Evidence map›Paper›PMID 36685025›Full record

ArticleJournal of research in medical sciences : the official journal of Isfahan University of Medical Sciences2022

Coronary artery calcification: Effects on severity and survival in patients with COVID-19.

Abbas Arjmand Shabestari, Arash Mahdavi, Alireza Abrishami, Sam Alahyari, Mahdieh Molla

Open access · goldAbstract read
In one paragraph

Article in Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences, 2022. 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
0.4field-weighted citation impact, top 37% 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, 3 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

5 authors at 1 institution in 1 country.

Abbas Arjmand ShabestariDepartment of Radiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Arash MahdaviDepartment of Radiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Alireza AbrishamiDepartment of Radiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Sam AlahyariDepartment of Internal Medicine, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mahdieh MollaDepartment of Radiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Shahid Beheshti University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The aim of this study was to evaluate the effect of coronary artery calcification on disease severity and prognosis in patients with coronavirus disease-2019 (COVID-19). Materials and Methods: One hundred and forty-one patients with COVID-19 were included in this study. The severity of pulmonary involvement and calcification of coronary arteries were assessed by computed tomography scan and calcification was classified by two methods: Weston and segmental. In both the methods, patients were divided into three groups with scores of 0, 1-6, and 7-12, which are called groups 1, 2, and 3, respectively. Results: The mean age of patients was 54.26 ± 14.55. Difference in score of pulmonary involvement was reported to be significant between deceased and discharged patients (11.73 ± 5.26 and 7.28 ± 4.47, Conclusion: Coronary artery calcification in patients with COVID-19 has a significant association with poor prognosis. However, no significant relationship was observed between this issue and the severity.

Indexed as

Calcificationcoronary vesselscoronavirus disease-2019prognosis

Identifiers

PMID36685025
PMCPMC9854912
OpenAlexW4312614048

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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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.