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Enregistrement W4311426544 · doi:10.1016/s2666-7568(22)00247-1

Association of the triglyceride glucose index as a measure of insulin resistance with mortality and cardiovascular disease in populations from five continents (PURE study): a prospective cohort study

2022· article· en· W4311426544 sur OpenAlexafffund
Patricio López‐Jaramillo, Diego Gómez-Arbeláez, Daniel Martínez-Bello, Marc Evans M. Abat, Khalid F. AlHabib, Álvaro Avezum, О. Л. Барбараш, Jephat Chifamba, Maria Luz Díaz, Sadi Güleç, Noor Hassim Ismail, Romaina Iqbal, Roya Kelishadi, Rasha Khatib, Fernando Laņas, Naomi Levitt, Yang Li, Viswanathan Mohan, Prem Mony, Paul Poirier, Annika Rosengren, Biju Soman, Chuangshi Wang, Yang Wang, Karen Yeates, Rita Yusuf, Afzalhussein Yusufali, Katarzyna Zatońska, Sumathy Rangarajan, Salim Yusuf

Notice bibliographique

RevueThe Lancet Healthy Longevity · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueDiabetes, Cardiovascular Risks, and Lipoproteins
Établissements canadiensMcMaster UniversityQueen's UniversityHamilton Health SciencesUniversité LavalPopulation Health Research InstituteInstitut Universitaire de Cardiologie et de Pneumologie de Québec
Organismes subventionnairesFuwai Hospital, Chinese Academy of Medical SciencesPhilippine Council for Health Research and DevelopmentServierKementerian Sains, Teknologi dan InovasiIndian Council of Medical ResearchSouth African Medical Research CouncilCanadian Institutes of Health ResearchUnited Nations Relief and Works Agency for Palestine RefugeesRiksförbundet HjärtLungDairy Farmers of CanadaPublic Health Agency of CanadaNovartis Pharmaceuticals CorporationMinistry of Higher Education, MalaysiaAstraZeneca CanadaSanofiBoehringer IngelheimVetenskapsrådetHeart and Stroke Foundation of CanadaOntario Ministry of Health and Long-Term CareHamilton Health SciencesMinisterstwo Edukacji i NaukiSaudi Heart AssociationGlaxoSmithKlineDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)AstraZeneca
Mots-clésInsulin resistanceTriglycerideMedicineProspective cohort studyInternal medicineDiseaseCohort studyIndex (typography)CohortInsulinDemographyCholesterol

Résumé

récupéré en direct d'OpenAlex

Background The triglyceride glucose (TyG) index is an easily accessible surrogate marker of insulin resistance, an important pathway in the development of type 2 diabetes and cardiovascular diseases. However, the association of the TyG index with cardiovascular diseases and mortality has mainly been investigated in Asia, with few data available from other regions of the world. We assessed the association of insulin resistance (as determined by the TyG index) with mortality and cardiovascular diseases in individuals from five continents at different levels of economic development, living in urban or rural areas. We also examined whether the associations differed according to the country's economical development. Methods We used the TyG index as a surrogate measure for insulin resistance. Fasting triglycerides and fasting plasma glucose were measured at the baseline visit in 141 243 individuals aged 35–70 years from 22 countries in the Prospective Urban Rural Epidemiology (PURE) study. The TyG index was calculated as Ln (fasting triglycerides [mg/dL] x fasting plasma glucose [mg/dL]/2). We calculated hazard ratios (HRs) using a multivariable Cox frailty model with random effects to test the associations between the TyG index and risk of cardiovascular diseases and mortality. The primary outcome of this analysis was the composite of mortality or major cardiovascular events (defined as death from cardiovascular causes, and non-fatal myocardial infarction, or stroke). Secondary outcomes were non-cardiovascular mortality, cardiovascular mortality, all myocardial infarctions, stroke, and incident diabetes. We also did subgroup analyses to examine the magnitude of associations between insulin resistance (ie, the TyG index) and outcome events according to the income level of the countries. Findings During a median follow-up of 13·2 years (IQR 11·9–14·6), we recorded 6345 composite cardiovascular diseases events, 2030 cardiovascular deaths, 3038 cases of myocardial infarction, 3291 cases of stroke, and 5191 incident cases of type 2 diabetes. After adjusting for all other variables, the risk of developing cardiovascular diseases increased across tertiles of the baseline TyG index. Compared with the lowest tertile of the TyG index, the highest tertile (tertile 3) was associated with a greater incidence of the composite outcome (HR 1·21; 95% CI 1·13–1·30), myocardial infarction (1·24; 1·12–1·38), stroke (1·16; 1·05–1·28), and incident type 2 diabetes (1·99; 1·82–2·16). No significant association of the TyG index was seen with non-cardiovascular mortality. In low-income countries (LICs) and middle-income countries (MICs), the highest tertile of the TyG index was associated with increased hazards for the composite outcome (LICs: HR 1·31; 95% CI 1·12–1·54; MICs: 1·20; 1·11–1·31; p interaction =0·01), cardiovascular mortality (LICs: 1·44; 1·15–1·80; p interaction =0·01), myocardial infarction (LICs: 1·29; 1·06–1·56; MICs: 1·26; 1·10–1·45; p interaction =0·08), stroke (LICs: 1·35; 1·02–1·78; MICs: 1·17; 1·05–1·30; p interaction =0·19), and incident diabetes (LICs: 1·64; 1·38–1·94; MICs: 2·68; 2·40–2·99; p interaction <0·0001). In contrast, in high-income countries, higher TyG index tertiles were only associated with an increased hazard of incident diabetes (2·95; 2·25–3·87; p interaction <0·0001), but not of cardiovascular diseases or mortality. Interpretation The TyG index is significantly associated with future cardiovascular mortality, myocardial infarction, stroke, and type 2 diabetes, suggesting that insulin resistance plays a promoting role in the pathogenesis of cardiovascular and metabolic diseases. Potentially, the association between the TyG index and the higher risk of cardiovascular diseases and type 2 diabetes in LICs and MICs might be explained by an increased vulnerability of these populations to the presence of insulin resistance. Funding Full funding sources are listed at the end of the paper (see Acknowledgments).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,012

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,028
Tête enseignante GPT0,286
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations345
Publié2022
Routes d'admission2
Résumé présentoui

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