Evidence map›Paper›PMID 37316323›Full record

ArticleBMJ open2023

Data-driven phenomapping for novel classification for cardiovascular outcomes compared with traditional obesity index: Tehran Lipid and Glucose Study.

Elahe Zare Borzeshi, Majid Valizadeh, Mohammad Hossein Panahi, Davood Khalili, Mostafa Mousavizadeh, Yadollah Mehrabi

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Elahe Zare BorzeshiDepartment of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0001-7646-3069
Majid ValizadehObesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohammad Hossein PanahiDepartment of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Davood KhaliliPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0003-4956-1039
Mostafa MousavizadehHeart Valve Disease Research Center, Rajaie Cardiovascular Medical and Research Center, Tehran, Iran.
Yadollah MehrabiDepartment of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran mehrabi@sbmu.ac.ir.
Research Institute for Endocrine Sciences · IRShahid Beheshti University of Medical Sciences · IRShaheed Rajaei Cardiovascular Medical and Research Center · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to propose a data-driven framework for classification of at-risk people for cardiovascular outcomes regarding obesity and metabolic syndrome.

designA population-based prospective cohort study with a long-term follow-up.

settingData from the Tehran Lipid and Glucose Study (TLGS) were interrogated.

participants12 808 participants of the TLGS cohort, aged ≥20 years who have followed for over 15 years were assessed.

main outcome measuresData for 12 808 participants, aged ≥20 years who have followed for over 15 years, collected through TLGS as a prospective, population-based cohort study, were analysed. Feature engineering followed by hierarchical clustering was used to determine meaningful clusters and novel endophenotypes. Cox regression was used to demonstrate the clinical validity of phenomapping. The performance of endophenotype compared with traditional classifications was evaluated by the value of Akaike information criterion/Bayesian information criterion. R software V.4.2 was employed.

resultsThe mean age was 42.1±14.9 years, 56.2% were female, 13.1%, 2.8% and 6.2% had experienced cardiovascular disease (CVD), CVD mortality and hard CVD, respectively. Low-risk cluster compared with the high risk had significant difference in age, body mass index, waist-to-hip ratio, 2 hours post load plasma glucose, triglyceride, triglycerides to high density lipoprotein ratio, education, marital status, smoking and the presence of metabolic syndrome. Eight distinct endophenotypes were detected with significantly different clinical characteristics and outcomes.

conclusionPhenomapping resulted in a novel classification of population with cardiovascular outcomes, which can, better, stratify individuals into homogeneous subclasses for prevention and intervention as an alternative of traditional methods solely based on either obesity or metabolic status. These findings have important clinical implications for a particular part of the Middle Eastern population for which it is a common practice to use tools/evidence derived from western populations with substantially different backgrounds and risk profiles.

Indexed as

Cardiovascular DiseasesMetabolic SyndromeAdultBayes TheoremCohort StudiesFemaleGlucoseHumansIranLipoproteins, HDLMaleMiddle AgedObesityProspective StudiesGlucoseLipoproteins, HDLcardiac epidemiologyepidemiologylipid disordersobesity

Identifiers

PMID37316323
PMCPMC10277045
OpenAlexW4380683059

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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.