The Effects of Risky Behaviors and Social Factors on the Frequency of Fraud Victimization Among Known Victims.

Background And Objectives: Routine activity theory (RAT) asserts that a suitable target's exposure to a motivated offender in the absence of capable guardians increases their likelihood of crime victimization. We use these principles to assess the extent to which engaging in risky routine activities-for example, entering sweepstakes drawings, answering unknown calls-is associated with victimization frequency among older adult mass marketing fraud victims across five types of scams: investment fraud, sweepstakes and lottery fraud, romance and family/friend imposter scams, fake products and services, and charity scams. We also examine whether financial and social vulnerability characteristics (loneliness, preference for taking financial risks, financial fragility) are associated with victimization frequency in older adults.

Association of glycemic control with Long COVID in patients with type 2 diabetes: findings from the National COVID Cohort Collaborative (N3C).

Introduction: Elevated glycosylated hemoglobin (HbA1c) in individuals with type 2 diabetes is associated with increased risk of hospitalization and death after acute COVID-19, however the effect of HbA1c on Long COVID is unclear.

Objective: Evaluate the association of glycemic control with the development of Long COVID in patients with type 2 diabetes (T2D).

Research Design And Methods: We conducted a retrospective cohort study using electronic health record data from the National COVID Cohort Collaborative.

Effect of nirmatrelvir/ritonavir (Paxlovid) on hospitalization among adults with COVID-19: An electronic health record-based target trial emulation from N3C.

Background: Nirmatrelvir with ritonavir (Paxlovid) is indicated for patients with Coronavirus Disease 2019 (COVID-19) who are at risk for progression to severe disease due to the presence of one or more risk factors. Millions of treatment courses have been prescribed in the United States alone. Paxlovid was highly effective at preventing hospitalization and death in clinical trials.

Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID.

Background: Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection.

Methods: We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative.

Enhancing post-traumatic stress disorder patient assessment: leveraging natural language processing for research of domain criteria identification using electronic medical records.

Background: Extracting research of domain criteria (RDoC) from high-risk populations like those with post-traumatic stress disorder (PTSD) is crucial for positive mental health improvements and policy enhancements. The intricacies of collecting, integrating, and effectively leveraging clinical notes for this purpose introduce complexities.

Methods: In our study, we created a natural language processing (NLP) workflow to analyze electronic medical record (EMR) data and identify and extract research of domain criteria using a pre-trained transformer-based natural language model, all-mpnet-base-v2.

Enhancing post-traumatic stress disorder patient assessment: Leveraging Natural Language Processing for Research of Domain Criteria Identification using electronic medical records.

Background: Extracting research of domain criteria (RDoC) from high-risk populations like those with post-traumatic stress disorder (PTSD) is crucial for positive mental health improvements and policy enhancements. The intricacies of collecting, integrating, and effectively leveraging clinical notes for this purpose introduce complexities.

Methods: In our study, we created an NLP workflow to analyze electronic medical record (EMR) data, and identify and extract research of domain criteria using a pre-trained transformer-based natural language model, allmpnet-base-v2.

Fraud victimization across the lifespan: evidence on repeat victimization using perpetrator data.

Older adults are thought to be more susceptible to scams, yet understanding the relationship between chronological age and victimization is limited by underreporting. This study avoids underreporting bias by merging four longitudinal databases of Americans ( = 1.33 million) who paid money in response to mail scams over 20 years.

Effect of Paxlovid Treatment During Acute COVID-19 on Long COVID Onset: An EHR-Based Target Trial Emulation from the N3C and RECOVER Consortia.

Preventing and treating post-acute sequelae of SARS-CoV-2 infection (PASC), commonly known as Long COVID, has become a public health priority. In this study, we examined whether treatment with Paxlovid in the acute phase of COVID-19 helps prevent the onset of PASC. We used electronic health records from the National Covid Cohort Collaborative (N3C) to define a cohort of 426,352 patients who had COVID-19 since April 1, 2022, and were eligible for Paxlovid treatment due to risk for progression to severe COVID-19.

DeepBiomarker2: Prediction of Alcohol and Substance Use Disorder Risk in Post-Traumatic Stress Disorder Patients Using Electronic Medical Records and Multiple Social Determinants of Health.

Prediction of high-risk events amongst patients with mental disorders is critical for personalized interventions. We developed DeepBiomarker2 by leveraging deep learning and natural language processing to analyze lab tests, medication use, diagnosis, social determinants of health (SDoH) parameters, and psychotherapy for outcome prediction. To increase the model's interpretability, we further refined our contribution analysis to identify key features by scaling with a factor from a reference feature.

Long COVID risk and pre-COVID vaccination in an EHR-based cohort study from the RECOVER program.

Long COVID, or complications arising from COVID-19 weeks after infection, has become a central concern for public health experts. The United States National Institutes of Health founded the RECOVER initiative to better understand long COVID. We used electronic health records available through the National COVID Cohort Collaborative to characterize the association between SARS-CoV-2 vaccination and long COVID diagnosis.

Effect of Nirmatrelvir/Ritonavir (Paxlovid) on Hospitalization among Adults with COVID-19: an EHR-based Target Trial Emulation from N3C.

This study leverages electronic health record data in the National COVID Cohort Collaborative's (N3C) repository to investigate disparities in Paxlovid treatment and to emulate a target trial assessing its effectiveness in reducing COVID-19 hospitalization rates. From an eligible population of 632,822 COVID-19 patients seen at 33 clinical sites across the United States between December 23, 2021 and December 31, 2022, patients were matched across observed treatment groups, yielding an analytical sample of 410,642 patients. We estimate a 65% reduced odds of hospitalization among Paxlovid-treated patients within a 28-day follow-up period, and this effect did not vary by patient vaccination status.

Long COVID Risk and Pre-COVID Vaccination: An EHR-Based Cohort Study from the RECOVER Program.

Importance: Characterizing the effect of vaccination on long COVID allows for better healthcare recommendations.

Objective: To determine if, and to what degree, vaccination prior to COVID-19 is associated with eventual long COVID onset, among those a documented COVID-19 infection.

Design Settings And Participants: Retrospective cohort study of adults with evidence of COVID-19 between August 1, 2021 and January 31, 2022 based on electronic health records from eleven healthcare institutions taking part in the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative, a project of the National Covid Cohort Collaborative (N3C).

Tunneling in H loss from energy selected ethanol ions.

The H/D loss and CH(3)/CD(3) loss reactions from energy selected ethanol isotopologue ions C(2)H(5)OH(+), C(2)D(5)OD(+), CD(3)CH(2)OH(+), and CH(3)CD(2)OH(+) have been studied by imaging threshold photoelectron photoion coincidence (iPEPICO) spectroscopy. In the lowest energy dissociation channel, the α-carbon loses a hydrogen or a deuterium atom. Asymmetry in the daughter ion time-of-flight (TOF) peaks, an ab initio study of the reaction rates, and shifts in the phenomenological onsets between isotopologues revealed that H/D loss is slow at its onset.