Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the ‘life course’ of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.

Exposure to maternal hyperglycemia in utero has been associated with adverse metabolic outcomes in offspring. However, few studies have investigated the relationship between maternal hyperglycemia and offspring cortisol levels. We assessed associations of gestational diabetes mellitus (GDM) with cortisol biomarkers in two longitudinal prebirth cohorts: Project Viva included 928 mother–child pairs and Gen3G included 313 mother–child pairs. In Project Viva, GDM was diagnosed in N = 48 (5.2%) women using a two-step procedure (50 g glucose challenge test, if abnormal followed by 100 g oral glucose tolerance test [OGTT]), and in N = 29 (9.3%) women participating in Gen3G using one-step 75 g OGTT. In Project Viva, we measured cord blood glucocorticoids and child hair cortisol levels during mid-childhood (mean (SD) age: 7.8 (0.8) years) and early adolescence (mean (SD) age: 13.2 (0.9) years). In Gen3G, we measured hair cortisol at 5.4 (0.3) years. We used multivariable linear regression to examine associations of GDM with offspring cortisol, adjusting for child age and sex, maternal prepregnancy body mass index, education, and socioeconomic status. We additionally adjusted for child race/ethnicity in the cord blood analyses. In both Project Viva and Gen3G, we observed null associations of GDM and maternal glucose markers in pregnancy with cortisol biomarkers in cord blood at birth (β = 16.6 nmol/L, 95% CI −60.7, 94.0 in Project Viva) and in hair samples during childhood (β = −0.56 pg/mg, 95% CI −1.16, 0.04 in Project Viva; β = 0.09 pg/mg, 95% CI −0.38, 0.57 in Gen3G). Our findings do not support the hypothesis that maternal hyperglycemia is related to hypothalamic–pituitary–adrenal axis activity.

Since the advent of direct-acting antiviral therapy, the elimination of hepatitis c virus (HCV) as a public health concern is now possible. However, identification of those who remain undiagnosed, and re-engagement of those who are diagnosed but remain untreated, will be essential to achieve this. We examined the extent of HCV infection among individuals undergoing liver function tests (LFT) in primary care. Residual biochemistry samples for 6007 patients, who had venous blood collected in primary care for LFT between July 2016 and January 2017, were tested for HCV antibody. Through data linkage to national and sentinel HCV surveillance databases, we also examined the extent of diagnosed infection, attendance at specialist service and HCV treatment for those found to be HCV positive. Overall HCV antibody prevalence was 4.0% and highest for males (5.0%), those aged 37–50 years (6.2%), and with an ALT result of 70 or greater (7.1%). Of those testing positive, 68.9% had been diagnosed with HCV in the past, 84.9% before the study period. Most (92.5%) of those diagnosed with chronic infection had attended specialist liver services and while 67.7% had ever been treated only 38% had successfully cleared infection. More than half of HCV-positive people required assessment, and potentially treatment, for their HCV infection but were not engaged with services during the study period. LFT in primary care are a key opportunity to diagnose, re-diagnose and re-engage patients with HCV infection and highlight the importance of GPs in efforts to eliminate HCV as a public health concern.

This paper introduces a new approach to the quantitative study of democratization. Building on the comparative case-study and large-N literature, it outlines an episode approach that identifies the discrete beginning of a period of political liberalization, traces its progression, and classifies episodes as successful versus different types of failing outcomes, thus avoiding potentially fallacious assumptions of unit homogeneity. We provide a description and analysis of all 383 liberalization episodes from 1900 to 2019, offering new insights on democratic “waves”. We also demonstrate the value of this approach by showing that while several established covariates are valuable for predicting the ultimate outcomes, none explain the onset of a period of liberalization.

The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.

One of six nursing home residents and staff with positive SARS-CoV-2 tests ≥90 days after initial infection had specimen cycle thresholds (Ct) <30. Individuals with specimen Ct<30 were more likely to report symptoms but were not different from individuals with high Ct value specimens by other clinical and testing data.

Background: Healthcare facilities have experienced many challenges during the COVID-19 pandemic, including limited personal protective equipment (PPE) supplies. Healthcare personnel (HCP) rely on PPE, vaccines, and other infection control measures to prevent SARS-CoV-2 infections. We describe PPE concerns reported by HCP who had close contact with COVID-19 patients in the workplace and tested positive for SARS-CoV-2. Method: The CDC collaborated with Emerging Infections Program (EIP) sites in 10 states to conduct surveillance for SARS-CoV-2 infections in HCP. EIP staff interviewed HCP with positive SARS-CoV-2 viral tests (ie, cases) to collect data on demographics, healthcare roles, exposures, PPE use, and concerns about their PPE use during COVID-19 patient care in the 14 days before the HCP’s SARS-CoV-2 positive test. PPE concerns were qualitatively coded as being related to supply (eg, low quality, shortages); use (eg, extended use, reuse, lack of fit test); or facility policy (eg, lack of guidance). We calculated and compared the percentages of cases reporting each concern type during the initial phase of the pandemic (April–May 2020), during the first US peak of daily COVID-19 cases (June–August 2020), and during the second US peak (September 2020–January 2021). We compared percentages using mid-P or Fisher exact tests (α = 0.05). Results: Among 1,998 HCP cases occurring during April 2020–January 2021 who had close contact with COVID-19 patients, 613 (30.7%) reported ≥1 PPE concern (Table 1). The percentage of cases reporting supply or use concerns was higher during the first peak period than the second peak period (supply concerns: 12.5% vs 7.5%; use concerns: 25.5% vs 18.2%; p Conclusions: Although lower percentages of HCP cases overall reported PPE concerns after the first US peak, our results highlight the importance of developing capacity to produce and distribute PPE during times of increased demand. The difference we observed among selected groups of cases may indicate that PPE access and use were more challenging for some, such as nonphysicians and nursing home HCP. These findings underscore the need to ensure that PPE is accessible and used correctly by HCP for whom use is recommended.

Funding: None

Disclosures: None

OBJECTIVES/GOALS: Using the covariate-rich Veteran Health Administration data, estimate the association between Proton Pump Inhibitor (PPI) use and severe COVID-19, rigorously adjusting for confounding using propensity score (PS)-weighting. METHODS/STUDY POPULATION: We assembled a national retrospective cohort of United States veterans who tested positive for SARS-CoV-2, with information on 33 covariates including comorbidity diagnoses, lab values, and medications. Current outpatient PPI use was compared to non-use (two or more fills and pills on hand at admission vs no PPI prescription fill in prior year). The primary composite outcome was mechanical ventilation use or death within 60 days; the secondary composite outcome included ICU admission. PS-weighting mimicked a 1:1 matching cohort, allowing inclusion of all patients while achieving good covariate balance. The weighted cohort was analyzed using logistic regression. RESULTS/ANTICIPATED RESULTS: Our analytic cohort included 97,674 veterans with SARS-CoV-2 testing, of whom 14,958 (15.3%) tested positive (6,262 [41.9%] current PPI-users, 8,696 [58.1%] non-users). After weighting, all covariates were well-balanced with standardized mean differences less than a threshold of 0.1. Prior to PS-weighting (no covariate adjustment), we observed higher odds of the primary (9.3% vs 7.5%; OR 1.27, 95% CI 1.13-1.43) and secondary (25.8% vs 21.4%; OR 1.27, 95% CI 1.18-1.37) outcomes among PPI users vs non-users. After PS-weighting, PPI use vs non-use was not associated with the primary (8.2% vs 8.0%; OR 1.03, 95% CI 0.91-1.16) or secondary (23.4% vs 22.9%;OR 1.03, 95% CI 0.95-1.12) outcomes. DISCUSSION/SIGNIFICANCE: The associations between PPI use and severe COVID-19 outcomes that have been previously reported may be due to limitations in the covariates available for adjustment. With respect to COVID-19, our robust PS-weighted analysis provides patients and providers with further evidence for PPI safety.

Early in the COVID-19 pandemic, the World Health Organization stressed the importance of daily clinical assessments of infected patients, yet current approaches frequently consider cross-sectional timepoints, cumulative summary measures, or time-to-event analyses. Statistical methods are available that make use of the rich information content of longitudinal assessments. We demonstrate the use of a multistate transition model to assess the dynamic nature of COVID-19-associated critical illness using daily evaluations of COVID-19 patients from 9 academic hospitals. We describe the accessibility and utility of methods that consider the clinical trajectory of critically ill COVID-19 patients.