Abstract
BACKGROUND
Nighttime blood pressure (BP) has greater prognostic importance for cardiovascular disease (CVD) than daytime BP, but less is known about nighttime and daytime BP associations with measures of subclinical CVD.
METHODS
Among 897 Systolic Blood Pressure Intervention Trial Study (SPRINT) participants with 24-hour ambulatory BP monitoring obtained near the 27-month study visit, 849 (95%) had N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) measured at the 24-month study visit. Multivariable linear regression analyses were performed to evaluate the associations of nighttime and daytime BP with cardiac biomarker levels.
RESULTS
The mean age was 69 ± 12 years, 28% were African American, and mean nighttime and daytime SBP were 121 ± 16 mm Hg and 132 ± 14 mm Hg, respectively. In multivariable models, compared with the lowest tertile of nighttime systolic BP, the highest tertile was associated with 48% higher NT-proBNP levels (adjusted geometric mean ratio [GMR] = 1.48, 95% CI: 1.22, 1.79), and 19% higher hs-cTnT levels (adjusted GMR = 1.19, 95% CI: 1.07, 1.32). In contrast, the highest vs. lowest tertile of daytime systolic BP was not associated with NT-proBNP (adjusted GMR = 1.09, 95% CI: 0.88, 1.34), but was associated with 16% higher hs-cTnT levels (adjusted GMR = 1.16, 95% CI: 1.04, 1.30). Similar results were observed using diastolic BP.
CONCLUSIONS
In SPRINT, both higher nighttime and daytime BP were independently associated with higher hs-cTnT levels, but only higher nighttime BP was associated with higher NT-proBNP levels.
Keywords: ambulatory blood pressure, blood pressure, hypertension, natriuretic peptide, nocturnal hypertension, SPRINT, troponin
Graphical abstract
Elevated nighttime blood pressure (BP) levels are common and have stronger associations with cardiovascular disease (CVD) outcomes compared with daytime BP.1–5 However, the mechanisms accounting for these differences in outcome associations have not been fully characterized. Utilizing intermediate markers of CVD risk may improve our understanding of the prognostic differences between nighttime and daytime BP. Low, detectable levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP), a marker of cardiac wall stress, and high-sensitivity cardiac troponin T (hs-cTnT), a marker of myocardial cell injury, are prevalent in the ambulatory setting and are strongly associated with CVD risk and mortality.6–11 Higher BP in the clinic and ambulatory settings are associated with higher NT-proBNP and hs-cTnT levels, but few studies have evaluated differences in nighttime and daytime BP associations with cardiac biomarker levels.4,12–19
In this ancillary analysis of the Systolic Blood Pressure Intervention Trial (SPRINT), we characterized the associations of nighttime BP, daytime BP, and dipping status obtained from ambulatory BP measures with NT-proBNP and hs-cTnT. We hypothesized that higher nighttime BP and night/day BP ratios would be independently associated with higher NT-proBNP and hs-cTnT levels.
METHODS
Study design
The design and protocol of SPRINT has been reported previously.20 In brief, SPRINT was a National Institutes of Health-funded, open-label randomized clinical trial that enrolled 9,361 participants with hypertension between November 2010 and March 2013. Participants were randomized to an “intensive” systolic BP (SBP) target of <120 mm Hg vs. a “standard” SBP target of <140 mm Hg based on in-clinic SBP measurements. Inclusion criteria were 50 years of age or older, SBP of 130–180 mm Hg, and increased CVD risk (defined as prior clinical or subclinical CVD other than stroke, chronic kidney disease, estimated glomerular filtration rate [eGFR] 20–59 ml/min per 1.73 m2, estimated 10-year risk for coronary heart disease of 15% or more based on the Framingham Risk Score, and/or 75 years of age or older). Key exclusion criteria included diabetes, previous stroke or transient ischemic attack, eGFR <20 ml/min per 1.73 m2, symptomatic heart failure, and left ventricular (LV) ejection fraction <35%. The trial was stopped early on the recommendation of the Data and Safety Monitoring Board due to interim CVD results that favored the intensive arm. The SPRINT study was approved by the Institutional Review Board at each participating study site, and all participants provided written informed consent.
The present study was an ancillary analysis of SPRINT participants who consented to and underwent ambulatory blood pressure monitoring (ABPM) within 3 weeks of the 27-month study visit.21 Consecutive SPRINT participants were recruited from 15 clinical sites to participate in the ABPM study. Exclusion criteria were: arm circumference >50 cm, shift worker or work regularly scheduled at night, history of breast cancer requiring mastectomy or radiation on the nondominant arm (to avoid frequent BP measurements in patients with lymphedema), and end‐stage kidney disease. Each site’s institutional review board approved the ABPM ancillary study. Among the 897 participants who underwent ABPM, we excluded 48 (5.4%) who did not have cardiac biomarker measurements available from the 24-month study visit. The UT Southwestern and UT Tyler Institutional Review Board determined that the present analysis is exempt in accordance with 45 CFR 46.101(b). The data that support the findings of this study are available from the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repositories and the corresponding author upon request.
Laboratory assays
Blood specimens collected at the 24-month visit were immediately frozen at −80 °C and stored at the SPRINT Central Laboratory at the University of Minnesota. Both NT-proBNP and hs-cTnT were measured from freshly thawed serum samples using an electrochemiluminescence immunoassay on the Roche COBAS 6000 platform (Roche Diagnostics) and utilized single lots of calibrators to avoid lot-to-lot variation in analytical reagents.17 The NT-proBNP assay has a lower limit of detection of 5 pg/ml and an inter-assay coefficient of variation of 2.9% at 140.3 pg/ml and 2.7% at 4,563 pg/ml. The hs-cTnT assay (5th Generation) has a lower limit of quantitation of 6 ng/l and an inter-assay coefficient of variation of 3.4% at 28.3 ng/l and 2.3% at 2,076 ng/l. We replaced undetectable hs-cTnT levels (14.9% <6 ng/l) and NT-proBNP levels (3.3% <5 pg/ml) as the lower limit of detection divided by two.
Ambulatory BP measurements
Ambulatory BP was obtained within 3 weeks of the 27-month study visit by SpaceLabs Medical Model 90207 monitors using 24-hour protocols from the British Hypertension Society.21 The monitor was attached to the participant’s non-dominant arm and measured blood pressure every 30 minutes with the display turned off. A valid recording required a minimum of 14 readings from 6:00 AM to midnight and at least six readings from midnight to 6:00 AM.21 Consistent with previous work in SPRINT, daytime BP was defined as the average of all BP readings from 9 AM to 9 PM, nighttime BP was defined as the average of all BP readings from 1 AM to 6 AM, and the night/day ratio of average SBP was used to categorize dipping status as extreme dipper (<0.8), dipper (≥0.8 and ≤0.9), non-dipper (>0.9 and ≤1), and reverse dipper (>1).21
Covariates
Questionnaires were used to obtain age, sex, race, ethnicity, medical history, medications, and smoking status (current, former, or never). Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Fasting serum low-density lipoprotein (LDL) cholesterol and serum creatinine were measured at the SPRINT Central Laboratory. Estimated GFR was calculated using the 4-variable Modification of Diet in Renal Disease (MDRD) equation.22 Adjustment variables for this analysis were taken at the 24-month or 27-month study visits.
Statistical analysis
Multivariable linear regression analyses were conducted to evaluate ambulatory BP associations with NT-proBNP and hs-cTnT levels. BP measures were modeled as continuous variables or categorized into tertiles, and each biomarker was modeled as a continuous variable on the log scale. Geometric mean ratios (GMRs) and 95% confidence intervals were estimated. The ratio of geometric means of log-transformed biomarker levels can be interpreted as a percentage difference in the means of the biomarker levels. Multivariable models adjusted for age, sex, race, randomization arm, smoking status, BMI, eGFR, LDL cholesterol level, history of CVD, and morning and evening dosing of BP medication. Underlying assumptions including normality and linearity were checked. We also evaluated whether the associations of BP measures with cardiac biomarker levels varied by race and randomization arm in multivariable-adjusted models using likelihood ratio tests. All analyses were conducted using SAS software, version 9.4 (SAS Institute, Inc, Cary, NC).
Results
Study population
Among the 849 SPRINT participants who underwent ABPM and had available NT-proBNP and hs-cTnT measurements, the mean age was 69 ± 12 years, 28% were African American, and 28% were female. Mean daytime and nighttime SBP were 132 ± 14 mm Hg and 121 ± 16 mm Hg, respectively. Compared with participants in the lowest tertile of nighttime SBP, those in the highest tertile were older, more were female, randomized to the standard arm, and had higher BMI and daytime SBP (Table 1).
Table 1.
Characteristics of SPRINT participants with ABPM stratified by tertile of nighttime SBP
| Characteristics | Nighttime SBP tertiles | ||
|---|---|---|---|
| Tertile 1 (N = 281) Median: 106 mm Hg |
Tertile 2 (N = 285) Median: 119 mm Hg |
Tertile 3 (N = 283) Median: 135 mm Hg |
|
| Intensive arm | 200 (71%) | 140 (49%) | 97 (34%) |
| Age, yearsa | 70 (9) | 71 (10) | 72 (10) |
| Female | 69 (25%) | 74 (26%) | 96 (34%) |
| African American | 76 (27%) | 72 (25%) | 91 (32%) |
| BMI, kg/m2a | 30 (5) | 30 (5) | 29 (6) |
| History of CVD | 53 (19%) | 56 (20%) | 74 (26%) |
| Current smokera | 25 (9%) | 20 (7%) | 24 (9%) |
| LDL-C, mg/dla | 107 (33) | 106 (35) | 103 (34) |
| Morning dose of BP medicationb,c | 208 (74%) | 191 (67%) | 188 (66%) |
| Evening dose of BP medicationb,d | 106 (38%) | 97 (34%) | 96 (34%) |
| Clinic SBP, mm Hgb | 121 (13) | 127 (14) | 134 (17) |
| Clinic DBP, mm Hgb | 68 (10) | 70 (11) | 71 (14) |
| eGFR, mL/min/1.73 m2a | 70 (20) | 70 (23) | 70 (20) |
| NT-proBNP, pg/mla | 73 (31, 145) | 87 (37, 218) | 134 (51, 290) |
| NT-proBNP > 125 pg/ml | 90 (32%) | 120 (42%) | 145 (51%) |
| hs-cTnT, ng/la | 9 (6, 15) | 10 (6, 15) | 12 (7, 18) |
| hs-cTnT > 14 ng/l | 72 (26%) | 77 (27%) | 98 (35%) |
Data displayed as N (%), mean (standard deviation), and median (interquartile range).
Abbreviations: BMI, body mass index; BP, blood pressure; CVD, cardiovascular disease; DBP, diastolic blood pressure; eGFR estimated glomerular filtration rate; hs-cTnT, high-sensitivity cardiac troponin T; LDL-C, low-density lipoprotein cholesterol; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SBP, systolic blood pressure; SPRINT, Systolic Blood Pressure Intervention Trial.
aCharacteristics collected at the 24-month SPRINT visit.
bCharacteristics collected at the 27-month SPRINT visit.
cMorning dose of antihypertensive medication was from 4 am to 10 am.
dEvening dose of antihypertensive medication was from 6 pm to 2 am.
Ambulatory BP associations with NT-proBNP
The median NT-proBNP level in the lowest tertile of nighttime SBP was 73 (IQR: 31, 145) pg/ml compared with 134 (IQR: 51, 290) pg/ml in the highest tertile. In contrast, there was a smaller difference in NT-proBNP levels across tertiles of daytime SBP (Figure 1). In multivariable models, each 10 mm Hg higher nighttime SBP was associated with 14% higher NT-proBNP levels (adjusted GMR: 1.14, 95% CI: 1.08, 1.20). Compared with the lowest tertile of nighttime SBP, the highest tertile was associated with 48% higher NT-proBNP levels (adjusted GMR: 1.48, 95% CI: 1.22, 1.79). There was no evidence of an association between daytime SBP modeled continuously or as tertiles with NT-proBNP (Figure 2 and Table 2).
Figure 1.
NT-proBNP and hs-cTnT levels stratified by tertiles of ambulatory SBP measures in SPRINT. (A) Displays NT-proBNP levels across tertiles of nighttime, daytime, and night/day ratio of systolic blood pressure obtained from ambulatory blood pressure monitoring in SPRINT participants. (B) Displays hs-cTnT levels across tertiles of similar ambulatory systolic blood pressure measurements. hs-cTnT, high-sensitivity cardiac troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SBP, systolic blood pressure; SPRINT, Systolic Blood Pressure Intervention Trial.
Figure 2.
Forest plots of multivariable-adjusted associations of nighttime, daytime, and night/day ratios of SBP and DBP with cardiac biomarker levels in SPRINT. Geometric mean ratios and 95% confidence intervals obtained from multivariable linear regression models adjusting for age, sex, race, treatment assignment, smoking status, body mass index, estimated glomerular filtration rate, low-density lipoprotein-cholesterol, history of cardiovascular disease, evening dose of blood pressure medication, and morning dose of blood pressure medication. (A) Displays multivariable-adjusted associations between ambulatory blood pressure measurements and NT-proBNP levels. (B) Displays multivariable-adjusted associations between ambulatory blood pressure measurements and hs-cTnT levels. DBP, diastolic blood pressure; hs-cTnT, high-sensitivity cardiac troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SBP, systolic blood pressure; SPRINT, Systolic Blood Pressure Intervention Trial.
Table 2.
Associations of ambulatory SBP measures with NT-proBNP and hs-cTnT levels in SPRINT
| SBP (mm Hg) or SBP ratio, median (IQR) | Adjusted GMR (95% CI)a | ||
|---|---|---|---|
| NT-proBNP | Hs-cTnT | ||
| Nighttime SBPb,c | |||
| Tertile 1 | 106 (101–109) | Reference | Reference |
| Tertile 2 | 119 (117–123) | 1.22 (1.02, 1.47) | 1.04 (0.94, 1.15) |
| Tertile 3 | 135 (135–143) | 1.48 (1.22, 1.79) | 1.19 (1.07, 1.32) |
| Daytime SBPd,e | |||
| Tertile 1 | 119 (115–123) | Reference | Reference |
| Tertile 2 | 132 (128–135) | 1.02 (0.85, 1.24) | 1.08 (0.97, 1.20) |
| Tertile 3 | 147 (143–153) | 1.09 (0.88, 1.34) | 1.16 (1.04, 1.30) |
| Night/day SBP ratiof | |||
| Tertile 1 | 0.83 (0.79–0.85) | Reference | Reference |
| Tertile 2 | 0.91 (0.85–0.92) | 1.22 (1.02, 1.47) | 0.99 (0.90, 1.09) |
| Tertile 3 | 0.99 (0.96–1.04) | 1.51 (1.26, 1.81) | 1.07 (0.97, 1.19) |
Bolded estimates indicate statistical significance.
Abbreviations: CI, confidence interval; GMR, geometric mean ratio; hs-cTnT, high-sensitivity cardiac troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SBP, systolic blood pressure.
aModels adjust for age, sex, race, treatment assignment, smoking, BMI, eGFR, LDL-cholesterol, history of CVD, evening dose of BP medication, and morning dose of BP medication.
bNighttime BP was defined as the average of all BP readings during the 1 AM to 6 AM window.
cRange of nighttime SBP within each tertile: Tertile 1: (72–113 mm Hg), Tertile 2: (113–126 mm Hg), and Tertile 3: (126–181 mm Hg).
dDaytime BP was defined as the average of all BP readings during the 9 AM to 9 PM window.
eRange of daytime SBP within each tertile: Tertile 1 (89–125 mm Hg), Tertile 2 (125–138 mm Hg), and Tertile 3 (138–179 mm Hg).
fRanges: Tertile 1 (0.55–0.87), Tertile 2 (0.87–0.94), and Tertile 3 (0.94–1.29).
A higher night/day ratio of SBP was also independently associated with higher NT-proBNP levels (Table 2). In analyses categorizing the night/day ratio of SBP by dipping status, compared with dippers (≥0.8 to ≤0.9), reverse dippers (>1) had 68% higher NT-proBNP levels (adjusted GMR: 1.68, 95% CI: 1.34, 2.10) (Table 3). Similar findings were observed when evaluating ambulatory DBP associations with NT-proBNP (Supplementary Table S1).
Table 3.
Associations of nocturnal SBP dipping status with NT-proBNP and hs-cTnT levels
| Dipping status | N (%) | Adjusted GMR (95% CI)a | |
|---|---|---|---|
| NT-proBNP | Hs-cTnT | ||
| Extreme dipper (<0.8) | 86 (10.1) | 0.80 (0.62, 1.04) | 0.96 (0.83, 1.11) |
| Dipper (≥0.8 to ≤0.9) | 305 (35.9) | Reference | Reference |
| Non-dipper (>0.9 to ≤1) | 330 (38.9) | 1.10 (0.93, 1.30) | 1.02 (0.93, 1.12) |
| Reverse dipper (>1) | 128 (15.1) | 1.68 (1.34, 2.10) | 1.14 (1.01, 1.29) |
Note: Bolded estimates indicate statistical significance.
Abbreviations: CI, confidence interval; GMR, geometric mean ratio; hs-cTnT, high-sensitivity cardiac troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SBP, systolic blood pressure.
aModels adjust for age, sex, race, treatment assignment, smoking, BMI, eGFR, LDL-cholesterol, history of CVD, evening dose of BP medication, and morning dose of BP medication.
The daytime SBP association with NT-proBNP was stronger in the intensive arm (adjusted GMR 1.09, 95% CI: 1.00, 1.19) compared with the standard arm (adjusted GMR 0.96, 95% CI: 0.88, 1.05; P for interaction = 0.04), whereas associations of nighttime SBP and night/day ratio of SBP with NT-proBNP did not vary by randomization arm (P for interactions > 0.10; Supplementary Table S2). Ambulatory SBP associations with NT-proBNP did not vary by race (P for interactions > 0.05; Supplementary Figure S1).
Ambulatory BP associations with hs-cTnT
The median hs-cTnT levels in the lowest and highest tertiles of nighttime SBP were 9 ng/l (IQR: 6, 15) and 12 ng/l (IQR: 7, 18), respectively. Across tertiles of daytime SBP, hs-cTnT levels were comparable (Figure 1). In multivariable models, each 10 mm Hg higher nighttime SBP was associated with 5% higher hs-cTnT levels (adjusted GMR: 1.05, 95% CI: 1.02, 1.08). In contrast to NT-proBNP, both nighttime and daytime SBP had positive associations with hs-cTnT levels (Table 2 and Figure 2).
The night/day ratio of SBP modeled continuously and as tertiles were not associated with hs-cTnT levels (Table 2 and Figure 2). In analyses categorizing the night/day ratio of SBP by dipping status, compared with dippers, reverse dippers had higher hs-cTnT levels, while non-dippers and extreme dippers had similar hs-cTnT levels (Table 3).
A similar pattern of results was observed using ambulatory DBP measurements (Supplementary Table S1). In addition, ambulatory SBP associations with hs-cTnT did not vary by randomization arm or by race (P for interactions > 0.05; Supplementary Table S2 and Figure S1).
DISCUSSION
In this ancillary analysis of SPRINT, higher nighttime BP and an abnormal dipping pattern (with higher nighttime vs. daytime BP) were independently associated with higher NT-proBNP levels, while daytime BP was not associated with NT-proBNP. In contrast, both higher nighttime and daytime BP were independently associated with higher hs-cTnT levels. These findings were largely similar among those randomized to the intensive or standard SBP-lowering arms of SPRINT.
Previous studies similarly observed that higher nighttime BP levels and an abnormal dipping pattern are associated with elevations in NT-proBNP and hs-cTnT levels, as well as increased LV mass index, LV dysfunction, and measures of LV strain.12–18,23–29 Our study expands upon these results in several ways. First, we demonstrate the associations with cardiac biomarkers are robust even among treated hypertensive individuals in SPRINT who had an office SBP target of <120 mm Hg. These findings suggest that nighttime BP and dipping status may have importance beyond achieving clinic BP control.
Second, we observed that higher nighttime BP, but not daytime BP, is independently associated with higher NT-proBNP levels. The low, detectable levels of NT-proBNP observed in this study are similar to levels measured in the general population, which have established associations with CVD and mortality.10,11 The more prominent nighttime BP associations with NT-proBNP may reflect increased circulating volume seen with high salt intake and salt sensitivity, which are major determinants of nocturnal hypertension and a blunted dipping response.30,31 Elevated NT-proBNP levels may also capture impaired baroreceptor-mediated nocturnal BP dipping resulting from increased atherosclerotic burden of the carotid arteries and aortic arch.32,33 Increased arterial stiffness can also cause nocturnal hypertension and lead to elevations in NT-proBNP and hs-cTnT through increased cardiac afterload and decreased coronary perfusion.34,35 Alternatively, our findings could be explained by reverse causality, whereby subclinical CVD leads to autonomic nervous system dysfunction or cardiac structural abnormalities that result in nocturnal hypertension.36,37 Future studies evaluating longitudinal associations of ambulatory BP with subclinical CVD measures and CVD outcomes are warranted to determine whether the greater CVD risk linked to nighttime BP results from increased myocardial stress reflected by higher NT-proBNP levels.
Our results also raise the possibility that cardiac biomarkers may help identify individuals who benefit from antihypertensive therapy directed at reducing elevated nighttime BP levels and restoring a normal dipping pattern. The stronger association with NT-proBNP also suggests that diuretic therapy may be particularly useful. These questions require additional evaluation in interventional studies. Recently, a large randomized trial among hypertensive adults demonstrated that randomization to evening vs. morning dosing of usual antihypertensive medications did not significantly impact long-term CVD outcomes.38 However, the trial did not select for participants with nocturnal hypertension or an abnormal dipping pattern. Prospective studies are needed to evaluate whether cardiac biomarkers may help guide the selection of evening dosing of antihypertensive medications.
Our study benefited from the use of ABPM data in SPRINT participants, which allowed for the use of ambulatory BP measures among individuals randomized to different clinic SBP targets, and the use of two widely available markers of CVD risk. Our study also has several important limitations. First, despite adjustment for multiple confounders, the cross-sectional design and potential for unmeasured confounding limit the inferences that can be made about the observed associations. However, it is unlikely that any residual confounding affects the daytime and nighttime BP associations differently. Second, consistent with prior studies in SPRINT, nighttime BP was defined according to clock time instead of sleep time.21,39,40 This may have led to non-differential measurement error of asleep BP that would bias our findings to the null. Third, biomarkers were measured 3 months prior to ABPM, and we cannot account for potential short-term fluctuations in biomarker concentrations or ambulatory BPs. However, any measurement error would likely be non-differential and bias our findings to the null. Fourth, ABPM was conducted in a subset of SPRINT, although participants with ABPM had similar clinical characteristics as the overall trial.21 We also did not have data on sleep quality or whether participants had obstructive sleep apnea. Finally, our findings may not generalize to hypertensive individuals who did not meet eligibility criteria for SPRINT, including those with diabetes, at younger ages, or with low CVD risk. Our study sample was also restricted to treated hypertensive patients with essential hypertension, who may have better daytime BP control than individuals with untreated or secondary hypertension.
In summary, in this ancillary analysis of SPRINT, higher nighttime BP and an abnormal dipping pattern (higher nighttime vs. daytime BP) were independently associated with higher NT-proBNP levels, whereas daytime BP was not associated with NT-proBNP. Meanwhile, higher nighttime and daytime BP were both associated with higher hs-cTnT levels. Our findings reinforce the importance of identifying hypertensive individuals with elevated nighttime BP levels and an abnormal dipping pattern and support future studies to understand the relationship between diurnal BP variations and subclinical CVD.
Supplementary Data
Supplementary materials are available at American Journal of Hypertension (http://ajh.oxfordjournals.org).
Acknowledgments
This ancillary study was supported by the NHLBI (1R01HL144112-01 and 1K24HL166681-01 for JDB), the National Center for Advancing Translational Sciences, NIH, through grant number UL1 TR001860 and linked award KL2 TR001859 (SBA), and the American Heart Association (CDA 936281 for SBA). Analytical reagents for hs-cTnT and NT-pro-BNP measurements were donated by Roche (Indianapolis, IN). The authors thank the participants and staff members of the Systolic Blood Pressure Intervention Trial, which was sponsored by the National Institutes of Health (NIH), including the National Heart, Lung, and Blood Institute (NHLBI), the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute on Aging (NIA), and the National Institute of Neurological Disorders and Stroke (NINDS), under Contract Numbers HHSN268200900040C, HHSN268200900046C, HHSN268200900047C, HHSN268200900048C, HHSN268200900049C, and Inter-Agency Agreement Number A-HL-13–002-001. It was also supported in part with resources and use of facilities through the Department of Veterans Affairs. The SPRINT investigators acknowledge the contribution of study medications (azilsartan and azilsartan combined with chlorthalidone) from Takeda Pharmaceuticals International, Inc. All components of the SPRINT study protocol were designed and implemented by the investigators. The investigative team collected, analyzed, and interpreted the data. All aspects of manuscript writing and revision were carried out by the co-authors. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, the U.S. Department of Veterans Affairs, or the United States Government. For a full list of contributors to SPRINT, please see the Supplementary material acknowledgement list: https://www.sprinttrial.org/public/dspScience.cfm. We also acknowledge the support from the following CTSAs funded by NCATS: CWRU: UL1TR000439, OSU: UL1RR025755, U Penn: UL1RR024134& UL1TR000003, Boston: UL1RR025771, Stanford: UL1TR000093, Tufts: UL1RR025752, UL1TR000073 & UL1TR001064, University of Illinois: UL1TR000050, University of Pittsburgh: UL1TR000005, UT Southwestern: 9U54TR000017–06, University of Utah: UL1TR000105–05, Vanderbilt University: UL1 TR000445, George Washington University: UL1TR000075, University of CA, Davis: UL1 TR000002, University of Florida: UL1 TR000064, University of Michigan: UL1TR000433, Tulane University: P30GM103337 COBRE Award NIGMS, Wake Forest University: UL1TR001420.
Contributor Information
Nikit Venishetty, Department of Medicine, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas, USA.
Jarett D Berry, Department of Medicine, University of Texas at Tyler Health Science Center, Tyler, Texas, USA.
James A de Lemos, Division of Cardiology, Department of Cardiology, the University of Texas at Southwestern Medical School, Dallas, Texas, USA.
Elaine Wu, Division of Cardiology, Department of Cardiology, the University of Texas at Southwestern Medical School, Dallas, Texas, USA.
MinJae Lee, Department of Biostatistics, Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Paul E Drawz, Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Vijay Nambi, Department of Medicine and Center for Cardiometabolic Disease Prevention, Baylor College of Medicine, Houston, Texas, USA; Department of Medicine, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA.
Christie M Ballantyne, Department of Medicine and Center for Cardiometabolic Disease Prevention, Baylor College of Medicine, Houston, Texas, USA.
Anthony A Killeen, Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Joachim H Ix, Nephrology Section, Veterans Affairs San Diego Healthcare System, San Diego, California, USA; Division of Nephrology-Hypertension, University of California San Diego, San Diego, California, USA.
Michael G Shlipak, Department of Medicine, Kidney Health Research Collaborative, San Francisco Veterans Affairs Health Care System and University of California San Francisco, San Francisco, California, USA.
Simon B Ascher, Department of Medicine, Kidney Health Research Collaborative, San Francisco Veterans Affairs Health Care System and University of California San Francisco, San Francisco, California, USA; Division of Hospital Medicine, University of California Davis, Sacramento, California, USA.
Conflict of Interest
JAd reports grant support from Roche Diagnostics and Abbott Diagnostics, consulting fees from Roche Diagnostics, Abbott Diagnostics, Ortho Clinical Diagnostics, Quidel Cardiovascular, Inc., and Siemen’s Health Care Diagnostics. He has been named a co-owner on a patent awarded to the University of Maryland (US Patent Application Number: 15/309,754) entitled: “Methods for Assessing Differential Risk for Developing Heart Failure.” JDB reports grant support from the NIH, Roche Diagnostics, and Abbott Diagnostics, consulting fees from Roche Diagnostics, and the Cooper Institute. The remaining authors have nothing to disclose.
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