Evidence map›Paper›PMID 34022791›Full record

ArticleBMC cardiovascular disorders2021

A prognostic nomogram for long-term major adverse cardiovascular events in patients with acute coronary syndrome after percutaneous coronary intervention.

Shuting Kong, Changxi Chen, Gaoshu Zheng, Hui Yao, Junfeng Li, Hong Ye, Xiaobo Wang, Xiang Qu, Xiaodong Zhou, Yucheng Lu and 1 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC cardiovascular disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Shuting KongDepartment of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Changxi ChenDepartment of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Gaoshu ZhengDepartment of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Hui YaoDepartment of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Junfeng LiDepartment of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Hong YeCardiac Interventional Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Xiaobo WangAffiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinghua, 321000, Zhejiang, China.
Xiang QuDepartment of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Xiaodong ZhouDepartment of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Yucheng LuThe First Clinical Medical College of Wenzhou Medical University, Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Hao ZhouDepartment of Cardiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China. wyzh66@126.com.ORCID 0000-0001-7964-2310
Wenzhou Medical University · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate prediction of major adverse cardiovascular events (MACEs) is very important for the management of acute coronary syndrome (ACS) patients. We aimed to construct an effective prognostic nomogram for individualized risk estimates of MACEs for patients with ACS after percutaneous coronary intervention (PCI).

methodsThis was a prospective study of patients with ACS after PCI from January 2013 to July 2019 (n = 2465). After removing patients with incomplete clinical information, a total of 1986 patients were randomly divided into evaluation (n = 1324) and validation (n = 662) groups. Predictors included in the nomogram were determined by a multivariate Cox proportional hazards regression model based on the training set. Receiver operating characteristic (ROC) curves and calibration curves were used to assess the discrimination and predictive accuracy of the nomogram, which were then compared with those of the classic models. The clinical utility of the nomogram was assessed by X-tile analysis and Kaplan-Meier curve analysis.

resultsIndependent prognostic factors, including lactate level, age, left anterior descending branch stenosis, right coronary artery stenosis, brain natriuretic peptide level, and left ventricular ejection fraction, were determined and contained in the nomogram. The nomogram achieved good areas under the ROC curve of 0.712-0.762 in the training set and 0.724-0.818 in the validation set and well-fitted calibration curves. In addition, participants could be divided into two risk groups (low and high) according to this model.

conclusionsA simple-to-use nomogram incorporating lactate level effectively predicted 6-month, 1-year, and 4-year MACE incidence among patients with ACS after PCI.

Indexed as

Decision Support TechniquesNomogramsPercutaneous Coronary InterventionAcute Coronary SyndromeAgedAngina, UnstableFemaleHumansMaleMiddle AgedNon-ST Elevated Myocardial InfarctionPredictive Value of TestsProspective StudiesReproducibility of ResultsRisk AssessmentRisk FactorsACS Nomogram predict MACE Risk

Identifiers

PMID34022791
PMCPMC8141252
OpenAlexW3164804038

What OpenQuestion holds

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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.