Faculty Bibliography

BACKGROUND:The association of PREVENT-HF (Predicting Risk of Cardiovascular Events-Heart Failure) risk estimates with preclinical heart failure (HF) and whether preclinical HF measures add to the predictive utility of PREVENT-HF remain undefined. OBJECTIVES/OBJECTIVE:The aims of this study were to evaluate the association between PREVENT-HF risk estimates and preclinical HF, to examine how preclinical HF measures correspond to absolute HF risk within PREVENT-HF categories, and to determine whether they provide predictive value beyond the PREVENT-HF score. METHODS:The authors performed a prospective analysis of 2,714 ARIC (Atherosclerosis Risk In Communities) Visit 5 participants <80 years of age, without baseline cardiovascular disease. Preclinical HF was defined by elevated cardiac biomarkers (N-terminal of pro-b-type natriuretic peptide ≥125 pg/mL or high-sensitivity cardiac troponin T ≥22 ng/L/≥14 ng/L in men/women) and/or abnormal echocardiographic findings. Within PREVENT-HF 10-year risk categories (<7.5%, ≥7.5% to <10%, ≥10% to <15%, ≥15% to <20%, and ≥20%), we assessed preclinical HF prevalence and compared 10-year HF incidence rates for those with and without preclinical HF. We assessed changes in predictive utility by adding preclinical HF measures to PREVENT-HF. RESULTS:The mean age was 74 years, with 63% women, and 22% Black adults. Higher PREVENT-HF risk was associated with higher preclinical HF prevalence, with the highest prevalence of combined elevated biomarkers plus abnormal echocardiograms (37%) in those with PREVENT-HF ≥20%. Over a median follow-up of 9.9 years, 262 HF events occurred. Within PREVENT-HF categories, preclinical HF measures were strongly associated with absolute HF risk: among those with PREVENT-HF ≥20%, HF incidence rates (per 1,000 person-years) were 9.5 with no preclinical HF and 51.5 with elevated biomarkers plus abnormal echocardiography. Adding cardiac biomarkers to PREVENT-HF improved risk discrimination (C statistic change 0.69 to 0.75; P < 0.001) and reclassification (categorical Net Reclassification Index: 0.17; 95% CI: 0.09-0.26), with modest further improvement from adding echocardiographic measures. CONCLUSIONS:Preclinical HF measures indicate higher absolute HF risk within PREVENT-HF categories and enhance HF risk prediction.

INTRODUCTION/BACKGROUND:The Neighborhoods Study (TNS) is a novel investigation of adverse social exposome and brain health leveraging 22 Alzheimer's Disease Research Centers (ADRCs). TNS aims to understand if the adverse social exposures increase Alzheimer's disease and related dementias (ADRD) risk. METHODS:TNS uses innovative methods to determine lifetime addresses of living (n = ≈ 3116) and brain bank cohorts (n = ≈ 8637). Addresses are linked to time-concordant adverse social exposome using the Area Deprivation Index (ADI) and summarized over time. Brain health measures are provided by the National Alzheimer's Coordinating Center. RESULTS:We highlight a general overview and methodology of TNS. Data collection is ongoing; however, preliminary findings indicate that the adverse social exposome is related to ADRD biomarkers, neuropathology, and cognitive function. DISCUSSION/CONCLUSIONS:TNS is the largest study of adverse social exposome and ADRD, using the ADRC network to build robust scientific consortia. Its findings will inform ADRD interventions, precision medicine, and policy. HIGHLIGHTS/CONCLUSIONS:The Neighborhoods Study (TNS) investigates adverse social exposome and brain health. TNS is a collaboration among 22 Alzheimer's Disease Research Centers. TNS will give insight on environmental and exposomal factors which may be modifiable. Participant lifetime addresses are linked to temporal adverse social exposome metrics. This study's findings will inform precision approaches to mitigate dementia risk.

Children face an urgent threat in the form of hazards posed by plastics in the environment. Despite robust and rapidly accumulating evidence on the effects of plastic on children's health, plastic presents a paradox for child health providers: while plastic is a vehicle for so many interventions, robust evidence from laboratory and human studies show that chemicals used to produce plastics contribute to chronic conditions in multiple organ systems and disrupt hormone function, and exposure to plastic-derived toxins is associated with adverse birth outcomes, metabolic conditions, neurodevelopmental disease and disability, and reproductive conditions. Evidence-based, safe, simple, and low-cost steps exist for child health providers in primary care to help families limit children's exposure to plastic-derived toxins. Health-care providers also have a crucial opportunity to protect the health and wellbeing of future generations of children by supporting local and global campaigns for governments, industries, and the general public to reduce the accumulation of plastics in the environment and minimise the use of plastics within health-care systems.

PURPOSE/OBJECTIVE:As differences in imaging patterns may indicate unnecessary care, this study examined differences in repeat imaging rates between imaging studies interpreted by a nonphysician practitioner (NPP) versus a radiologist. METHODS:This multiyear (2013-2022) retrospective study evaluated imaging performed on Medicare fee-for-service beneficiaries using a CMS Research Identifiable File. Imaging studies, grouped by anatomic region and modality (eg, shoulder radiography [XR]) with ≥30 repeat studies within 90 days for both NPP-interpreted and radiologist-interpreted index studies, were included. Logistic regression was used to assess the likelihood of repeat imaging within 90 days for NPP-interpreted versus radiologist-interpreted index studies, adjusted for patient gender, age, race or ethnicity, comorbidities, urbanicity, and community income. RESULTS:There were 1,397,002 imaging studies that met the selection criteria. Of these, repeat imaging occurred for 12.5%. Unadjusted repeat imaging rates were higher for NPP-interpreted versus radiologist-interpreted imaging for XR (20.4% versus 14.6%), ultrasound (11.6% versus 4.5%), and MR (8.8% versus 3.8%). Adjusted for covariates, the odds ratio (OR) for repeat imaging was higher for NPP-interpreted versus radiologist-interpreted imaging: 1.35 (95% confidence interval [CI]: 1.33-1.37) for XR, 2.41 (95% CI: 2.21-2.63) for ultrasound, and 2.56 (95% CI: 1.81-3.64) for MR. By anatomic region-modality, these ORs ranged from 1.39 (95% CI: 1.34-1.44) for shoulder XR to 3.40 (95% CI: 2.80-4.14) for abdominal ultrasound, but was not significantly different for knee XR (OR: 1.01, 95% CI: 0.99-1.04). CONCLUSION/CONCLUSIONS:Among Medicare beneficiaries, imaging studies are more likely to be repeated when interpreted by a NPP than when interpreted by a radiologist. Potential excess reimaging has implications for unnecessary care.

AIMS/OBJECTIVE:To evaluate a previously proposed type 2 diabetes staging schema by examining the decline in oral beta-cell compensation and the increase in diabetes risk. METHODS:We analyzed 1,235 participants (43-85 years) from one ELSA-Brasil center. We defined stages as previously proposed: stage 1, isolated 1-h PG ≥155 mg/dL; stage 2, also having prediabetes/intermediate hyperglycemia (preDM/IH) defined by the American Diabetes Association (ADA); and stage 3, diabetes. We made additional evaluations defining IH based on the World Health Organization (WHO)/International Expert Committee (IEC) criteria. We estimated beta-cell compensation with the insulin secretion-sensitivity index-2 (ISSI-2). RESULTS:ISSI-2 declined (p < 0.001) across stages. After 5.29 (0.44) years (n = 850), the adjusted diabetes incidence increased from stage 0 (normoglycemia) to stage 1 (RR = 2.64;1.12,6.22) and stage 2 (RR = 5.94;2.83,12.44), considering WHO/IEC criteria. With the ADA criteria, RRs were larger but not progressive. Adding 1-h PG testing doubled the detection of unknown diabetes. A strategy combining FPG with 1-h PG performed just as well as using all four tests. CONCLUSIONS:Staging captured progressive deterioration to type 2 diabetes. Adding 1-h PG improved current and future case detection, which represents a major advance in diabetes prevention. However, refinements in staging will require further evaluation of tests and their thresholds.

RATIONALE/BACKGROUND:Abrupt air quality improvements have followed the closure or dramatic emission control of large air pollution sources. These "natural experiments" provide ideal opportunities to assess the real-world health benefits of air quality improvements. The shutdown of the Shenango coking plant, a significant fossil-fuel pollution source located on an island in the Ohio River near Pittsburgh, PA, presented such an opportunity to test for changes in respiratory health in the local community following the closure. OBJECTIVES/OBJECTIVE:To identify and quantify the immediate and/or longer-term changes in respiratory hospitalizations and emergency department (ED) visits among the population residing near the Shenango coke plant at the time of its closure. METHODS:We acquired data for respiratory hospitalizations and ED visit counts by residents living in zip codes surrounding the plant, as well as at comparison control sites, three years before and after the shutdown date. The immediate and longer-term changes of respiratory health outcomes were tested with an interrupted time series model, and compared with external control sites and internal control outcomes. MEASUREMENTS AND MAIN RESULTS/RESULTS:We found the closure of the Shenango plant was associated with an immediate 20.5% (95% CI: 12.8%-27.6%) decrease for weekly respiratory ED visits, and an immediate 41.2% (95% CI: 14.4%-59.9%) decrease in pediatric asthma ED visits, followed by an additional 4% per month longer-term downward trend. Longer-term reductions, as compared to pre-closure trends, were also observed for chronic obstructive pulmonary disease hospitalizations. CONCLUSIONS:Our study provides strong confirmation that reductions in fossil-fuel-related air pollution produce both short and longer-term respiratory health benefits. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Older (aged ≥55 years) kidney transplant (KT) recipients diagnosed with a sleep disorder after transplantation may be at increased risk for developing dementia. Using the United States Renal Data System/Medicare claims (2010-2020), we identified 16 573 older KT recipients with a functioning graft 1-year post-KT. First-time sleep disorders and newly prescribed sleep medications were ascertained within the first year post-KT. We used cause-specific hazard models to estimate the adjusted hazard ratio of diagnosed dementia with inverse probability of treatment weights. Overall, 3615 (21.8%) KT recipients were newly diagnosed with sleep disorders. Recipients diagnosed with a sleep disorder had a 1.32-fold increased risk for dementia (95% CI:1.15-1.51); those with insomnia had a 1.56-fold increased risk (95% CI:1.20-2.03). Of those diagnosed with insomnia, only 7.5% underwent cognitive behavioral therapy for insomnia. Of the recipients, 12.9% with a sleep disorder were prescribed sleep medications. Recipients prescribed sleep medication had a 1.44-fold increased risk for dementia (95% CI:1.16-1.77). Those prescribed zolpidem, the most commonly prescribed medication (80.1%), had a 1.41-fold increased risk (95% CI:1.12-1.78) for dementia; those prescribed other sleep medications had 3.13-fold (95% CI:1.41-6.98) increased risk for dementia. Post-KT sleep disorders are modifiable dementia risk factors; medication-associated dementia risk should be weighed against other therapies such as cognitive behavioral therapy for insomnia during management.

OBJECTIVE:To evaluate urinalysis testing patterns within the Veterans Health Administration (VHA), estimate the proportion and likelihood of patients who completed a urinalysis to have microscopic hematuria (MH), and explore how urinalysis testing patterns may influence MH detection. METHODS:This was a retrospective cross-sectional study using VHA data. We identified adult patients without a known urologic cancer history who had at least 1 outpatient visit at any VHA site and at least 1 interpretable urinalysis performed in 2015. The factors associated with the number or urinalyses performed on each patient and associations with the presence of MH were investigated. RESULTS:Among 5,719,966 adults, 39% completed a urinalysis. Variation in the proportion of patients who completed urinalyses was highest by age, among patients with hypertension and diabetes, and by region. Of patients who underwent urinalysis and had no prior genitourinary cancer history, 54% did not have an interpretable urinalysis result. Among patients with at least one interpretable microscopic urinalysis, 37% had MH. This was more common among older patients, females, current smokers, and patients with more comorbidities. Variation in the likelihood of patients having MH remained after adjusting for multiple factors and when contextualized by urinalysis completion and interpretability patterns. CONCLUSION/CONCLUSIONS:The number of urinalyses performed in the VHA system is remarkably high. Detection of MH is influenced by the frequency of urinalysis testing and interpretability of results. The presence and detection of MH varies by factors which should be considered when adjudicating the need for further evaluation of MH.

INTRODUCTION/BACKGROUND:Sleep, depression, stress, and neighborhood support are independently linked to cognition, but how these factors interact when sleep quality is poor remains understudied. METHODS:We analyzed cross-sectional baseline data from 233 adults aged ≥ 65 years in the Aging Adult Brain Connectome study. Sleep quality, depressive symptoms, stress, and neighborhood support were assessed with validated scales, and cognition was measured using the Preclinical Alzheimer's Cognitive Composite (PACC). Models tested two- and three-way interactions, adjusting for sociodemographics. RESULTS:Poor sleep quality was associated with lower PACC scores (β = -0.57, p = 0.002). This association was even more pronounced in older adults who also had depressive symptoms (β = -0.09, p < 0.001) or increased stress (β = -0.31, p < 0.001). This effect was attenuated by greater neighborhood support (interaction estimates 0.007-0.021, all p ≤ 0.014). DISCUSSION/CONCLUSIONS:Poor sleep quality was associated with lower cognition, compounded by psychosocial burden and buffered by neighborhood support. HIGHLIGHTS/CONCLUSIONS:Poor sleep quality worsened late-life cognitive performance in older adults. Depressive symptoms and stress further worsened the effect of poor sleep on cognitive performance. Neighborhood support buffered negative sleep-psychosocial impacts on cognitive performance.