Evidence map›Paper›PMID 36096832›Full record

Observational studyBMC pulmonary medicine2022

A prediction model for major adverse cardiovascular events (MACE) in patients with coronavirus disease 2019 (COVID-19).

Dong Huang, Huan Yang, He Yu, Ting Wang, Zhu Chen, Rong Yao, Zongan Liang

Open access · goldAbstract readMulticenter StudyObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in BMC pulmonary medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

7 authors at 3 institutions in 1 country.

Dong HuangDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No 37 Guoxue Alley, Chengdu, 610041, Sichuan, China.
Huan YangDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No 37 Guoxue Alley, Chengdu, 610041, Sichuan, China.
He YuDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No 37 Guoxue Alley, Chengdu, 610041, Sichuan, China.
Ting WangDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No 37 Guoxue Alley, Chengdu, 610041, Sichuan, China.
Zhu ChenDepartment of Infectional Inpatient Ward Two, Chengdu Public Health Clinical Medical Center, Chengdu, Sichuan, China.
Rong YaoDepartment of Emergency Medicine, Emergency Medical Laboratory, West China Hospital, Sichuan University, No 37 Guoxue Alley, Chengdu, 610041, Sichuan, China. yaorong@wchscu.cn.
Zongan LiangDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No 37 Guoxue Alley, Chengdu, 610041, Sichuan, China. liangza@scu.edu.cn.
Sichuan University · CNWest China Hospital of Sichuan University · CNPublic Health Clinical Center of Chengdu · CN

Funding

the Emergency Response Project for New Coronavirus of Science and Technology Department of Sichuan Provincial 2020YFS0005 and 2020YFS0009
6 · The paper itself

Abstract

backgroundEmerging evidence shows that cardiovascular injuries and events in coronavirus disease 2019 (COVID-19) should be considered. The current study was conducted to develop an early prediction model for major adverse cardiovascular events (MACE) during hospitalizations of COVID-19 patients.

methodsThis was a retrospective, multicenter, observational study. Hospitalized COVID-19 patients from Wuhan city, Hubei Province and Sichuan Province, China, between January 14 and March 9, 2020, were randomly divided into a training set (70% of patients) and a testing set (30%). All baseline data were recorded at admission or within 24 h after admission to hospitals. The primary outcome was MACE during hospitalization, including nonfatal myocardial infarction, nonfatal stroke and cardiovascular death. The risk factors were selected by LASSO regression and multivariate logistic regression analysis. The nomogram was assessed by calibration curve and decision curve analysis (DCA).

resultsUltimately, 1206 adult COVID-19 patients were included. In the training set, 48 (5.7%) patients eventually developed MACE. Six factors associated with MACE were included in the nomogram: age, PaO

conclusionsWe developed and validated a nomogram to predict the development of MACE in hospitalized COVID-19 patients. More prospective multicenter studies are needed to confirm our results.

Indexed as

COVID-19Myocardial InfarctionAdultHumansNomogramsProspective StudiesRetrospective StudiesCOVID-19MACENomogramRisk factors

Identifiers

PMID36096832
PMCPMC9466355
OpenAlexW4295441951

What OpenQuestion holds

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LicenceCC BY
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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.