Evidence map›Paper›PMID 37275621›Full record

ArticleEmergency medicine international2023

Evaluation of the Canadian Clinical Practice Guidelines Risk Prediction Tool for Acute Aortic Syndrome: The RIPP Score.

Robert Ohle, Sarah McIsaac, Madison Van Drusen, Aaron Regis, Owen Montpellier, Mackenzie Ludgate, Oluwadamilola Bodunde, David W Savage, Krishan Yadav

Open access · goldAbstract read
In one paragraph

Article in Emergency medicine international, 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
2.1field-weighted citation impact, top 13% 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, 8 citations in OpenAlex.

  1. Article
  2. Review
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 at 4 institutions in 1 country.

Robert OhleThe Department of Emergency Medicine, Health Science North Research Institute, Northern Ontario School of Medicine University, Sudbury, Ontario, Canada.ORCID https://orcid.org/0000-0001-8263-0556
Sarah McIsaacDepartment of Critical Care, Department of Anaesthesia, Northern Ontario School of Medicine University, Sudbury, Ontario, Canada.
Madison Van DrusenDepartment of Undergraduate Medicine, University of Ottawa, Ottawa, Ontario, Canada.ORCID https://orcid.org/0000-0003-3555-9253
Aaron RegisDepartment of Undergraduate Medicine, Northern Ontario School of Medicine, Sudbury, Ontario, Canada.
Owen MontpellierDepartment of Undergraduate Medicine, Northern Ontario School of Medicine, Sudbury, Ontario, Canada.
Mackenzie LudgateDepartment of Undergraduate Medicine, Northern Ontario School of Medicine, Sudbury, Ontario, Canada.
Oluwadamilola BodundeDepartment of Undergraduate Medicine, Northern Ontario School of Medicine, Sudbury, Ontario, Canada.
David W SavageClinical Sciences Division, Nortner Ontario School of Medicine University, Thunder Bay, Ontario, Canada.ORCID https://orcid.org/0000-0003-2837-3127
Krishan YadavClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
NOSM University · CAOttawa Hospital · CAScience North · CAUniversity of Ottawa · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Acute aortic syndrome (AAS) is a rare clinical syndrome with a high mortality rate. The Canadian clinical practice guideline for the diagnosis of AAS was developed in order to reduce the frequency of misdiagnoses. As part of the guideline, a clinical decision aid was developed to facilitate clinician decision-making (RIPP score). The aim of this study is to validate the diagnostic accuracy of this tool and assess its performance in comparison to other risk prediction tools that have been developed. Methods: This was a historical case-control study. Consecutive cases and controls were recruited from three academic emergency departments from 2002-2020. Cases were identified through an admission, discharge, or death certificated diagnosis of acute aortic syndrome. Controls were identified through presenting complaint of chest, abdominal, flank, back pain, and/or perfusion deficit. We compared the clinical decision tools' C statistic and used the DeLong method to test for the significance of these differences and report sensitivity and specificity with 95% confidence intervals. Results: We collected data on 379 cases of acute aortic syndrome and 1340 potential eligible controls; 379 patients were randomly selected from the final population. The RIPP score had a sensitivity of 99.7% (98.54-99.99). This higher sensitivity resulted in a lower specificity (53%) compared to the other clinical decision aids (63-86%). The DeLong comparison of the C statistics found that the RIPP score had a higher C statistic than the ADDRS (-0.0423 (95% confidence interval -0.07-0.02); Conclusion: The Canadian clinical practice guideline's AAS clinical decision aid is a highly sensitive tool that uses readily available clinical information. It has the potential to improve diagnosis of AAS in the emergency department.

Identifiers

PMID37275621
PMCPMC10234704
OpenAlexW4378193473

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.