Evidence map›Paper›PMID 35174226›Full record

ArticleFrontiers in cardiovascular medicine2021

Coronary Computed Tomography Angiographic Predictors of Non-culprit Territory Unrecognized Myocardial Infarction Assessed by Cardiac Magnetic Resonance in Non-ST-elevation Acute Coronary Syndrome.

Kazuki Matsuda, Masahiro Hoshino, Yoshihisa Kanaji, Tomoyo Sugiyama, Toru Misawa, Masahiro Hada, Tatsuhiro Nagamine, Kai Nogami, Kodai Sayama, Yun Teng and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 22% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
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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

14 authors at 2 institutions in 1 country.

Kazuki MatsudaDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Masahiro HoshinoDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Yoshihisa KanajiDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Tomoyo SugiyamaDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Toru MisawaDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Masahiro HadaDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Tatsuhiro NagamineDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Kai NogamiDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Kodai SayamaDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Yun TengDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Hiroki UenoDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Taishi YonetsuDepartment of Cardiovascular Medicine, Tokyo Medical and Dental University, Tokyo, Japan.
Tetsuo SasanoDepartment of Cardiovascular Medicine, Tokyo Medical and Dental University, Tokyo, Japan.
Tsunekazu KakutaDivision of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Tsuchiura Kyodo General Hospital · JPTokyo Medical and Dental University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study sought to assess the predictors of coronary computed tomography angiographic findings for non-infarct-related (non-IR) territory unrecognized myocardial infarction (UMI) in patients with a first episode of non-ST-elevation acute coronary syndrome (NSTE-ACS).

backgroundUMI detected by cardiac magnetic resonance imaging (CMR) is associated with adverse outcomes in patients with both acute coronary syndrome and chronic coronary syndrome. However, the association between the presence of UMI and coronary computed tomography angiographic (CCTA) findings remains unknown.

methodsWe investigated 158 patients with a first clinical episode of NSTE-ACS, who underwent pre-PCI 320-slice CCTA and uncomplicated urgent percutaneous coronary intervention (PCI) within 48 h of admission. In these patients, post-PCI CMR was performed within 30 days from urgent PCI and before non-IR lesion staged PCI. UMI was assessed using late gadolinium enhancement (LGE)-CMR by identifying regions of hyperenhancement with an ischemic distribution pattern in non-IR territories (non-IR UMI). CCTA analysis included qualitative and quantitative assessments of the culprit segment, Agatston score, mean peri-coronary fat attenuation index (FAI), epicardial fat volume (EFV) and epicardial fat attenuation (EFA).

resultsNon-IR UMI was detected in 30 vessel territories (9.7%, 30/308 vessels) of 28 patients (17.7%, 28/158 patients). The presence of low-attenuation plaque, spotty calcification, napkin ring sign, and positive remodeling was not significantly different between vessels with and without subtended non-IR UMI. Agatston score >30.0 (OR: 8.39, 95% confidence interval (CI): 2.17 to 32.45,

conclusionThe prevalence of non-IR UMI was 17.7 % in patients with first NSTE-ACS presentation. Agatston score, mean FAI, and coronary stenosis severity were independent CCTA predictors of the presence of non-IR UMI. The integrated CCTA assessment may help identify the presence of non-IR UMI before urgent PCI.

Indexed as

acute coronary syndromecardiac magnetic resonance imagingcoronary computed tomography angiographypercutaneous coronary interventionunrecognized myocardial infarction

Identifiers

PMID35174226
PMCPMC8841688
OpenAlexW4210629041

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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.