Chamberlain, Alanna M

Background Reductions in blood pressure (BP) control among patients with hypertension were observed early in the COVID‐19 pandemic. The degree to which BP control may have returned to prepandemic levels is unknown. Methods Individuals aged 18 to 85 years with hypertension from 17 health systems participating in the National Patient‐Centered Clinical Research Network were identified using electronic health record data collected as part of routine care. BP control (percentage of patients whose most recent BP measurement was <140/<90 mm Hg) was estimated in a series of 12‐month rolling measurement periods from 2017 through 2022 (January 1, 2017 through December 31, 2017; April 1, 2017 through March 31, 2018; … January 1, 2022 through December 31, 2022). Differences in average BP control between 2022 (January 1, 2022 through December 31, 2022) and 2019 (January 1, 2019 through December 31, 2019) were estimated overall (adjusted for age, sex, and race and ethnicity) and by race and ethnicity (adjusted for age and sex). Results Our sample included 1 193 314 persons with hypertension in 2019 (48.9% aged 65–85 years, 52.9% men, 66.2% non‐Hispanic White) and 1 499 418 individuals in 2022 (50.6% aged 65–85 years, 47.1% men, 62.7% non‐Hispanic White). The weighted average BP control dropped from 65.3% in 2019 to 61.8% in 2020 and then partially recovered to 62.6% in 2022 (adjusted mean difference, −2.6 percentage points [95% CI, −5.0 to −0.2]). Non‐Hispanic Asian individuals experienced the largest temporal drop in BP control, declining from 68.4% in 2019 to 63.9% in 2022. Conclusions BP control was disrupted during the COVID‐19 pandemic and had not fully rebounded to prepandemic levels by the end of 2022. Continued surveillance is needed to determine whether the decline in BP control will persist and will result in future adverse cardiovascular events.

Background Area‐based deprivation indices have been linked to hypertension and diabetes outcomes, but limited information exists about their relative performance. We compared 2 area‐based deprivation measures (Area Deprivation Index and Yost Index) as risk factors for hypertension and diabetes control. Methods This cohort study identified adults with hypertension or diabetes in a 19‐county region of Southeast Minnesota covered by the Rochester Epidemiology Project. The deprivation indices were operationalized as quintiles for state and national ranks. We assessed agreement using the weighted kappa statistic. We used modified Poisson regression to evaluate associations of the deprivation indices with blood pressure or diabetes control in 2022. We compared relative model fit using the area under the receiver operating characteristic curve. Results We identified 67 386 individuals with hypertension and 30 435 with diabetes. There was moderate to substantial agreement between indices, but the agreement was higher for the state rank (weighted kappa 0.68 for both cohorts) than the national rank (0.54 for both). Although the indices were not associated with hypertension control, greater deprivation was associated with worse diabetes control for the Yost Index (relative risk [RR], 1.21 [95% CI, 1.07–1.38]) and Area Deprivation Index (RR, 1.39 [95% CI, 1.12–1.73]) national ranks. The full‐model area under the receiver operating characteristic curve was similar across indices but differed across cohorts with worse fit for hypertension (0.53 for both) than diabetes (0.63 for both). Conclusions Two common area‐based deprivation indices had similar strength of association with diabetes control, suggesting that either index would be appropriate for researching and developing interventions for diabetes control.

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.

BACKGROUND: While health systems have implemented resources to improve lipid management in people with atherosclerotic cardiovascular disease, the population-level effectiveness is unclear. METHODS: Electronic health record data from patients with atherosclerotic cardiovascular disease between January 1, 2021, and December 31, 2023, across 16 US academic health systems were analyzed. Atherosclerotic cardiovascular disease (defined by diagnosis and procedure codes) was established on or before the index date defined as the date of the most recent LDL-C (low-density lipoprotein-cholesterol) or the last day of the study period for those without an LDL-C available. Systems were surveyed to identify lipid management programs (eg, prevention/lipid clinic, electronic health record–based tools, and lipid management algorithms). Sequential multilevel multivariable logistic regression modeling was used to (1) assess the system-level association between an LDL-C <70 mg/dL and the presence of lipid management programs, adjusting for patient-level demographic and clinical characteristics, and (2) whether system-level uptake of statin or nonstatin lipid-lowering therapy was associated with an LDL-C <70 mg/dL. RESULTS: We included 1 738 042 patients with atherosclerotic cardiovascular disease (median, 88 365 per system; range, 17 086–2 48 371). About 81% of the health systems had prevention or lipid clinics. The proportion of those on statins ranged from 31.0% to 60.4% across health systems (median, 46.3%). Lower proportions were observed in the use of high-intensity statins (16.2%–33.1%), nonstatins (2.6%–8.1%), and combination lipid-lowering therapy (1.7%–6.3%). Among those with an LDL-C level available (n=890 521), 42.5% had an LDL-C <70 mg/dL, ranging 35.8% to 49.4% across systems. There was no association between the odds of achieving LDL-C <70 mg/dL and health system lipid management algorithm, prevention clinics/lipid clinics, or electronic health record–based tools. Neither system-level high-intensity statin utilization nor nonstatin use was associated with an LDL-C <70 mg/dL. CONCLUSIONS: Despite variability in lipid management resources and lipid-lowering therapy use across systems, many did not reach an LDL-C <70 mg/dL, and there was low uptake of lipid-lowering therapy. Innovative implementation strategies are needed for system-level lipid management.

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.

ObjectiveWe aimed to characterize presentation and care pathways of patients with systemic lupus erythematosus (SLE), and delays in access to SLE‐specialized care.MethodsWe included patients with incident SLE from the Lupus Midwest Network registry. Time from the first medical encounter for SLE clinical manifestation to access to SLE‐specialized care, physician diagnosis, and treatment was estimated. Delays were defined as ≥6 months to access specialized care. We compared SLE manifestations, disease activity, and Systemic Lupus International Collaborating Clinics/American College of Rheumatology damage indexes (SDI) between patients with and without delays. Logistic regression models assessed associations with delays.ResultsThe study included 373 patients with SLE. The median time to access SLE‐specialized care was 1.1 (95% confidence interval [CI] 0.9–1.5) months, time to diagnosis was 30.6 (95% CI 18.9–48.1) months, and time to treatment initiation was 4.7 (95% CI 3.9–8.4) months. Approximately 25% of patients (93 out of 373) experienced delays accessing specialized care, which were associated with fewer SLE manifestations at first SLE‐related encounter (fewer than two SLE domains; 92% vs 72%, P < 0.001). Patients with mucocutaneous or musculoskeletal manifestations were less likely to experience delays, whereas hematologic (odds ratio [OR] 1.71, 95% CI 1.03–2.84) or antiphospholipid antibodies domains (OR 6.05, 95% CI 2.46–14.88) were associated with delays. Delays were associated with damage at first access to SLE‐specialized care (SDI ≥1; 30% vs 7%, P < 0.001).ConclusionPatients follow a heterogeneous pathway to receive care. One‐fourth of patients experienced delays accessing SLE‐specialized care, which was associated with disease‐related damage. Fewer manifestations, hematologic manifestations, or antiphospholipid antibodies were associated with delays.image

BACKGROUND: Senescence, a mechanism of cellular aging, which is characterized by irreversible proliferation arrest and a proinflammatory secretory phenotype, has been documented in women with preeclampsia. As cellular senescence can persist and progress, we postulated that it is associated with accelerated aging phenotype and accumulation of comorbidities in women with a history of preeclampsia. METHODS: We included a cohort of women with a history of preeclampsia (n=40) age- and parity-matched to a group of referent women with normotensive pregnancies (n=40). Women with prior major cardiovascular events, neurological, or autoimmune conditions were excluded. We collected urine and blood samples to study markers of aging, data on multimorbidity at the time of enrollment, and prospectively followed them for events over the course of 6 years, on average. RESULTS: Women with a history of preeclampsia exhibited unfavorable aging profiles compared with referent women, including decreased urinary α-Klotho ( P =0.018); increased leptin ( P =0.016) and leptin/adiponectin ratio ( P =0.027), and increased extracellular vesicles positive for tissue factor ( P =0.025). Women with a history of preeclampsia likewise had a higher rate of comorbidities at the time of enrollment ( P =0.003) and had a 4× higher risk of developing major cardiovascular events compared with referent women ( P =0.003). CONCLUSIONS: Our data suggest that a history of preeclampsia is associated with accelerated aging as indicated by senescence marker differences and the accumulation of multimorbidity later in life. Targeting cellular senescence may offer novel, mechanism-based approaches for the diagnosis and treatment of adverse health outcomes in women with a history of preeclampsia.

Abstract Objectives The objectives of this study were to assess the prevalence and incidence of multimorbidity and its association with the SLICC/ACR damage index (SDI) among patients with SLE. Methods Using prevalent and incident population–based cohorts of patients with SLE and their matched comparators, we assessed 57 chronic conditions. Chronic conditions were categorized as SDI-related or SDI-unrelated. Multimorbidity was defined as the presence of two or more chronic conditions. The prevalence of multimorbidity for both cohorts was compared using logistic regression. Cox models were used to examine the development of multimorbidity after SLE incidence. Results The prevalent cohort included 449 patients with established SLE on 1 January 2015. They were three times more likely to have multimorbidity compared with non-SLE comparators [odds ratio (OR) 2.98, 95% CI 2.18–4.11]. The incident cohort included 270 patients with new-onset SLE. At SLE incidence, patients with SLE were more likely to have multimorbidity than comparators (OR 2.27, 95% CI 1.59–3.27). After incidence, the risk of developing multimorbidity was 2-fold higher among patients with SLE than among comparators [hazard ratio (HR) 2.11, 95% CI 1.59–2.80]. The development of multimorbidity was higher in patients with SLE based on SDI-related conditions (HR 2.91, 95% CI 2.17–3.88) than on SDI-unrelated conditions (HR 1.73, 95% CI, 1.32–2.26). Conclusion Patients with SLE had a higher burden of multimorbidity, even before the onset of the disease. The risk disparity continued after SLE classification and was also seen in a prevalent SLE cohort. Multimorbidity was driven both by SDI-related and unrelated conditions.

Background Heart failure (HF) is a complex disease that contributes to a high number of hospitalizations, deaths, and economic health care costs each year. However, among patients with HF, there is a lack of awareness of their HF diagnosis that has not been fully examined. Methods and Results Residents from 3 counties of southeast Minnesota with a first‐ever International Classification of Diseases, Ninth Revision ( ICD‐9 ) code 428 or Tenth Revision ( ICD‐10 ) code I50 between January 1, 2013 and March 31, 2016 (N=2461) were prospectively surveyed to measure HF self‐awareness. A total of 1114 patients returned the survey (response rate, 45%), and 787 had validated HF upon medical record review. Among these 787 patients with HF (mean age, 76 years; 53% men), 37% (n=293) were aware of their HF diagnosis. After adjustment, being a woman (odds ratio [OR], 1.56 [95% CI, 1.10–2.22]), having HF with reduced ejection fraction (OR, 1.58 [95% CI, 1.13–2.22]), attending the HF clinic (OR, 4.07 [95% CI, 2.25–7.36]), and having coronary artery disease (OR, 1.65 [95% CI, 1.16–2.37]) were all associated with increased awareness of an HF diagnosis. Conversely, having diabetes was associated with decreased awareness of an HF diagnosis (adjusted OR, 0.69 [95% CI, 0.50–0.95]). Conclusions Awareness of an HF diagnosis is low in a community population of patients with HF. Strategies to improve patient awareness of their diagnosis should be implemented to improve self‐care behaviors and outcomes in patients with HF.

BACKGROUND: Hypertensive disorders of pregnancy (HDP) have been associated with an increased risk of chronic hypertension for both mothers and offspring. We sought to quantify the incidence of chronic hypertension in offspring from HDP-affected pregnancies in a large, population-based cohort study. Furthermore, we evaluate the association of HDP exposure in utero and maternal chronic hypertension in offspring. METHODS: We performed a population-based cohort study of 8755 individuals born during 1976 to 1982 to 7544 women who all resided in the same community at the time of delivery. HDP were identified using a previously validated algorithm. Diagnosis of chronic hypertension in mothers and their offspring was determined using diagnostic codes. Cox proportional hazards regression was used to assess the association between HDP and chronic hypertension. RESULTS: HDP exposure (hazard ratio, 1.50 [95% CI, 1.18–1.90]) and maternal chronic hypertension (hazard ratio, 1.73 [95% CI, 1.48–2.02]) were both associated with a significant increased risk for chronic hypertension in offspring. Both risk factors remained significantly associated with increased risk of hypertension in offspring when included together in a multivariate model. Having both exposures was associated with a 2.4-fold increase in the risk of hypertension in offspring, suggesting a synergistic additive interaction. CONCLUSIONS: HDP exposure in gestation and maternal hypertension are both independently associated with an increased risk of chronic hypertension in offspring. Our results suggest that HDP exposure in utero, in addition to maternal chronic hypertension, may lead to a greater risk for the development of hypertension in offspring.