Ryu, Euijung

Objective Respiratory syncytial virus (RSV) is an important viral pathogen in children, older adults and adults with certain high-risk conditions. In our prospective community-based cohort study of adults 50 years and older before the COVID-19 pandemic, the incidence of RSV acute respiratory infection (ARI) was 48.6 cases/1000 person-years (PY), which decreased to near zero during the COVID-19 pandemic. Our objective was to determine the incidence of RSV-ARI during the 2 years following the initial phase of the pandemic (2021–2022 and 2022–2023). Design This is a community-based prospective cohort study. Setting Adults living in southeast Minnesota from October 2021 to September 2022 (year 3) and October 2022 to September 2023 (year 4). Participants Adults≥50 years (n=2500). Primary and secondary outcomes We calculated incidence and attack rates for RSV-ARI as primary outcome and reported hospitalisations, pneumonia and death following ARI as secondary outcome. Results There were 2500 participants in the study with a mean age of 68.2 years (SD 9.3) at the start of year 3. Participants were predominantly female (60%), non-Hispanic white (96%) and residing in urban areas (76%). The incidence rate of RSV-ARI was 6.12/1000 PY (95% CI 3.42 to 10.09) in 2021–2022 and 16.40/1000 PY (95% CI 11.66 to 22.42) in 2022–2023. We noted higher attack rates of RSV-ARI during the winter months. There were no hospitalisations, pneumonia or deaths within 30 days of RSV-ARI. Conclusions Compared with the period before the COVID-19 pandemic, RSV-ARI incidence was lower in both 2021–2022 and 2022–2023 periods. In 2022–2023, the incidence increased 2.7-fold compared with the 2021–2022 period. The observed incidence rates, particularly the significant increase in the most recent season, underscore the continued public health relevance of RSV-ARI and support the rationale for ongoing RSV vaccination efforts to mitigate its overall burden in the population.

Background Multimorbidity is common in patients with atrial fibrillation (AF); however, the impact of the number and type of comorbid conditions on outcomes remains uncertain. Methods This cohort study included patients with new‐onset AF from a Midwest region between 2013 and 2017. Eighteen chronic conditions at the time of AF were classified into groups: cardiometabolic, other somatic, and mental health. Cox regression determined associations between the number of each condition type with death, ischemic stroke/transient ischemic attack, and congestive heart failure, stratified by age. Results Among 16 509 patients with AF (mean age, 74 years; 43% women), the mean number of cardiometabolic, other somatic, and mental health conditions was 2.7, 1.4, and 0.5, respectively. The number and type of conditions had a varying impact on outcomes and differed by age. A higher number of cardiometabolic conditions were associated with increased risk of death within 90 days only in people aged ≥85 years (≥4 conditions versus 0: hazard ratio [HR], 1.74 [95% CI, 1.05–2.87]), whereas for death after 90 days, associations were strongest in the youngest age group (<65 years: HR, 1.83 [95% CI, 1.35–2.46]; 65–74 years: HR, 1.34 [95% CI, 1.04–1.73]; 75–84 years: HR, 1.32 [95% CI, 1.09–1.60]; ≥85 years: HR, 1.14 [95% CI, 0.96–1.35]). Associations with outcomes were generally strongest in the youngest age group and attenuated with older age for higher number of other somatic conditions, whereas the pattern was less consistent for mental health conditions. Conclusions Along with cardiometabolic‐related conditions, other somatic and mental health conditions are important predictors of outcomes in AF, with effects differing by age, and should be considered when caring for these patients.

Abstract Background/Objective: Decentralized research has many advantages; however, little is known about the representativeness of a source population in decentralized studies. We recruited participants aged 18-64 years from four states from June to December 2022 for a prospective cohort study to assess viral epidemiology. Our aim was to determine the association between age, gender, race/ethnicity, rurality, and socioeconomic status (SES) on study participation in a decentralized prospective cohort study. Methods: We consented 9,286 participants from 231,099 (4.0%) adults with the mean age of 45.6 years (±12.0). We used an electronic decentralized approach for recruitment. Consented participants were more likely to be non-Hispanic White, female, older, urban residents, have more health conditions, and possessed higher socioeconomic status (SES) compared to those non-consented. Results: We observed an interaction between SES and race-ethnicity on the odds of consent (P = 0.006). Specifically, SES did not affect non-Hispanic white participation rates(OR 1.24 95% CI 1.16 – 1.32] for the highest SES quartile compared to those with the lowest SES quartile) as much as it did participants combined across the other races (OR 1.73; 95% CI 1.45 – 2.98]) Conclusion: The relationship between SES and consent rates might be disproportionately greater in historically disadvantaged groups, compared to non-Hispanic White. It suggests that instead of focusing on enrollment of specific minority groups in research, there is value in future research exploring and addressing the diversity of barriers to trials within minority groups. Our study highlights that decentralized studies need to address social determinants of health, especially in under-resourced populations.

Purpose The Sangre Por Salud (SPS) Biobank was established to facilitate biomedical research opportunities for the Latino community by creating an easily accessible prospective cohort for scientists interested in studying health conditions and health disparities in this population. Participants Individuals self-identifying as Latino, aged 18–85 years, were prospectively recruited from the primary care Internal Medicine clinic at Mountain Park Health Center in Phoenix, Arizona. After obtaining informed consent, detailed medical history questionnaires were captured, and blood samples were obtained for common laboratory tests. Participants authorised the research team to access their electronic health records for research purposes. In addition, participants had serum, plasma and DNA samples isolated and stored at the Mayo Clinic Arizona Biorepository Laboratory for long-term storage and future access. As part of the study, participants consented and agreed to be contacted for potential participation in future research studies. Findings to date 3756 participants provided informed consent, of whom 3733 completed all study questionnaires, an oral glucose tolerance test and had blood collected and stored. The SPS cohort is predominantly composed of females (72%), with a median age at time of consent of 42 years. All participants self-identified as Hispanic/Latino, 45% were married, 53% were employed for wages and 60% had less than a high school degree. Around 25% of participants met diagnostic criteria for overweight (BMI 25–29 kg/m 2 ), and 49% met for obesity (BMI≥30 kg/m 2 ). At time of recruitment, hypertension, hyperlipidaemia and depression affected 22%, 20% and 13% of the cohort, respectively. Future plans We plan to regularly update the participants’ electronic health records and self-reported health data to longitudinal research. Additionally, we plan to obtain a more comprehensive genomic analysis on the entire cohort, ensuring greater research interest and investigation into the underlying genetic factors that contribute to disease susceptibility in this cohort.

Background Multimorbidity is common in patients with atrial fibrillation (AF), yet comorbidity patterns are not well documented. Methods The prevalence of 18 chronic conditions (6 cardiometabolic, 7 other somatic, 5 mental health) was obtained in patients with new-onset AF from 2013-2017 from a 27-county region and controls matched 1:1 on age, sex, and county of residence. For AF patients and controls separately, clustering of conditions and co-occurrence beyond chance was estimated (using the asymmetric Somers’ D statistic), overall and for ages <65, 65-74, 75-84, and ≥85 years. Results Among 16,509 patients with AF (median age 76 years, 57% men), few (4%) did not have any of the 18 chronic conditions, whereas nearly one-quarter of controls (23%) did not have any chronic conditions. Clustering of cardiometabolic conditions was common in both AF patients and controls, but clustering of other somatic conditions was more common in AF. Although the prevalence of most condition pairs was higher in AF patients, controls had a larger number of condition pairs occurring together beyond chance. In persons aged <65 years, AF patients more frequently exhibited concordance of condition pairs that included either pairs of somatic conditions or a combination of conditions from different condition groups. In persons aged 65-74 years, AF patients more frequently had pairs of other somatic conditions. Conclusion Patterns of co-existing conditions differed between patients with AF and controls, particularly in younger ages. A better understanding of the clinical consequences of multimorbidity in AF patients, including those diagnosed at younger ages, is needed.

Background. The limitations of conventional measures of socioeconomic status (SES) limit our ability to elucidate the role of SES as a key element of social determinants of health in kidney transplantation. This study’s objective was to use an innovative SES measure, the HOUsing-based SES measure (HOUSES) index, to examine the effects of social determinants of health on access to and outcomes of kidney transplantation. Methods. Our study included residents of Minnesota (age older than 18 y) who underwent kidney transplantation at a single center between 2010 and 2020. SES was determined using the HOUSES index, categorized into quartiles (Q1 for lower, Q2–Q4 for higher SES). We used mixed-effects multivariable logistic and Cox models to examine the effects of HOUSES on preemptive transplants, pretransplant dialysis duration, and death-censored graft loss, adjusting for covariates. Results. Among 1975 eligible patients, 29.4% received preemptive transplants, 34.9% underwent pretransplant dialysis for >3 y, and 15.1% experienced death-censored graft loss for a median follow-up of 7.15 (interquartile range, 4.25–11.38) y. Lower SES recipients (Q1) demonstrated decreased preemptive transplant likelihood (adjusted odds ratio [aOR]: 0.74; 95% confidence interval [CI], 0.57-0.97; P = 0.03), longer dialysis duration (>3 y; aOR: 1.43; 95% CI, 1.01-2.03; P = 0.046), and higher death-censored graft loss (adjusted hazard ratio 1.36; 95% CI, 1.02-1.12; P = 0.036) versus higher SES recipients (Q2–Q4). Conclusions. We observed significant socioeconomic disparities in kidney transplant access, dialysis duration, and graft survival. The HOUSES index may be a promising tool for individual-based targeted interventions as it identifies SES on an individual rather than an area-level basis.

Abstract Objectives Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), individual-level SS/SI is typically documented in narrative clinical notes rather than as structured coded data. Natural language processing (NLP) algorithms can automate the otherwise labor-intensive process of extraction of such information. Materials and Methods Psychiatric encounter notes from Mount Sinai Health System (MSHS, n = 300) and Weill Cornell Medicine (WCM, n = 225) were annotated to create a gold-standard corpus. A rule-based system (RBS) involving lexicons and a large language model (LLM) using FLAN-T5-XL were developed to identify mentions of SS and SI and their subcategories (eg, social network, instrumental support, and loneliness). Results For extracting SS/SI, the RBS obtained higher macroaveraged F1-scores than the LLM at both MSHS (0.89 versus 0.65) and WCM (0.85 versus 0.82). For extracting the subcategories, the RBS also outperformed the LLM at both MSHS (0.90 versus 0.62) and WCM (0.82 versus 0.81). Discussion and Conclusion Unexpectedly, the RBS outperformed the LLMs across all metrics. An intensive review demonstrates that this finding is due to the divergent approach taken by the RBS and LLM. The RBS was designed and refined to follow the same specific rules as the gold-standard annotations. Conversely, the LLM was more inclusive with categorization and conformed to common English-language understanding. Both approaches offer advantages, although additional replication studies are warranted.

Background: Multimorbidity is common in atrial fibrillation (AF), particularly among older patients who generally have multiple cardiovascular and non-cardiovascular chronic conditions. However, less is known about the accumulation of chronic conditions in younger patients with AF. Methods: Patients aged <65 with incident AF from 2013-2019 from a 27-county region in the Midwest (N=4907) were matched 1:1 on age (±5 years) and sex to referents from the same community. The index date for the matched pair was the date of first diagnosis of AF. Diagnosis of 20 other chronic conditions was ascertained from 3 years prior to index through 12/31/2022. Mean cumulative function curves were used to visualize the accumulation of conditions; Andersen-Gill models estimated associations between AF/referent status and accumulation of conditions. Results: The mean age was 55 years for both patients with AF and matched referents; 71% were male. In the 3 years leading up to AF diagnosis, only 4% of patients with AF had no additional chronic conditions and 69% had ≥3 chronic conditions. In contrast, 35% of referents had 0 and 32% had ≥3 chronic conditions. The accumulation of chronic conditions was accelerated in patients with AF compared to referents prior to AF diagnosis/index (Figure). After index, patients with AF had increased accumulation of chronic conditions (HR (95% CI): 1.93 (1.71-2.20), 1.82 (1.62-2.05), 1.68 (1.55-1.83), and 1.53 (1.44-1.64) for ages <50, 50-54, 55-59, and 60-64 years, respectively). After 1 year, the differences were attenuated in all age groups with no difference observed between patients with AF and referents in the oldest age group (1.26 (1.08-1.46), 1.28 (1.11-1.47), 1.13 (1.02-1.24), and 1.05 (0.97-1.13) for ages <50, 50-54, 55-59, and 60-64 years). Conclusion: Patients <65 years with AF have an increased accumulation of chronic conditions compared to those without AF, in particular prior to their AF diagnosis and within the first year after AF diagnosis.

Introduction: Using a digital process that leverages electronic health records (EHRs) can ease many of the challenges presented by the traditional enrollment process for clinical trials. We tested if automated batch enrollment using a technology-enabled subject recruitment system (TESRS) enhances recruitment while preserving representation of research subjects for the study population in our study setting. Methods: An ongoing community-based prospective adult cohort study was used to randomize 600 subjects who were eligible by age and residential address to TESRS (n = 300) and standard mailing method (n = 300), respectively, for 3 months. Then, TESRS was initiated and included automatic identification of patients’ preference for being contacted (online patient portal vs postal mail) from EHRs and automatic sending out of invitation letters followed by completion of a short online survey for checking eligibility and the digital consent process if eligible. We compared (1) median time to consent from invitation sent out per subject and total subjects recruited after a 3-month recruitment period, (2) the estimated study staff’s time, and (3) representation of sociodemographic characteristics (e.g., age, sex, race, SES measured by HOUSES index, and rural residence) between subjects recruited via TESRS and those via traditional mailing methods. Results: Median age of randomized subjects (n = 600) was 63 years with 52.0% female and 89.2% non-Hispanic White. Over a 3-month period, results showed consent rate via TESRS was 13% (39/297) similar to 11% (31/295) via standard mailing. However, recruitment was significantly faster with the TESRS approach (median 7 vs 26 days) given the study staff’s effort. Study staff’s time saved by using TESRS compared to standard mailing approach was estimated at 40 min per subject (equivalent to 200 h for 300 subjects). No significant differences in characteristics of research subjects from the study population were found. Conclusion: Our study demonstrated the utility of TESRS as a subject recruitment digital technology which significantly enhanced the recruitment effort while reducing the study staff burden of recruitment while maintaining the consistency of characteristics of recruited subjects. The strategy and support for implementing and testing TESRS in other study settings should be considered.