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Record W2131306453 · doi:10.1186/2047-0525-2-14

What evidence is there for intraoperative predictors of perioperative cardiac outcomes? A systematic review

2013· review· en· W2131306453 on OpenAlex
Bruce Biccard, Reitze Rodseth

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePerioperative Medicine · 2013
Typereview
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsHamilton Health SciencesPopulation Health Research Institute
FundersMedical Research CouncilCanadian Institutes of Health ResearchInyuvesi Yakwazulu-Natali
KeywordsMedicinePerioperativeOdds ratioCardiac surgeryConfidence intervalCochrane LibraryBlood pressureAtrial fibrillationAdverse effectTachycardiaInternal medicineAnesthesiaCardiologyVascular surgery

Abstract

fetched live from OpenAlex

BACKGROUND: Patients undergo cardiac preoperative evaluation to identify those at risk of adverse perioperative cardiac events. The Revised Cardiac Risk index is commonly used for this task, although it is unable to accurately risk stratify in all patients. This may be partly a result of intraoperative events which significantly modify preoperative risk. METHODS: We conducted a systematic review to identify independent intraoperative predictors of adverse cardiac events in patients undergoing non-cardiac surgery. Four databases (Ovid Healthstar 1966 to Jan 2012, Ovid Medline 1946 to 6 March 2012, EMBASE 1974 to March 05 2012 and The Cochrane Library to March 06 2012) were searched. RESULTS: Fourteen eligible studies were identified. The need for intraoperative blood transfusion (odds ratio (OR), 2.3; 95% confidence interval (CI), 1.4-3.3), vascular surgery (OR, 2.3; 95% CI, 1.2-3.4) and emergent/urgent surgery (OR, 2.3; 95% CI, 1.1-3.5) were the only independent intraoperative risk predictors identified in more than study. Other independent intraoperative factors identified included a >20 mmHg fall in mean arterial blood pressure for > 60 min (OR, 3.0; 95% CI, 1.8-4.9), >30% increase in baseline systolic pressure (OR, 8.0; 95% CI, 1.3-50), tachycardia in the recovery room (>30 beats per min (bpm) from baseline for >5 min) (OR, 7; 95% CI, 1.9-26), new onset atrial fibrillation (OR, 6.6; 95% CI, 2.5-20), hypothermia (OR, 2.2; 95% CI, 1.1-5) and remote ischemic preconditioning (OR, 0.22; 95% CI, 0.07-0.67). Other markers of surgical complexity were not independently associated with postoperative adverse cardiac outcomes. None of these studies controlled for blood transfusion. CONCLUSIONS: Intraoperative events significantly increase the risk for postoperative cardiac complications, although only intraoperative blood transfusion has strong evidence supporting this finding. It is possible that modification of these intraoperative risk factors by anesthetists and surgeons may reduce postoperative cardiac events and improve outcome. The Vascular Events in Noncardiac Surgery Patients Cohort Evaluation (VISION) Study will add important information to understanding intraoperative risk factors for adverse cardiac events.

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.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.371
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0260.004
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.091
GPT teacher head0.404
Teacher spread0.313 · 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