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Outcomes in vascular surgical patients with isolated postoperative troponin leak: a meta‐analysis

2011· review· en· W1528436158 on OpenAlexfundno aff
Gemma Redfern, Reitze Rodseth, Bruce Biccard

Bibliographic record

VenueAnaesthesia · 2011
Typereview
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
FundersMedical Research CouncilCanadian Institutes of Health Research
KeywordsMedicineTroponinMyocardial infarctionLeakCardiologyTroponin IInternal medicineTroponin TSurgery

Abstract

fetched live from OpenAlex

Although peri-operative myocardial infarction remains a significant cause of morbidity and mortality following vascular surgery, the significance of an isolated troponin leak is uncertain. This is an elevation of troponin below the diagnostic threshold for a peri-operative myocardial infarction, without symptoms or ischaemic electrocardiography changes or echocardiography signs such as new regional wall motion abnormalities. This meta-analysis aimed to determine the early (< 30 days) and intermediate (< 180 days) outcomes of vascular surgical patients with an isolated troponin leak. A full literature search up to December 2010 identified 593 studies, of which nine (consisting of eight distinct patient cohorts) underwent analysis. An isolated troponin leak was strongly predictive of all-cause mortality at 30 days (OR 5.03, 95% CI 2.88-8.79, p < 0.00001). The associated 30-day mortality in patients with no troponin elevation, an isolated troponin leak or peri-operative myocardial infarction was 2.3%, 11.6% and 21.6%, respectively (p = 0.000001). Insufficient data were available to analyse intermediate-term outcomes. An isolated troponin leak following vascular surgery is strongly associated with short-term mortality.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.020
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.304
Teacher spread0.265 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations82
Published2011
Admission routes1
Has abstractyes

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