Evidence map›Paper›PMID 42319234›Full record

ArticlePaediatric anaesthesia2026

Intraoperative Cardiac Events During Pediatric Cardiac Magnetic Resonance Imaging Under Anesthesia: A Retrospective Cohort Study.

Theodora Wingert, Justine Liang, Kelly Feldman, Amelie Delaporte, Christine Nguyen-Buckley, Tristan Grogan, Alexandre Joosten, John Paul Finn, Ihab Ayad

Abstract read
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In one paragraph

Article in Paediatric anaesthesia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Theodora WingertDepartment of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, USA.ORCID https://orcid.org/0000-0001-7149-9150
Justine LiangDepartment of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, USA.
Kelly FeldmanDivision of Critical Care Medicine, Department of Pediatrics, University of California Los Angeles, Los Angeles, California, USA.
Amelie DelaporteDepartment of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, USA.
Christine Nguyen-BuckleyDepartment of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, USA.
Tristan GroganDepartment of Medicine Statistics Core, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Alexandre JoostenDepartment of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, USA.
John Paul FinnDepartment of Radiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Ihab AyadDepartment of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, USA.

Funding

Predicting Pediatric Postoperative Complications using Waveform and Electronic Health Record DataK08EB038393 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Theodora E Wingert · 2026 to 2026
$175k
Foundation for Anesthesia Education and ResearchNIBIB NIH HHS 1K08EB038393NIBIB NIH HHS K08 EB038393
6 · The paper itself

Abstract

backgroundChildren with congenital heart disease (CHD) frequently undergo cardiac magnetic resonance imaging (MRI) under anesthesia. Although these procedures lack surgical stimulus, patients remain physiologically vulnerable, and the incidence of perioperative cardiovascular instability in this setting is poorly defined. We aimed to determine the incidence and predictors of intraoperative cardiac events during pediatric cardiac MRI using a recently proposed composite framework of intraoperative cardiovascular instability.

methodsThis single-center retrospective cohort study analyzed patients ≤ 18 years undergoing cardiac MRI under anesthesia from 2013 to 2025. The primary outcome was intraoperative cardiac events, defined as ≥ 5 cumulative minutes with mean arterial pressure > 2 standard deviations below age- and sex-adjusted reference values, vasopressor administration, or severe adverse cardiac events. Multivariable logistic regression identified independent predictors. Thirty-day mortality was evaluated descriptively.

resultsAmong 330 cases, intraoperative cardiac events occurred in 29.7% (98/330). Hypotension was most common (24.2%), followed by vasopressor administration (9.7%); no severe adverse cardiac events were observed. Thirty-day mortality was 1.8% (6/330). Independent predictors included increasing age (OR 1.13 per year, 95% CI: 1.04-1.21), and higher-acuity preoperative location, including neonatal intensive care unit (ICU) (OR 4.42, 95% CI: 1.86-10.52) and pediatric ICU (OR 4.84, 95% CI: 1.91-12.26). Sensitivity analyses demonstrated consistent findings across model specifications.

conclusionsIntraoperative cardiac events, primarily hypotension of unknown significance, were common during pediatric cardiac MRI under anesthesia; no severe adverse cardiac events occurred. Our findings highlight the physiologic complexity of this population and support the need for thoughtful perioperative risk stratification and management.

Indexed as

AnesthesiaHeart Defects, CongenitalIntraoperative ComplicationsMagnetic Resonance ImagingAdolescentChildChild, PreschoolCohort StudiesFemaleHumansInfantInfant, NewbornMalePediatric AnesthesiaRetrospective Studieshypotensionintraoperative cardiac eventsmortalitypediatricperioperative complications

Identifiers

PMID42319234
PMCPMC13460832

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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.