no consensus exists on individual conversion predictors, delaying BD's timely recognition and treatment. We aimed to build a predictive model of MDD to BD conversion and to validate it across a multi-national network of patient databases using the standardization afforded by the Observational Medical Outcomes Partnership (OMOP) common data model. Five "training" US databases were retrospectively analyzed: IBM MarketScan CCAE, MDCR, MDCD, Optum EHR, and Optum Claims. Cyclops regularized logistic regression models were developed on one-year MDD-BD conversion with all standard covariates from the HADES PatientLevelPrediction package. Time-to-conversion Kaplan-Meier analysis was performed up to a decade after MDD, stratified by model-estimated risk. External validation of the final prediction model was performed across 9 patient record databases within the Observational Health Data Sciences and Informatics (OHDSI) network internationally. The model's area under the curve (AUC) varied 0.633-0.745 (µ = 0.689) across the five US training databases. Nine variables predicted one-year MDD-BD transition. Factors that increased risk were: younger age, severe depression, psychosis, anxiety, substance misuse, self-harm thoughts/actions, and prior mental disorder. AUCs of the validation datasets ranged 0.570-0.785 (µ = 0.664). An assessment algorithm was built for MDD to BD conversion that allows distinguishing as much as 100-fold risk differences among patients and validates well across multiple international data sources.

Valores normales de la perimetría cinética cuantitativa / Normal values of quantitative kinetic perimetry

Los autores realizan un estudio de la perimetría cinética cuantitativa a 20 pacientes de ambos sexos y edades comprendidas entre 25 y 35 años. Su examen oftalmológico es normal y su agudeza visual es de 1,0 en ambos ojos. Los datos son procesados estadísticamente y se determinan los valores medios y la variación estándar para cada uno de los 4 meridianos en las sumas 3, 4 y 5

Valores normales de la perimetría cinética cuantitativa / Noral values of quantitative kinetic perimetry

Los autores realizan un estudio de la perimetría cinética cuantitativa a 20 pacientes de ambos sexos y edades comprendidas entre 25 y 35 años. Su examen oftalmológico es normal y su agudeza visual es de 1,0 en ambos ojos. Los datos son procesados estadísticamente y se determinan los valores medios y la variación estándar para cada uno de los 4 meridianos en las sumas 3, 4 y 5

Pesquizaje oftalmológico en el área de salud "Dr. Gustavo Aldereguía": su interrelación con el médico de la familia / Ophthalmologic searching in the \"Dr. Gustavo Aldereguía\" health area: its interrelation to the family doctor

Se realiza un estudio de los pacientes interconsultados en oftalmología por el médico de la familia en el área de salud "Dr. Gustavo Aldereguía". Se establece comparación de los años 1986 y 1987 con el incremento en el número de médicos de la familia en esa área. Posteriormente se realiza fondoscopía a todos los diabéticos e hipertensos del área; se obtienen resultados que se exponen en el trabajo

Pesquizaje oftalmológico en el área de salud "Dr. Gustavo Aldereguía": su interrelación con el médico de la familia / Ophthalologic searching in the "Dr. Gustavo Aldereguía" health area: its interrelation to the family doctor

Se realiza un estudio de los pacientes interconsultados en oftalmología por el médico de la familia en el área de salud "Dr. Gustavo Aldereguía". Se establece comparación de los años 1986 y 1987 con el incremento en el número de médicos de la familia en esa área. Posteriormente se realiza fondoscopía a todos los diabéticos e hipertensos del área; se obtienen resultados que se exponen en el trabajo