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Record W7073789942

Three-month stroke outcome The European Registers of Stroke (EROS) Investigators

2011· article· en· W7073789942 on OpenAlexaff

Bibliographic record

VenueResearch Portal (King's College London) · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsInstitute of Population and Public Health
Fundersnot available
KeywordsStroke (engine)Confidence intervalCase fatality rateLogistic regressionPopulationOutcome (game theory)NeurologyEpidemiology
DOInot available

Abstract

fetched live from OpenAlex

Background: Contemporaneous data on variations in outcome after first-ever-lifetime stroke between European populations are lacking. We compared differences in case fatality rates, functional outcome, and living conditions 3 months after stroke within the European Registers of Stroke Collaboration. Methods: Population-based stroke registers were established in France (Dijon), Italy (Sesto Fiorentino), Lithuania (Kaunas), the United Kingdom (London), Spain (Menorca), and Poland (Warsaw). All patients with first-ever-lifetime stroke of all age groups from the source population (1,087,048 inhabitants) were included. Data collection took part between 2004 and 2006. The study investigated population variations in outcome at 3 months (death, institutionalization due to stroke, or Barthel Index below 12 points) using multivariable logistic regression analyses adjusted for age, sex, stroke severity, stroke subtype, and comorbidities. Results: A total of 2,034 patients with first-ever-lifetime stroke were included. Median age was 73 years, 52% were female. The mean weighted cumulative risk of death was 21.8% (95% confidence interval 20.0 to 23.6) with a 3-fold variation across populations. The weighted proportion of poor outcome was 41.3% (95% confidence interval 39.0 to 43.7) with a 2-fold variation across populations. Conclusion: More than 40% of patients had a poor outcome, defined as being dead, dependent, or institutionalized 3 months after stroke. Substantial outcome variations were found between populations that were explained by case mix variables in this analysis, yet a trend toward a higher risk of poor outcome was present in Kaunas. Neurology (R) 2011;76:159-165

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)0.005
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.517
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.106
GPT teacher head0.334
Teacher spread0.228 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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