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Record W606191789

Cerebral microbleeds as a marker of small vessel disease : new insights from neuro-imaging and clinical studies in stroke patients

2014· dissertation· en· W606191789 on OpenAlexaboutno aff
Simone M. Gregoire

Bibliographic record

VenueUCL Discovery (University College London) · 2014
Typedissertation
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
Fundersnot available
KeywordsCerebral amyloid angiopathyMedicineNeurologyClinical significanceNeuroradiologyStroke (engine)Magnetic resonance imagingBiomarkerInternal medicineMontreal Cognitive AssessmentNeuroimagingAngiopathyDiseaseRadiologyCardiologyCognitive impairmentDementiaPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Introduction: A portfolio of studies is presented aimed at understanding the clinical and pathophysiological significance of cerebral microbleeds (CMBs) in stroke patients. CMBs are the radiological marker of microscopic haemosiderin deposits on iron-sensitiveMRI sequences (mainly gradient-recalled echo [GRE] T2* MRI). They are common in patients with cerebrovascular disease and are hypothesised to be a biomarker for brain small vessel diseases, including hypertensive arteriopathy and cerebral amyloid angiopathy (CAA). Important questions relating to CMBs include their use as a prognostic marker for antithrombotic-related intracerebral haemorrhage (ICH) and cognitive impairment. Our aims were to address the pathophysiological and clinical relevance of CMBs using longitudinal, case-control and cross-sectional studies. Methods: Patients were ascertained from prospective databases of admissions to the stroke service at the National Hospital for Neurology and Neurosurgery and at University College London Hospital’s (UCLH) NHS Trust. Magnetic resonance imaging data was collected and analysed for markers of small vessel disease including CMBs. Clinical and radiological associations of CMBs were determined using appropriate statistical tests. Objectives: First, ways of improving microbleed detection and reporting were explored through the development of a visual rating scale (theMicrobleed Anatomical Rating Scale, MARS) aimed at reliably rating CMBs. Second, the prognostic relevance of CMBs was investigated for antiplatelet-related ICH in a case-comparison study. Third, the detection of new CMBs over time and the factors that influence this were explored. Fourth, the impact of CMBs on cognitive impairment was studied in a cross-sectional study. Finally, the association between CMBs and acute silent ischaemia on diffusion-weighted MRI was investigated via a multi-centre cross-sectional MRI study of patients with ICH. Main findings: 1. MARS is a reliable scale with good intra- and inter-rater agreement for rating CMBs presence and number in any brain location. 2. Lobar CMBs, especially if numerous, are a risk factor for antiplatelet-related ICH independent of the extent of white matter changes. 3. CMBs accumulate over time in stroke patients, and the risk is related to baseline systolic blood pressure. 4. Lobar CMBs are an independent predictor of frontal executive impairment; this suggests that CAA is a potential underlying contributor to cognitive impairment. 5. Silent acute infarcts are frequent in patients within 3 months of ICH, especially in those with probable CAA, and are associated with markers of small vessel disease severity, including CMBs. Conclusion: These studies provide new information on detection, clinical impact and associations of CMBs in stroke patients. They suggest that CMBs have useful roles in understanding pathophysiology, diagnosis and prognosis in patients with small vessel diseases. Further studies are required to determine the direct therapeutic consequences of CMBs, but the present work suggests several promising areas for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.273
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

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