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Record W2326790748 · doi:10.1097/hco.0000000000000069

Myocardial injury after noncardiac surgery

2014· review· en· W2326790748 on OpenAlexaff
James S. Khan, Pablo Alonso‐Coello, P.J. Devereaux

Bibliographic record

VenueCurrent Opinion in Cardiology · 2014
Typereview
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsHamilton Health SciencesMcMaster UniversityPopulation Health Research InstituteUniversity of Toronto
FundersAmerican Heart Association
KeywordsMedicinePerioperativeTroponinObservational studyTroponin IAspirinMyocardial ischemiaInternal medicineMyocardial infarctionSurgeryIschemia

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Recent investigations have substantially improved our understanding of myocardial injury after noncardiac surgery (MINS). RECENT FINDINGS: MINS is defined as a prognostically relevant myocardial injury due to ischemia that occurs during or within 30 days after noncardiac surgery. MINS occurs in 8% of adults undergoing major noncardiac surgery and is diagnosed with an elevated postoperative troponin measurement. MINS is associated with significant morbidity, and approximately 10% of patients experiencing MINS will die within 30 days. There is a dose-graded response in mortality and time to death with increasing levels of postoperative troponin elevations. Most patients (>80%) suffering from MINS will not experience an ischemic symptom. Without troponin monitoring, the majority of MINS events would go undetected. To avoid missing these prognostically relevant events, guidelines now recommend perioperative troponin monitoring in high-risk patients having noncardiac surgery. In patients who suffer MINS, risk-adjusted observational data suggest that aspirin and a statin can reduce the risk of 30-day mortality. SUMMARY: Among adults, MINS is the most common cardiovascular complication that occurs after noncardiac surgery. Given that worldwide 200 million adult patients undergo major noncardiac surgery each year, at least 8 million of these patients will suffer MINS making this a substantial public health problem.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0120.008
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.087
GPT teacher head0.407
Teacher spread0.320 · 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 designNot applicable
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

Citations74
Published2014
Admission routes1
Has abstractyes

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