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.


Journal

JAMA network open
ISSN: 2574-3805
Titre abrégé: JAMA Netw Open
Pays: United States
ID NLM: 101729235

Informations de publication

Date de publication:
01 03 2023
Historique:
entrez: 1 3 2023
pubmed: 2 3 2023
medline: 4 3 2023
Statut: epublish

Résumé

Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers. 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). 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. At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment. The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest). 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]). 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. ClinicalTrials.gov Identifier: NCT01206062.

Identifiants

pubmed: 36857053
pii: 2801835
doi: 10.1001/jamanetworkopen.2023.1055
pmc: PMC9978954
doi:

Substances chimiques

Biomarkers 0

Banques de données

ClinicalTrials.gov
['NCT01206062']

Types de publication

Randomized Controlled Trial Multicenter Study Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

e231055

Subventions

Organisme : NCATS NIH HHS
ID : UL1 TR000439
Pays : United States
Organisme : NIA NIH HHS
ID : U24 AG074855
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002548
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000005
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000073
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL127659
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG066546
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000003
Pays : United States
Organisme : NCRR NIH HHS
ID : UL1 RR025752
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268200900040C
Pays : United States
Organisme : NCRR NIH HHS
ID : UL1 RR024134
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268200900049C
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268200900046C
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000105
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG055606
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000075
Pays : United States
Organisme : NIGMS NIH HHS
ID : P30 GM103337
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000064
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG080821
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268200900047C
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000050
Pays : United States
Organisme : NIH HHS
ID : S10 OD023495
Pays : United States
Organisme : NCRR NIH HHS
ID : UL1 RR025755
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000433
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000093
Pays : United States
Organisme : NHLBI NIH HHS
ID : HHSN268200900048C
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG065805
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG072979
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000002
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001064
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000445
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR003142
Pays : United States
Organisme : NCRR NIH HHS
ID : UL1 RR025771
Pays : United States

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Auteurs

Tanweer Rashid (T)

Neuroimage 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 Li (K)

Neuroimage 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 Toledo (JB)

Department of Neurology, University of Florida, Gainesville.
Department of Neurology, Houston Methodist Hospital, Houston, Texas.

Ilya Nasrallah (I)

Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia.
Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia.

Nicholas M Pajewski (NM)

Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina.

Sudipto Dolui (S)

Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia.

John Detre (J)

Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia.
Department of Neurology, University of Pennsylvania, Philadelphia.

David A Wolk (DA)

Department of Neurology, University of Pennsylvania, Philadelphia.

Hangfan Liu (H)

Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia.

Susan R Heckbert (SR)

Department of Epidemiology, University of Washington, Seattle.

R Nick Bryan (RN)

Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia.

Jeff Williamson (J)

Section of Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina.

Christos Davatzikos (C)

Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia.
Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia.

Sudha Seshadri (S)

Neuroimage 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 Launer (LJ)

Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland.

Mohamad Habes (M)

Neuroimage 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.
Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia.

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