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Record W7054590508

Aggressive care following hospital admission for acute myocardial infarction : analysis of effects on mortality using instrumental variables

2001· dissertation· en· W7054590508 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2001
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMyocardial infarctionInstrumental variableHospital admissionHospital careConfoundingHealth careAcute careMEDLINE
DOInot available

Abstract

fetched live from OpenAlex

Certain regions adopt an aggressive approach (routine cardiac catheterization and frequent invasive revascularization) to care for acute myocardial infarction (AMI), while other regions adopt a conservative approach (selective use of invasive procedures). Administrative data provide a means to estimate the effects of these variations on patient outcomes, but they are limited by their potential for confounding bias due to unobserved case-mix variation as treatment assignment is not random. This study applied instrumental variables, a methodology that can account for this bias, to estimate the effectiveness of aggressive care in a Canadian patient population. The study used administrative data of hospital admissions and health services for all patients admitted for a first AMI in Quebec in 1988 (n = 8674). Incremental (marginal) mortality up to 4 years after admission was measured using distances to hospitals offering aggressive care as instrumental variables.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.265
Teacher spread0.254 · 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 designBench or experimental
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
Published2001
Admission routes1
Has abstractyes

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