- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT07589374
Cf-PWV and TyG Index Study (RIGID-TyG)
Correlation Between Carotid-Femoral Pulse Wave Velocity and Triglyceride-Glucose Index and Its Derived Metrics
This study aims to investigate how metabolic health is related to arterial stiffness and daily blood pressure patterns. High blood pressure is one of the leading causes of heart disease worldwide, but cardiovascular risk is not determined only by average blood pressure values. Changes in blood vessel structure and metabolic function also play an important role in the development of cardiovascular disease.
Arterial stiffness reflects how flexible or rigid the arteries are. It can be measured using carotid-femoral pulse wave velocity (cf-PWV), which is considered a reliable and widely used method to assess vascular health. Increased arterial stiffness is associated with aging and higher cardiovascular risk.
At the same time, metabolic factors such as insulin resistance and central obesity are strongly linked to vascular damage. The triglyceride-glucose (TyG) index is a simple measure derived from routine blood tests and has been shown to reflect insulin resistance. Additional derived indices that combine TyG with body measurements (such as waist circumference and body mass index) may provide an even more comprehensive evaluation of metabolic risk.
Another important aspect of cardiovascular regulation is how blood pressure changes throughout the day. Blood pressure naturally rises in the morning after waking, a phenomenon known as the morning blood pressure surge. When this increase is excessive, it has been associated with a higher risk of cardiovascular events such as stroke and heart attack.
This study will evaluate the relationship between metabolic indices, arterial stiffness, and morning blood pressure patterns in adults undergoing ambulatory blood pressure monitoring as part of routine clinical care. The study will include both previously collected data and new participants evaluated using standardized methods.
No additional interventions will be performed, and all data will be collected as part of routine clinical evaluation. The results of this study may help improve cardiovascular risk assessment by integrating simple metabolic markers with vascular measurements and daily blood pressure behavior, potentially allowing earlier identification of individuals at higher risk.
Study Overview
Status
Detailed Description
Introduction
Hypertension remains a major global health problem and a leading contributor to cardiovascular morbidity and mortality. Large epidemiological studies have demonstrated a continuous and graded relationship between blood pressure levels and cardiovascular events, including myocardial infarction, stroke, and heart failure. However, traditional office blood pressure measurements do not fully capture the complexity of cardiovascular risk.
Arterial stiffness has emerged as a key marker of vascular aging and cardiovascular risk. Carotid-femoral pulse wave velocity (cf-PWV) is considered the gold standard non-invasive method for assessing aortic stiffness. Increased cf-PWV reflects cumulative vascular damage resulting from structural and functional alterations in the arterial wall, including elastin degradation, collagen deposition, vascular calcification, and endothelial dysfunction.
Insulin resistance is a central mechanism linking metabolic disorders to vascular dysfunction. It is associated with reduced nitric oxide bioavailability, increased sympathetic activity, chronic low-grade inflammation, and vascular remodeling. The triglyceride-glucose (TyG) index has been validated as a reliable surrogate marker of insulin resistance and has shown consistent associations with cardiometabolic outcomes.
Derived indices incorporating anthropometric parameters, such as TyG-WC, TyG-BMI, and TyG-WHtR, have been proposed to better capture the interaction between metabolic dysfunction and central adiposity. In addition, composite indices such as the body roundness index (BRI), metabolic score for insulin resistance (METS-IR), and cardiometabolic index (CMI) integrate multiple physiological domains and may provide incremental value in cardiovascular risk stratification.
Circadian blood pressure variation represents another important dimension of cardiovascular physiology. Blood pressure follows a daily rhythm, with a physiological increase in the early morning associated with sympathetic activation and hormonal changes. This phenomenon, known as the morning blood pressure surge (MBPS), has been associated with increased risk of cardiovascular events when exaggerated.
Arterial stiffness may amplify this morning increase in blood pressure due to reduced arterial compliance and impaired buffering of pulsatile flow. In addition, metabolic dysfunction may alter autonomic regulation and baroreflex sensitivity, further influencing circadian blood pressure patterns.
Despite strong biological plausibility, the integrated relationship between metabolic indices, arterial stiffness, and morning blood pressure parameters remains insufficiently explored. Understanding these interactions may improve early identification of individuals at increased cardiovascular risk.
Objectives
Primary Objective
To evaluate the association between arterial stiffness, measured by carotid-femoral pulse wave velocity, and the triglyceride-glucose (TyG) index.
Secondary Objectives
To assess associations between cf-PWV and TyG-derived indices (TyG-WC, TyG-BMI, TyG-WHtR); To evaluate associations between cf-PWV and composite metabolic indices (METS-IR, CMI, BRI); To investigate relationships between metabolic indices and morning blood pressure levels; To assess associations between metabolic indices and morning blood pressure surge (MBPS); To compare the performance of different metabolic indices in identifying increased arterial stiffness and morning hemodynamic load.
Methods Study Design and Data Sources
This is an observational, cross-sectional study with a prospective component, designed to evaluate the integrated relationship between metabolic indices, arterial stiffness, and circadian blood pressure patterns. The study adopts a hybrid design, combining data from two complementary sources: (1) previously collected data from an ethically approved research protocol and (2) prospectively collected data obtained under a standardized protocol.
Previously collected data will be used as secondary data, ensuring full anonymization and confidentiality. Prospectively recruited participants will provide written informed consent prior to inclusion. To ensure comparability, identical measurement protocols and definitions will be applied across both datasets.
Study Population
The study will include adults aged 18 to 65 years referred for ambulatory blood pressure monitoring (ABPM) as part of routine clinical evaluation in a specialized cardiovascular center. Participants will be included regardless of sex.
Only individuals not receiving antihypertensive treatment at the time of evaluation will be eligible for inclusion, in order to minimize the confounding effects of pharmacological therapy on arterial stiffness, metabolic indices, and circadian blood pressure patterns.
Participants will be classified according to 24-hour ABPM results into:
Normotensive individuals Untreated hypertensive individuals (defined as 24-hour mean blood pressure ≥130/80 mmHg) Clinical and Anthropometric Assessment
Baseline clinical data will include age, sex, and relevant medical history. Anthropometric measurements will be obtained using standardized procedures:
Body weight and height will be measured with participants wearing light clothing and no shoes; Body mass index (BMI) will be calculated as weight (kg) divided by height squared (m²); Waist circumference will be measured at the midpoint between the lowest rib and the iliac crest using a flexible tape measure.
In addition, the Body Roundness Index (BRI) will be calculated using a validated geometric formula incorporating waist circumference and height, providing an estimate of body fat distribution and central adiposity.
Office Blood Pressure Measurement
Office blood pressure (OBP) will be measured using a validated automated oscillometric device under standardized conditions. Measurements will be obtained after at least 5 minutes of seated rest, with the participant in a quiet environment.
Three consecutive readings will be recorded at short intervals, and the average of these measurements will be used for analysis. Heart rate will be recorded simultaneously.
Ambulatory Blood Pressure Monitoring (ABPM)
All participants will undergo 24-hour ABPM using a validated oscillometric device, applied to the non-dominant arm with an appropriately sized cuff.
The device will be programmed to obtain measurements:
Every 20 minutes during daytime (awake period) Every 30 minutes during nighttime (sleep period)
Daytime and nighttime periods will be defined based on individual sleep diaries. Only recordings meeting established quality criteria will be considered valid.
Mean systolic and diastolic blood pressure values will be calculated for:
24-hour period Daytime period Nighttime period
Hypertension will be defined based on a 24-hour mean blood pressure ≥130/80 mmHg.
Morning Blood Pressure and Morning Surge Definitions
Morning systolic and diastolic blood pressure will be defined as the average of readings obtained during the first two hours after awakening.
Morning blood pressure surge (MBPS) will be assessed using two complementary definitions:
Sleep-through MBPS (ST-MBPS): difference between morning systolic BP and the lowest nocturnal systolic BP value (including adjacent readings); Prewaking MBPS (PW-MBPS): difference between morning systolic BP and the average systolic BP during the two hours preceding awakening.
These indices will be analyzed as continuous variables and may also be evaluated across quartiles of metabolic indices.
Arterial Stiffness Assessment
Arterial stiffness will be assessed using carotid-femoral pulse wave velocity (cf-PWV), measured with a validated device under standardized conditions.
Participants will be evaluated in the supine position after at least 10 minutes of rest. Pulse waveforms will be recorded simultaneously at carotid and femoral sites.
At least three consecutive measurements will be obtained. For analysis, the mean of the two closest values will be used, provided that the difference between them is ≤0.5 m/s, ensuring measurement reproducibility and quality control.
Laboratory Data and Metabolic Indices
Laboratory data will be obtained from routine clinical tests performed under fasting conditions (minimum 8 hours), as requested by the treating physician.
The following parameters will be collected:
Fasting glucose Triglycerides HDL cholesterol
These values will be used to calculate metabolic indices:
Primary metabolic index TyG index: Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL) / 2] Derived indices TyG-WC = TyG × waist circumference TyG-BMI = TyG × BMI TyG-WHtR = TyG × waist-to-height ratio Composite indices METS-IR: Ln [(2 × glucose) + triglycerides] × BMI / Ln (HDL-C) CMI: (waist-to-height ratio) × (triglycerides / HDL-C) BRI: geometric index of body adiposity
All indices will be analyzed both as continuous variables and categorized into quartiles.
Study Variables Primary exposure: TyG index and derived metabolic indices Primary outcome: cf-PWV
Secondary outcomes:
Morning systolic and diastolic blood pressure ST-MBPS and PW-MBPS
Potential confounders will include:
Age Sex BMI 24-hour blood pressure Hypertension status Sample Size Considerations
The sample size was defined based on the primary association between cf-PWV and the TyG index, as well as the need to perform stratified analyses.
Given planned analyses involving quartiles of metabolic indices and stratification by hypertension status, a total sample size of approximately 800 participants was established to ensure adequate statistical power and stability of subgroup estimates.
Statistical Analysis
Continuous variables will be expressed as mean ± standard deviation or median (interquartile range), depending on distribution. Categorical variables will be presented as frequencies and percentages.
Participants will be categorized into quartiles according to metabolic indices. Comparisons across quartiles will be performed using analysis of variance (ANOVA) or appropriate non-parametric tests, with evaluation of linear trends.
Associations between metabolic indices and cf-PWV, as well as between metabolic indices and morning blood pressure parameters, will be assessed using linear regression models.
Multivariable models will be adjusted for predefined confounders based on biological plausibility. Interaction terms (e.g., metabolic indices × hypertension status) will be explored.
Additional analyses may include:
Concordance correlation coefficient (Lin's CCC) Bland-Altman analysis for bias assessment
A two-sided p-value <0.05 will be considered statistically significant.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Marco A VIEIRA-da-SILVA, MSc
- Phone Number: +55 (34) 99645-0117
- Email: vilelamartin@uol.com.br
Study Contact Backup
- Name: Marco A de Almeida, MD
- Phone Number: +55 (34) 99122-7594
- Email: telelo60@hotmail.com
Study Locations
-
-
São Paulo
-
São José do Rio Preto, São Paulo, Brazil, 15090-000
- Medicine School of São José do Rio Preto
-
Contact:
- Jose F VILELA-MARTIN, PhD
- Phone Number: +55 (17) 99155-5084
- Email: vilelamartin@uol.com.br
-
Contact:
- Kleber A de Oliveira, MSc
- Phone Number: +55 (17) 99209-4646
- Email: kleberapoliveira095@gmail.com
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Sub-Investigator:
- Luciana N COSENSO-MARTIN, PhD
-
Sub-Investigator:
- Marco A VIEIRA-da-SILVA, MSc
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Sub-Investigator:
- Marco A de Almeida, MD
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Adults aged 18 to 65 years;
- Both sexes;
- Referred for ambulatory blood pressure monitoring (ABPM) as part of routine clinical evaluation;
- Not receiving antihypertensive medication at the time of assessment;
- Availability of valid 24-hour ABPM data;
- Availability of carotid-femoral pulse wave velocity (cf-PWV) measurement;
- Availability of fasting laboratory data, including glucose and triglycerides, for calculation of the triglyceride-glucose (TyG) index;
- Ability and willingness to provide written informed consent (for prospectively recruited participants).
Exclusion Criteria:
- Use of antihypertensive medication at the time of evaluation;
- Cardiac arrhythmias that may interfere with accurate blood pressure or pulse wave velocity measurements;
- Invalid or poor-quality ambulatory blood pressure monitoring (ABPM) recordings;
- Inability to obtain reliable carotid-femoral pulse wave velocity (cf-PWV) measurements;
- Presence of severe vascular disease or conditions affecting arterial waveform assessment;
- Missing essential clinical, laboratory, or hemodynamic data required for the primary analysis;
- Pregnancy;
- Refusal or inability to provide informed consent (for prospectively recruited participants).
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
|---|
|
Normotensive participants
Adults with normal 24-hour blood pressure based on ABPM (< 130/80 mmHg)
|
|
Untreated hypertensive participants
Adults with elevated 24-hour blood pressure (≥130/80 mmHg) not receiving antihypertensive treatment.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Carotid-femoral pulse wave velocity (cf-PWV)
Time Frame: Baseline
|
Carotid-femoral pulse wave velocity (cf-PWV) will be measured as a marker of arterial stiffness using a validated non-invasive device under standardized conditions.
The association between cf-PWV and the triglyceride-glucose (TyG) index will be evaluated.
|
Baseline
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Morning systolic blood pressure
Time Frame: Average systolic blood pressure during the first two hours after awakening, obtained from 24-hour ambulatory blood pressure monitoring (ABPM).
|
Baseline
|
Average systolic blood pressure during the first two hours after awakening, obtained from 24-hour ambulatory blood pressure monitoring (ABPM).
|
|
Morning diastolic blood pressure
Time Frame: Average diastolic blood pressure during the first two hours after awakening, obtained from ABPM.
|
Baseline
|
Average diastolic blood pressure during the first two hours after awakening, obtained from ABPM.
|
|
Sleep-through morning blood pressure surge
Time Frame: Difference between morning systolic blood pressure and the lowest nocturnal systolic blood pressure value.
|
Baseline
|
Difference between morning systolic blood pressure and the lowest nocturnal systolic blood pressure value.
|
|
Prewaking morning blood pressure surge
Time Frame: Difference between morning systolic blood pressure and the average systolic blood pressure during the two hours preceding awakening.
|
Baseline
|
Difference between morning systolic blood pressure and the average systolic blood pressure during the two hours preceding awakening.
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Jose F VILELA-MARTIN, PhD, Medicine School of São José do Rio Preto - SP - Brazil
Publications and helpful links
General Publications
- Parati G, Stergiou G, O'Brien E, Asmar R, Beilin L, Bilo G, Clement D, de la Sierra A, de Leeuw P, Dolan E, Fagard R, Graves J, Head GA, Imai Y, Kario K, Lurbe E, Mallion JM, Mancia G, Mengden T, Myers M, Ogedegbe G, Ohkubo T, Omboni S, Palatini P, Redon J, Ruilope LM, Shennan A, Staessen JA, vanMontfrans G, Verdecchia P, Waeber B, Wang J, Zanchetti A, Zhang Y; European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability. European Society of Hypertension practice guidelines for ambulatory blood pressure monitoring. J Hypertens. 2014 Jul;32(7):1359-66. doi: 10.1097/HJH.0000000000000221.
- Arima H, Barzi F, Chalmers J. Mortality patterns in hypertension. J Hypertens. 2011 Dec;29 Suppl 1:S3-7. doi: 10.1097/01.hjh.0000410246.59221.b1.
- Van Bortel LM, Laurent S, Boutouyrie P, Chowienczyk P, Cruickshank JK, De Backer T, Filipovsky J, Huybrechts S, Mattace-Raso FU, Protogerou AD, Schillaci G, Segers P, Vermeersch S, Weber T; Artery Society; European Society of Hypertension Working Group on Vascular Structure and Function; European Network for Noninvasive Investigation of Large Arteries. Expert consensus document on the measurement of aortic stiffness in daily practice using carotid-femoral pulse wave velocity. J Hypertens. 2012 Mar;30(3):445-8. doi: 10.1097/HJH.0b013e32834fa8b0.
- Townsend RR, Wilkinson IB, Schiffrin EL, Avolio AP, Chirinos JA, Cockcroft JR, Heffernan KS, Lakatta EG, McEniery CM, Mitchell GF, Najjar SS, Nichols WW, Urbina EM, Weber T; American Heart Association Council on Hypertension. Recommendations for Improving and Standardizing Vascular Research on Arterial Stiffness: A Scientific Statement From the American Heart Association. Hypertension. 2015 Sep;66(3):698-722. doi: 10.1161/HYP.0000000000000033. Epub 2015 Jul 9. No abstract available.
- Lewington S, Clarke R, Qizilbash N, Peto R, Collins R; Prospective Studies Collaboration. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet. 2002 Dec 14;360(9349):1903-13. doi: 10.1016/s0140-6736(02)11911-8.
- Franklin SS, Gustin W 4th, Wong ND, Larson MG, Weber MA, Kannel WB, Levy D. Hemodynamic patterns of age-related changes in blood pressure. The Framingham Heart Study. Circulation. 1997 Jul 1;96(1):308-15. doi: 10.1161/01.cir.96.1.308.
- Chirinos JA, Segers P, Hughes T, Townsend R. Large-Artery Stiffness in Health and Disease: JACC State-of-the-Art Review. J Am Coll Cardiol. 2019 Sep 3;74(9):1237-1263. doi: 10.1016/j.jacc.2019.07.012.
- O'Brien E, Parati G, Stergiou G, Asmar R, Beilin L, Bilo G, Clement D, de la Sierra A, de Leeuw P, Dolan E, Fagard R, Graves J, Head GA, Imai Y, Kario K, Lurbe E, Mallion JM, Mancia G, Mengden T, Myers M, Ogedegbe G, Ohkubo T, Omboni S, Palatini P, Redon J, Ruilope LM, Shennan A, Staessen JA, vanMontfrans G, Verdecchia P, Waeber B, Wang J, Zanchetti A, Zhang Y; European Society of Hypertension Working Group on Blood Pressure Monitoring. European Society of Hypertension position paper on ambulatory blood pressure monitoring. J Hypertens. 2013 Sep;31(9):1731-68. doi: 10.1097/HJH.0b013e328363e964.
- Muntner P, Shimbo D, Carey RM, Charleston JB, Gaillard T, Misra S, Myers MG, Ogedegbe G, Schwartz JE, Townsend RR, Urbina EM, Viera AJ, White WB, Wright JT Jr. Measurement of Blood Pressure in Humans: A Scientific Statement From the American Heart Association. Hypertension. 2019 May;73(5):e35-e66. doi: 10.1161/HYP.0000000000000087.
- Johnson AW, Hissen SL, Macefield VG, Brown R, Taylor CE. Magnitude of Morning Surge in Blood Pressure Is Associated with Sympathetic but Not Cardiac Baroreflex Sensitivity. Front Neurosci. 2016 Sep 8;10:412. doi: 10.3389/fnins.2016.00412. eCollection 2016.
- Bilo G, Grillo A, Guida V, Parati G. Morning blood pressure surge: pathophysiology, clinical relevance and therapeutic aspects. Integr Blood Press Control. 2018 May 24;11:47-56. doi: 10.2147/IBPC.S130277. eCollection 2018.
- Renna NF, Ramirez JM, Murua M, Bernasconi PA, Repetto JM, Verdugo RA, Farez BG, Miatello RM, Diez ER. Morning blood pressure surge as a predictor of cardiovascular events in patients with hypertension. Blood Press Monit. 2023 Jun 1;28(3):149-157. doi: 10.1097/MBP.0000000000000641. Epub 2023 Apr 13.
- Booth JN 3rd, Jaeger BC, Huang L, Abdalla M, Sims M, Butler M, Muntner P, Shimbo D. Morning Blood Pressure Surge and Cardiovascular Disease Events and All-Cause Mortality in Blacks: The Jackson Heart Study. Hypertension. 2020 Mar;75(3):835-843. doi: 10.1161/HYPERTENSIONAHA.119.14233. Epub 2020 Feb 3.
- Bombelli M, Fodri D, Toso E, Macchiarulo M, Cairo M, Facchetti R, Dell'Oro R, Grassi G, Mancia G. Relationship among morning blood pressure surge, 24-hour blood pressure variability, and cardiovascular outcomes in a white population. Hypertension. 2014 Nov;64(5):943-50. doi: 10.1161/HYPERTENSIONAHA.114.03675. Epub 2014 Aug 25.
- Kario K. Morning surge in blood pressure and cardiovascular risk: evidence and perspectives. Hypertension. 2010 Nov;56(5):765-73. doi: 10.1161/HYPERTENSIONAHA.110.157149. Epub 2010 Oct 11. No abstract available.
- Kario K, Pickering TG, Umeda Y, Hoshide S, Hoshide Y, Morinari M, Murata M, Kuroda T, Schwartz JE, Shimada K. Morning surge in blood pressure as a predictor of silent and clinical cerebrovascular disease in elderly hypertensives: a prospective study. Circulation. 2003 Mar 18;107(10):1401-6. doi: 10.1161/01.cir.0000056521.67546.aa.
- Wakabayashi I, Daimon T. The "cardiometabolic index" as a new marker determined by adiposity and blood lipids for discrimination of diabetes mellitus. Clin Chim Acta. 2015 Jan 1;438:274-8. doi: 10.1016/j.cca.2014.08.042. Epub 2014 Sep 6.
- Liu H, Meng C, Wang Z, Liu C, Yu C, Li Z. Association of Novel Insulin Resistance Indices with Blood Pressure in New-Onset Hypertension and Elevated Blood Pressure Individuals: A Cross-Sectional Study. Diabetes Metab Syndr Obes. 2023 Dec 5;16:3953-3965. doi: 10.2147/DMSO.S432049. eCollection 2023.
- Thomas DM, Bredlau C, Bosy-Westphal A, Mueller M, Shen W, Gallagher D, Maeda Y, McDougall A, Peterson CM, Ravussin E, Heymsfield SB. Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obesity (Silver Spring). 2013 Nov;21(11):2264-71. doi: 10.1002/oby.20408. Epub 2013 Jun 11.
- Xuan W, Liu D, Zhong J, Luo H, Zhang X. Impacts of Triglyceride Glucose-Waist to Height Ratio on Diabetes Incidence: A Secondary Analysis of A Population-Based Longitudinal Data. Front Endocrinol (Lausanne). 2022 Jul 22;13:949831. doi: 10.3389/fendo.2022.949831. eCollection 2022.
- Song K, Xu Y, Wu S, Zhang X, Wang Y, Pan S. Research status of triglyceride glucose-body mass index (TyG-BMI index). Front Cardiovasc Med. 2025 Jul 18;12:1597112. doi: 10.3389/fcvm.2025.1597112. eCollection 2025.
- Cui H, Liu Q, Wu Y, Cao L. Cumulative triglyceride-glucose index is a risk for CVD: a prospective cohort study. Cardiovasc Diabetol. 2022 Feb 10;21(1):22. doi: 10.1186/s12933-022-01456-1.
- Avagimyan A, Pogosova N, Fogacci F, Aghajanova E, Djndoyan Z, Patoulias D, Sasso LL, Bernardi M, Faggiano A, Mohammadifard N, Neglia D, Carugo S, Cicero A, Rizzo M, Biondi-Zoccai G, De Caterina R, Sarrafzadegan N. Triglyceride-glucose index (TyG) as a novel biomarker in the era of cardiometabolic medicine. Int J Cardiol. 2025 Jan 1;418:132663. doi: 10.1016/j.ijcard.2024.132663. Epub 2024 Oct 18.
- Simental-Mendia LE, Rodriguez-Moran M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord. 2008 Dec;6(4):299-304. doi: 10.1089/met.2008.0034.
- Schram MT, Henry RM, van Dijk RA, Kostense PJ, Dekker JM, Nijpels G, Heine RJ, Bouter LM, Westerhof N, Stehouwer CD. Increased central artery stiffness in impaired glucose metabolism and type 2 diabetes: the Hoorn Study. Hypertension. 2004 Feb;43(2):176-81. doi: 10.1161/01.HYP.0000111829.46090.92. Epub 2003 Dec 29.
- Kalil GZ, Haynes WG. Sympathetic nervous system in obesity-related hypertension: mechanisms and clinical implications. Hypertens Res. 2012 Jan;35(1):4-16. doi: 10.1038/hr.2011.173. Epub 2011 Nov 3.
- Vlachopoulos C, Aznaouridis K, Stefanadis C. Prediction of cardiovascular events and all-cause mortality with arterial stiffness: a systematic review and meta-analysis. J Am Coll Cardiol. 2010 Mar 30;55(13):1318-27. doi: 10.1016/j.jacc.2009.10.061.
Study record dates
Study Major Dates
Study Start (Estimated)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- RIGID-TyG
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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