Wi, Chung-Ii

Abstract Background Data on respiratory syncytial virus (RSV) acute respiratory infection (ARI) among community-dwelling U.S. adults aged 18 to 64 years, particularly those with high-risk conditions (HRC), remain limited. This study estimated incidence and attack rates of RSV-ARI and RSV lower respiratory tract disease (LRTD) in adults with and without HRCs. Methods A multistate, community-based prospective cohort of adults aged 18 to 64 years with and without HRCs was followed from October 2022 to September 2024. Incidence rates and annual attack rates of RSV-ARI and RSV-LRTD were calculated by HRC presence and age group. Results Of 3375 adults with at least 1 HRC, the RSV-ARI incidence rate was 17.9 per 1000 person-years (attack rates: year 1, 1.87%; year 2, 1.56%), compared with 14.8 per 1000 person-years (year 1, 1.33%; year 2, 1.50%) among adults without HRCs. RSV-LRTD incidence was 10.0 per 1000 person-years in adults with HRCs versus 5.7 per 1000 person-years in those without. Asthma, congenital immunodeficiency, and immunosuppressive medication use were associated with increased incidence of RSV-ARI and RSV-LRTD; whereas adults with solid organ transplant and chronic kidney disease had a significantly higher incidence rate of RSV-LRTD compared to those without these conditions. Adults aged 18 to 49 years with HRCs had significantly higher RSV-LRTD incidence (9.6 vs 4.3 per 1000 person-years). After adjustment for age and sex, having ≥1 HRC was associated with a 62% increased RSV-LRTD risk, rising to 117% among adults aged 18 to 49 years. Conclusions Adults with HRCs—particularly asthma, congenital immunodeficiency, chronic kidney disease, immunosuppressive medication use, and solid organ transplant—experienced higher RSV-ARI and RSV-LRTD incidence. The elevated RSV-LRTD burden was most pronounced in adults aged 18 to 49 years with HRCs.

ABSTRACT Importance Rural-urban disparities in chronic disease prevalence are well established; however, the extent to which individual-level socioeconomic status (SES) contributes to these disparities remains unclear. Objective To examine the associations of rurality and SES with the prevalence of five most burdensome chronic diseases among adults. Design We conducted a retrospective cross-sectional study of adults across 27 Upper Midwest counties using the Expanded Rochester Epidemiology Project (E-REP) medical record data linkage system to evaluate associations between rurality, SES and chronic disease prevalence. Prevalence of clinically diagnosed asthma, diabetes, hypertension, coronary heart disease, and mood disorders was identified from International Classification of Diseases ICD9/10 codes over a five-year period (2014-2019). Setting Population based Participants Adults over 18 years residing in the 27 E-REP counties, excluding those missing rural-urban residence status. Exposure HOUSES index, an individual-level measure of SES, served as the primary measure, while rurality based on Rural Urban Commuting Area (RUCA) codes 4-10 was the secondary measure. Main Outcome Prevalence of the five clinically diagnosed chronic diseases was identified using ICD9/10 codes from 2014–2019. Mixed effect logistic regression models were used and adjusted for demographics and general medical examination receipt, to assess rural-urban and SES differences for prevalence of each chronic disease. Results Among 455,802 adults with available HOUSES index, 42.8% lived in rural areas, 53.8% were female and 87.4% were non-Hispanic White. In the unadjusted analysis, rural and urban populations showed comparable asthma and CHD prevalence, while mood disorders, hypertension, and diabetes were more common in urban areas. After adjusting for demographic factors and healthcare utilization, rural-urban differences were no longer statistically significant, whereas SES remained strongly associated with all diseases in a dose response manner (e.g., adjusted Odds Ratio for hypertension (ref: HOUSES index Q4): 1.14, 1.27, and 1.42 for HOUSES index Q3, Q2, and Q1, respectively). Conclusions and Relevance Individual-level SES measured by the HOUSES index, was more strongly associated with chronic disease prevalence than rurality, supporting its integration into population health assessment and risk stratification.

Background Mortality in adults with congenital heart disease (CHD) is strongly driven by disease complexity. Social determinants of health (SDOH) influence adult CHD (ACHD) health outcomes but their impact on mortality is unclear. This study examined the influence of clinical factors and SDOH on all‐cause mortality in patients with ACHD. Methods Single‐center retrospective cohort study of patients with ACHD in the Mayo ACHD Registry who had a verifiable residential address between January 1, 2004 and December 31, 2023. Clinical and SDOH indicators were extracted, including insurance type, language, rural–urban commuting area code, and a housing‐based socioeconomic index, an individual‐level measure of socioeconomic status derived from 4 objective housing characteristics and categorized into quartiles (Q1–Q4). Cox proportional‐hazards models were fitted to evaluate associations with mortality, incorporating CHD severity, arrhythmias, SDOH indicators, and other comorbidities. County of residence was included as a random effect, and model discrimination was assessed using the concordance statistic. Results Among 6134 patients with ACHD, the mean age was 38±16 years; 51% were male; 78.7% were White and 44.9% had rural residence. Independent predictors of mortality included cyanotic CHD (adjusted hazard ratio [aHR], 5.70 [95% CI, 2.90–11.23]), Fontan palliation (aHR, 4.98 [95% CI, 2.56–9.70]), ventricular tachycardia (aHR, 1.71 [95% CI, 1.16–2.52]), older age at first visit (aHR, 1.05 per year [95% CI, 1.04–1.05]), male sex (aHR, 1.19 [95% CI, 1.03–1.39]), public insurance (aHR, 1.60 [95% CI, 1.35–1.90]), rural residence (aHR, 1.25 [95%, CI 1.06–1.47]), and non‐English language (aHR 1.75 [95% CI 1.38–2.23]). The housing‐based socioeconomic index quartile was not associated with mortality. The final model achieved a concordance statistic of 0.77. Conclusions Mortality in patients with ACHD is strongly influenced by both clinical factors and SDOH, independent of socioeconomic status. Addressing barriers to care such as language, insurance, and geography is essential for improving ACHD survival particularly in those at increased mortality risk.

ABSTRACT Background As head and neck cancer survival rates improve, there is growing demand for quality survivorship care and tools to predict patient adherence; this study aims to evaluate an advanced practice provider ( APP )‐led survivorship clinic and assess these key metrics. Methods We performed a retrospective review of 213 head and neck cancer patients treated with curative radiation therapy between 2016 and 2023, to assess follow‐up adherence in an advanced practice provider–led survivorship clinic. Results With a median follow‐up of 2.4 years, follow‐up care metrics identified high completion percentages (> 90%) for lung cancer screening, smoking cessation, thyroid screening, dental evaluation, xerostomia, dysphagia, and dysgeusia. The HOUsing ‐based SocioEconomic Status ( HOUSES ) index at diagnosis showed a significant adherence difference (median percentile, 78% vs. 55%, adherent vs. nonadherent; p = 0.03). Conclusions High adherence rates with guideline‐defined care metrics are achievable in an advanced practice provider‐led head and neck cancer survivorship clinic. The HOUSES index may assist in predicting nonadherence; however, further studies are needed.

Introduction/Objectives: Little is known about the prevalence of patient-reported social risk factors and the use of the HOUSES Index, a simple, reliable method of assessing socioeconomic status (SES) based on publicly available housing data, in a predominantly rural, primary care population. Methods: We conducted a cross-sectional analysis of adult patients paneled to family medicine clinicians in a US Midwest health system as of December 31, 2022. Patients’ listed address determined HOUSES Index as quartile rank (Q1 lowest SES) and rural/urban status. Social risk data including housing, food, transportation, finances, and violence were collected from health record questionnaires. A mixed effect model was used to assess associations between social risk, HOUSES Index, and rurality. Results: Of the 352 355 patients included, rural patients were more likely than urban patients to report all social risk factors and had lower SES as measured by HOUSES quartiles. In the mixed effects analysis, HOUSES quartile was independently predictive of reporting an at-risk social risk factor (Q1 vs Q4 OR = 2.27, 95% CI = 2.19-2.37), but rurality was not (OR = 1.02, 95% CI = 0.97-1.07) after adjusting for HOUSES. Conclusions: The increased prevalence of social risk factors among rural residents is largely explained by individual SES measured by HOUSES Index.

Key Points Pediatric preemptive kidney transplantation rates in the United States vary by socioeconomic status (SES). The HOUsing-based index of SES, an individual-level SES measure derived from residential addresses, effectively predicts pediatric preemptive kidney transplant rates. Background Preemptive kidney transplantation in children is associated with better patient and graft survival compared with transplants after dialysis. However, preemptive kidney transplantation rates in children remain low. This study aimed to evaluate the effect of socioeconomic status (SES) on preemptive transplantation in children. Methods Our study included 173 Minnesota-resident pediatric kidney transplant recipients (younger than 18 years) transplanted at the University of Minnesota from 2010 to 2020. Using the HOUsing-based index of SES (HOUSES) index, a validated, individual SES measure based on housing units categorized into quartiles (Q1: lower SES; Q2–Q4: higher SES), we applied mixed-effects multivariable logistic models to examine the effects of HOUSES on preemptive kidney transplants and pretransplant dialysis duration. Results Of 173 pediatric kidney transplant recipients, 46 (26.6%) received a preemptive transplant, and of 109 recipients with dialysis duration data, 39 (35.8%) received dialysis for >1 year. After adjusting for age at kidney failure, sex, donor type, insurance type, and underlying cause of kidney failure, we observed significantly lower odds of preemptive transplantation among Q1 recipients compared with Q2–4 recipients (adjusted odds ratio, 0.31; 95% confidence interval, 0.11 to 0.90; P = 0.03). Conclusions Using the HOUSES index, we found significant socioeconomic disparities in preemptive kidney transplantation rates among children.

Introduction/Objectives: We aimed to investigate the effect of family structure on depression program outcomes for adolescents enrolled in a depression-focused, primary care-based collaborative care program. Methods: This was a retrospective study of primary care patients ages 12 to 18 years seen at a Midwestern academic center with data obtained by medical record review. We used logistic regression models to assess the effect of family structure on program graduation and achievement of a single Patient Health Questionnaire 9–Modified for Adolescents (PHQ-9M) score <5 at any time while enrolled. Results: Adolescents were divided into 2 groups, Both Parents in Household (n = 179) and Parents Not Together (n = 161). The Both Parents in Household group had higher rates of graduation (38.0% vs 23.6%, P = .005) and achieving single PHQ-9M scores <5 (64.1% vs 46.2%, P = .002) than the Parents Not Together group. Discussion: Youth residing with both parents had higher rates of successful outcomes in a depression-focused collaborative care program.

Abstract Background The incidence of respiratory syncytial virus (RSV)–acute respiratory infection (ARI) in community-dwelling adults after the Omicron variant of the COVID-19 pandemic is unknown. Our aim was to assess the incidence of RSV-ARI in adults aged 18 to 64 years over 2 consecutive RSV seasons (October–April 2022–2024) in 4 US states. Methods This community-based prospective cohort study comprised 7501 participants in Minnesota, Wisconsin, Florida, and Arizona. We calculated RSV-ARI and RSV–lower respiratory tract disease (LRTD) incidence and attack rates. We reported unadjusted incidence by age group, gender, race and ethnicity, Charlson Comorbidity Index, socioeconomic status, residential state, and rural/urban setting. Results Seasons 1 and 2 had 2250 and 2377 ARI episodes, respectively, with an RSV-ARI positivity rate of 5.5% for season 1 and 5.8% for season 2 among those tested. In season 1, the overall incidence of RSV-ARI was 27.71 (95% CI, 22.82–33.34) per 1000 person-years (1.49% attack rate). Almost half (49.0%) had RSV-LRTD, with an incidence of 13.53 (95% CI, 10.19–17.61) per 1000 person-years (0.73% attack rate). In season 2, the RSV-ARI and RSV-LRTD incidence rates were 26.39 (95% CI, 21.73–31.75) per 1000 person-years (1.51% attack rate) and 12.43 (95% CI, 9.31–16.26) per 1000 person-years (0.72% attack rate). RSV-ARI incidence peaked in November 2022 and December 2023. Conclusions Our observations suggest that RSV-ARI incidence and seasonal pattern are shifting to prepandemic RSV epidemiology.

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.