The REDCap consortium: Building an international community of software platform partners.

Importance Coronavirus disease 2019 (COVID-19) continues to cause considerable morbidity and mortality worldwide. Case reports of hospitalized patients suggest that COVID-19 prominently affects the cardiovascular system, but the overall impact remains unknown. Objective To evaluate the presence of myocardial injury in unselected patients recently recovered from COVID-19 illness. Design, Setting, and Participants In this prospective observational cohort study, 100 patients recently recovered from COVID-19 illness were identified from the University Hospital Frankfurt COVID-19 Registry between April and June 2020. Exposure Recent recovery from severe acute respiratory syndrome coronavirus 2 infection, as determined by reverse transcription–polymerase chain reaction on swab test of the upper respiratory tract. Main Outcomes and Measures Demographic characteristics, cardiac blood markers, and cardiovascular magnetic resonance (CMR) imaging were obtained. Comparisons were made with age-matched and sex-matched control groups of healthy volunteers (n = 50) and risk factor–matched patients (n = 57). Results Of the 100 included patients, 53 (53%) were male, and the mean (SD) age was 49 (14) years. The median (IQR) time interval between COVID-19 diagnosis and CMR was 71 (64-92) days. Of the 100 patients recently recovered from COVID-19, 67 (67%) recovered at home, while 33 (33%) required hospitalization. At the time of CMR, high-sensitivity troponin T (hsTnT) was detectable (greater than 3 pg/mL) in 71 patients recently recovered from COVID-19 (71%) and significantly elevated (greater than 13.9 pg/mL) in 5 patients (5%). Compared with healthy controls and risk factor–matched controls, patients recently recovered from COVID-19 had lower left ventricular ejection fraction, higher left ventricle volumes, and raised native T1 and T2. A total of 78 patients recently recovered from COVID-19 (78%) had abnormal CMR findings, including raised myocardial native T1 (n = 73), raised myocardial native T2 (n = 60), myocardial late gadolinium enhancement (n = 32), or pericardial enhancement (n = 22). There was a small but significant difference between patients who recovered at home vs in the hospital for native T1 mapping (median [IQR], 1119 [1092-1150] ms vs 1141 [1121-1175] ms;P = .008) and hsTnT (4.2 [3.0-5.9] pg/dL vs 6.3 [3.4-7.9] pg/dL;P = .002) but not for native T2 mapping. None of these measures were correlated with time from COVID-19 diagnosis (native T1:r = 0.07;P = .47; native T2:r = 0.14;P = .15; hsTnT:r = −0.07;P = .50). High-sensitivity troponin T was significantly correlated with native T1 mapping (r = 0.33;P  Conclusions and Relevance In this study of a cohort of German patients recently recovered from COVID-19 infection, CMR revealed cardiac involvement in 78 patients (78%) and ongoing myocardial inflammation in 60 patients (60%), independent of preexisting conditions, severity and overall course of the acute illness, and time from the original diagnosis. These findings indicate the need for ongoing investigation of the long-term cardiovascular consequences of COVID-19.

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Outcomes of Cardiovascular Magnetic Resonance Imaging in Patients Recently Recovered From Coronavirus Disease 2019 (COVID-19).

Scale development and validation are critical to much of the work in the health, social, and behavioral sciences. However, the constellation of techniques required for scale development and evaluation can be onerous, jargon-filled, unfamiliar, and resource-intensive. Further, it is often not a part of graduate training. Therefore, our goal was to concisely review the process of scale development in as straightforward a manner as possible, both to facilitate the development of new, valid, and reliable scales, and to help improve existing ones. To do this, we have created a primer for best practices for scale development in measuring complex phenomena. This is not a systematic review, but rather the amalgamation of technical literature and lessons learned from our experiences spent creating or adapting a number of scales over the past several decades. We identified three phases that span nine steps. In the first phase, items are generated and the validity of their content is assessed. In the second phase, the scale is constructed. Steps in scale construction include pre-testing the questions, administering the survey, reducing the number of items, and understanding how many factors the scale captures. In the third phase, scale evaluation, the number of dimensions is tested, reliability is tested, and validity is assessed. We have also added examples of best practices to each step. In sum, this primer will equip both scientists and practitioners to understand the ontology and methodology of scale development and validation, thereby facilitating the advancement of our understanding of a range of health, social, and behavioral outcomes.

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Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer.

Prevalence of posttraumatic stress disorder (PTSD) defined according to the American Psychiatric Association's Diagnostic and Statistical Manual fifth edition (DSM-5; 2013) and fourth edition (DSM-IV; 1994) was compared in a national sample of U.S. adults (N = 2,953) recruited from an online panel. Exposure to traumatic events, PTSD symptoms, and functional impairment were assessed online using a highly structured, self-administered survey. Traumatic event exposure using DSM-5 criteria was high (89.7%), and exposure to multiple traumatic event types was the norm. PTSD caseness was determined using Same Event (i.e., all symptom criteria met to the same event type) and Composite Event (i.e., symptom criteria met to a combination of event types) definitions. Lifetime, past-12-month, and past 6-month PTSD prevalence using the Same Event definition for DSM-5 was 8.3%, 4.7%, and 3.8% respectively. All 6 DSM-5 prevalence estimates were slightly lower than their DSM-IV counterparts, although only 2 of these differences were statistically significant. DSM-5 PTSD prevalence was higher among women than among men, and prevalence increased with greater traumatic event exposure. Major reasons individuals met DSM-IV criteria, but not DSM-5 criteria were the exclusion of nonaccidental, nonviolent deaths from Criterion A, and the new requirement of at least 1 active avoidance symptom.

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National estimates of exposure to traumatic events and PTSD prevalence using DSM-IV and DSM-5 criteria.

OBJECTIVETraumatic brain injury (TBI)—the “silent epidemic”—contributes to worldwide death and disability more than any other traumatic insult. Yet, TBI incidence and distribution across regions and socioeconomic divides remain unknown. In an effort to promote advocacy, understanding, and targeted intervention, the authors sought to quantify the case burden of TBI across World Health Organization (WHO) regions and World Bank (WB) income groups.METHODSOpen-source epidemiological data on road traffic injuries (RTIs) were used to model the incidence of TBI using literature-derived ratios. First, a systematic review on the proportion of RTIs resulting in TBI was conducted, and a meta-analysis of study-derived proportions was performed. Next, a separate systematic review identified primary source studies describing mechanisms of injury contributing to TBI, and an additional meta-analysis yielded a proportion of TBI that is secondary to the mechanism of RTI. Then, the incidence of RTI as published by the Global...

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Jonathon Payne

Papers

Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support