Evidence map›Paper›PMID 37441833›Full record

ArticleJournal of clinical anesthesia2023

Diagnostic and prognostic value of cardiac stress testing before major noncardiac surgery-A cohort study.

Matthew A Pappas, Andrew D Auerbach, Michael W Kattan, Eugene H Blackstone, Michael B Rothberg, Daniel I Sessler

Abstract read
In one paragraph

Article in Journal of clinical anesthesia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Matthew A PappasCenter for Value-based Care Research, Cleveland Clinic, Cleveland, OH, United States of America; Department of Hospital Medicine, Cleveland Clinic, Cleveland, OH, United States of America; Outcomes Research Consortium, Cleveland, OH, United States of America. Electronic address: pappasm@ccf.org.
Andrew D AuerbachDepartment of Hospital Medicine, University of California, San Francisco, San Francisco, CA, United States of America.
Michael W KattanDepartment of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States of America.
Eugene H BlackstoneMiller Family Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, United States of America.
Michael B RothbergCenter for Value-based Care Research, Cleveland Clinic, Cleveland, OH, United States of America.
Daniel I SesslerOutcomes Research Consortium, Cleveland, OH, United States of America; Department of Outcomes Research, Anesthesiology Institute, Cleveland Clinic, Cleveland, OH, United States of America.

Funding

Personalizing Preoperative Stress Testing Using Machine LearningK08HL141598 · NHLBI · CLEVELAND CLINIC LERNER COM-CWRU · PI PAPPAS, MATTHEW · 2019 to 2023
$805k
NHLBI NIH HHS K08 HL141598
6 · The paper itself

Abstract

objectiveTo assess the incremental contribution of preoperative stress test results toward a diagnosis of obstructive coronary artery disease (CAD), prediction of mortality, or prediction of perioperative myocardial infarction in patients considering noncardiac, nonophthalmologic surgery. DESIGN, SETTING,

participantsA retrospective cohort study of visits to a preoperative risk assessment and optimization clinic in a large health system between 2008 and 2018. MEASUREMENTS: To assess diagnostic information of preoperative stress testing, we used the Begg and Greenes method to calculate test characteristics adjusted for referral bias, with a gold standard of angiography. To assess prognostic information, we first created multiply-imputed logistic regression models to predict 90-day mortality and perioperative myocardial infarction (MI), starting with two tools commonly used to assess perioperative cardiac risk, Revised Cardiac Risk Index (RCRI) and Myocardial Infarction or Cardiac Arrest (MICA). We then added stress test results and compared the discrimination for models with and without stress test results. MAIN

resultsAmong 136,935 visits by patients without an existing diagnosis of CAD, the decision to obtain preoperative stress testing identified around 4.0% of likely new diagnoses. Stress testing increased the likelihood of CAD (likelihood ratio: 1.31), but for over 99% of patients, stress testing should not change a decision on whether to proceed to angiography. In 117,445 visits with subsequent noncardiac surgery, stress test results failed to improve predictions of either perioperative MI or 90-day mortality. Reweighting the models and adding hemoglobin improved the prediction of both outcomes.

conclusionsCardiac stress testing before noncardiac, nonophthalmologic surgery does not improve predictions of either perioperative mortality or myocardial infarction. Very few patients considering noncardiac, nonophthalmologic surgery have a pretest probability of CAD in a range where stress testing could usefully select patients for angiography. Better use of existing patient data could improve predictions of perioperative adverse events without additional patient testing.

Indexed as

Coronary Artery DiseaseMyocardial InfarctionCohort StudiesExercise TestHumansPostoperative ComplicationsPrognosisRetrospective StudiesRisk AssessmentRisk FactorsCardiovascularDiagnosisDiagnostic techniquesPerioperative carePreoperative period

Identifiers

PMID37441833
PMCPMC10529226

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.