Publications

OBJECTIVE: Renal failure is a predictor of adverse outcomes in carotid revascularization. There has been debate regarding the benefit of revascularization in patients with severe CKD or on dialysis.

METHODS: VQI patients undergoing TCAR, tfCAS, or CEA between 2016 and 2023 with eGFR <30 ml/min/1.73m2 or on dialysis were included. Patients were divided into cohorts based on procedure. Additional analyses were performed for patients on dialysis only and by symptomatology. Primary outcomes were perioperative stroke/death/MI (SDM). Secondary outcomes included perioperative death, stroke, MI, CNI and stroke/death. Inverse probability of treatment weighting (IPW) was performed based on treatment assignment to TCAR, tfCAS, and CEA patients and adjusted for demographics, comorbidities, and pre-op symptoms. Chi-square and multivariable logistic regression analysis were used to evaluate the association of procedure with perioperative outcomes in the weighted cohort. Five-year survival was evaluated using Kaplan-Meier and weighted Cox regression.

RESULTS: In the weighted cohort, 13,851 patients with eGFR of <30 (2,506 on dialysis) underwent TCAR (3,639, dialysis 704), tfCAS (1,975, 393) or CEA (8,237, 1,409) during the study period. Compared with TCAR, CEA had higher odds of stroke/death/MI (2.8% vs 3.6%, aOR 1.27 [1.00,1.61], p=.049), and MI (0.7% vs 1.5%, aOR 2.00 [1.31,3.05], p=.001)... Compared to TCAR, rates of SDM (2.8%vs5.8%), stroke (1.2%vs2.6%), death (0.9%vs2,4%)were all higher for tfCAS. In asymptomatic patients CEA patients had higher odds of MI (0.7% vs 1.3%, aOR 1.85[1.15, 2.97]p=.011) and CNI (0.3% vs 1.9%, aOR 7.23[3.28, 15.9] p<.001). Like the primary analysis, asymptomatic tfCAS patients demonstrated higher odds of death, and stroke/death. Symptomatic CEA patients demonstrated no difference in stroke, death or stroke/death. While tfCAS patients demonstrated higher odds of death, stroke, MI, stroke/death, and SDM. In both groups, 5-year survival was similar for TCAR and CEA (eGFR <30: 75.1% vs 74.2%, aHR1.06, p=.3) and lower for tfCAS (eGFR <30: 75.1% vs 70.4%, aHR1.44, p<.001) CONCLUSION: CEA and TCAR had similar odds of stroke and death and are both a reasonable choice in this population; however, TCAR may be better in patients with increased risk of MI. Additionally, tfCAS patients were more likely to have worse outcomes after weighting for symptom status. Finally, while patients with reduced eGFR have worse outcomes than their healthy peers, this analysis shows that the majority of patients survive long enough to benefit from the potential stroke risk reduction provided by all revascularization procedures.

Despite ample evidence linking social determinants of health (SDoH) and hypertension outcomes, efforts to address SDoH in the context of hypertension prevention and self-management are not commensurate with the burden and impact of hypertension. To provide valuable insights into the development of targeted and effective strategies for preventing and managing hypertension, this systematic review, guided by the Healthy People 2030 SDoH framework, aims to summarize the inclusion, measurement, and evaluation of SDoH in studies examining hypertension outcomes, with a focus on characterizing SDoH constructs and summarizing the current evidence of their influence on hypertension outcomes. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, a comprehensive search of electronic databases identified 10 608 unique records, from which 57 articles meeting inclusion criteria were analyzed. The studies, conducted nationally or regionally across the United States, revealed that higher educational attainment, health insurance coverage, income, and favorable neighborhood characteristics were associated with lower hypertension prevalence and better hypertension control among US adults. The findings underscore the importance of addressing SDoH such as education, health care access, economic stability, neighborhood environments, and social context to reduce hypertension disparities. Multilevel collaboration and community-engaged practices are necessary to tackle these disparities effectively.

INTRODUCTION: Consumer-oriented health information technologies (CHIT) such as the patient portal have a growing role in care delivery redesign initiatives such as the Learning Health System. Care partners commonly navigate CHIT demands alongside persons with complex health and social needs, but their role is not well specified.

METHODS: We assemble evidence and concepts from the literature describing interpersonal communication, relational coordination theory, and systems-thinking to develop an integrative framework describing the care partner's role in applied CHIT innovations. Our framework describes pathways through which systematic engagement of the care partner affects longitudinal work processes and multi-level outcomes relevant to Learning Health Systems.

RESULTS: Our framework is grounded in relational coordination, an emerging theory for understanding the dynamics of coordinating work that emphasizes role-based relationships and communication, and the Systems Engineering Initiative for Patient Safety (SEIPS) model. Cross-cutting work systems geared toward explicit and purposeful support of the care partner role through CHIT may advance work processes by promoting frequent, timely, accurate, problem-solving communication, reinforced by shared goals, shared knowledge, and mutual respect between patients, care partners, and care team. We further contend that systematic engagement of the care partner in longitudinal work processes exerts beneficial effects on care delivery experiences and efficiencies at both individual and organizational levels. We discuss the utility of our framework through the lens of an illustrative case study involving patient portal-mediated pre-visit agenda setting.

CONCLUSIONS: Our framework can be used to guide applied embedded CHIT interventions that support the care partner role and bring value to Learning Health Systems through advancing digital health equity, improving user experiences, and driving efficiencies through improved coordination within complex work systems.

Previous studies suggest a role for inflammation in hepatocarcinogenesis. However, no study has comprehensively evaluated associations between circulating inflammatory proteins and risk of hepatocellular carcinoma (HCC) among the general population. We conducted a nested case-control study in the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS) with 56 pairs of incident HCC cases and controls. External validation was performed in the UK Biobank (34 HCC cases and 48,471 non-HCC controls). Inflammatory protein levels were measured in pre-diagnostic plasma using the Olink® Inflammation Panel. We used conditional logistic regression to calculate multivariable odds ratios (ORs) with 95% confidence intervals (CIs) for associations between a 1-standard deviation (SD) increase in biomarker levels and HCC risk, considering a statistically significant threshold of false discovery rate (FDR)-adjusted p < .05. In the NHS/HPFS, among 70 analyzed proteins with call rates >80%, 15 proteins had significant associations with HCC risk (pFDR < .05). Two proteins (stem cell factor, OR per SD = 0.31, 95% CI = 0.16-0.58; tumor necrosis factor superfamily member 12, OR per SD = 0.51, 95% CI = 0.31-0.85) were inversely associated whereas 13 proteins were positively associated with risk of HCC; positive ORs per SD ranged from 1.73 for interleukin (IL)-10 to 2.35 for C-C motif chemokine-19. A total of 11 proteins were further replicated in the UK Biobank. Seven of the eight selected positively associated proteins also showed positive associations with HCC risk by enzyme-linked immunosorbent assay, with ORs ranging from 1.56 for IL-10 to 2.72 for hepatocyte growth factor. More studies are warranted to further investigate the roles of these observed inflammatory proteins in HCC etiology, early detection, risk stratification, and disease treatment.

OBJECTIVE: This study utilizes the latest data from the Vascular Quality Initiative (VQI), which now encompasses over 50,000 transcarotid artery revascularization (TCAR) procedures, to offer a sizeable dataset for comparing the effectiveness and safety of TCAR, transfemoral carotid artery stenting (tfCAS), and carotid endarterectomy (CEA). Given this substantial dataset, we are now able to compare outcomes overall and stratified by symptom status across revascularization techniques.

METHODS: Utilizing VQI data from September 2016 to August 2023, we conducted a risk-adjusted analysis by applying inverse probability of treatment weighting to compare in-hospital outcomes between TCAR vs tfCAS, CEA vs tfCAS, and TCAR vs CEA. Our primary outcome measure was in-hospital stroke/death. Secondary outcomes included myocardial infarction and cranial nerve injury.

RESULTS: A total of 50,068 patients underwent TCAR, 25,361 patients underwent tfCAS, and 122,737 patients underwent CEA. TCAR patients were older, more likely to have coronary artery disease, chronic kidney disease, and undergo coronary artery bypass grafting/percutaneous coronary intervention as well as prior contralateral CEA/CAS compared with both CEA and tfCAS. TfCAS had higher odds of stroke/death when compared with TCAR (2.9% vs 1.6%; adjusted odds ratio [aOR], 1.84; 95% confidence interval [CI], 1.65-2.06; P < .001) and CEA (2.9% vs 1.3%; aOR, 2.21; 95% CI, 2.01-2.43; P < .001). CEA had slightly lower odds of stroke/death compared with TCAR (1.3% vs 1.6%; aOR, 0.83; 95% CI, 0.76-0.91; P < .001). TfCAS had lower odds of cranial nerve injury compared with TCAR (0.0% vs 0.3%; aOR, 0.00; 95% CI, 0.00-0.00; P < .001) and CEA (0.0% vs 2.3%; aOR, 0.00; 95% CI, 0.0-0.0; P < .001) as well as lower odds of myocardial infarction compared with CEA (0.4% vs 0.6%; aOR, 0.67; 95% CI, 0.54-0.84; P < .001). CEA compared with TCAR had higher odds of myocardial infarction (0.6% vs 0.5%; aOR, 1.31; 95% CI, 1.13-1.54; P < .001) and cranial nerve injury (2.3% vs 0.3%; aOR, 9.42; 95% CI, 7.78-11.4; P < .001).

CONCLUSIONS: Although tfCAS may be beneficial for select patients, the lower stroke/death rates associated with CEA and TCAR are preferred. When deciding between CEA and TCAR, it is important to weigh additional procedural factors and outcomes such as myocardial infarction and cranial nerve injury, particularly when stroke/death rates are similar. Additionally, evaluating subgroups that may benefit from one procedure over another is essential for informed decision-making and enhanced patient care in the treatment of carotid stenosis.

IMPORTANCE: Emergency department (ED) visits by older adults with life-limiting illnesses are a critical opportunity to establish patient care end-of-life preferences, but little is known about the optimal screening criteria for resource-constrained EDs.

OBJECTIVES: To externally validate the Geriatric End-of-Life Screening Tool (GEST) in an independent population and compare it with commonly used serious illness diagnostic criteria.

DESIGN, SETTING, AND PARTICIPANTS: This prognostic study assessed a cohort of patients aged 65 years and older who were treated in a tertiary care ED in Boston, Massachusetts, from 2017 to 2021. Patients arriving in cardiac arrest or who died within 1 day of ED arrival were excluded. Data analysis was performed from August 1, 2023, to March 27, 2024.

EXPOSURE: GEST, a logistic regression algorithm that uses commonly available electronic health record (EHR) datapoints and was developed and validated across 9 EDs, was compared with serious illness diagnoses as documented in the EHR. Serious illnesses included stroke/transient ischemic attack, liver disease, cancer, lung disease, and age greater than 80 years, among others.

MAIN OUTCOMES AND MEASURES: The primary outcome was 6-month mortality following an ED encounter. Statistical analyses included area under the receiver operating characteristic curve, calibration analyses, Kaplan-Meier survival curves, and decision curves.

RESULTS: This external validation included 82 371 ED encounters by 40 505 unique individuals (mean [SD] age, 76.8 [8.4] years; 54.3% women, 13.8% 6-month mortality rate). GEST had an external validation area under the receiver operating characteristic curve of 0.79 (95% CI, 0.78-0.79) that was stable across years and demographic subgroups. Of included encounters, 53.4% had a serious illness, with a sensitivity of 77.4% (95% CI, 76.6%-78.2%) and specificity of 50.5% (95% CI, 50.1%-50.8%). Varying GEST cutoffs from 5% to 30% increased specificity (5%: 49.1% [95% CI, 48.7%-49.5%]; 30%: 92.2% [95% CI, 92.0%-92.4%]) at the cost of sensitivity (5%: 89.3% [95% CI, 88.8-89.9]; 30%: 36.2% [95% CI, 35.3-37.1]). In a decision curve analysis, GEST outperformed serious illness criteria across all tested thresholds. When comparing patients referred to intervention by GEST with serious illness criteria, GEST reclassified 45.1% of patients with serious illness as having low risk of mortality with an observed mortality rate 8.1% and 2.6% of patients without serious illness as having high mortality risk with an observed mortality rate of 34.3% for a total reclassification rate of 25.3%.

CONCLUSIONS AND RELEVANCE: The findings of this study suggest that both serious illness criteria and GEST identified older ED patients at risk for 6-month mortality, but GEST offered more useful screening characteristics. Future trials of serious illness interventions for high mortality risk in older adults may consider transitioning from diagnosis code criteria to GEST, an automatable EHR-based algorithm.

BACKGROUND: International standards used for device validation protocols require that the reference cuff conform to a width and length that is 37 to 50% and 75 to 100% of the arm circumference, respectively. However, there is no published chart of appropriate width and length dimensions across the range of arm circumferences. Our objective was to create a chart that could be used to guide reference cuff selection and compare recommended dimensions with two common cuff systems.

METHODS: Arm circumferences, ranging from 22 to 52 cm were used to create a reference table for width and length requirements. Arm circumferences were grouped following the American Heart Association recommendation for cuff sizes. Cuff dimension data was extracted from the website of a cuff system commonly used for validations (the Baum Corporation) and compared both the American Heart Association recommendations and Baum sizes with the recommended reference dimensions.

RESULTS: There were discrepancies in size naming conventions between the Baum Corporation and the American Heart Association cuff systems. Moreover, there were gaps in both systems where the cuff would not be recommended for validation (31-32 cm for Baum and 30-31 cm for the American Heart Association). Neither system had cuffs that could be used for the largest arm circumferences.

CONCLUSIONS: Our chart highlights the need for more than one cuff system in validation studies and the critical need for cuffs that could be used for validation among larger arm circumferences.

BACKGROUND: Accurate quantification of sodium intake based on self-reported dietary assessments has been a persistent challenge. We aimed to apply machine-learning (ML) algorithms to predict 24-hour urinary sodium excretion from self-reported questionnaire information.

METHODS AND RESULTS: We analyzed 3454 participants from the NHS (Nurses' Health Study), NHS-II (Nurses' Health Study II), and HPFS (Health Professionals Follow-Up Study), with repeated measures of 24-hour urinary sodium excretion over 1 year. We used an ensemble approach to predict averaged 24-hour urinary sodium excretion using 36 characteristics. The TOHP-I (Trial of Hypertension Prevention I) was used for the external validation. The final ML algorithms were applied to 167 920 nonhypertensive adults with 30-year follow-up to estimate confounder-adjusted hazard ratio (HR) of incident hypertension for predicted sodium. Averaged 24-hour urinary sodium excretion was better predicted and calibrated with ML compared with the food frequency questionnaire (Spearman correlation coefficient, 0.51 [95% CI, 0.49-0.54] with ML; 0.19 [95% CI, 0.16-0.23] with the food frequency questionnaire; 0.46 [95% CI, 0.42-0.50] in the TOHP-I). However, the prediction heavily depended on body size, and the prediction of energy-adjusted 24-hour sodium excretion was modestly better using ML. ML-predicted sodium was modestly more strongly associated than food frequency questionnaire-based sodium in the NHS-II (HR comparing Q5 versus Q1, 1.48 [95% CI, 1.40-1.56] with ML; 1.04 [95% CI, 0.99-1.08] with the food frequency questionnaire), but no material differences were observed in the NHS or HPFS.

CONCLUSIONS: The present ML algorithm improved prediction of participants' absolute 24-hour urinary sodium excretion. The present algorithms may be a generalizable approach for predicting absolute sodium intake but do not substantially reduce the bias stemming from measurement error in disease associations.