Citations

ABSTRACT Purpose This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

BACKGROUND: Improved cleaning in the anesthesia workspace is important for surgical site infection prevention. We sought to identify high-priority cleaning targets to guide post-induction surface disinfection and use of a triangular ultraviolet-C (UV-C) configuration involving placement of one emitter at the head and one on each side of the surgical bed. METHODS: The 20 sites most frequently touched by anesthesia practitioners, previously identified via video-based workflow analysis, were filtered to remove disposable (eg, stopcocks) and transient (eg, the patient bed) sites, leaving durable cleaning targets amenable to repeated surface disinfection and UV-C irradiation within and/or between cases. Inequality in the distribution of cleaning target touches was quantified using the Gini coefficient, and uncertainty was estimated using bootstrap resampling (10,000 iterations). We then assessed residual contamination after standard terminal cleaning across three operating rooms and 171 sites to evaluate the difficulty of cleaning high-touch surfaces and the efficacy of UV-C disinfection. Simulations using medical devices composed of materials representative of cleaning targets contaminated with high-level Clostridium difficile were conducted to evaluate generalizability to more resistant pathogens. RESULTS: There were 13 of 20 frequently touched sites that were considered durable cleaning targets. Touches were relatively equal among the 13 cleaning targets (Gini coefficient 0.16, 95% confidence interval [CI], 0.12–0.20). Cleaning targets included components of the anesthesia cart (first and second drawer handles); anesthesia machine (reservoir bag, circuit ventilator control, oxygen dial, vaporizer dial, adjustable pressure-limiting valve), monitoring equipment (screen buttons/knob, electrocardiogram leads); and room infrastructure (intravenous pole, operating room table and chair). Residual contamination after cleaning was identified at 4% (7/171) of sites, mostly (6/7) within the anesthesia workspace, involving the anesthesia cart (N = 2), machine (N = 3), and monitor (N = 1). Only one site outside of the anesthesia workspace, the circulating nurse’s mouse, had residual contamination. Triangular UV-C reduced mean (standard deviation [SD]) colony-forming units (CFU) from 60.47 (542.22) to 0.12 (1.08), achieving a 2.7-log reduction. Simulation with high-level C. difficile contamination demonstrated ≥3-log reductions on surfaces representative of high-touch sites, confirming applicability to resistant pathogens. CONCLUSIONS: Thirteen durable cleaning targets in the anesthesia workspace are largely equivalent in terms of risk of touch. They are amenable to UV-C augmentation of surface disinfection in the real-world clinical environment. These findings can guide targeted post-induction cleaning and use of triangular UV-C, particularly for surfaces with substantial contamination or resistant pathogens.

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.

Introduction: Abnormal sleep has been linked to increased dementia risk, but the pathophysiological processes driving this connection are unclear. To provide insight into the biological pathways underlying the relationship between sleep and brain health, we tested the hypothesis that increased obstructive sleep apnea (OSA) severity and shorter habitual sleep duration are associated with a higher burden of Alzheimer’s disease (AD) pathology, neurodegeneration, and neuroinflammation measured through plasma biomarkers. Methods: ARIC participants who took part in the Sleep Heart Health Study at Visit 4 (1996-98) with stored plasma samples at Visit 3 (1993-95) and Visit 5 (2011-13) were examined (n=261; mean age 61.3 years; 43.3% male). OSA severity, categorized based on the number of apneas and hypopneas per hour of sleep (<5 events/hour [Normal], 5 to <15 events/hour [Mild OSA], or ≥15 events/hour [Moderate/Severe OSA]) was assessed via in-home polysomnography, and average habitual sleep duration (<7 hours, 7 to <8 hours, or ≥8 hours) was self-reported. Plasma biomarkers of amyloid beta (Aβ) 42 and 40, phosphorylated Tau 181 (p-Tau181), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were measured using Quanterix Simoa immunoassays. Covariate-adjusted linear regression models estimated associations of sleep indices in 1996-98 with standardized plasma biomarker measurements in 1993-95 (3 years earlier) and in 2011-13 (15 years later). Covariate-adjusted linear mixed effects models quantified associations of sleep measures with the 5-year rates of change in standardized biomarker levels (1993-2013). Results: Compared to a habitual sleep duration of 8 hours or more, sleeping less than 7 hours per night was associated with higher NfL, a biomarker of neurodegeneration, 15 years later (β = 0.252; 95% confidence interval [CI]: 0.003, 0.501). Sleep indices were not associated with biomarker levels 3 years earlier. Counter to our hypothesis, Moderate/Severe OSA was associated with slower increases in p-Tau181 (β = -0.102; 95% CI: -0.198, -0.006), a biomarker of AD pathology, over a median of 17.9 years. Conclusions: Short habitual sleep duration may impact dementia outcomes through neurodegenerative and other processes rather than through pathways specific to AD pathology or neuroinflammation. Longitudinal studies with sleep measurements in larger, more diverse samples are needed to further distinguish the pathways linking sleep to dementia.

Abstract Purpose: Familial adenomatous polyposis (FAP) confers a significant risk of colorectal/duodenal cancer. Encapsulated rapamycin (eRapa) has demonstrated promise as FAP chemoprevention in early clinical studies. Patients and Methods: Thirty patients with FAP enrolled to three dosing regimens of eRapa (0.5 mg): cohort 1—every other day, cohort 2—daily every other week, or cohort 3—daily. The primary endpoints were safety/tolerability, pharmacokinetics, and percentage change from baseline (PCFB) in colorectal polyp burden (CPB) at 6 months. Secondary endpoints included PCFB total (TPB) and duodenal (DPB) polyp burden and change in International Society for Gastrointestinal Hereditary Tumors stage and Spigelman score at 6 and 12 months. Results: Twenty nine of thirty patients (97%) completed the 12-month study with predictable bioavailability. Low-grade adverse events were frequent but most pronounced in daily dosing. Two patients discontinued treatment related to toxicity. Cohort 1 had the largest decrease median PCFB CPB, DPB, and TPB at 6 months: −39.4 % (IQR, 108.9; P = 0.28), −33.33 % (IQR, 90; P = 0.04), and −38.6 % (IQR, 88.5; P = 0.26), respectively. At 12 months, cohort 2 had the largest decrease median PCFB CPB and TPB: −29.3 % (IQR, 67.6; P = 0.37) and −26.3 % (IQR, 49.5; P = 0.29), respectively. Intermittent dosing cohorts (1 and 2) reduced DPB at 6 months (P = 0.04) and improved TPB at 12 months (P = 0.05) compared with daily dosing. Conclusions: eRapa was safe, tolerable, and showed preliminary efficacy for FAP chemoprevention. The 0.5 mg daily every-other-week schedule will be evaluated in an upcoming phase III trial.

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.

Objectives: To assess how social risk factors and socioeconomic status (SES) affect health care costs at a large, integrated health system of 45 clinics in Iowa, Minnesota, and Wisconsin. Methods: We retrospectively reviewed administrative patient cost data from January 1 through December 31, 2022. Social risk factors (lack of financial resources, food insecurity, intimate partner violence, unmet transportation needs, and housing instability) were determined with patient questionnaires. Cost z -scores were compared across all risk-factor quartiles. We used a housing-based measure to objectively determine SES. Results: We analyzed data from 410 624 patients empaneled with 689 family medicine clinicians. Self-reported risk factor data were incomplete for 219 321 patients. Costs were higher for those with higher social risk (mean cost z -score: high risk = 0.38, low risk = 0.11; P < .001). In addition, higher costs were associated with increasing age, greater medical complexity (higher Adjusted Clinical Group scores), White race, and lack of financial resources. Although we observed geographic variations in cost, urban and rural locations did not have significant cost differences. Costs were similar across all quartiles of SES, and the absolute difference in cost z -scores between the highest and lowest SES quartiles was only 0.04. The multivariate analysis, which adjusted for age, medical complexity, race, sex, and objective SES, showed that these specific associations were substantially decreased and no longer significantly associated with mean cost z -scores. Conclusions: Patient-reported social risk factors were significantly associated with increased cost of care in a large, multispecialty health system in the midwestern US. These associations were decreased in the multivariate analysis. Results should be interpreted cautiously for readers outside the midwestern US, given potential responder bias and the racial homogeneity (92% White) of the study cohort.

With most states lacking comprehensive legislation addressing overdose preparedness in schools, there is an urgent necessity for prompt and effective solutions that accommodate existing resource constraints. Arizona, the primary entry point for over 55% of US fentanyl trafficking, responded to this critical public health challenge by initiating the nation’s first unfunded grassroots collaboration between community and government sectors to enhance statewide school overdose prevention and preparedness. The School Training, Overdose Preparedness and Intelligence Task force (STOP-IT) included more than 60 volunteers from the health care, legal, education, local government and behavioral health fields and worked collaboratively with the Arizona Department of Education to develop a response. Within 6 months of inception, STOP-IT conducted a comprehensive school survey to identify barriers to naloxone accessibility, created evidence-based school policies, established a sustainable and complimentary naloxone supply chain for schools with an ordering platform, and implemented a statewide naloxone distribution plan. The amassed resources were organized into a Fentanyl and Overdose Response Toolkit, widely disseminated to more than 2000 public, private, and charter schools. Moreover, STOP-IT launched both a local and national public information campaign to effectively raise awareness about the opioid crisis in schools. Using various media channels such as webinars, podcasts, media broadcasts, newsletters, and peer-reviewed publications, the campaign successfully amplified its message and enhanced community engagement. The STOP-IT initiative emerged as an innovative collaboration between government and community leaders, united in their mission to combat the growing opioid crisis in schools.