Evidence map›Paper›PMID 39341612›Full record

ReviewThe Medical clinics of North America2024

Coronary Disease Risk Prediction, Risk Reduction, and Postoperative Myocardial Injury.

Matthew A Pappas, Leonard S Feldman, Andrew D Auerbach

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in The Medical clinics of North America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

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

3 authors.

Matthew A PappasDepartment of Hospital Medicine, Cleveland Clinic, Cleveland, OH, USA; Center for Value-based Care Research, Cleveland Clinic, Cleveland, OH, USA; Outcomes Research Consortium, Cleveland, OH, USA. Electronic address: pappasm@ccf.org.
Leonard S FeldmanDepartments of Medicine and Pediatrics, Division of Hospital Medicine, Johns Hopkins Hospital, Baltimore, MD, USA.
Andrew D AuerbachDepartment of Hospital Medicine, University of California, San Francisco, CA, USA.

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

For patients considering surgery, the preoperative evaluation allows physicians to identify and treat acute cardiac conditions before less-urgent surgery, predict the benefits and harms of a proposed surgery, and make temporary management changes to reduce operative risk. Multiple risk prediction tools are reasonable for use in estimating perioperative cardiac risk, but management changes to reduce risk have proven elusive. For all but the most urgent surgical procedures, patients with active coronary syndromes or decompensated heart failure should have surgery postponed.

Indexed as

Postoperative ComplicationsCoronary DiseaseHumansRisk AssessmentRisk FactorsRisk Reduction BehaviorCardiovascular diagnostic techniquesPerioperative carePreoperative period

Identifiers

PMID39341612
PMCPMC11439086

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.