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Record W2143515023 · doi:10.1053/euhj.2001.2583

Geographic variation in patient and hospital characteristics, management, and clinical outcomes in ST-elevation myocardial infarction treated with fibrinolysis. Results from InTIME-II

2001· article· en· W2143515023 on OpenAlexaboutno aff
Robert P. Giugliano

Bibliographic record

VenueEuropean Heart Journal · 2001
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLatin AmericansMyocardial infarctionDemographyOdds ratioMortality rateFibrinolysisRevascularizationConfidence intervalInternal medicine

Abstract

fetched live from OpenAlex

AIMS: We examined the geographic variations in InTIME-II, a randomized double-blind trial comparing alteplase with lanoteplase for myocardial infarction. METHODS AND RESULTS: We compared baseline characteristics, management, and outcomes in four regions (Western Europe, Eastern Europe, North America, and Latin America) and in countries with historically different management approaches (Germany vs the U.K., the U.S. vs Canada). Thirty-day mortality in Western Europe, Eastern Europe, North America and Latin America was 6.7%, 7.3%, 5.7%, 10.1%, P<0.0001. Adjusted mortality for Europe was intermediate between North America and Latin America (odds ratios (OR) [95% confidence intervals (CI)] compared to Western Europe: North America 0.84 [0.67-1.0], Eastern Europe 1.2 [1.0-1.4], and Latin America 1.8 [1.3-2.7]). Revascularization rates varied 10-fold but did not explain regional mortality differences. Germany and the U.K. had similar adjusted 1-year mortality (OR for the U.K. 1.16 [0.92-1.5]), although invasive procedures were four- to 10-fold more common in Germany. Similarly the U.S. and Canada had equal adjusted 1-year mortality (OR for Canada 0.85 [0.61-1.17]) despite three-fold higher use of invasive procedures in the U.S. CONCLUSIONS: Significant geographic variations in practice and adjusted mortality following fibrinolysis persist despite recent guidelines. These findings have important implications in the design and interpretation of international studies, identify under- and over-utilized therapies, and support further study of treatments with marked worldwide variations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.300
Teacher spread0.275 · 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.

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

Citations73
Published2001
Admission routes1
Has abstractyes

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