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Record W1509384784 · doi:10.1161/str.46.suppl_1.tp168

Abstract T P168: A Wake-up Call for Wake-up Strokes

2015· article· en· W1509384784 on OpenAlexaboutno aff
Josephine F. Huang, Jennifer E. Fugate, Alejandro A. Rabinstein

Bibliographic record

VenueStroke · 2015
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)Modified Rankin ScaleDemographicsIschemic strokeMedical recordInternal medicineRetrospective cohort studyCardiologyPediatricsEmergency medicineIschemiaDemography

Abstract

fetched live from OpenAlex

INTRODUCTION: Studies suggest 8%-28% of ischemic strokes present as wake-up strokes (WUS). The unknown time of symptom onset precludes these patients from approved treatments for acute ischemic stroke, but a substantial proportion of patients may be deemed candidates for treatment if other factors are considered. The aim of this study was to identify characteristics associated with clinical outcomes of WUS patients. METHODS: We retrospectively reviewed the medical record of patients with ischemic stroke admitted to a large academic medical center between January 2011 and May 2012. We identified patients with stroke symptoms upon awakening or those who were found with stroke symptoms with an unknown time of onset. Baseline demographics, stroke mechanism, presenting NIHSS, Alberta Stroke Program Early Computed Tomography Score (ASPECTS), and modified Rankin Scale (mRS) scores on discharge and at 3-month follow-up were obtained. A good outcome was defined as mRS 0-2. RESULTS: WUS patients comprised 22% (162/731) of all patients with ischemic stroke at our institution during this time period. Median age was 74 years (range 15-100), median presenting NIHSS was 5 (range 0-28), and median initial ASPECTS 10 (range 0-10). A cardioembolic mechanism was identified in 68 patients (42%). Predictors of good outcome at hospital discharge were lower initial NIHSS (3.5 versus 12.0, p<0.0001) and higher ASPECTS (9.8 versus 8.1, p=0.0002). The predictors of good outcomes at 3 months were younger age (69.1 versus 75.8, p=0.009), lower initial NIHSS (5.0 versus 12.6, p<0.0001), and higher ASPECTS (9.5 versus 8.1, p=0.0006). One hundred and eleven patients (68.5%) had initial ASPECTS of 10. Of those, 19 had NIHSS≥10 and 7 were treated with acute recanalization therapies. Four of the 7 treated patients had good outcomes, and 2 of the 12 untreated patients had good outcomes. CONCLUSIONS: Few patients with strokes of unknown onset and severe deficits have good outcomes without acute stroke treatment. Patients with NIHSS≥10 and ASPECTS 10 may be candidates for acute recanalization therapy.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.041
GPT teacher head0.302
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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