Predicted Cardiovascular Risk by the PREVENT Equations in US Adults With Stage 1 Hypertension.

BACKGROUND: The 2017 American College of Cardiology/American Heart Association blood pressure guideline recommends initiation of antihypertensive medication for adults with stage 1 hypertension (systolic blood pressure, 130-139 mm Hg, or diastolic blood pressure, 80-89 mm Hg) and 10-year atherosclerotic cardiovascular disease (ASCVD) risk ≥10% estimated by the pooled cohort equations (PCEs). In 2023, the American Heart Association published the predicting risk of cardiovascular disease events (PREVENT) equations to estimate ASCVD and total cardiovascular disease risk. METHODS: We analyzed US National Health and Nutrition Examination Survey data from 2013 to 2020 for 1703 adults aged 30 to 79 years without self-reported cardiovascular disease with stage 1 hypertension. We estimated 10-year ASCVD risk by the PCEs and 10-year ASCVD and total cardiovascular disease risk by the base PREVENT equations. Analyses were weighted to represent noninstitutionalized US adults with stage 1 hypertension. RESULTS: Mean 10-year ASCVD risk was 5.4% (95% CI, 5.0%-5.9%) and 2.9% (95% CI, 2.7%-3.1%) using the PCEs and PREVENT equations, respectively. The proportion with 10-year ASCVD risk of 10% to <15% and ≥15% was 8.1% and 7.8% estimated by the PCEs, respectively, and 3.0% and 0.3% estimated by the PREVENT equations, respectively. No participants had a 10-year ASCVD risk ≥10% on the PREVENT equations and <10% on the PCEs, while 12.5% had a 10-year ASCVD risk ≥10% on the PCEs and <10% on the PREVENT equations. The mean 10-year total cardiovascular disease risk estimated by the PREVENT equations was lower than the mean 10-year ASCVD risk on the PCEs. CONCLUSIONS: Among US adults with stage 1 hypertension, the 10-year predicted ASCVD risk estimated by the PREVENT equations was approximately half the risk estimated by the PCEs.

Feasibility of remote monitoring for fatal coronary heart disease using Apple Watch ECGs.

Background: Fatal coronary heart disease (FCHD) is often described as sudden cardiac death (affects >4 million people/year), where coronary artery disease is the only identified condition. Electrocardiographic artificial intelligence (ECG-AI) models for FCHD risk prediction using ECG data from wearable devices could enable wider screening/monitoring efforts. Objectives: To develop a single-lead ECG-based deep learning model for FCHD risk prediction and assess concordance between clinical and Apple Watch ECGs. Methods: An FCHD single-lead ("lead I" from 12-lead ECGs) ECG-AI model was developed using 167,662 ECGs (50,132 patients) from the University of Tennessee Health Sciences Center. Eighty percent of the data (5-fold cross-validation) was used for training and 20% as a holdout. Cox proportional hazards (CPH) models incorporating ECG-AI predictions with age, sex, and race were also developed. The models were tested on paired clinical single-lead and Apple Watch ECGs from 243 St. Jude Lifetime Cohort Study participants. The correlation and concordance of the predictions were assessed using Pearson correlation (R), Spearman correlation (ρ), and Cohen's kappa. Results: The ECG-AI and CPH models resulted in AUC = 0.76 and 0.79, respectively, on the 20% holdout and AUC = 0.85 and 0.87 on the Atrium Health Wake Forest Baptist external validation data. There was moderate-strong positive correlation between predictions (R = 0.74, ρ = 0.67, and κ = 0.58) when tested on the 243 paired ECGs. The clinical (lead I) and Apple Watch predictions led to the same low/high-risk FCHD classification for 99% of the participants. CPH prediction correlation resulted in an R = 0.81, ρ = 0.76, and κ = 0.78. Conclusion: Risk of FCHD can be predicted from single-lead ECGs obtained from wearable devices and are statistically concordant with lead I of a 12-lead ECG.

Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Five-Year Cumulative Cardiovascular Health and Clinical Events in Patients With Chronic Kidney Disease: The CRIC Study.

BACKGROUND: Higher cardiovascular health (CVH) score is associated with lower risks of cardiovascular disease (CVD) and mortality in the general population. However, it is unclear whether cumulative CVH is associated with CVD, end-stage kidney disease (ESKD), and death in patients with chronic kidney disease. METHODS AND RESULTS: Among individuals from the prospective CRIC (Chronic Renal Insufficiency Cohort) Study, we used the percentage of the maximum possible CVH score attained from baseline to the year 5 visit to calculate cumulative CVH score. Multivariable-adjusted Cox proportional hazards regression was used to investigate the associations of cumulative CVH with risks of adjudicated CVD (myocardial infarction, stroke, and heart failure), ESKD, and all-cause mortality. A total of 3939 participants (mean age, 57.7 years; 54.9% men) were included. The mean (SD) cumulative CVH score attained during 5 years was 55.5% (12.3%). Over a subsequent median 10.2-year follow-up, 597 participants developed CVD, 656 had ESKD, and 1324 died. A higher cumulative CVH score was significantly associated with lower risks of CVD, ESKD, and mortality, independent of the CVH score at year 5. Multivariable-adjusted hazard ratios and 95% CIs per 10% higher cumulative CVH score during 5 years were 0.81 (0.69-0.95) for CVD, 0.82 (0.70-0.97) for ESKD, and 0.80 (0.72-0.89) for mortality. CONCLUSIONS: Among patients with chronic kidney disease stages 2 to 4, a better CVH status maintained throughout 5 years is associated with lower risks of CVD, ESKD, and all-cause mortality. The findings support the need for interventions to maintain ideal CVH status for prevention of adverse outcomes in the population with chronic kidney disease.

Social Determinants of Health and Incident Apparent Treatment-Resistant Hypertension Among White and Black US Adults: The REGARDS Study.

BACKGROUND: We examined the association of multilevel social determinants of health with incident apparent treatment-resistant hypertension (aTRH). METHODS AND RESULTS: We analyzed data from 2774 White and 2257 Black US adults from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study taking antihypertensive medication without aTRH at baseline to estimate the association of social determinants of health with incident aTRH. Selection of social determinants of health was guided by the Healthy People 2030 domains of education, economic stability, social context, neighborhood environment, and health care access. Blood pressure (BP) was measured during study visits, and antihypertensive medication classes were identified through a pill bottle review. Incident aTRH was defined as (1) systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg, or systolic BP ≥130 mm Hg or diastolic BP ≥80 mm Hg for those with diabetes or chronic kidney disease while taking ≥3 classes of antihypertensive medication or (2) taking ≥4 classes of antihypertensive medication regardless of BP level, at the follow-up visit. Over a median 9.5 years of follow-up, 15.9% of White and 24.0% of Black adults developed aTRH. A percent of the excess aTRH risk among Black versus White adults was mediated by low education (14.2%), low income (16.0%), not seeing a friend or relative in the past month (8.1%), not having someone to care for them if ill or disabled (7.6%), lack of health insurance (10.6%), living in a disadvantaged neighborhood (18.0%), and living in states with poor public health infrastructure (6.0%). CONCLUSIONS: Part of the association between race and incident aTRH risk was mediated by social determinants of health.

MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric.

Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.

Race differences in ambulatory blood pressure monitoring parameters.

BACKGROUND: Mean systolic and diastolic blood pressure (SBP and DBP) on ambulatory blood pressure (BP) monitoring (ABPM) are higher among Black compared with White adults. With 48 to 72 BP measurements obtained over 24 h, ABPM can generate parameters other than mean BP that are associated with increased risk for cardiovascular events. There are few data on race differences in ABPM parameters other than mean BP. METHODS: To estimate differences between White and Black participants in ABPM parameters, we used pooled data from five US-based studies in which participants completed ABPM (n = 2580). We calculated measures of SBP and DBP level, including mean, load, peak, and measures of SBP and DBP variability, including average real variability (ARV) and peak increase. RESULTS: There were 1513 (58.6%) Black and 1067 (41.4%) White participants with mean ages of 56.1 and 49.0 years, respectively. After multivariable adjustment, asleep SBP and DBP load were 5.7% (95% CI: 3.5-7.9%) and 2.7% (95% CI: 1.1-4.3%) higher, respectively, among Black compared with White participants. Black compared with White participants also had higher awake DBP ARV (0.3 [95%CI: 0.0-0.6] mmHg) and peak increase in DBP (0.4 [95% CI: 0.0-0.8] mmHg). There was no evidence of Black:White differences in awake measures of SBP level, asleep peak SBP or DBP, awake and asleep measures of SBP variability or asleep measures of DBP variability after multivariable adjustment. CONCLUSION: Asleep SBP load, awake DBP ARV and peak increase in awake DBP were higher in Black compared to White participants, independent of mean BP on ABPM.

Outcomes of SARS-CoV-2 infection among patients with orthopaedic fracture surgery in the National COVID Cohort Collaborative (N3C).

BACKGROUND: The objective of this study was to investigate the outcomes of COVID-19-positive patients undergoing orthopaedic fracture surgery using data from a national database of U.S. adults with a COVID-19 test for SARS-CoV-2. METHODS: This is a retrospective cohort study using data from a national database to compare orthopaedic fracture surgery outcomes between COVID-19-positive and COVID-19-negative patients in the United States. Participants aged 18-99 with orthopaedic fracture surgery between March and December 2020 were included. The main exposure was COVID-19 status. Outcomes included perioperative complications, 30-day all-cause mortality, and overall all-cause mortality. Multivariable adjusted models were fitted to determine the association of COVID-positivity with all-cause mortality. RESULTS: The total population of 6.5 million patient records was queried, identifying 76,697 participants with a fracture. There were 7,628 participants in the National COVID Cohort who had a fracture and operative management. The Charlson Comorbidity Index was higher in the COVID-19-positive group (n = 476, 6.2 %) than the COVID-19-negative group (n = 7,152, 93.8 %) (2.2 vs 1.4, p<0.001). The COVID-19-positive group had higher mortality (13.2 % vs 5.2 %, p<0.001) than the COVID-19-negative group with higher odds of death in the fully adjusted model (Odds Ratio=1.59; 95 % Confidence Interval: 1.16-2.18). CONCLUSION: COVID-19-positive participants with a fracture requiring surgery had higher mortality and perioperative complications than COVID-19-negative patients in this national cohort of U.S. adults tested for COVID-19. The risks associated with COVID-19 can guide potential treatment options and counseling of patients and their families. Future studies can be conducted as data accumulates. LEVEL OF EVIDENCE: Level III.

Risk factors for 1-year allograft loss in pediatric heart transplant patients using machine learning: An analysis of the pediatric heart transplant society database.

BACKGROUND: Pediatric heart transplant patients are at greatest risk of allograft loss in the first year. We assessed whether machine learning could improve 1-year risk assessment using the Pediatric Heart Transplant Society database. METHODS: Patients transplanted from 2010 to 2019 were included. The primary outcome was 1-year graft loss free survival. We developed a prediction model using cross-validation, by comparing Cox regression, gradient boosting, and random forests. The modeling strategy with the best discrimination and calibration was applied to fit a final prediction model. We used Shapley additive explanation (SHAP) values to perform variable selection and to estimate effect sizes and importance of individual variables when interpreting the final prediction model. RESULTS: Cumulative incidence of graft loss or mortality was 7.6%. Random forests had favorable discrimination and calibration compared to Cox proportional hazards with a C-statistic (95% confidence interval [CI]) of 0.74 (0.72, 0.76) versus 0.71 (0.69, 0.73), and closer alignment between predicted and observed risk. SHAP values computed using the final prediction model indicated that the diagnosis of congenital heart disease (CHD) increased 1 year predicted risk of graft loss by 1.7 (i.e., from 7.6% to 9.3%), need for mechanical circulatory support increased predicted risk by 2, and single ventricle CHD increased predicted risk by 1.9. These three predictors, respectively, were also estimated to be the most important among the 15 predictors in the final model. CONCLUSIONS: Risk prediction models used to facilitate patient selection for pediatric heart transplant can be improved without loss of interpretability using machine learning.

Social Determinants of Health and Uncontrolled Blood Pressure in a National Cohort of Black and White US Adults: the REGARDS Study.

BACKGROUND: Determining the contribution of social determinants of health (SDOH) to the higher proportion of Black adults with uncontrolled blood pressure (BP) could inform interventions to improve BP control and reduce cardiovascular disease. METHODS: We analyzed data from 7306 White and 7497 Black US adults taking antihypertensive medication from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study (2003-2007). SDOH were defined using the Healthy People 2030 domains of education, economic stability, social context, neighborhood environment, and health care access. Uncontrolled BP was defined as systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg. RESULTS: Among participants taking antihypertensive medication, 25.4% of White and 33.7% of Black participants had uncontrolled BP. The SDOH included in the current analysis mediated the Black-White difference in uncontrolled BP by 33.0% (95% CI, 22.1%-46.8%). SDOH that contributed to excess uncontrolled BP among Black compared with White adults included low annual household income (percent-mediated 15.8% [95% CI, 10.8%-22.8%]), low education (10.5% [5.6%-15.4%]), living in a health professional shortage area (10.4% [6.5%-14.7%]), disadvantaged neighborhood (11.0% [4.4%-18.0%]), and high-poverty zip code (9.7% [3.8%-15.5%]). Together, the neighborhood-domain accounted for 14.1% (95% CI, 5.9%-22.9%), the health care domain accounted for 12.7% (95% CI, 8.4%-17.3%), and the social-context-domain accounted for 3.8% (95% CI, 1.2%-6.6%) of the excess likelihood of uncontrolled BP among Black compared with White adults, respectively. CONCLUSIONS: SDOH including low education, low income, living in a health professional shortage area, disadvantaged neighborhood, and high-poverty zip code contributed to the excess likelihood of uncontrolled BP among Black compared with White adults.

Hypertension Statistics for US Adults: An Open-Source Web Application for Analysis and Visualization of National Health and Nutrition Examination Survey Data.

BACKGROUND: Data from the US National Health and Nutrition Examination Survey are freely available and can be analyzed to produce hypertension statistics for the noninstitutionalized US population. The analysis of these data requires statistical programming expertise and knowledge of National Health and Nutrition Examination Survey methodology. METHODS: We developed a web-based application that provides hypertension statistics for US adults using 10 cycles of National Health and Nutrition Examination Survey data, 1999 to 2000 through 2017 to 2020. We validated the application by reproducing results from prior publications. The application's interface allows users to estimate crude and age-adjusted means, quantiles, and proportions. Population counts can also be estimated. To demonstrate the application's capabilities, we estimated hypertension statistics for noninstitutionalized US adults. RESULTS: The estimated mean systolic blood pressure (BP) declined from 123 mm Hg in 1999 to 2000 to 120 mm Hg in 2009 to 2010 and increased to 123 mm Hg in 2017 to 2020. The age-adjusted prevalence of hypertension (ie, systolic BP≥130 mm Hg, diastolic BP≥80 mm Hg or self-reported antihypertensive medication use) was 47.9% in 1999 to 2000, 43.0% in 2009 to 2010, and 44.7% in 2017 to 2020. In 2017 to 2020, an estimated 115.3 million US adults had hypertension. The age-adjusted prevalence of controlled BP, defined by the 2017 American College of Cardiology/American Heart Association BP guideline, among nonpregnant US adults with hypertension was 9.7% in 1999 to 2000, 25.0% in 2013 to 2014, and 21.9% in 2017 to 2020. After age adjustment and among nonpregnant US adults who self-reported taking antihypertensive medication, 27.5%, 48.5%, and 43.0% had controlled BP in 1999 to 2000, 2013 to 2014, and 2017 to 2020, respectively. CONCLUSIONS: The application developed in the current study is publicly available at https://bcjaeger.shinyapps.io/nhanesShinyBP/ and produced valid, transparent and reproducible results.

Analysis of Cardiorespiratory Fitness in Early Adulthood and Midlife With All-Cause Mortality and Fatal or Nonfatal Cardiovascular Disease.

Importance: Optimizing cardiovascular fitness is a prevention strategy against premature death and cardiovascular disease (CVD) events. Since this evidence has largely been established in older populations, the importance of cardiorespiratory fitness during earlier periods of adulthood remains unclear. Objective: To examine the association of early-adulthood cardiorespiratory fitness and percentage of early-adulthood cardiorespiratory fitness retained during midlife with subsequent risk of all-cause mortality and CVD-related morbidity and mortality overall as well as by sex and race. Design, Setting, and Participants: This retrospective population-based cohort study analyzed data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, an ongoing prospective cohort study conducted at field center clinics in Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and Oakland, California. Participants in the CARDIA study were aged 18 to 30 years when they completed the baseline graded exercise test protocol in 1985 to 1986 and have since undergone follow-up examinations biannually and every 2 to 5 years. Data were collected through August 31, 2020, and were analyzed in October 2022. Exposures: Cardiorespiratory fitness was estimated from a symptom-limited, maximal graded exercise test protocol conducted at baseline and at year 7 and year 20 follow-up examinations. Main Outcomes and Measures: All-cause mortality and combined fatal and nonfatal CVD events were obtained since year 20 of follow-up examinations through August 31, 2020. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) for each primary exposure with each outcome. Results: A total of 4808 participants (mean [SD] age at baseline, 24.8 [3.7] years; 2670 females [56%]; 2438 Black individuals [51%]) were included in the sample. During 68 751 person-years of follow-up, there were 302 deaths (6.3%) and 274 CVD events (5.7%) since year 20. Every 1-minute increment in cardiorespiratory fitness at baseline was associated with a lower risk of all-cause mortality in females (HR, 0.73; 95% CI, 0.64-0.82) and males (HR, 0.87; 95% CI, 0.80-0.96). Every 5% increment in cardiorespiratory fitness retained through year 20 was associated with a lower risk of all-cause mortality (HR, 0.89; 95% CI, 0.79-0.99), but no evidence of effect modification by race or sex was found. Every 1-minute increment in cardiorespiratory fitness at baseline was associated with a lower risk of fatal or nonfatal CVD (HR, 0.89; 95% CI, 0.82-0.96), and the estimated HR per 5% increment in cardiorespiratory fitness retained throughout midlife was 0.89 (95% CI, 0.78-1.00), with no evidence for interaction by race or sex. Conclusions and Relevance: This cohort study found that higher early-adulthood cardiorespiratory fitness and greater retention of early-adulthood cardiorespiratory fitness throughout midlife were associated with a lower risk of premature death and CVD events. Additional research is needed to clarify the association of cardiorespiratory fitness timing across the life course with risk of clinical outcomes.

Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1% to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8% to 5.1% (SBP) and 4.7% to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs.

Longer-Term All-Cause and Cardiovascular Mortality With Intensive Blood Pressure Control: A Secondary Analysis of a Randomized Clinical Trial.

Importance: The Systolic Blood Pressure Intervention Trial (SPRINT) showed that intensive blood pressure control reduced cardiovascular morbidity and mortality. However, the legacy effect of intensive treatment is unknown. Objective: To evaluate the long-term effects of randomization to intensive treatment with the incidence of cardiovascular and all-cause mortality approximately 4.5 years after the trial ended. Design, Setting, and Participants: In this secondary analysis of a multicenter randomized clinical trial, randomization began on November 8, 2010, the trial intervention ended on August 20, 2015, and trial close-out visits occurred through July 2016. Patients 50 years and older with hypertension and increased cardiovascular risk but without diabetes or history of stroke were included from 102 clinic sites in the US and Puerto Rico. Analyses were conducted between October 2021 and February 2022. Interventions: Randomization to systolic blood pressure (SBP) goal of less than 120 mm Hg (intensive treatment group; n = 4678) vs less than 140 mm Hg (standard treatment group; n = 4683). Main Outcomes and Measures: Extended observational follow-up for mortality via the US National Death Index from 2016 through 2020. In a subset of 2944 trial participants, outpatient SBP from electronic health records during and after the trial were examined. Results: Among 9361 randomized participants, the mean (SD) age was 67.9 (9.4) years, and 3332 (35.6%) were women. Over a median (IQR) intervention period of 3.3 (2.9-3.9) years, intensive treatment was beneficial for both cardiovascular mortality (hazard ratio [HR], 0.66; 95% CI, 0.49-0.89) and all-cause mortality (HR, 0.83; 95% CI, 0.68-1.01). However, at the median (IQR) total follow-up of 8.8 (8.3-9.3) years, there was no longer evidence of benefit for cardiovascular mortality (HR, 1.02; 95% CI, 0.84-1.24) or all-cause mortality (HR, 1.08; 95% CI, 0.94-1.23). In a subgroup of participants, the estimated mean outpatient SBP among participants randomized to intensive treatment increased from 132.8 mm Hg (95% CI, 132.0-133.7) at 5 years to 140.4 mm Hg (95% CI, 137.8-143.0) at 10 years following randomization. Conclusions and Relevance: The beneficial effect of intensive treatment on cardiovascular and all-cause mortality did not persist after the trial. Given increasing outpatient SBP levels in participants randomized to intensive treatment following the trial, these results highlight the importance of consistent long-term management of hypertension. Trial Registration: ClinicalTrials.gov Identifier: NCT01206062.

Prolonged hospital length of stay after pediatric heart transplantation: A machine learning and logistic regression predictive model from the Pediatric Heart Transplant Society.

BACKGROUND: Heart transplantation (HT) is the gold standard for managing end-stage heart failure. Multiple quality metrics, including length of stay (LOS), have been used in solid organ transplantation. However, limited data are available regarding trends and factors influencing LOS after pediatric HT. We hypothesized that various donor, peri-transplant and recipient factors affect LOS after pediatric HT. METHODS: We analyzed patients <18years at time of HT from January 2005 to December 2018 in the Pediatric Heart Transplant Society database, and examined LOS trends, defined prolonged LOS (PLOS = LOS>30days after HT), identified factors associated with PLOS and assessed outcomes. RESULTS: Of 4827 patients undergoing HT, 4414 patients were discharged and included for analysis. Overall median LOS was 19days[13,34]. Median LOS was longer in patients with congenital heart disease(CHD = 25days[15,43] than with cardiomyopathy(CM = 17days[12,27] across all ages. Median LOS in age <1year was 26-days[16,45.5] and in age >10year was 16days[11,26]. PLOS was seen in 1313 patients(30%). Patients with PLOS were younger, smaller and had longer CPB times. There was no difference in utilization of VAD at HT between groups, however, ECMO use at listing(8.45% vs 2.93%,p < 0.05) and HT was higher in the PLOS group(9.22% vs 1.58%,p < 0.05). PLOS was more common in patients with previous surgery, CHD, single ventricle physiology, recipient history of cardiac arrest or CPR, end organ dysfunction, lower GFR, use of mechanical ventilation at HT and Status 1A at HT. CONCLUSION: We present novel findings of LOS distribution and define PLOS after pediatric HT, providing a quality metric for individual programs to utilize and study in their practice.

Prevalence, risk factors, and cardiovascular disease outcomes associated with persistent blood pressure control: The Jackson Heart Study.

BACKGROUND: Maintaining blood pressure (BP) control over time may contribute to lower risk for cardiovascular disease (CVD) among individuals who are taking antihypertensive medication. METHODS: The Jackson Heart Study (JHS) enrolled 5,306 African-American adults ≥21 years of age and was used to determine the proportion of African Americans that maintain persistent BP control, identify factors associated with persistent BP control, and determine the association of persistent BP control with CVD events. This analysis included 1,604 participants who were taking antihypertensive medication at Visit 1 and had BP data at Visits 1 (2000-2004), 2 (2005-2008), and 3 (2009-2013). Persistent BP control was defined as systolic BP <140 mm Hg and diastolic BP <90 mm Hg at all three visits. CVD events were assessed from Visit 3 through December 31, 2016. Hazard ratios (HR) for the association of persistent BP control with CVD outcomes were adjusted for age, sex, systolic BP, smoking, diabetes, and total and high-density lipoprotein cholesterol at Visit 3. RESULTS: At Visit 1, 1,226 of 1,604 participants (76.4%) with hypertension had controlled BP. Overall, 48.9% of participants taking antihypertensive medication at Visit 1 had persistent BP control. After multivariable adjustment for demographic, socioeconomic, clinical, behavioral, and psychosocial factors, and access-to-care, participants were more likely to have persistent BP control if they were <65 years of age, women, had family income ≥$25,000 at each visit, and visited a health professional in the year prior to each visit. The multivariable adjusted HR (95% confidence interval) comparing participants with versus without persistent BP control was 0.71 (0.46-1.10) for CVD, 0.68 (0.34-1.34) for coronary heart disease, 0.65 (0.27-1.52) for stroke, and 0.55 (0.33-0.90) for heart failure. CONCLUSION: Less than half of JHS participants taking antihypertensive medication had persistent BP control, putting them at increased risk for heart failure.

Inflammation biomarkers and incident coronary heart disease: the Reasons for Geographic And Racial Differences in Stroke Study.

BACKGROUND: Individual inflammation biomarkers are associated with incident coronary heart disease (CHD) events. However, there is limited research on whether the risk for incident CHD is progressively higher with a higher number of inflammation biomarkers in abnormal levels. METHODS: We used data from 15,758 Reasons for Geographic and Racial Differences in Stroke (REGARDS) study participants aged ≥45 years without a history of CHD at baseline in 2003-2007. Abnormal levels of baseline high-sensitivity C-reactive protein, leukocyte count and serum albumin were defined as ≥3.8 mg/L (3rd tertile), ≥6.3 x 109 cells/L (3rd tertile), and <4.0 g/dL (1st tertile), respectively. The outcome was a composite of incident myocardial infarction or CHD death. RESULTS: Overall, 38.9% (n = 6,123) had 0, 36.6% (n = 5,774) had 1, 19.8% (n = 3,113) had 2 and 4.7% (n = 748) had 3 biomarkers of inflammation in abnormal levels. Over a median follow-up of 11.4 years, 954 (6.1%) participants had incident CHD. The rate of incident CHD per 1000 person-years for individuals with 0, 1, 2, and 3 biomarkers of inflammation in abnormal levels was 4.4 (95% confidence interval [CI]: 3.9-5.0), 6.3 (95% CI: 5.6-6.9), 8.8 (95% CI: 7.8-9.9), and 10.6 (95% CI: 8.1-13.1), respectively. Multi-variable adjusted hazard ratios for incident CHD associated with 1, 2 and 3 versus no inflammation biomarker in abnormal levels were 1.26 (95% CI: 1.07-1.49), 1.72 (95% CI: 1.43-2.07), and 1.84 (95% CI: 1.37-2.47), respectively (P-trend < .001). CONCLUSIONS: The number of inflammation markers in abnormal levels was associated with increased risk of incident CHD after multi-variable adjustment.

Spike-and-slab least absolute shrinkage and selection operator generalized additive models and scalable algorithms for high-dimensional data analysis.

There are proposals that extend the classical generalized additive models (GAMs) to accommodate high-dimensional data ( p ≫ n $$ p\gg n $$ ) using group sparse regularization. However, the sparse regularization may induce excess shrinkage when estimating smooth functions, damaging predictive performance. Moreover, most of these GAMs consider an "all-in-all-out" approach for functional selection, rendering them difficult to answer if nonlinear effects are necessary. While some Bayesian models can address these shortcomings, using Markov chain Monte Carlo algorithms for model fitting creates a new challenge, scalability. Hence, we propose Bayesian hierarchical generalized additive models as a solution: we consider the smoothing penalty for proper shrinkage of curve interpolation via reparameterization. A novel two-part spike-and-slab LASSO prior for smooth functions is developed to address the sparsity of signals while providing extra flexibility to select the linear or nonlinear components of smooth functions. A scalable and deterministic algorithm, EM-Coordinate Descent, is implemented in an open-source R package BHAM. Simulation studies and metabolomics data analyses demonstrate improved predictive and computational performance against state-of-the-art models. Functional selection performance suggests trade-offs exist regarding the effect hierarchy assumption.

Evaluating novel approaches for estimating awake and sleep blood pressure: design of the Better BP Study - a randomised, crossover trial.

INTRODUCTION: For many people, blood pressure (BP) levels differ when measured in a medical office versus outside of the office setting. Out-of-office BP has a stronger association with cardiovascular disease (CVD) events compared with BP measured in the office. Many BP guidelines recommend measuring BP outside of the office to confirm the levels obtained in the office. Ambulatory BP monitoring (ABPM) can assess out-of-office BP but is not available in many US practices and some individuals find it uncomfortable. The aims of the Better BP Study are to (1) test if unattended office BP is closer to awake BP on ABPM compared with attended office BP, (2) assess if sleep BP assessed by home BP monitoring (HBPM) agrees with sleep BP from a full night of ABPM and (3) compare the strengths of associations of unattended versus attended office BP, unattended office BP versus awake BP on ABPM and sleep BP on HBPM versus ABPM with markers of end-organ damage. METHODS AND ANALYSIS: We are recruiting 630 adults not taking antihypertensive medication in Birmingham, Alabama, and New York, New York. Participants are having their office BP measured with (attended) and without (unattended) a technician present, in random order, using an automated oscillometric office BP device during each of two visits within one week. Following these visits, participants complete 24 hours of ABPM and one night of HBPM, in random order. Psychosocial factors, anthropometrics, left ventricular mass index and albumin-to-creatinine ratio are also being assessed. ETHICS AND DISSEMINATION: This study was approved by the University of Alabama at Birmingham and the Columbia University Medical Center Institutional Review Boards. The study results will be disseminated at scientific conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04307004.

Factors Associated with Age-Related Declines in Cardiorespiratory Fitness from Early Adulthood Through Midlife: CARDIA.

PURPOSE: This study aimed to describe maximal and submaximal cardiorespiratory fitness from early adulthood to midlife and examine differences in maximal fitness at age 20 yr and changes in fitness overtime by subcategories of sociodemographic, behavioral, and health-related factors. METHODS: Data include 5018 Coronary Artery Risk Development in Young Adults participants (mean (SD) age, 24.8 (3.7) yr; 53.3% female; and 51.4% Black participants) who completed at least one maximal graded exercise test at baseline and/or the year 7 and 20 exams. Maximal and submaximal fitness were estimated by exercise duration and heart rate at the end of stage 2. Multivariable adjusted linear-mixed models were used to estimate fitness trajectories using age as the mechanism for time after adjustment for covariates. Fitness trajectories from ages 20 to 50 yr in 5-yr increments were estimated overall and by subgroups determined by each factor after adjustment for duration within the less favorable category. RESULTS: Mean (95% confidence interval) maximal fitness at age 20 and 50 yr was 613 (607-616) and 357 (350-362) s; submaximal heart rate during this period also reflected age-related fitness declines (126 (125-127) and 138 (137-138) bpm). Compared with men, women had lower maximal fitness at age 20 yr (P < 0.001), which persisted over follow-up (P < 0.001); differences were also found by race within sex strata (all P < 0.001). Differences in maximal fitness at age 20 yr were noted by socioeconomic, behavioral, and health-related status in young adulthood (all P < 0.05), which persisted over follow-up (all P < 0.001) and were generally consistent in sex-stratified analyses. CONCLUSIONS: Targeting individuals experiencing accelerated fitness declines with tailored intervention strategies may provide an opportunity to preserve fitness throughout midlife to reduce lifetime cardiovascular disease risk.