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Record W2509777123 · doi:10.1161/str.47.suppl_1.wmp88

Abstract WMP88: Perihematomal Edema Expansion Rate Predicts Functional Outcome in Deep Intracerebral Hemorrhage

2016· article· en· W2509777123 on OpenAlexaff
Zachary Grunwald, Sebastian Urday, Lauren A. Beslow, Anastasia Vashkevich, Alison Ayres, Steven M. Greenberg, Joshua N. Goldstein, Thomas W.K. Battey, Jocelyne Simard, Jonathan Rosand, W. Taylor Kimberly, Kevin N. Sheth

Bibliographic record

VenueStroke · 2016
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsKimberly-Clark (Canada)
Fundersnot available
KeywordsMedicineIntracerebral hemorrhageModified Rankin ScaleIntraventricular hemorrhageGlasgow Coma ScaleOdds ratioInternal medicineAnesthesiaCardiologyGestational ageIschemic strokeIschemia

Abstract

fetched live from OpenAlex

Introduction: Perihematomal edema (PHE) expansion rate may be an independent predictor of poor functional outcome following spontaneous intracerebral hemorrhage (ICH). We examined whether this association varies by ICH location. Hypothesis: The effect size of PHE expansion rate on mortality and poor functional outcome will be greater for deep ICH compared to lobar ICH. Methods: Subjects (n=139) were retrospectively identified from a prospective ICH cohort enrolled from 2000-2013. Inclusion criteria: ≥18 years of age, spontaneous supratentorial ICH, and known time of onset. Exclusion criteria: infratentorial or primary intraventricular hemorrhage, subsequent surgery, trauma, or warfarin-related ICH. ICH, PHE, and intraventricular hemorrhage (IVH) volumes were measured from CT scans. PHE expansion rates were calculated from serial PHE volume measurements. Logistic regression assessed the association between PHE expansion rate and mortality or poor functional outcome (modified Rankin Scale >2) at 90 days. Odds ratios are per 0.04 mL/h. Results: PHE expansion rate from baseline to 24 hours (PHE24) predicts mortality for deep (p=0.03, OR 1.13[1.02-1.26]) and lobar ICH (p=0.02, OR 1.03[1.00-1.06]) in unadjusted regression, and in models adjusted for age (Deep: p=0.02; Lobar: p=0.03), blood pressure (Deep: p=0.02; Lobar: p=0.04), IVH volume (Deep: p=0.02; Lobar: p=0.05), Glasgow Coma Scale (Deep: p=0.03; Lobar: p=0.02), or time to baseline CT (Deep: p=0.05; Lobar: p=0.05). PHE24 also predicts mortality for lobar ICH adjusting for ICH volume (p=0.05, OR 1.03[1-1.06]). A significant interaction exists between ICH location and PHE expansion rate from baseline to 72 hours (PHE72) in models predicting mRS>2 (p=0.04). PHE72 predicts mRS>2 for deep but not lobar ICH (p-values not shown) in models that are unadjusted (p=0.02, OR 4.04[1.25-13.04]) or adjusted for ICH volume (p=0.02, OR 4.3[1.25-14.98]), age (p=0.03, OR 5.4[1.21-24.11]), blood pressure (p=0.05, OR 3.28[1.02-10.57]), IVH volume (p=0.02, OR 4.59[1.28-16.41]), GCS (p=0.02, OR 4.19[1.2-14.55]), or time to first CT (p=0.03, OR 4.02[1.19-13.56]). Conclusion: PHE72 predicts poor functional outcomes exclusively after deep ICH, whereas PHE24 predicts mortality for deep and lobar ICH.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.284
Teacher spread0.258 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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