title: Comparison of two surrogate estimates of insulin resistance to predict cardiovascular disease in apparently healthy individuals.
abstract: OBJECTIVE
  Insulin resistance is associated with a cluster of abnormalities that increase cardiovascular disease (CVD). Several indices have been proposed to identify individuals who are insulin resistant, and thereby at increased CVD risk. The aim of this study was to compare the abilities of 3 indices to accomplish that goal: 1) plasma triglyceride × glucose index (TG × G); 2) plasma triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-C); and 3) Metabolic Syndrome (MetS).
  
  
  RESULTS
  In a population sample of 723 individuals (486 women and 237 men, 50 ± 16 and 51 ± 16 years old, respectively), baseline demographic and metabolic variables known to increase CVD risk and incident CVD were compared among individuals defined as high vs. low risk by: TG × G; TG/HDL-C; or MetS. CVD risk profiles appeared comparable in high risk subjects, irrespective of criteria. Crude incidence of CVD events was increased in high risk subjects: 12.2 vs. 5.3% subjects/10 years, p = 0.005 defined by TG/HDL-C; 13.4 vs. 5.3% subjects/10 years, p = 0.002 defined by TG × G; and 13.4% vs. 4.5% of subjects/10 years, p < 0.001 in subjects with the MetS. The area under the ROC curves to predict CVD were similar, 0.66 vs. 0.67 for TG/HDL-C and TG × G, respectively. However, when adjusted by age, sex and multiple covariates, hazard ratios for incident CVD were significantly increased in high risk patients classified by either TG/HDL-C ratio (2.18, p = 0.021) or MetS (1.93, p = 0.037), but not by TG × G index (1.72, p = 0.087).
  
  
  CONCLUSIONS
  Although the 3 indices identify CVD risk comparably, the TG × G index seems somewhat less effective at predicting CVD.
authors.affiliation: Hospital Universitario General San Martín, La Plata, Buenos Aires, Argentina; Facultad de Ciencias Médicas, UNLP, Argentina. Electronic address: salazarlandea@gmail.com.
authors.forename: M R
authors.initials: MR
authors.lastname: Salazar
authors.affiliation: Facultad de Ciencias Médicas, UNLP, Argentina.
authors.forename: H A
authors.initials: HA
authors.lastname: Carbajal
authors.affiliation: Hospital Universitario General San Martín, La Plata, Buenos Aires, Argentina; Facultad de Ciencias Médicas, UNLP, Argentina.
authors.forename: W G
authors.initials: WG
authors.lastname: Espeche
authors.affiliation: Hospital Municipal de Rauch, Buenos Aires, Argentina.
authors.forename: M
authors.initials: M
authors.lastname: Aizpurúa
authors.affiliation: Hospital Universitario General San Martín, La Plata, Buenos Aires, Argentina; Facultad de Ciencias Médicas, UNLP, Argentina.
authors.forename: C A
authors.initials: CA
authors.lastname: Dulbecco
authors.affiliation: Stanford University School of Medicine, Stanford, CA, USA.
authors.forename: G M
authors.initials: GM
authors.lastname: Reaven
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis*; D008076:Cholesterol, HDL / Q000097:blood*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000175:diagnosis / Q000209:etiology*; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D006973:Hypertension / Q000097:blood / Q000175:diagnosis / Q000209:etiology*; D007333:Insulin Resistance; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000175:diagnosis / Q000209:etiology*; D008875:Middle Aged; D011237:Predictive Value of Tests; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D014280:Triglycerides / Q000097:blood*
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D008076:Cholesterol, HDL; D014280:Triglycerides
keywords: Cardiovascular disease; Insulin resistance; Metabolic syndrome; TG/HDL-C ratio; TG × G index