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Risk Factors for Silent Brain Infarcts and White Matter Disease in a Real-World Cohort Identified by Natural Language Processing



      To assess the frequency of silent brain infarcts (SBIs) and white matter disease (WMD) and associations with stroke risk factors (RFs) in a real-world population.

      Patients and Methods

      This was an observational study of patients 50 years or older in the Kaiser Permanente Southern California health system from January 1, 2009, through June 30, 2019, with head computed tomography or magnetic resonance imaging for nonstroke indications and no history of stroke, transient ischemic attack, or dementia. A natural language processing (NLP) algorithm was applied to the electronic health record to identify individuals with reported SBIs or WMD. Multivariable Poisson regression estimated risk ratios of demographic characteristics, RFs, and scan modality on the presence of SBIs or WMD.


      Among 262,875 individuals, the NLP identified 13,154 (5.0%) with SBIs and 78,330 (29.8%) with WMD. Stroke RFs were highly prevalent. Advanced age was strongly associated with increased risk of SBIs (adjusted relative risks [aRRs], 1.90, 3.23, and 4.72 for those aged in their 60s, 70s, and ≥80s compared with those in their 50s) and increased risk of WMD (aRRs, 1.79, 3.02, and 4.53 for those aged in their 60s, 70s, and ≥80s compared with those in their 50s). Magnetic resonance imaging was associated with a reduced risk of SBIs (aRR, 0.87; 95% CI, 0.83 to 0.91) and an increased risk of WMD (aRR, 2.86; 95% CI, 2.83 to 2.90). Stroke RFs had modest associations with increased risk of SBIs or WMD.


      An NLP algorithm can identify a large cohort of patients with incidentally discovered SBIs and WMD. Advanced age is strongly associated with incidentally discovered SBIs and WMD.

      Abbreviations and Acronyms:

      ARR (adjusted relative risk), CT (computed tomography), EHR (electronic health record), HC (hypercholesterolemia), HTN (hypertension), ICD (International Classification of Diseases), KPSC (Kaiser Permanente Southern California), MRI (magnetic resonance imaging), NLP (natural language processing), RF (risk factor), SBI (silent brain infarct), SBP (systolic blood pressure), SCD (silent cerebrovascular disease), WMD (white matter disease)
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        • Smith E.E.
        • Saposnik G.
        • Biessels G.J.
        • et al.
        Prevention of stroke in patients with silent cerebrovascular disease: a scientific statement for healthcare professionals from the American Heart Association/American Stroke Association.
        Stroke. 2017; 48: e44-e71
        • Fanning J.P.
        • Wong A.A.
        • Fraser J.F.
        The epidemiology of silent brain infarction: a systematic review of population-based cohorts.
        BMC Med. 2014; 12: 119
        • Gupta A.
        • Giambrone A.E.
        • Gialdini G.
        • et al.
        Silent brain infarction and risk of future stroke: a systematic review and meta-analysis.
        Stroke. 2016; 47: 719-725
        • Kuller L.H.
        • Longstreth Jr., W.T.
        • Arnold A.M.
        • et al.
        White matter hyperintensity on cranial magnetic resonance imaging: a predictor of stroke.
        Stroke. 2004; 35: 1821-1825
        • Alosco M.L.
        • Sugarman M.A.
        • Besser L.M.
        • et al.
        A clinicopathological investigation of white matter hyperintensities and Alzheimer’s disease neuropathology.
        J Alzheimers Dis. 2018; 63: 1347-1360
        • Leung L.Y.
        • Han P.K.J.
        • Lundquist C.
        • Weinstein G.
        • Thaler D.E.
        • Kent D.M.
        Clinicians’ perspectives on incidentally discovered silent brain infarcts: a qualitative study.
        PLoS One. 2018; 13e0194971
        • Fu S.
        • Leung L.Y.
        • Wang Y.
        • et al.
        Natural language processing for the identification of silent brain infarcts from neuroimaging reports.
        JMIR Med Inform. 2019; 7e12109
        • Leung L.Y.
        • Fu S.
        • Nelson J.
        • et al.
        Agreement between neuroimages and reports for natural language processing-based detection of silent brain infarcts and white matter disease.
        BMC Neurol. 2021; 21: 189
        • Wolf P.A.
        • D’Agostino R.B.
        • Belanger A.J.
        • Kannel W.B.
        Probability of stroke: a risk profile from the Framingham Study.
        Stroke. 1991; 22: 312-318
        • Longstreth W.T.
        • Manolio T.A.
        • Arnold A.
        • et al.
        • for the Cardiovascular Health Study Collaborative Research Group
        Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people: the Cardiovascular Health Study.
        Stroke. 1996; 27: 1274-1282
        • Liao D.
        • Cooper L.
        • Cai J.
        • et al.
        Presence and severity of cerebral white matter lesions and hypertension, its treatment, and its control: the ARIC study (Atherosclerosis Risk in Communities Study).
        Stroke. 1996; 27: 2262-2270
        • De Leeuw F.E.
        • De Groot J.C.
        • Achten E.
        • et al.
        Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study: the Rotterdam Scan Study.
        J Neurol Neurosurg Psychiatry. 2001; 70: 9-14
        • Vermeer S.E.
        • Koudstaal P.J.
        • Oudkerk M.
        • Hofman A.
        • Breteler M.M.B.
        Prevalence and risk factors of silent brain infarcts in the population-based Rotterdam Scan Study.
        Stroke. 2002; 33: 21-25
        • Gottesman R.F.
        • Coresh J.
        • Catellier D.J.
        • et al.
        Blood pressure and white-matter disease progression in a biethnic cohort: Atherosclerosis Risk in Communities (ARIC) study.
        Stroke. 2010; 41: 3-8
        • Leung L.Y.
        • Bartz T.M.
        • Rice K.
        • et al.
        Blood pressure and heart rate measures associated with increased risk of covert brain infarction and worsening leukoaraiosis in older adults.
        Arterioscler Thromb Vasc Biol. 2017; 37: 1579-1586
        • Muntner P.
        • Whittle J.
        • Lynch A.I.
        • et al.
        Visit-to-visit variability of blood pressure and coronary heart disease, stroke, heart failure, and mortality: a cohort study.
        Ann Intern Med. 2015; 163: 329-338
        • Wardlaw J.M.
        • Smith E.E.
        • Biessels G.J.
        • et al.
        STandards for ReportIng Vascular changes on nEuroimaging (STRIVE v1). Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration.
        Lancet Neurol. 2013; 12: 822-838