Evidence map›Paper›PMID 32436009›Full record

ArticleJournal of thrombosis and thrombolysis2021

Decreased size of the left anterior descending coronary artery is an independent predictor of deterioration in non-high-risk patients with acute pulmonary embolism.

Dong Jia, Yizhuo Gao

Abstract read
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Article in Journal of thrombosis and thrombolysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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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

2 authors at 1 institution in 1 country.

Dong JiaDepartment of Emergency Medicine, Shengjing Hospital of China Medical University, No. 36, Sanhao Street, Shenyang, China.
Yizhuo GaoDepartment of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, No. 36, Sanhao Street, Shenyang, China. gaoyizhuo.sy@hotmail.com.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To evaluate the efficacy of measuring left coronary artery size to predict deterioration in non-high-risk acute pulmonary embolism (PE) patients. This retrospective study enrolled non-high-risk acute PE patients from January 2011 to December 2019. Patient deterioration was defined as the occurrence of adverse events within 30 days of hospital admission. Patients with adverse events were sex- and age-matched to patients without adverse events. Risk stratification was performed. Cross-sectional areas (CSAs) of the left main and left anterior descending (LAD) coronary artery inlets were measured. The main pulmonary artery (MPA) inlet and outlet and MPA LAD plane, which adjoined the LAD in the MPA, were reconstructed. CSAs, perimeters, and hydraulic diameters were measured to evaluate MPA size and deformation. Cardiac volume was also measured. Quantitative parameters were divided into tertiles. After adjustment by risk stratification, univariate and multivariate analyses were performed. Correlations between different parameters were analysed. Seventy-three patients with adverse events were matched to 73 patients without adverse events. The results of the univariate and multivariate analyses revealed that LAD inlet CSAs (middle and high) predicted adverse events (odds ratio: 0.28 and 0.07, 95% confidence interval: 0.10-0.77 and 0.02-0.22, p = 0.013 and < 0.0001). LAD inlet CSA was strongly and negatively correlated with MPA LAD hydraulic diameter and CSA (correlation coefficients: - 0.643 and - 0.604, p < 0.001). LAD inlet CSA measurement would facilitate adverse event prediction in non-high-risk acute PE patients on the basis of risk stratification. The dilated MPA may involve the decrease in LAD inlet CSA.

Indexed as

Acute DiseaseAdultCoronary VesselsFemaleHumansMaleMiddle AgedPrognosisPulmonary EmbolismRetrospective StudiesComputed tomographyCoronary arteryPulmonary arteryPulmonary embolism

Identifiers

PMID32436009
OpenAlexW3028397477

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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.