MétaCan
Menu
Back to cohort
Record W2911974579 · doi:10.1161/str.50.suppl_1.wp449

Abstract WP449: Distribution of Cerebellar Microbleeds and Their Correlation with Underlying Microangiopathy in Patients with Spontaneous Supratentorial Intracerebral Hemorrhage

2019· article· en· W2911974579 on OpenAlexaff
Ravinder‐Jeet Singh, Ericka Teleg, Nima Kashani, Eric E. Smith

Bibliographic record

VenueStroke · 2019
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCerebral amyloid angiopathyIntracerebral hemorrhageMicroangiopathyCerebellumFluid-attenuated inversion recoveryPathologyStroke (engine)AngiopathyMagnetic resonance imagingRadiologyInternal medicineDiseaseDementia

Abstract

fetched live from OpenAlex

Background: Cerebral amyloid angiopathy (CAA) and hypertensive cerebral small vessel disease (HTN-cSVD) exhibit distinct distributions of intracerebral hemorrhages (ICHs) and microbleeds (MBs), but little is known about cerebellar hemorrhage patterns and how they relate to the underlying microangiopathy. The Boston criteria for CAA do not discriminate between lobar and deep cerebellar hemorrhages. We investigated if distinct topographical patterns of MBs exists in the cerebellum. Methods: Patients with spontaneous symptomatic supratentorial ICH were included if they had brain MRI with gradient echo T2*-weighted sequence. Cerebellar MBs were classified into lobar or superficial (cortical/corticosubcortical), deep (dentate/peridentate) and mixed patterns. We compared the frequency and distribution of cerebellar MBs between lobar and deep/mixed ICH and correlated with supratentorial MBs (dichotomized into lobar and deep/mixed MBs). Results: 130 patients were included (median age 68.6-years [IQR 57.9-79.0]; 50% male); 87 patients (67%) had lobar ICH (possible CAA, n=26; probable CAA, n=37; nonCAA, n=24) and 43 (33%) had deep/mixed ICH. Cerebellar MBs were seen in 26 patients (20.0%); lobar pattern among 16 patients (61.5%), deep in 4 (15.4%), and mixed pattern in 6 patients (23.1%). Lobar ICH patients often had superficial cerebellar MBs (81.3% vs deep/mixed in 18.8%) while deep/mixed ICH patients more often demonstrated deep/mixed cerebellar MBs (66.7% vs superficial in 23.5%) [ P =0.046]. The distribution of supratentorial MBs correlated with the distribution of cerebellar MBs ( P= 0.047). Two patients with possible CAA had MBs confined to superficial cerebellum and incorporation of cerebellar MBs into the Boston criteria would have resulted in their reclassification into probable CAA, while another two probable CAA had deep/mixed cerebellar MBs reclassifying them into nonCAA ICH. Conclusion: Distinct superficial and deep cerebellar MB patterns can be distinguished which segregate with lobar and deep/mixed ICH locations, suggesting differential cerebellar involvement by CAA and HTN-cSVD. If validated, lobar (superficial) cerebellar MBs might be used to further improve the accuracy of the Boston criteria for CAA.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueStrokeSame topicIntracerebral and Subarachnoid Hemorrhage ResearchFrench-language works237,207