<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04457908</url>
  </required_header>
  <id_info>
    <org_study_id>2018YFC1312900-05</org_study_id>
    <nct_id>NCT04457908</nct_id>
  </id_info>
  <brief_title>The Effectiveness and Cost Effectiveness of Intelligent Assessment of Gait Disorder in Silent Cerebrovascular Disease</brief_title>
  <acronym>ACCURATE-1</acronym>
  <official_title>the Effectiveness and Cost Effectiveness in Screening Gait Disorder of Silent Cerebrovascular Disease Assisted by Artificial Intelligent System and Clinical Doctors - A Randomized Parallel-controlled Study</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Shanghai Zhongshan Hospital</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Fudan University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>The Affiliated Hospital Of Guizhou Medical University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Shanghai Zhongshan Hospital</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This is a multi-center, randomized, double-blind, parallel-controlled, prospective study to&#xD;
      compare the effectiveness and cost-effectiveness of intelligent and doctor groups for gait&#xD;
      disorder screening.&#xD;
&#xD;
      Clinical data, including demographic characteristics, socioeconomic level, medical history,&#xD;
      assessment of neurological function, laboratory tests, imaging tests, health service&#xD;
      utilization, and costs will be collected from the subjects. All subjects will be divided into&#xD;
      an intelligent group and a doctor group according to a 1:1 ratio. The intelligent group will&#xD;
      undergo intelligent system evaluation, and the doctor group will undergo the clinician's&#xD;
      conventional treatment process. At the same time, all the subjects will undergo gold-standard&#xD;
      panel gait and cognitive rating scale assessments.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      All subjects in the intelligent group will undergo tests to evaluate their nervous system&#xD;
      function, including the timed up-and-go test, mini-cognitive assessment, and sentence&#xD;
      repetition. Subjects will be recorded using a camera and microphone. The intelligent system&#xD;
      uses the built-in intelligent algorithm to analyze the gait video, sound, and picture to&#xD;
      provide information on gait features (stand-up time, turnaround time, stride length, step&#xD;
      velocity, stride length, step width, etc.), language features (pronunciation, intonation,&#xD;
      word order, language accuracy, language fluency, etc.), and clock features (contour, numbers,&#xD;
      pointers, etc.).&#xD;
&#xD;
      All subjects in the doctor group will consult with a doctor in the non-intelligent group&#xD;
      according to the routine treatment procedure. Doctors in the non-intelligent group are&#xD;
      required to be internal medicine clinicians with intermediate title or below, and they should&#xD;
      have registered their qualifications, relevant knowledge and training experience, educational&#xD;
      background, and other information in the early stage of the study. The doctors in the&#xD;
      non-intelligent group will make clinical diagnoses for the subjects based on routine medical&#xD;
      operations such as a history of the present illness, previous history, and physical&#xD;
      examination, and the data in medical records in the outpatient department will help determine&#xD;
      whether the subjects have gait disorders.&#xD;
&#xD;
      All subjects' walking videos will be assessed by the gold-standard panel, which will consist&#xD;
      of 2 experts of movement disorders. If there is any difference, a third expert will be&#xD;
      included in the evaluation. According to the clinical experience, the expert doctors will&#xD;
      evaluate the subjects' gait, and the results will be divided into normal gait and abnormal&#xD;
      gait.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date type="Anticipated">July 1, 2020</start_date>
  <completion_date type="Anticipated">December 31, 2020</completion_date>
  <primary_completion_date type="Anticipated">October 31, 2020</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Diagnostic</primary_purpose>
    <masking>Double (Participant, Care Provider)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Sensitivity</measure>
    <time_frame>baseline</time_frame>
    <description>Compared with the gold standard panel of neurology, the sensitivity of the intelligent system and clinicians to screen for gait disorders</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Specificity</measure>
    <time_frame>baseline</time_frame>
    <description>the specificity of the intelligent system and clinicians to screen for gait disorders</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Coincidence</measure>
    <time_frame>baseline</time_frame>
    <description>the coincidence of the intelligent system and clinicians to screen for gait disorders</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Yoden index</measure>
    <time_frame>baseline</time_frame>
    <description>the Yoden index of the intelligent system and clinicians to screen for gait disorders</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Positive predictive value and negative predictive value</measure>
    <time_frame>baseline</time_frame>
    <description>the positive predictive value and negative predictive value of the intelligent system and clinicians at different levels to screen for gait disorders</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Cost and cost-effectiveness</measure>
    <time_frame>baseline</time_frame>
    <description>Health care utilization and costs will be collected to calculate direct and indirect costs of the intelligent system and clinicians to screen for gait disorders, and the incremental cost-effectiveness ratio (ICER) will be computed.</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Anticipated">1000</enrollment>
  <condition>Silent Stroke</condition>
  <arm_group>
    <arm_group_label>intelligent</arm_group_label>
    <arm_group_type>Other</arm_group_type>
    <description>receive the neurological function assessment by artificial intelligence</description>
  </arm_group>
  <arm_group>
    <arm_group_label>manual</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>receive the neurological function assessment by doctor</description>
  </arm_group>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>intelligent assessment</intervention_name>
    <description>intelligent neurological function assessment</description>
    <arm_group_label>intelligent</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. Aged between 60 and 85 years.&#xD;
&#xD;
          2. Diagnosed with silent cerebrovascular disease/silent stroke, which is consistent with&#xD;
             the 2016 statement issued by the American Heart Association (AHA) and American Stroke&#xD;
             Association (ASA):&#xD;
&#xD;
               1. No previous clear history of stroke and no clinical symptoms or mild clinical&#xD;
                  symptoms that fail to attract clinical attention;&#xD;
&#xD;
               2. Cranial MRI showing at least one of the following within 5 years: lacunar infarct&#xD;
                  of vascular origin, white matter hyperintensity of vascular origin, cerebral&#xD;
                  microbleeds;&#xD;
&#xD;
          3. Consciousness and ability to complete cognitive assessment&#xD;
&#xD;
          4. Ability to stand and walk independently and complete gait assessment without&#xD;
             assistance from others.&#xD;
&#xD;
          5. Ability to sign the informed consent.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Intracranial lesions that have been clearly diagnosed as demyelination disease, white&#xD;
             matter dystrophy, intracranial space-occupying lesions, or autoimmune encephalitis.&#xD;
&#xD;
          2. Gait disorder that has been diagnosed as Parkinson's disease, normal cranial&#xD;
             hydrocephalus, an otogenic disease, subacute combined degeneration, peripheral&#xD;
             neuropathy, osteoarthritis, or lumbar disease.&#xD;
&#xD;
          3. Cognitive disorders that have been diagnosed, such as Alzheimer's disease,&#xD;
             frontotemporal dementia, Lewy body dementia, etc.&#xD;
&#xD;
          4. Severe neurological diseases such as previous cerebral trauma, epilepsy, and&#xD;
             myelopathy, etc.&#xD;
&#xD;
          5. Severe cardiovascular complications and intolerance to the assessment&#xD;
&#xD;
          6. Severe visual or hearing impairment, aphasia, cognitive disorder, gait disorder, etc.,&#xD;
             that results in the inability to cooperate for cognitive and gait assessment&#xD;
&#xD;
          7. Refusal to participate in the study&#xD;
&#xD;
          8. Other anomalies that could not be included in the exclusion criteria, but are&#xD;
             considered inappropriate to be included in this study.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>60 Years</minimum_age>
    <maximum_age>85 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Jing Ding, MD</last_name>
    <role>Study Director</role>
    <affiliation>Shanghai Zhongshan Hospital</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Beini Fei, MB</last_name>
    <phone>+86 13701699684</phone>
    <email>fbeini@sina.com</email>
  </overall_contact>
  <reference>
    <citation>Poels MM, Steyerberg EW, Wieberdink RG, Hofman A, Koudstaal PJ, Ikram MA, Breteler MM. Assessment of cerebral small vessel disease predicts individual stroke risk. J Neurol Neurosurg Psychiatry. 2012 Dec;83(12):1174-9. doi: 10.1136/jnnp-2012-302381. Epub 2012 Aug 23.</citation>
    <PMID>22917672</PMID>
  </reference>
  <reference>
    <citation>Kim BJ, Lee SH. Prognostic Impact of Cerebral Small Vessel Disease on Stroke Outcome. J Stroke. 2015 May;17(2):101-10. doi: 10.5853/jos.2015.17.2.101. Epub 2015 May 29.</citation>
    <PMID>26060797</PMID>
  </reference>
  <reference>
    <citation>Sachdev PS, Wen W, Christensen H, Jorm AF. White matter hyperintensities are related to physical disability and poor motor function. J Neurol Neurosurg Psychiatry. 2005 Mar;76(3):362-7. doi: 10.1136/jnnp.2004.042945.</citation>
    <PMID>15716527</PMID>
  </reference>
  <reference>
    <citation>Murray ME, Senjem ML, Petersen RC, Hollman JH, Preboske GM, Weigand SD, Knopman DS, Ferman TJ, Dickson DW, Jack CR Jr. Functional impact of white matter hyperintensities in cognitively normal elderly subjects. Arch Neurol. 2010 Nov;67(11):1379-85. doi: 10.1001/archneurol.2010.280.</citation>
    <PMID>21060015</PMID>
  </reference>
  <reference>
    <citation>Wakefield DB, Moscufo N, Guttmann CR, Kuchel GA, Kaplan RF, Pearlson G, Wolfson L. White matter hyperintensities predict functional decline in voiding, mobility, and cognition in older adults. J Am Geriatr Soc. 2010 Feb;58(2):275-81. doi: 10.1111/j.1532-5415.2009.02699.x. Epub 2010 Jan 26.</citation>
    <PMID>20374403</PMID>
  </reference>
  <reference>
    <citation>Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ. 2010 Jul 26;341:c3666. doi: 10.1136/bmj.c3666.</citation>
    <PMID>20660506</PMID>
  </reference>
  <reference>
    <citation>Brickman AM, Provenzano FA, Muraskin J, Manly JJ, Blum S, Apa Z, Stern Y, Brown TR, Luchsinger JA, Mayeux R. Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community. Arch Neurol. 2012 Dec;69(12):1621-7. doi: 10.1001/archneurol.2012.1527.</citation>
    <PMID>22945686</PMID>
  </reference>
  <reference>
    <citation>Maillard P, Carmichael O, Fletcher E, Reed B, Mungas D, DeCarli C. Coevolution of white matter hyperintensities and cognition in the elderly. Neurology. 2012 Jul 31;79(5):442-8. doi: 10.1212/WNL.0b013e3182617136. Epub 2012 Jul 18.</citation>
    <PMID>22815562</PMID>
  </reference>
  <reference>
    <citation>Smith EE, Saposnik G, Biessels GJ, Doubal FN, Fornage M, Gorelick PB, Greenberg SM, Higashida RT, Kasner SE, Seshadri S; American Heart Association Stroke Council; Council on Cardiovascular Radiology and Intervention; Council on Functional Genomics and Translational Biology; and Council on Hypertension. 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 Feb;48(2):e44-e71. doi: 10.1161/STR.0000000000000116. Epub 2016 Dec 15.</citation>
    <PMID>27980126</PMID>
  </reference>
  <reference>
    <citation>Leary MC, Saver JL. Annual incidence of first silent stroke in the United States: a preliminary estimate. Cerebrovasc Dis. 2003;16(3):280-5. doi: 10.1159/000071128.</citation>
    <PMID>12865617</PMID>
  </reference>
  <reference>
    <citation>Kim YJ, Kwon HK, Lee JM, Cho H, Kim HJ, Park HK, Jung NY, San Lee J, Lee J, Jang YK, Kim ST, Lee KH, Choe YS, Kim YJ, Na DL, Seo SW. Gray and white matter changes linking cerebral small vessel disease to gait disturbances. Neurology. 2016 Mar 29;86(13):1199-207. doi: 10.1212/WNL.0000000000002516. Epub 2016 Mar 2.</citation>
    <PMID>26935893</PMID>
  </reference>
  <reference>
    <citation>de Laat KF, van Norden AG, Gons RA, van Oudheusden LJ, van Uden IW, Bloem BR, Zwiers MP, de Leeuw FE. Gait in elderly with cerebral small vessel disease. Stroke. 2010 Aug;41(8):1652-8. doi: 10.1161/STROKEAHA.110.583229. Epub 2010 Jun 24.</citation>
    <PMID>20576951</PMID>
  </reference>
  <reference>
    <citation>Montero-Odasso MM, Sarquis-Adamson Y, Speechley M, Borrie MJ, Hachinski VC, Wells J, Riccio PM, Schapira M, Sejdic E, Camicioli RM, Bartha R, McIlroy WE, Muir-Hunter S. Association of Dual-Task Gait With Incident Dementia in Mild Cognitive Impairment: Results From the Gait and Brain Study. JAMA Neurol. 2017 Jul 1;74(7):857-865. doi: 10.1001/jamaneurol.2017.0643. Erratum In: JAMA Neurol. 2017 Nov 1;74(11):1381.</citation>
    <PMID>28505243</PMID>
  </reference>
  <reference>
    <citation>Wardlaw JM, Smith EE, Biessels GJ, Cordonnier C, Fazekas F, Frayne R, Lindley RI, O'Brien JT, Barkhof F, Benavente OR, Black SE, Brayne C, Breteler M, Chabriat H, Decarli C, de Leeuw FE, Doubal F, Duering M, Fox NC, Greenberg S, Hachinski V, Kilimann I, Mok V, Oostenbrugge Rv, Pantoni L, Speck O, Stephan BC, Teipel S, Viswanathan A, Werring D, Chen C, Smith C, van Buchem M, Norrving B, Gorelick PB, Dichgans M; 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 Aug;12(8):822-38. doi: 10.1016/S1474-4422(13)70124-8.</citation>
    <PMID>23867200</PMID>
  </reference>
  <results_reference>
    <citation>Vermeer SE, Longstreth WT Jr, Koudstaal PJ. Silent brain infarcts: a systematic review. Lancet Neurol. 2007 Jul;6(7):611-9. doi: 10.1016/S1474-4422(07)70170-9.</citation>
    <PMID>17582361</PMID>
  </results_reference>
  <results_reference>
    <citation>Vermeer SE, Hollander M, van Dijk EJ, Hofman A, Koudstaal PJ, Breteler MM; Rotterdam Scan Study. Silent brain infarcts and white matter lesions increase stroke risk in the general population: the Rotterdam Scan Study. Stroke. 2003 May;34(5):1126-9. doi: 10.1161/01.STR.0000068408.82115.D2. Epub 2003 Apr 10.</citation>
    <PMID>12690219</PMID>
  </results_reference>
  <results_reference>
    <citation>Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H. Abnormality of gait as a predictor of non-Alzheimer's dementia. N Engl J Med. 2002 Nov 28;347(22):1761-8. doi: 10.1056/NEJMoa020441.</citation>
    <PMID>12456852</PMID>
  </results_reference>
  <results_reference>
    <citation>Dumurgier J, Artaud F, Touraine C, Rouaud O, Tavernier B, Dufouil C, Singh-Manoux A, Tzourio C, Elbaz A. Gait Speed and Decline in Gait Speed as Predictors of Incident Dementia. J Gerontol A Biol Sci Med Sci. 2017 May 1;72(5):655-661. doi: 10.1093/gerona/glw110.</citation>
    <PMID>27302701</PMID>
  </results_reference>
  <verification_date>October 2019</verification_date>
  <study_first_submitted>July 1, 2020</study_first_submitted>
  <study_first_submitted_qc>July 1, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 7, 2020</study_first_posted>
  <last_update_submitted>July 1, 2020</last_update_submitted>
  <last_update_submitted_qc>July 1, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">July 7, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Cerebrovascular Disorders</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04457908
org study id: 2018YFC1312900-05
nct id: NCT04457908
lead sponsor: 
collaborator: 
collaborator: 
is fda regulated drug: No
is fda regulated device: No
This is a multi-center, randomized, double-blind, parallel-controlled, prospective study to
      compare the effectiveness and cost-effectiveness of intelligent and doctor groups for gait
      disorder screening.

      Clinical data, including demographic characteristics, socioeconomic level, medical history,
      assessment of neurological function, laboratory tests, imaging tests, health service
      utilization, and costs will be collected from the subjects. All subjects will be divided into
      an intelligent group and a doctor group according to a 1:1 ratio. The intelligent group will
      undergo intelligent system evaluation, and the doctor group will undergo the clinician's
      conventional treatment process. At the same time, all the subjects will undergo gold-standard
      panel gait and cognitive rating scale assessments.
All subjects in the intelligent group will undergo tests to evaluate their nervous system
      function, including the timed up-and-go test, mini-cognitive assessment, and sentence
      repetition. Subjects will be recorded using a camera and microphone. The intelligent system
      uses the built-in intelligent algorithm to analyze the gait video, sound, and picture to
      provide information on gait features (stand-up time, turnaround time, stride length, step
      velocity, stride length, step width, etc.), language features (pronunciation, intonation,
      word order, language accuracy, language fluency, etc.), and clock features (contour, numbers,
      pointers, etc.).

      All subjects in the doctor group will consult with a doctor in the non-intelligent group
      according to the routine treatment procedure. Doctors in the non-intelligent group are
      required to be internal medicine clinicians with intermediate title or below, and they should
      have registered their qualifications, relevant knowledge and training experience, educational
      background, and other information in the early stage of the study. The doctors in the
      non-intelligent group will make clinical diagnoses for the subjects based on routine medical
      operations such as a history of the present illness, previous history, and physical
      examination, and the data in medical records in the outpatient department will help determine
      whether the subjects have gait disorders.

      All subjects' walking videos will be assessed by the gold-standard panel, which will consist
      of 2 experts of movement disorders. If there is any difference, a third expert will be
      included in the evaluation. According to the clinical experience, the expert doctors will
      evaluate the subjects' gait, and the results will be divided into normal gait and abnormal
      gait.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Diagnostic
masking: Double (Participant, Care Provider)
measure: Sensitivity
time frame: baseline
description: Compared with the gold standard panel of neurology, the sensitivity of the intelligent system and clinicians to screen for gait disorders
measure: Specificity
time frame: baseline
description: the specificity of the intelligent system and clinicians to screen for gait disorders
measure: Coincidence
time frame: baseline
description: the coincidence of the intelligent system and clinicians to screen for gait disorders
measure: Yoden index
time frame: baseline
description: the Yoden index of the intelligent system and clinicians to screen for gait disorders
measure: Positive predictive value and negative predictive value
time frame: baseline
description: the positive predictive value and negative predictive value of the intelligent system and clinicians at different levels to screen for gait disorders
measure: Cost and cost-effectiveness
time frame: baseline
description: Health care utilization and costs will be collected to calculate direct and indirect costs of the intelligent system and clinicians to screen for gait disorders, and the incremental cost-effectiveness ratio (ICER) will be computed.
arm group label: intelligent
arm group type: Other
description: receive the neurological function assessment by artificial intelligence
arm group label: manual
arm group type: No Intervention
description: receive the neurological function assessment by doctor
intervention type: Diagnostic Test
intervention name: intelligent assessment
description: intelligent neurological function assessment
arm group label: intelligent
criteria: 
gender: All
minimum age: 60 Years
maximum age: 85 Years
healthy volunteers: No
last name: Jing Ding, MD
role: Study Director
affiliation: Shanghai Zhongshan Hospital
last name: Beini Fei, MB
phone: +86 13701699684
email: fbeini@sina.com
citation: Poels MM, Steyerberg EW, Wieberdink RG, Hofman A, Koudstaal PJ, Ikram MA, Breteler MM. Assessment of cerebral small vessel disease predicts individual stroke risk. J Neurol Neurosurg Psychiatry. 2012 Dec;83(12):1174-9. doi: 10.1136/jnnp-2012-302381. Epub 2012 Aug 23.
PMID: 22917672
citation: Kim BJ, Lee SH. Prognostic Impact of Cerebral Small Vessel Disease on Stroke Outcome. J Stroke. 2015 May;17(2):101-10. doi: 10.5853/jos.2015.17.2.101. Epub 2015 May 29.
PMID: 26060797
citation: Sachdev PS, Wen W, Christensen H, Jorm AF. White matter hyperintensities are related to physical disability and poor motor function. J Neurol Neurosurg Psychiatry. 2005 Mar;76(3):362-7. doi: 10.1136/jnnp.2004.042945.
PMID: 15716527
citation: Murray ME, Senjem ML, Petersen RC, Hollman JH, Preboske GM, Weigand SD, Knopman DS, Ferman TJ, Dickson DW, Jack CR Jr. Functional impact of white matter hyperintensities in cognitively normal elderly subjects. Arch Neurol. 2010 Nov;67(11):1379-85. doi: 10.1001/archneurol.2010.280.
PMID: 21060015
citation: Wakefield DB, Moscufo N, Guttmann CR, Kuchel GA, Kaplan RF, Pearlson G, Wolfson L. White matter hyperintensities predict functional decline in voiding, mobility, and cognition in older adults. J Am Geriatr Soc. 2010 Feb;58(2):275-81. doi: 10.1111/j.1532-5415.2009.02699.x. Epub 2010 Jan 26.
PMID: 20374403
citation: Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ. 2010 Jul 26;341:c3666. doi: 10.1136/bmj.c3666.
PMID: 20660506
citation: Brickman AM, Provenzano FA, Muraskin J, Manly JJ, Blum S, Apa Z, Stern Y, Brown TR, Luchsinger JA, Mayeux R. Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community. Arch Neurol. 2012 Dec;69(12):1621-7. doi: 10.1001/archneurol.2012.1527.
PMID: 22945686
citation: Maillard P, Carmichael O, Fletcher E, Reed B, Mungas D, DeCarli C. Coevolution of white matter hyperintensities and cognition in the elderly. Neurology. 2012 Jul 31;79(5):442-8. doi: 10.1212/WNL.0b013e3182617136. Epub 2012 Jul 18.
PMID: 22815562
citation: Smith EE, Saposnik G, Biessels GJ, Doubal FN, Fornage M, Gorelick PB, Greenberg SM, Higashida RT, Kasner SE, Seshadri S; American Heart Association Stroke Council; Council on Cardiovascular Radiology and Intervention; Council on Functional Genomics and Translational Biology; and Council on Hypertension. 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 Feb;48(2):e44-e71. doi: 10.1161/STR.0000000000000116. Epub 2016 Dec 15.
PMID: 27980126
citation: Leary MC, Saver JL. Annual incidence of first silent stroke in the United States: a preliminary estimate. Cerebrovasc Dis. 2003;16(3):280-5. doi: 10.1159/000071128.
PMID: 12865617
citation: Kim YJ, Kwon HK, Lee JM, Cho H, Kim HJ, Park HK, Jung NY, San Lee J, Lee J, Jang YK, Kim ST, Lee KH, Choe YS, Kim YJ, Na DL, Seo SW. Gray and white matter changes linking cerebral small vessel disease to gait disturbances. Neurology. 2016 Mar 29;86(13):1199-207. doi: 10.1212/WNL.0000000000002516. Epub 2016 Mar 2.
PMID: 26935893
citation: de Laat KF, van Norden AG, Gons RA, van Oudheusden LJ, van Uden IW, Bloem BR, Zwiers MP, de Leeuw FE. Gait in elderly with cerebral small vessel disease. Stroke. 2010 Aug;41(8):1652-8. doi: 10.1161/STROKEAHA.110.583229. Epub 2010 Jun 24.
PMID: 20576951
citation: Montero-Odasso MM, Sarquis-Adamson Y, Speechley M, Borrie MJ, Hachinski VC, Wells J, Riccio PM, Schapira M, Sejdic E, Camicioli RM, Bartha R, McIlroy WE, Muir-Hunter S. Association of Dual-Task Gait With Incident Dementia in Mild Cognitive Impairment: Results From the Gait and Brain Study. JAMA Neurol. 2017 Jul 1;74(7):857-865. doi: 10.1001/jamaneurol.2017.0643. Erratum In: JAMA Neurol. 2017 Nov 1;74(11):1381.
PMID: 28505243
citation: Wardlaw JM, Smith EE, Biessels GJ, Cordonnier C, Fazekas F, Frayne R, Lindley RI, O'Brien JT, Barkhof F, Benavente OR, Black SE, Brayne C, Breteler M, Chabriat H, Decarli C, de Leeuw FE, Doubal F, Duering M, Fox NC, Greenberg S, Hachinski V, Kilimann I, Mok V, Oostenbrugge Rv, Pantoni L, Speck O, Stephan BC, Teipel S, Viswanathan A, Werring D, Chen C, Smith C, van Buchem M, Norrving B, Gorelick PB, Dichgans M; 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 Aug;12(8):822-38. doi: 10.1016/S1474-4422(13)70124-8.
PMID: 23867200
citation: Vermeer SE, Longstreth WT Jr, Koudstaal PJ. Silent brain infarcts: a systematic review. Lancet Neurol. 2007 Jul;6(7):611-9. doi: 10.1016/S1474-4422(07)70170-9.
PMID: 17582361
citation: Vermeer SE, Hollander M, van Dijk EJ, Hofman A, Koudstaal PJ, Breteler MM; Rotterdam Scan Study. Silent brain infarcts and white matter lesions increase stroke risk in the general population: the Rotterdam Scan Study. Stroke. 2003 May;34(5):1126-9. doi: 10.1161/01.STR.0000068408.82115.D2. Epub 2003 Apr 10.
PMID: 12690219
citation: Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H. Abnormality of gait as a predictor of non-Alzheimer's dementia. N Engl J Med. 2002 Nov 28;347(22):1761-8. doi: 10.1056/NEJMoa020441.
PMID: 12456852
citation: Dumurgier J, Artaud F, Touraine C, Rouaud O, Tavernier B, Dufouil C, Singh-Manoux A, Tzourio C, Elbaz A. Gait Speed and Decline in Gait Speed as Predictors of Incident Dementia. J Gerontol A Biol Sci Med Sci. 2017 May 1;72(5):655-661. doi: 10.1093/gerona/glw110.
PMID: 27302701
responsible party type: Sponsor
mesh term: Cerebrovascular Disorders
sharing ipd: No