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A Longitudinal Characterization of Cerebral Microbleeds in a Marginalized Population with High Rates of Mental Illness, Substance Abuse and Viral Infection (P3.390)

2016· article· en· W2746562745 on OpenAlexaffabout
Jan Mosion, Alexander Rauscher, Taylor S. Willi, Donna J. Lang, Talia Vertinsky, Fidel Vila‐Rodriguez, Christian Kames, William J. Panenka, Mike Jarrett, William G. Honer, Alasdair M. Barr

Bibliographic record

VenueNeurology · 2016
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMental illnessSubstance abusePopulationPsychiatryMedicinePsychologyMental healthEnvironmental health

Abstract

fetched live from OpenAlex

Objective: To evaluate the incidence, regional localization, volume, and change in volume of cerebral microbleeds (CMBs) over a three year period in a marginalized urban population. Background: Living in a marginalized urban environment is associated with exposure to a large number of variables, including physical violence, infection and substance abuse, which can harm the brain. Additionally, many people living in this environment experience early life trauma and have severe mental illness. CMBs are small, chronic brain hemorrhages that may represent an index of this harm. Methods: Subjects living in Single Room Occupancy hotels in the Downtown Eastside of Vancouver, Canada were recruited for the Hotel study. Subjects had MRI brain scans at entry into the study, and once per year for the next three years. Data were acquired on a 3T Philips Achieva. Parameters for SWI: 3D flow compensated gradient echo scan, TE/TR 20/ms, voxel size=0.45x0.7x2mm3, reconstructed to 0.39x0.39x1mm3. Final SWI images were computed offline and lesions were marked using in-house developed software; lesion volume was measured across the manually defined regions. Results: The mean age of subjects was 45 years (80[percnt] male). Useful baseline scans from 245 subjects were collected at baseline, 217 scans at 12 months, 182 at 24 months and 79 at 36 months. CMBs were present in 22[percnt] of scans. These were localized to: frontal lobe (33[percnt]), temporal lobe (25[percnt]), parietal lobe (21[percnt]), occipital lobe (11[percnt]) and subcortical (10[percnt]). Modal CMB volume was 4.5-6mm3. 61[percnt] of scans showed a year-to-year decrease in CMB volume (-27[percnt]) and 28[percnt] showed an increase in volume (+29[percnt]), while 11[percnt] showed no change. Conclusions: Rates of CMBs in this marginalized population were greater than expected based on age. Further study is needed to determine the etiology and neurocognitive sequelae of CMBs in this cohort.

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)0.001
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 score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.252
Teacher spread0.241 · 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
Published2016
Admission routes2
Has abstractyes

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