Evidence map›Paper›PMID 35289978›Full record

ArticleAcademic emergency medicine : official journal of the Society for Academic Emergency Medicine2022

Can right ventricular assessments improve triaging of low risk pulmonary embolism?

Jaron D Raper, Alyssa M Thomas, Kathryn Lupez, Carly A Cox, Dasia Esener, Jeremy S Boyd, Jason T Nomura, Jillian Davison, Patrick M Ockerse, Stephen Leech and 6 more

Abstract read
In one paragraph

Article in Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Disposition of emergency department patients with acute pulmonary embolism after ambulance arrival.Journal of the American College of Emergency Physicians open · 2023
    Article
  4. Quality of life 1 month after acute pulmonary embolism in emergency department patients.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2023
    Article
  5. Article
  6. Article
  7. Machine Learning-Based Prediction of Pulmonary Embolism Prognosis Using Nutritional and Inflammatory Indices.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 9 institutions in 1 country.

Jaron D RaperDepartment of Emergency Medicine, Atrium Health's Carolinas Medical Center, Charlotte, North Carolina, USA.
Alyssa M ThomasDepartment of Emergency Medicine, Atrium Health's Carolinas Medical Center, Charlotte, North Carolina, USA.
Kathryn LupezDepartment of Emergency Medicine, Atrium Health's Carolinas Medical Center, Charlotte, North Carolina, USA.
Carly A CoxDepartment of Emergency Medicine, Atrium Health's Carolinas Medical Center, Charlotte, North Carolina, USA.
Dasia EsenerDepartment of Emergency Medicine Kaiser Permanente, San Diego, California, USA.
Jeremy S BoydDepartment of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jason T NomuraDepartment of Emergency Medicine, Christiana Care, Newark, Delaware, USA.
Jillian DavisonDepartment of Emergency Medicine Orlando Health, Orlando, Florida, USA.
Patrick M OckerseDivision of Emergency Medicine, University of Utah Health, Salt Lake City, Utah, USA.
Stephen LeechDepartment of Emergency Medicine Orlando Health, Orlando, Florida, USA.
Jakea JohnsonDepartment of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Eric AbramsDepartment of Emergency Medicine Kaiser Permanente, San Diego, California, USA.
Kathleen MurphyDepartment of Emergency Medicine, Christiana Care, Newark, Delaware, USA.
Christopher KellyDivision of Emergency Medicine, University of Utah Health, Salt Lake City, Utah, USA.
Nathaniel S O'ConnellDepartment of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
Anthony J WeekesDepartment of Emergency Medicine, Atrium Health's Carolinas Medical Center, Charlotte, North Carolina, USA.ORCID 0000-0001-9309-7910
Carolinas Medical Center · USChristiana Care Health System · USKaiser Permanente San Diego Medical Center · USOrlando Health · USUniversity of Utah · USVanderbilt University Medical Center · USHouston Methodist · USTufts Medical Center · USWake Forest University · US

Funding

Short-term Clinical Deterioration After Acute Pulmonary EmbolismR01HS025979 · AHRQ · CAROLINAS MEDICAL CENTER · PI WEEKES, ANTHONY J · 2018 to 2020
$1.0M
AHRQ HHS R01 HS025979
6 · The paper itself

Abstract

objectivesIdentifying right ventricle (RV) abnormalities is important to stratifying pulmonary embolism (PE) severity. Disposition decisions are influenced by concerns about early deterioration. Triaging strategies, like the Simplified Pulmonary Embolism Severity Index (sPESI), do not include RV assessments as predictors or early deterioration as outcome(s). We aimed to (1) determine if RV assessment variables add prognostic accuracy for 5-day clinical deterioration in patients classified low risk by sPESI, and (2) determine the prognostic importance of RV assessments compared to other variables and to each other.

methodsWe identified low risk sPESI patients (sPESI = 0) from a prospective PE registry. From a large field of candidate variables, we developed, and compared prognostic accuracy of, full and reduced random forest models (with and without RV assessment variables, respectively) on a validation database. We reported variable importance plots from full random forest and provided odds ratios for statistical inference of importance from multivariable logistic regression. Outcomes were death, cardiac arrest, hypotension, dysrhythmia, or respiratory failure within 5 days of PE.

resultsOf 1736 patients, 610 (35.1%) were low risk by sPESI and 72 (11.8%) experienced early deterioration. Of the 610, RV abnormality was present in 157 (25.7%) by CT, 121 (19.8%) by echocardiography, 132 (21.6%) by natriuretic peptide, and 107 (17.5%) by troponin. For deterioration, the receiver operating characteristics for full and reduced random forest prognostic models were 0.80 (0.77-0.82) and 0.71 (0.68-0.73), respectively. RV assessments were the top four in the variable importance plot for the random forest model. Echocardiography and CT significantly increased predicted probability of 5-day clinical deterioration by the multivariable logistic regression.

conclusionsA PE triaging strategy with RV imaging assessments had superior prognostic performance at classifying low risk for 5-day clinical deterioration versus one without.

Indexed as

Clinical DeteriorationPulmonary EmbolismVentricular Dysfunction, RightAcute DiseaseHeart VentriclesHumansPrognosisProspective StudiesRisk AssessmentSeverity of Illness Index

Identifiers

PMID35289978
PMCPMC11998612
OpenAlexW4220952161

What OpenQuestion holds

Textmetadata
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.