Evidence map›Paper›PMID 35419856›Full record

ArticleClinical cardiology2022

Scoring systems of metabolic syndrome and prediction of cardiovascular events: A population based cohort study.

Nima Motamed, Hossein Ajdarkosh, Mohammad Hadi Karbalaie Niya, Mahshid Panahi, Behzad Farahani, Nader Rezaie, Mehdi Nikkhah, Amir H Faraji, Gholamreza Hemmasi, Dhayaneethie Perumal and 5 more

Open access · goldAbstract read
In one paragraph

Article in Clinical cardiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 11 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

15 authors at 3 institutions in 2 countries.

Nima MotamedDepartment of Social Medicine, Zanjan University of Medical Sciences, Zanjan, Iran.
Hossein AjdarkoshGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Mohammad Hadi Karbalaie NiyaGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Mahshid PanahiGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Behzad FarahaniDepartment of Cardiology, Iran University of Medical Sciences, Tehran, Iran.
Nader RezaieDepartment of Pulmonology, Firouzgar Hospital, Iran University of Medical Sciences, Tehran, Iran.
Mehdi NikkhahGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Amir H FarajiGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Gholamreza HemmasiGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Dhayaneethie PerumalFaculty of Science, Engineering and Computing, Kingston University, Kingston, UK.
G Hossein AshrafiCancer Theme SEC Faculty, Kingston University, London, UK.
Fahimeh Safarnezhad TameshkelGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Esmaeel GholizadehGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Mahmoodreza KhoonsariGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.
Farhad ZamaniGastrointestinal and Liver Diseases Research Center, Iran University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0001-7409-3412
Iran University of Medical Sciences · IRKingston University · GBZanjan University of Medical Sciences · IR

Funding

Iran University of Medical Sciences 1397-2-30-12380
6 · The paper itself

Abstract

BACKGROUND AND

aimsContinuous scoring systems were developed versus traditional dichotomous approaches to define metabolic syndrome. The current study was carried out to evaluate the ability of scoring systems to predict fatal and nonfatal cardiovascular events. MATERIALS AND

methodsThe data of 5147 individuals aged 18 years or more obtained from a population-based cohort study were analyzed. The occurrence of atherosclerotic cardiovascular disease (ASCVD) in the period of 7 years follow-up was considered as the associated outcome. Joint Interim Statement (JIS) definition, as a traditional definition of metabolic syndrome (MetS), and two versions of MetS scoring systems, based on standardized regression weights from structural equation modeling (SEM) and simple method for quantifying metabolic syndrome (siMS) were considered as potential predictors.

resultsThe scoring systems, particularly, based on SEM, were observed to have a significant association with composite cardiovascular events (HR = 1.388 [95% CI = 1.153-1.670], p = .001 in men and HR = 1.307 [0.95% CI = 1.120-1.526] in women) in multiple Cox proportional hazard regression analyses, whereas the traditional definition of MetS did not show any significant association. While both two scoring systems showed acceptable predictive abilities for cardiovascular events in women (MetS score based on SEM: area of under curve [AUC] = 0.7438 [95% CI = 0.6195-0.7903] and siMS: AUC = 0.7207 [95% CI = 0.6676-0.7738]), the two systems were not acceptable for identifying risk in men.

conclusionUnlike the dichotomous definition of MetS, the scoring systems showed an independent association with cardiovascular events. Scoring systems, particularly those based on SEM, may be useful for the prediction of cardiovascular events in women.

Indexed as

Cardiovascular DiseasesMetabolic SyndromeAdolescentAdultArea Under CurveCohort StudiesFemaleHumansMaleRisk Assessmentcardiovascular eventsmetabolic syndrome scoring systemstructural equation modeling

Identifiers

PMID35419856
PMCPMC9175260
OpenAlexW4223968562

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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.