Evidence map›Paper›PMID 36857053›Full record

Trial reportJAMA network open2023

Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers: Post Hoc Secondary Analysis of the SPRINT MIND Randomized Clinical Trial.

Tanweer Rashid, Karl Li, Jon B Toledo, Ilya Nasrallah, Nicholas M Pajewski, Sudipto Dolui, John Detre, David A Wolk, Hangfan Liu, Susan R Heckbert and 6 more

Registry-linked trialOpen access · goldAbstract readRandomized Controlled TrialMulticenter Study
In one paragraph

Trial report in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01206062 (Systolic Blood Pressure Intervention Trial), which is not on this map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
8.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT01206062 nacompletednot on this map

Systolic Blood Pressure Intervention Trial

TypeinterventionalSponsorNational Heart, Lung, and Blood Institute (NHLBI)Ran2010 to 2019Enrolled9,361ConditionsHypertensionArmsIntensive control of SBP, Standard control of SBP
3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Elevated AD biomarkers do not explain cognitive performance in a community-recruited clinical trial cohort.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  4. Article
  5. Article
  6. Aging and the Spectral Properties of Brain Hemodynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  7. Article
  8. Review
  9. Article
  10. Microstructural damage and lower myelin content in the Brainstem associated with hypertension.Hypertension research : official journal of the Japanese Society of Hypertension · 2025
    Article
  11. Blood Pressure and Cognitive Function in Older Adults.Clinics in geriatric medicine · 2024
    Review
  12. Hypertension, Neurodegeneration, and Cognitive Decline.Hypertension (Dallas, Tex. : 1979) · 2024
    Review
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 8 institutions in 1 country.

Tanweer RashidNeuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio.
Karl LiNeuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio.
Jon B ToledoDepartment of Neurology, University of Florida, Gainesville.
Ilya NasrallahDepartment of Radiology, Hospital of the University of Pennsylvania, Philadelphia.
Nicholas M PajewskiDepartment of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina.
Sudipto DoluiDepartment of Radiology, Hospital of the University of Pennsylvania, Philadelphia.
John DetreDepartment of Radiology, Hospital of the University of Pennsylvania, Philadelphia.
David A WolkDepartment of Neurology, University of Pennsylvania, Philadelphia.
Hangfan LiuCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia.
Susan R HeckbertDepartment of Epidemiology, University of Washington, Seattle.
R Nick BryanDepartment of Radiology, Hospital of the University of Pennsylvania, Philadelphia.
Jeff WilliamsonSection of Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina.
Christos DavatzikosDepartment of Radiology, Hospital of the University of Pennsylvania, Philadelphia.
Sudha SeshadriNeuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio.
Lenore J LaunerIntramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland.
Mohamad HabesNeuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio.
Hospital of the University of Pennsylvania · USThe University of Texas Health Science Center at San Antonio · USUniversity of Pennsylvania · USWake Forest University · USInstitute for Neurodegenerative Disorders · USNational Institute on Aging · USUniversity of Florida · USUniversity of Washington · US

Funding

INSTITUTIONAL CLINICAL AND TRANSLATIONAL SCIENCE AWARDUL1RR024134 · NCRR · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2006 to 2011
$70.4M
University of Pittsburgh Clinical and Translational Science InstituteUL1TR000005 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$50.8M
Clinical and Translational Science Collaborative of ClevelandUL1TR000439 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI KONSTAN, MICHAEL W. · 2012 to 2016
$50.0M
Michigan Institute for Clinical and Health Research (MCHR)UL1TR000433 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MASHOUR, GEORGE ALEXANDER · 2012 to 2016
$49.9M
Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Institutional Clinical and Translational Science AwardUL1TR000003 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2012 to 2015
$38.9M
MVP Data Integration into the ADSP Phenotype Harmonization ConsortiumU24AG074855 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CUCCARO, MICHAEL L, HOHMAN, TIMOTHY J · 2021 to 2025
$37.5M
Clinical and Translational Science Collaborative of ClevelandUL1TR002548 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI MCCOMSEY, GRACE A · 2018 to 2022
$35.5M
Tufts Clinical and Translational Research InstituteUL1TR001064 · NCATS · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2013 to 2017
$26.4M
University of Iowa Clinical and Translational Science Program (TL1)UL1RR025755 · NCRR · OHIO STATE UNIVERSITY · PI JACKSON, REBECCA D · 2008 to 2011
$26.3M
Research Education ComponentP30AG072979 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVID A WOLK · 2021 to 2026
$24.8M
NCATS NIH HHS UL1 TR000002NCATS NIH HHS UL1 TR000003NCATS NIH HHS UL1 TR000005NCATS NIH HHS UL1 TR000050NCATS NIH HHS UL1 TR000064NCATS NIH HHS UL1 TR000073NCATS NIH HHS UL1 TR000075NCATS NIH HHS UL1 TR000093NCATS NIH HHS UL1 TR000105NCATS NIH HHS UL1 TR000433NCATS NIH HHS UL1 TR000439NCATS NIH HHS UL1 TR000445NCATS NIH HHS UL1 TR001064NCATS NIH HHS UL1 TR002548NCATS NIH HHS UL1 TR003142NCRR NIH HHS UL1 RR024134NCRR NIH HHS UL1 RR025752NCRR NIH HHS UL1 RR025755NCRR NIH HHS UL1 RR025771NHLBI NIH HHS HHSN268200900040CNHLBI NIH HHS HHSN268200900046CNHLBI NIH HHS HHSN268200900047CNHLBI NIH HHS HHSN268200900048CNHLBI NIH HHS HHSN268200900049CNHLBI NIH HHS R01 HL127659NIA NIH HHS P30 AG066546NIA NIH HHS P30 AG072979NIA NIH HHS R01 AG055606NIA NIH HHS R01 AG065805NIA NIH HHS R01 AG080821NIA NIH HHS U24 AG074855NIGMS NIH HHS P30 GM103337NIH HHS S10 OD023495
6 · The paper itself

Abstract

Importance: Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers. Objective: To investigate the regional associations of intensive vs standard BP control with small vessel disease biomarkers, such as white matter lesions (WMLs), fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF). Design, Setting, and Participants: The Systolic Blood Pressure Intervention Trial (SPRINT) is a multicenter randomized clinical trial that compared intensive systolic BP (SBP) control (SBP target <120 mm Hg) vs standard control (SBP target <140 mm Hg) among participants aged 50 years or older with hypertension and without diabetes or a history of stroke. The study began randomization on November 8, 2010, and stopped July 1, 2016, with a follow-up duration of approximately 4 years. A total of 670 and 458 participants completed brain magnetic resonance imaging at baseline and follow-up, respectively, and comprise the cohort for this post hoc analysis. Statistical analyses for this post hoc analysis were performed between August 2020 and October 2022. Interventions: At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment. Main Outcomes and Measures: The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest). Results: At baseline, 355 participants (mean [SD] age, 67.7 [8.0] years; 200 men [56.3%]) received intensive BP treatment and 315 participants (mean [SD] age, 67.0 [8.4] years; 199 men [63.2%]) received standard BP treatment. Intensive treatment was associated with smaller mean increases in WML volume compared with standard treatment (644.5 mm3 vs 1258.1 mm3). The smaller mean increases were observed specifically in the deep white matter regions of the left anterior corona radiata (intensive treatment, 30.3 mm3 [95% CI, 16.0-44.5 mm3]; standard treatment, 80.5 mm3 [95% CI, 53.8-107.2 mm3]), left tapetum (intensive treatment, 11.8 mm3 [95% CI, 4.4-19.2 mm3]; standard treatment, 27.2 mm3 [95% CI, 19.4-35.0 mm3]), left superior fronto-occipital fasciculus (intensive treatment, 3.2 mm3 [95% CI, 0.7-5.8 mm3]; standard treatment, 9.4 mm3 [95% CI, 5.5-13.4 mm3]), left posterior corona radiata (intensive treatment, 26.0 mm3 [95% CI, 12.9-39.1 mm3]; standard treatment, 52.3 mm3 [95% CI, 34.8-69.8 mm3]), left splenium of the corpus callosum (intensive treatment, 45.4 mm3 [95% CI, 25.1-65.7 mm3]; standard treatment, 83.0 mm3 [95% CI, 58.7-107.2 mm3]), left posterior thalamic radiation (intensive treatment, 53.0 mm3 [95% CI, 29.8-76.2 mm3]; standard treatment, 106.9 mm3 [95% CI, 73.4-140.3 mm3]), and right posterior thalamic radiation (intensive treatment, 49.5 mm3 [95% CI, 24.3-74.7 mm3]; standard treatment, 102.6 mm3 [95% CI, 71.0-134.2 mm3]). Conclusions and Relevance: This study suggests that intensive BP treatment, compared with standard treatment, was associated with a slower increase of WMLs, improved diffusion tensor imaging, and FA and CBF changes in several brain regions that represent vulnerable areas that may benefit from more strict BP control. Trial Registration: ClinicalTrials.gov Identifier: NCT01206062.

Indexed as

Cerebral Small Vessel DiseasesHypertensionAgedBiomarkersBlood PressureDiffusion Tensor ImagingHumansMaleBiomarkers

Identifiers

PMID36857053
PMCPMC9978954
OpenAlexW4322719030

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.