Evidence map›Paper›PMID 24714416›Full record

ArticlePloS one2014

Validation of a novel clinical prediction score for severe coronary artery diseases before elective coronary angiography.

Zhang-Wei Chen, Ying-Hua Chen, Ju-Ying Qian, Jian-Ying Ma, Jun-Bo Ge

Abstract read
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Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

10 citing papers in PubMed, 1 synthesis or guideline 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

5 authors.

Zhang-Wei ChenDepartment of Cardiology, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.
Ying-Hua ChenDepartment of Endocrinology Medicine, East Hospital affiliated to Tongji University, Shanghai, China.
Ju-Ying QianDepartment of Cardiology, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.
Jian-Ying MaDepartment of Cardiology, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.
Jun-Bo GeDepartment of Cardiology, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesCoronary artery disease (CAD) severity is associated with patient prognosis. However, few efficient scoring systems have been developed to screen severe CAD in patients with stable angina and suspected CAD before coronary angiography. Here, we present a novel scoring system for CAD severity before elective coronary angiography.

methodsFive hundred fifty-one patients with stable angina who were admitted for coronary angiography were enrolled in this study. Patients were divided into training (n = 347) and validation (n = 204) cohorts. Severe CAD was defined as having a Gensini score of 20 or more. All patients underwent echocardiography (ECG) to detect ejection fraction and aortic valve calcification (AVC). Multivariable analysis was applied to determine independent risk factors and develop the scoring system.

resultsIn the training cohort, age, male sex, AVC, abnormal ECG, diabetes, hyperlipidemia, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol were identified as independent factors for severe CAD by multivariable analysis, and the Severe Prediction Scoring (SPS) system was developed. C-indices of receiver operating characteristic (ROC) curves for severe CAD were 0.744 and 0.710 in the training and validation groups, respectively. The SPS system also performed well during calibration, as demonstrated by Hosmer-Lemeshow analysis in the validation group. Compared with the Diamond-Forrester score, the SPS system performed better for severe CAD prediction before elective coronary angiography.

conclusionsSevere CAD prediction was achieved by analyzing age, sex, AVC, ECG, diabetes status, and lipid levels. Angina patients who achieve high scores using this predicting system should undergo early coronary angiography.

Indexed as

AgedAngina PectorisCoronary AngiographyCoronary Artery DiseaseEchocardiographyElectrocardiographyFemaleHumansMaleMiddle AgedPrognosisReproducibility of ResultsRisk AssessmentRisk FactorsROC CurveSeverity of Illness Index

Identifiers

PMID24714416
PMCPMC3979855

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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.