Evidence map›Paper›PMID 34968532›Full record

ArticleResuscitation2022

A risk-adjustment model for patients presenting to hospitals with out-of-hospital cardiac arrest and ST-elevation myocardial infarction.

Andy T Tran, Anthony J Hart, John A Spertus, Philip G Jones, Bryan F McNally, Ali O Malik, Paul S Chan

Open access · greenAbstract read
In one paragraph

Article in Resuscitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 15% of its field
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, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Future of Patient-Reported Outcomes: Bringing Patients' Voices Into Health Care.Circulation. Cardiovascular quality and outcomes · 2024
    Article
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

7 authors at 1 institution in 1 country.

Andy T TranDepartment of Medicine, University of California, Irvine School of Medicine, Orange, CA, USA; Saint Luke's Mid America Heart Institute, Kansas City, MO, USA. Electronic address: andytt6@uci.edu.
Anthony J HartSaint Luke's Mid America Heart Institute, Kansas City, MO, USA; University of Missouri-Kansas City, Kansas City, MO, USA.
John A SpertusSaint Luke's Mid America Heart Institute, Kansas City, MO, USA; University of Missouri-Kansas City, Kansas City, MO, USA.
Philip G JonesSaint Luke's Mid America Heart Institute, Kansas City, MO, USA.
Bryan F McNallyDepartment of Emergency Medicine, Emory University School of Medicine, Atlanta, GA, USA; Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Ali O MalikSaint Luke's Mid America Heart Institute, Kansas City, MO, USA; University of Missouri-Kansas City, Kansas City, MO, USA.
Paul S ChanSaint Luke's Mid America Heart Institute, Kansas City, MO, USA; University of Missouri-Kansas City, Kansas City, MO, USA. Electronic address: paulchan.mahi@gmail.com.
Saint Luke's Hospital · US

Funding

CARDIOVASCULAR OUTCOMES RESEARCH TRAINING PROGRAMT32HL110837 · NHLBI · UNIVERSITY OF MISSOURI KANSAS CITY · PI JOHN A SPERTUS · 2012 to 2026
$5.0M
NHLBI NIH HHS T32 HL110837
6 · The paper itself

Abstract

backgroundPatients with ST-elevation myocardial infarction (STEMI) complicated by an out-of-hospital-cardiac-arrest (OHCA) may vary widely in their probability of dying. Large variation in mortality may have implications for current national efforts to benchmark operator and hospital mortality rates for coronary angiography. We aimed to build a risk-adjustment model of in-hospital mortality among OHCA survivors with concurrent STEMI.

methodsWithin the Cardiac Arrest Registry to Enhance Survival (CARES), we included adults with OHCA and STEMI who underwent emergent angiography within 2 hours of hospital arrival between January 2013 and December 2019. Using multivariable logistic regression to adjust for patient and cardiac arrest factors, we developed a risk-adjustment model for in-hospital mortality and examined variation in patients' predicted mortality.

resultsOf 2,999 patients (mean age 61.2 ± 12.0, 23.1% female, 64.6% white), 996 (33.2%) died during their hospitalization. The final risk-adjustment model included higher age (OR per 10-year increase, 1.50 [95% CI: 1.39-1.63]), unwitnessed OHCA (OR, 2.51 [1.99-3.16]), initial non-shockable rhythm [OR, 5.66 [4.52-7.13]), lack of sustained pulse for > 20 minutes (OR, 2.52 [1.88-3.36]), and longer resuscitation time (increased with each 10-minute interval) (c-statistic = 0.804 with excellent calibration). There was large variability in predicted mortality: median, 25.2%, inter-quartile-range: 14.0% to 47.8%, 10th-90th percentile: 8.2 % to 74.1%.

conclusionsIn a large national registry, we identified 5 key predictors for mortality in patients with STEMI and OHCA and found wide variability in mortality risk. Our findings suggest that current national benchmarking efforts for coronary angiography, which simply adjusts for the presence of OHCA, may not adequately capture patient case-mix severity.

Indexed as

Cardiopulmonary ResuscitationOut-of-Hospital Cardiac ArrestPercutaneous Coronary InterventionST Elevation Myocardial InfarctionAdultCoronary AngiographyFemaleHospitalsHumansMaleRegistriesAngiographyCardiac arrestMortalityOutcomesRisk adjustmentSTEMI

Identifiers

PMID34968532
PMCPMC8840945
OpenAlexW4200363309

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.