Evidence map›Paper›PMID 34830723›Full record

ArticleJournal of clinical medicine2021

Use of Coronary CT Angiography to Predict Obstructive Lesions in Patients with Chest Pain without Enzyme and ST-Segment Elevation.

June-Sung Kim, Youn-Jung Kim, Yo Sep Shin, Shin Ahn, Won Young Kim

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2021. 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
0.1field-weighted citation impact, top 48% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

5 authors at 1 institution in 1 country.

June-Sung KimDepartment of Emergency Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.
Youn-Jung KimDepartment of Emergency Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.
Yo Sep ShinDepartment of Emergency Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.
Shin AhnDepartment of Emergency Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.
Won Young KimDepartment of Emergency Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea.ORCID 0000-0002-6904-5966
Ulsan College · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is challenging to rule out acute coronary syndrome among chest pain patients without both ST-segment elevation in electrocardiography and troponin elevation at emergency departments (ED). The purpose of this study was to develop a prediction model for rapidly determining the occurrence of significant stenosis in coronary computed tomography angiography (CCTA). Retrospective observational cohort study was conducted with 904 patients who had presented with chest pain without troponin elevation and ST-segment changes and underwent CCTA between January 2017 and December 2018. The primary endpoint was the presence of significant stenosis on CCTA, defined as narrowing above 70% diameter. The logistic regression model was used for development a new predictive model. One hundred and thirty-four patients (14.8%) were shown severe stenosis. The independent associated factors for significant stenosis were age ≥65 years, male, diabetes, history of acute coronary syndrome, and typical chest pain. Based these results, we developed a new prediction model. The area under the curve was 0.782 (95% confidence interval 0.742-0.822). Moreover, score of ≥5 was chosen as cut-off values with 86.6% sensitivity and 56.4% specificity. In conclusion, among chest pain patients without ST changes and troponin elevation, the new score will be helpful to identify potential candidate for CCTA such as patients with significant stenosis.

Indexed as

acute coronary syndromechest paincoronary computed tomography angiographyemergency department

Identifiers

PMID34830723
PMCPMC8625085
OpenAlexW3216978357

What OpenQuestion holds

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LicenceCC BY
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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.