Triglyceride-glucose (TyG) index is a predictor of arterial stiffness, incidence of diabetes, cardiovascular disease, and all-cause and cardiovascular mortality: A longitudinal two-cohort analysis

Impact of the Triglyceride-Glucose index on all-cause and cardiovascular mortalities across different metabolic health and obesity statuses in US adults

BACKGROUND

Data for the study cohort were sourced from the National Health and Nutrition Examination Survey (1999-2018). Study participants were classified as obese (BMI ≥ 30 kg/m²) or nonobese (BMI < 30 kg/m²) then further categorized as metabolically healthy or unhealthy on the basis of metabolic syndrome criteria, resulting in four groups: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy nonobese (MHNO), and metabolically unhealthy nonobese (MUNO). Complex sampling statistical methods were employed for descriptive analysis. The associations between the TyG index and mortality, including all-cause and cardiovascular mortalities, were examined by using multivariable Cox regression and restricted cubic splines (RCS). The reliability of the results was confirmed through multiple sensitivity analyses.

METHODS

Data for the study cohort were sourced from the National Health and Nutrition Examination Survey (1999-2018). Study participants were classified as obese (BMI ≥ 30 kg/m²) or nonobese (BMI < 30 kg/m²) then further categorized as metabolically healthy or unhealthy on the basis of metabolic syndrome criteria, resulting in four groups: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy nonobese (MHNO), and metabolically unhealthy nonobese (MUNO). Complex sampling statistical methods were employed for descriptive analysis. The associations between the TyG index and mortality, including all-cause and cardiovascular mortalities, were examined by using multivariable Cox regression and restricted cubic splines (RCS). The reliability of the results was confirmed through multiple sensitivity analyses.

RESULTS

A total of 16 179 participants were included, with a median follow-up of 129 months. Over this follow-up period, 1875 participants (11.59%) died from all causes, including 568 (3.51%) who died due to cardiovascular diseases. After adjustment for confounding variables, the TyG index significantly predicted mortality in the overall and metabolically unhealthy populations: for each one standard deviation increase in the TyG index, all-cause mortality increased by 1.42 times (95% confidence interval [CI]: 1.27, 1.58) in the overall population, by 1.62 times (95% CI: 1.36, 1.93) in the MUNO group, and by 1.47 times (95% CI: 1.26, 1.71) in the MUO group. Cardiovascular mortality in the overall population increased by 1.52 times (95% CI: 1.27, 1.82), that in the MUNO group increased by 2.01 times (95% CI: 1.49, 2.72), and that in the MUO group increased by 1.47 times (95% CI: 1.14, 1.88). No significant association was found in the metabolically healthy populations regardless of obesity status. RCS and sensitivity analyses further confirmed and visualized these conclusions.

CONCLUSIONS

The TyG index is positively correlated with mortality risk in the overall and metabolically unhealthy populations but not in the metabolically healthy populations. This finding indicates that the predictive value of the TyG index for mortality differs across populations, highlighting the necessity of accounting for metabolic status when the TyG index is used for prognostic evaluation.

The association between the triglyceride-glucose index with all-cause and cardiovascular mortality within the infertility population

BACKGROUND

The relationship between triglyceride-glucose (TyG) index and all-cause or cardiovascular mortality among infertile women remains unclear. In this study, we intended to utilize a national cohort from National Health and Nutrition Examination Survey (NHANES) to check the association between them.

METHODS

Ten datasets from the NHANES database spanning almost 20 years were used as the data source and were combined within National Death Index for mortality follow-up. Multiple-variable Cox proportionate hazards regression models and three others were employed in this study to for assessing relationships among TyG index levels with all-cause and cardiovascular mortality. SPSS (version 29.0) and online websites were utilized for conducting the primary statistical analyses.

RESULTS

1,450 female participants were identified in this study. The samples were classified based on TyG index quartiles (7.05-11.95). The TyG index had a mean of 8.58±0.66. Participants with higher TyG indices were older-aged, had greater body mass index (BMI), and a stronger likelihood of having hypertension and diabetes (P < 0.05). Participants whose TyG indices were higher were older in age, along with increased BMI, and blood pressure along with diabetes (P < 0.05). Significant positive associations were observed among the TyG index and total mortality in the crude model (HR: 1.81, 95% CI: 1.27-2.58). Correlation persisted in Model 2 (following the adjustment of age and race) and Model 3 (following the adjustment of age, race, BMI, education, family poverty income ratio, smoking and drinking habits, menstrual regularity, hypertension, and diabetes). The TyG index did not affect the cardiovascular mortality in infertile women.

CONCLUSION

TyG index levels were in positive association with all-cause mortality within the female infertile population.

Triglyceride-glucose index: a novel predictor of major adverse cardiovascular events and cerebrovascular events in patients with acute ST-segment elevation myocardial infarction

INTRODUCTION

Numerous studies have indicated the association of the triglyceride-glucose index (TyG) index with coronary artery disease, particularly myocardial infarction. However, limited mention exists regarding the predictive effects of major adverse cardiovascular events (MACE) and major adverse cardiac and cerebrovascular events (MACCE) in patients with ST-segment Elevation Myocardial Infarction (STEMI). This study aimed to investigate the predictive role of the TyG index on MACE and MACCE within 30 days in patients with STEMI.

METHODS

This study enrolled 586 patients with STEMI and conducted lipid, glucose, and myocardial biochemical testing. The TyG index was calculated; univariate analysis, multivariate analysis, and logistic regression analysis were employed to further investigate the correlation of the TyG index with MACE and MACCE. Subsequently, restricted cubic spline (RCS) analysis was conducted to determine whether they exhibit a linear correlation.

RESULTS

The study reported 105 MACCE patients. The results revealed a significant positive correlation between the TyG index and the occurrence of MACE and MACCE (odds ratio [OR] = 1.461, 95% confidence interval [CI] [1.091-1.956], p = 0.011 and OR = 1.427, 95%CI [1.064-1.914], p = 0.017, respectively). In univariate and multivariate analysis, the TyG index remains correlated with MACE and MACCE even after adjusting for related variables. Subsequent RCS analysis, accounting for different factors such as age, white blood cell count, and N-terminal pro-B-type natriuretic peptide (NT-proBNP), indicated that the correlation of TyG index with MACE and MACCE remains linear (p-non-linear = 0.662, p-non-linear = 0.781, respectively).

CONCLUSION

The TyG index effectively predicts MACE and MACCE in patients with STEMI within 30 days.

CLINICAL TRIAL NUMBER

Not applicable.

Associations of the triglyceride-glucose index and triglyceride-glucose/body mass index with all-cause mortality in Chinese centenarians

BACKGROUND

The triglyceride-glucose (TyG) index and triglyceride-glucose/body mass index (TyG-BMI) have been shown to be associated with cardiovascular and cerebrovascular disorders and the risk of death. The aim of this study was to explore the relationships of the TyG index and TyG-BMI with all-cause mortality among Chinese centenarians.

METHODS

Data from the China Hainan Centenarian Cohort Study (CHCCS) were analyzed. Eligible centenarians were divided into quartiles on the basis of their TyG and TyG-BMI indices. Kaplan‒Meier analysis was used to compare survival times across groups. The associations of the TyG index and TyG-BMI with all-cause mortality were investigated using restricted cubic splines (RCSs) and Cox proportional hazards regression models. Moreover, the concordance of the associations of the TyG index and TyG-BMI with all-cause mortality in different subgroups was further explored by subgroup analysis.

RESULTS

A total of 921 centenarian participants were included in this study. During a median follow-up of 29.70 months, 852 (92.5%) centenarians died. The results of the RCS analysis demonstrated that the TyG index and TyG-BMI were both linearly and negatively associated with all-cause mortality. Compared with that for the highest the TyG index and TyG-BMI quartile groups, higher risks of death were found for the lowest quartile groups (TyG Q1 vs. Q4, HR 1.27, 95% CI 1.03-1.56, P = 0.024; TyG-BMI Q1 vs. Q4, HR 1.60, 95% CI 1.30-1.96, P < 0.001). Centenarians with lower TyG index and TyG-BMI values had significantly greater mortality risks according to the Kaplan‒Meier analysis (log-rank P = 0.020, log-rank P < 0.001, respectively). Subgroup analysis demonstrated that blood pressure could influence the linear negative correlation between the TyG-BMI and all-cause mortality.

CONCLUSION

Both lower TyG and TyG-BMI indices were significantly associated with higher all-cause mortality in Chinese centenarians, whereas the TyG-BMI was superior to the TyG index in predicting the mortality risk of centenarians.

Triglyceride-glucose index: a novel prognostic marker for sepsis-associated encephalopathy severity and outcomes

Background

Sepsis-associated encephalopathy (SAE) is a complex condition with variable outcomes. This study investigates the potential of the Triglyceride-glucose (TyG) index as a marker for disease severity and prognosis in SAE patients.

Methods

We conducted a retrospective cohort study using data from the Medical Information Mart for Intensive Care (MIMIC-IV) database. Patients with sepsis who were admitted to the intensive care unit (ICU) were categorized into two groups based on the occurrence of SAE. Key clinical outcomes were 90-day survival (primary outcome) and length of ICU and hospital stays, as well as the use of vasoactive medications (secondary outcomes). The TyG index was calculated, and its association with disease severity scores and patient outcomes was analyzed using statistical methods, including survival analysis, Cox regression, and correlation analyses.

Results

The study population's median age was 65.96 years, predominantly male (60.1%). Higher TyG index scores correlated with elevated clinical severity scores (APSIII, LODS, OASIS, SAPSII, and CCI) and increased ICU and hospital stay durations. TyG index categorization revealed significant differences in 90-day survival probabilities, with "high TyG" associated with a 25% increased mortality risk compared to "low TyG." Furthermore, TyG index showed a moderate positive correlation with ICU stay duration and use of norepinephrine and vasopressin, but not with dopamine and epinephrine use.

Conclusion

The TyG index is a significant independent predictor of disease severity and prognosis in SAE patients. High TyG levels correlate with worse clinical outcomes and increased mortality risk, suggesting its potential as a valuable tool in managing SAE.

The association between triglyceride-glucose index and its combination with post-stroke depression: NHANES 2005-2018

BACKGROUND

Growing evidence indicates a link between insulin resistance and post-stroke depression (PSD). This study employed the triglyceride glucose (TyG) index as a measure of insulin resistance to investigate its relationship with PSD.

METHODS

This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (2005-2018). PSD was assessed using data from patient health questionnaires, while the TyG index was calculated based on fasting venous blood glucose and fasting triglyceride levels. The formula used for the TyG index is ln[triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2]. Participants were categorized into four groups according to the TyG index quartiles. A weighted multivariable logistic regression model was applied to examine the relationship between the TyG index and PSD.

RESULTS

A total of 1217 patients were included in the study, of which 232 were diagnosed with PSD. The TyG index was divided into quartiles (Q1-Q4) for analysis. After adjusting for potential confounders, we found a significant positive association between the highest quartile of the TyG index (Q4: ≥9.33) and PSD (OR = 2.51, 95% CI: 1.04-6.07, p = 0.041). This suggests that in the U.S. adult stroke population, individuals with higher TyG indices are more likely to experience depressive symptoms. Subgroup analysis further confirmed a stable and independent positive association between the TyG index and PSD (all trend p > 0.05).

CONCLUSION

In this large cross-sectional study, our results suggest that among US adults who have experienced a stroke, those with higher TyG index levels are more likely to exhibit depressive symptoms. This provides a novel approach for the clinical prevention of PSD. Patients with higher TyG indices in the stroke population may require closer psychological health monitoring and timely intervention. Additionally, since the TyG index is calculated using only fasting blood glucose and triglyceride levels, it can help identify high-risk PSD patients, particularly in regions with limited healthcare resources.

Is the triglyceride-glucose index ready for cardiovascular risk assessment?

AIMS

Insulin resistance is a major risk factor for cardiovascular disease. Thus, early identification of insulin resistance is important for classifying individuals at high cardiovascular risk. All the tools commonly used in epidemiological studies and clinical practice to assess insulin resistance require measuring insulin levels, which is a limitation. Hence, simpler methods have been proposed to overcome these limitations. One of the most promising is the triglyceride-glucose index. Therefore, this narrative review focuses on the most significant epidemiological findings concerning the relationship between the triglyceride-glucose index and cardiovascular risk. Furthermore, it also highlights this new tool's strengths, limitations, and perspectives for assessing cardiovascular risk.

DATA SYNTHESIS

Even though the assessment of this index is relatively recent, there are numerous papers on this topic, and their number is constantly increasing. Observational studies have shown a substantial positive association between the triglyceride-glucose index and cardiovascular risk, although some conflicting results have been observed.

CONCLUSIONS

The index is strongly associated with cardiovascular mortality and cardiovascular risk factors. However, some gaps need to be addressed.

Risk factor analysis and predictive model construction of lean MAFLD: a cross-sectional study of a health check-up population in China

AIM

Cardiovascular disease morbidity and mortality rates are high in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). The objective of this study was to analyze the risk factors and differences between lean MAFLD and overweight MAFLD, and establish and validate a nomogram model for predicting lean MAFLD.

METHODS

This retrospective cross-sectional study included 4363 participants who underwent annual health checkup at Yuyao from 2019 to 2022. The study population was stratified into three groups: non-MAFLD, lean MAFLD (defined as the presence of fatty liver changes as determined by ultrasound in individuals with a BMI < 25 kg/m2), and overweight MAFLD (BMI ≥ 25.0 kg/m2). Subsequent modeling analysis was conducted in a population that included healthy subjects with < 25 kg/m2 (n = 2104) and subjects with lean MAFLD (n = 849). The study population was randomly split (7:3 ratio) to a training vs. a validation cohort. Risk factors for lean MAFLD was identify by multivariate regression of the training cohort, and used to construct a nomogram to estimate the probability of lean MAFLD. Model performance was examined using the receiver operating characteristic (ROC) curve analysis and k-fold cross-validation (k = 5). Decision curve analysis (DCA) was applied to evaluate the clinical usefulness of the prediction model.

RESULTS

The multivariate regression analysis indicated that the triglycerides and glucose index (TyG) was the most significant risk factor for lean MAFLD (OR: 4.03, 95% CI 2.806-5.786). The restricted cubic spline curves (RCS) regression model demonstrated that the relationships between systolic pressure (SBP), alanine aminotransferase (ALT), serum urate (UA), total cholesterol (TCHO), triglyceride (TG), triglyceride glucose (TyG) index, high density lipoprotein cholesterol (HDLC), and MAFLD were nonlinear and the cutoff values for lean MAFLD and overweight MAFLD were different. The nomogram was constructed based on seven predictors: glycosylated hemoglobin A1c (HbA1c), serum ferritin (SF), ALT, UA, BMI, TyG index, and age. In the validation cohort, the area under the ROC curve was 0.866 (95% CI 0.842-0.891), with 83.8% sensitivity and 76.6% specificity at the optimal cutoff. The PPV and NPV was 63.3% and 90.8%, respectively. Furthermore, we used fivefold cross-validation and the average area under the ROC curve was 0.866 (Figure S3). The calibration curves for the model's predictions and the actual outcomes were in good agreement. The DCA findings demonstrated that the nomogram model was clinically useful throughout a broad threshold probability range.

CONCLUSIONS

Lean and overweight MAFLD exhibit distinct metabolic profiles. The nomogram model developed in this study is designed to assist clinicians in the early identification of high-risk individuals with lean MAFLD, including those with a normal BMI but at metabolic risk, as well as those with abnormal blood lipid, glucose, uric acid or transaminase levels. In addition, this model enhances screening efforts in communities and medical screening centers, ultimately ensuring more timely and effective medical services for patients.

Triglyceride-glucose index and the risk of in-hospital and ICU all-cause mortality: a systematic review and meta-analysis of observational studies

Several studies have illustrated the association of the triglyceride glucose (TyG) index with in-hospital and intensive care unit (ICU) mortality. However, no studies have compiled this evidence and reached a conclusion. This study aimed to quantify the association of the TYG index with the risk of in-hospital and ICU mortality. An extensive search of databases including PubMed, Scopus, and Web of Science, was performed up to 21 Jan 2024. Nineteen studies were included in the meta-analysis. The outcomes were in-hospital mortality in 18 studies and ICU mortality in 8 studies. Among the 42,525 participants, 5233 in-hospital and 1754 ICU mortality cases were reported. The pooled analysis revealed that each unit increase in the TYG index was associated with a 33% and 45% increase in the risk of in-hospital (RR = 1.33; 95% CI: 1.23, 1.43; I squared = 90.3%) and ICU (RR: 1.45; 95% CI: 1.25, 1.67; I squared = 44.8%) mortality, respectively. Subgroup analysis revealed a stronger association between the TYG index and the risk of in-hospital mortality in patients with cardiovascular diseases than in those with cerebrovascular diseases (Pheterogeneity between Groups = 0.014). The findings of this study showed a positive association between the TyG index and the risk of in-hospital and ICU mortality. (PROSPERO registration ID: CRD420245414390).

Association of triglyceride-glucose index and derived indices with cataract in middle-aged and elderly Americans: NHANES 2005-2008

AIM

Explore the relationship between the triglyceride-glucose (TyG) index, along with its derivative indices, and the prevalence of cataracts.

METHODS

Data from 20,497 participants in the 2005-2008 National Health and Nutrition Examination Survey (NHANES) were compiled. A final total of 4,499 individuals met the eligibility criteria. Cataract presence was assessed through a self-reported history of cataract surgery. The TyG index and its derivatives-TyG-waist-to-height ratio (WHtR), TyG-neutrophil-to-lymphocyte ratio (NLR), TyG-monocyte-to-lymphocyte ratio (MLR), TyG-log platelet-to-lymphocyte ratio (lgPLR), TyG-log systemic inflammation index (lgSII), and TyG-systemic inflammation response index (SIRI)-were calculated. Statistical analyses included multivariable logistic regression, restricted cubic spline (RCS) curves for nonlinear relationships, and receiver operating characteristic (ROC) analysis.

RESULTS

Higher TyG indices were significantly associated with cataract presence (P < 0.001). Specifically, TyG-WHtR, TyG-NLR, TyG-lgPLR, TyG-lgSII, and TyG-SIRI exhibited positive correlations with cataract prevalence, even after adjustment for potential confounders (odds ratio [OR] = 1.17; 95% confidence interval [CI]: 1.01, 1.37; P = 0.0403; [OR] = 1.01; 95% [CI]: 1.00, 1.02; P = 0.0258; [OR] = 1.08; 95% [CI]: 1.01, 1.16; P = 0.0223; [OR] = 1.08; 95% [CI]: 1.03, 1.14; P = 0.001; [OR] = 1.02; 95% [CI]: 1.00, 1.04; P = 0.0120). Furthermore, the stratified analysis showed that in the 61-85 age group, TyG-lgPLR and TyG-lgSII remained positively associated with cataract prevalence ([OR] = 1.09; 95% [CI]: 1.01, 1.17; P = 0.024; [OR] = 1.08; 95% [CI]: 1.02, 1.13; P = 0.005). RCS analysis revealed a linear association between these indices and cataracts, with no apparent threshold effect. ROC analysis indicated that TyG-MLR demonstrated the highest predictive ability for cataract presence.

CONCLUSION

The study results indicate a positive association between TyG-related indicators and cataract the prevalence of cataracts in middle-aged and elderly individuals, suggesting that these markers may serve as practical biomarkers for identifying high-risk individuals. Early detection and management of metabolic and inflammatory factors could contribute to effective preventive strategies for cataract development in the elderly population.

Use of the FHTHWA Index as a Novel Approach for Predicting the Incidence of Diabetes in a Japanese Population Without Diabetes: Data Analysis Study

Background

Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.

Objective

We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.

Methods

We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database. The least absolute shrinkage and selection operator model was used to select potentially relevant features. Multiple Cox proportional hazard analysis was used to develop a model based on the training set.

Results

The final study population of 15464 participants had a mean age of 42 (range 18-79) years; 54.5% (8430) were men. The mean follow-up duration was 6.05 (SD 3.78) years. A total of 373 (2.41%) participants showed progression to diabetes during the follow-up period. Then, we established a novel parameter (the FHTHWA index), to evaluate the incidence of diabetes in a population without diabetes, comprising 6 parameters based on the training set. After multivariable adjustment, individuals in tertile 3 had a significantly higher rate of diabetes compared with those in tertile 1 (hazard ratio 32.141, 95% CI 11.545-89.476). Time receiver operating characteristic curve analyses showed that the FHTHWA index had high accuracy, with the area under the curve value being around 0.9 during the more than 12 years of follow-up.

Conclusions

This research successfully developed a diabetes risk assessment index tailored for the Japanese population by utilizing an extensive dataset and a wide range of indices. By categorizing the diabetes risk levels among Japanese individuals, this study offers a novel predictive tool for identifying potential patients, while also delivering valuable insights into diabetes prevention strategies for the healthy Japanese populace.

Triglyceride-glucose Index and Mortality in a Large Regional-based Italian Database (URRAH Project)

PURPOSE

Recently, a novel index [the triglyceride-glucose (TyG) index]) was considered a surrogate marker of insulin resistance (IR); in addition, it was estimated to be a better expression of IR than widely used tools. Few and heterogeneous data are available on the relationship between this index and mortality risk in non-Asian populations. Therefore, we estimated the predictive role of baseline TyG on the incidence of all-cause and cardiovascular (CV) mortality in a large sample of the general population. Moreover, in consideration of the well-recognized role of serum uric acid (SUA) on CV risk and the close correlation between SUA and IR, we also evaluated the combined effect of TyG and SUA on mortality risk.

METHODS

The analysis included 16 649 participants from the URRAH cohort. The risk of all-cause and CV mortality was evaluated by the Kaplan-Meier estimator and Cox multivariate analysis.

RESULTS

During a median follow-up of 144 months, 2569 deaths occurred. We stratified the sample by the optimal cut-off point for all-cause (4.62) and CV mortality (4.53). In the multivariate Cox regression analyses, participants with TyG above cut-off had a significantly higher risk of all-cause and CV mortality than those with TyG below the cut-off. Moreover, the simultaneous presence of high levels of TyG and SUA was associated with a higher mortality risk than none or only 1 of the 2 factors.

CONCLUSION

The results of this study indicate that these TyG (a low-cost and simple, noninvasive marker) thresholds are predictive of an increased risk of mortality in a large and homogeneous general population. In addition, these results show a synergic effect of TyG and SUA on the risk of mortality.

Predictive role of triglyceride-glucose index and HOMA index on development of arterial stiffening in non-diabetic men

BACKGROUND AND AIMS

Insulin resistance (IR) is a major risk factor for cardiovascular disease. Recently, a novel index (triglyceride-glucose index-TyG) has been proposed as a surrogate marker of IR and a better expression of IR than the Homeostatic Model Assessment of IR (HOMA-IR) index. Few and heterogeneous data are so far available on the relationship between vascular damage and this novel index. Therefore, we aimed to estimate the predictive role of TyG, in comparison with the HOMA-IR, on the development of arterial stiffening (AS), defined as a pulse pressure>60 mmHg, in an 8-year follow-up observation of a sample of non-diabetic adult men (the Olivetti Heart Study).

METHODS AND RESULTS

The analysis included 527 non-diabetic men, with normal arterial elasticity at baseline and not on antihypertensive or hypolipidemic treatment. TyG was significantly greater in those who developed AS than those who did not (p = 0.006). On the contrary, the HOMA-IR index was not different between the two groups (p = 0.24). Similar trends were shown by logistic regression analysis adjusting for main confounders. After the stratification by the optimal cut-off point, values of TyG >4.70 were significantly associated with the development of AS, also after adjustment for main confounders. On the contrary, the HOMA-IR index >1.90 was not associated with the risk of AS development in multivariate models.

CONCLUSION

The results of this study indicate a predictive role of TyG on AS, independently of the main potential confounders. Moreover, the predictive power of TyG seems to be greater than that of the HOMA-IR index.

The association between triglyceride glucose index and gout: a cross-sectional analysis based on NHANES 2007-2018

BACKGROUND

The triglyceride glucose (TyG) index, defined as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2], provides insights into overall metabolic status. However, the association between the TyG index and gout has not been investigated. Therefore, this study explored the correlation between the TyG index and gout.

METHODS

Using data from the National Health and Nutrition Examination Survey, which was conducted from 2007 to 2018, this study investigated the relationship between the TyG index and gout. Demographic data and potential risk factors were analyzed and compared using t tests for continuous data and chi-square tests for categorical data. Logistic regression and subgroup analysis were performed to examine the association between the TyG index and gout.

RESULTS

A total of 14,924 participants were enrolled, among whom 726 (4.86%) were diagnosed with gout. Without controlling for any covariates, a significant positive correlation was observed between an elevated TyG index and increased risk of gout, with an odds ratio (OR) of 2.07 and a 95% confidence interval (CI) ranging from 1.76 to 2.43. After full adjustment, this association remained statistically significant, with an adjusted OR of 1.43 and a 95% CI from 1.14 to 1.80. Subgroup analyses revealed significant interactions, particularly for females (OR = 2.55; 95% CI: 2.00-3.26), individuals with no military service history (OR = 2.15; 95% CI: 1.66-2.43), and those without diabetes (OR = 2.00; 95% CI: 1.64-2.43).

CONCLUSION

A positive correlation was observed between the TyG index and gout. Consequently, further large-scale prospective studies are warranted for a comprehensive analysis of the role of the TyG index in gout.

Association of triglyceride glucose index with stroke: from two large cohort studies and Mendelian randomization analysis

INTRODUCTION

The triglyceride glucose index (TyG) is associated with cardiovascular diseases; however, its association with stroke remains unclear. This study aimed to elucidate this relationship by examining two extensive cohort studies using two-sample Mendelian randomization (MR).

METHODS

Using data from the 1999-2018 National Health and Nutrition Examination Survey (NHANES) and the Medical Information Mart for Intensive Care (MIMIC)-IV, the correlation between TyG (continuous and quartile) and stroke was examined using multivariate Cox regression models and sensitivity analyses. Two-sample MR was employed to establish causality between TyG and stroke using the inverse variance weighting method. Genome-wide association study catalog queries were performed for single nucleotide polymorphism-mapped genes, and the STRING platform used to assess protein interactions. Functional annotation and enrichment analyses were also conducted.

RESULTS

From the NHANES and MIMIC-IV cohorts, we included 740 and 589 participants with stroke, respectively. After adjusting for covariates, TyG was linearly associated with the risk of stroke death (NHANES: hazard ratio [HR] 0.64, 95% CI: 0.41-0.99, P =0.047; Q3 vs. Q1, HR 0.62, 95% CI: 0.40-0.96, P =0.033; MIMIC-IV: HR 0.46, 95% CI: 0.27-0.80, P =0.006; Q3 vs. Q1, HR 0.32, 95% CI: 0.12-0.86; Q4 vs. Q1, HR 0.30, 95% CI: 0.10-0.89, P =0.030, P for trend=0.017). Two-sample MR analysis showed genetic prediction supported a causal association between a higher TyG and a reduced risk of stroke (odds ratio 0.711, 95% CI: 0.641-0.788, P =7.64e -11 ).

CONCLUSIONS

TyG was causally associated with a reduced risk of stroke. TyG is a critical factor for stroke risk management.

Association of the triglyceride-glucose index with all-cause and cause-specific mortality: a population-based cohort study of 3.5 million adults in China

Background

The triglyceride-glucose (TyG) index has been recognized as a crucial risk factor for cardiovascular diseases. However, the association between the TyG index and mortality in the general population remains elusive.

Methods

Participants were enrolled from the China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART), a nationwide prospective cohort study. The outcomes of interest were all-cause, cardiovascular, and cancer mortality. Restricted cubic splines and Cox regression models were used to assess the associations between the TyG index and outcomes.

Findings

In total, 3,524,459 participants with a median follow-up of 4.6 (IQR, 3.1-5.8) years were included. The associations of the TyG index with all-cause and cardiovascular mortality were reverse L-shaped, with cut-off values of 9.75 for all-cause mortality and 9.85 for cardiovascular mortality. For each 1-unit increase in the TyG index, when below the cut-off values, the TyG index was not significantly associated with all-cause mortality (HR = 1.02, 95% CI: 1.00-1.03) and was only modestly associated with cardiovascular mortality (HR = 1.09, 95% CI: 1.06-1.11). Conversely, when the cut-off values were exceeded, the HRs (95% CI) were 2.10 (1.94-2.29) for all-cause mortality and 1.99 (1.72-2.30) for cardiovascular mortality. However, the association between the TyG index and cancer mortality was linearly negative (HR = 0.97, 95% CI: 0.94-0.99).

Interpretation

The associations of the TyG index with all-cause and cardiovascular mortality displayed reverse L-shaped patterns, while an elevated TyG index showed a slight negative association with cancer mortality. We suggest that <9.75 could be the optimal TyG index cut-off value among the Chinese general population. Individuals at high risk of mortality might benefit from proper management of a high TyG index.

Funding

The National High Level Hospital Clinical Research Funding (2023-GSP-ZD-2, 2023-GSP-RC-01), the Ministry of Finance of China and National Health Commission of China.

U shape association between triglyceride glucose index and congestive heart failure in patients with diabetes and prediabetes

BACKGROUND

While previous population studies have shown that higher triglyceride-glucose (TyG) index values are associated with an increased risk of congestive heart failure (CHF), the relationship between TyG and CHF in patients with abnormal glucose metabolism remains understudied. This study aimed to evaluate the association between TyG and CHF in individuals with diabetes and prediabetes.

METHODS

The study population was derived from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. The exposure variable, TyG, was calculated based on triglyceride and fasting blood glucose levels, while the outcome of interest was CHF. A multivariate logistic regression analysis was employed to assess the association between TyG and CHF.

RESULTS

A total of 13,644 patients with diabetes and prediabetes were included in this study. The results from the fitting curve analysis demonstrated a non-linear U-shaped correlation between TyG and CHF. Additionally, linear logistic regression analysis showed that each additional unit of TyG was associated with a non-significant odds ratio (OR) of 1.03 (95%CI: 0.88-1.22, P = 0.697) for the prevalence of CHF. A two-piecewise logistic regression model was used to calculate the threshold effect of the TyG. The log likelihood ratio test (p < 0.05) indicated that the two-piecewise logistic regression model was superior to the single-line logistic regression model. The TyG tangent point was observed at 8.60, and on the left side of this point, there existed a negative correlation between TyG and CHF (OR: 0.54, 95%CI: 0.36-0.81). Conversely, on the right side of the inflection point, a significant 28% increase in the prevalence of CHF was observed per unit increment in TyG (OR: 1.28, 95%CI: 1.04-1.56).

CONCLUSIONS

The findings from this study suggest a U-shaped correlation between TyG and CHF, indicating that both elevated and reduced levels of TyG are associated with an increased prevalence of CHF.

The role of triglyceride-glucose index in the differential diagnosis of atherosclerotic stroke and cardiogenic stroke

OBJECTIVE

This study aims to investigate the role of the triglyceride glucose (TyG) index in differentiating cardiogenic stroke (CE) from large atherosclerotic stroke (LAA).

METHOD

In this retrospective study, patients with acute ischemic stroke were recruited from the First Affiliated Hospital of Soochow University, Lianyungang Second People's Hospital and Lianyungang First People's Hospital. Their general data, medical history and laboratory indicators were collected and TyG index was calculated. Groups were classified by the TyG index quartile to compare the differences between groups. Logistic regression was utilized to assess the relationship between the TyG index and LAA. The receiver operating characteristic curve (ROC) curve was used to evaluate the diagnostic efficiency of the TyG index in differentiating LAA from CE.

RESULT

The study recruited 1149 patients. After adjusting for several identified risk factors, groups TyG-Q2, TyG-Q3, and TyG-Q4 had a higher risk of developing LAA compared to group TyG-Q1(odds ratio (OR) = 1.63,95% confidence interval (CI) = 1.11-2.39, OR = 1.72,95%CI = 1.16-2.55, OR = 2.06,95%CI = 1.36-3.09). TyG has certain diagnostic value in distinguishing LAA from CE(AUC = 0.595, 95%CI0.566-0.623;P<0.001).

CONCLUSION

Summarily, the TyG index has slight significance in the identification of LAA and CE; it is particularly a marker for their preliminary identification.

Dose-response associations of triglyceride to high-density lipoprotein cholesterol ratio and triglyceride-glucose index with arterial stiffness risk

BACKGROUND

The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio and triglyceride-glucose (TyG) index are novel indexes for insulin resistance (IR). We aimed to evaluate associations of TG/HDL-C and TyG with arterial stiffness risk.

METHODS

We enrolled 1979 participants from the Rural Chinese Cohort Study, examining arterial stiffness by brachial-ankle pulse wave velocity (baPWV). Logistic and linear regression models were employed to calculate effect estimates. For meta-analysis, we searched relevant articles from PubMed, Embase and Web of Science up to August 26, 2023. The fixed-effects or random-effects models were used to calculate the pooled estimates. We evaluated dose-response associations using restricted cubic splines.

RESULTS

For cross-sectional studies, the adjusted ORs (95%CIs) for arterial stiffness were 1.12 (1.01-1.23) and 1.78 (1.38-2.30) for per 1 unit increment in TG/HDL-C and TyG. In the meta-analysis, the pooled ORs (95% CIs) were 1.26 (1.14-1.39) and 1.57 (1.36-1.82) for per 1 unit increment of TG/HDL-C and TyG. Additionally, both TG/HDL-C and TyG were positively related to PWV, with β of 0.09 (95% CI 0.04-0.14) and 0.57 (95% CI 0.35-0.78) m/s. We also found linear associations of TG/HDL-C and TyG with arterial stiffness risk.

CONCLUSIONS

High TG/HDL-C and TyG were related to increased arterial stiffness risk, indicating TG/HDL-C and TyG may be convincing predictors of arterial stiffness.

Mean platelet volume (MPV) as new marker of diabetic macrovascular complications in patients with different glucose homeostasis : Platelets in cardiovascular risk

BACKGROUND

Platelets play an important role in the development of cardiovascular disease (CVD). Mean platelet volume (MPV) is considered as biological marker of platelets activity and function. The aim of the present study was to evaluate MPV values and its possible correlation with arterial stiffness and subclinical myocardial damage, in normal glucose tolerance patients (NGT), in newly diagnosed type 2 diabetic (T2DM) patients and in individuals with pre-diabetes.

METHODS

We enrolled 400 newly diagnosed hypertensive patients. All patients underwent an Oral Glucose Tolerance test (OGTT). Arterial stiffness (AS) was evaluated with the measurement of carotid-femoral pulse wave velocity (PWV), augmentation pressure (AP) and augmentation index (AI). Echocardiographic recordings were performed using an E-95 Pro ultrasound system.

RESULTS

Among groups there was an increase in fasting plasma glucose (FPG) (p < 0.0001), fasting plasma insulin (FPI) (p < 0.0001), high sensitivity c reactive protein (hs-CRP) levels (p < 0.0001) and a decrease in renal function as demonstrated by e-GFR values (p < 0.0001). From the NGT group to the T2DM group there was a rise in MPV value (p < 0.0001). Moreover, in the evaluation of arterial stiffness and subclinical myocardial damage, MPV showed a positive correlation with these parameters.

CONCLUSIONS

In the present study we highlighted that MPV is significantly increased, not only in newly diagnosed T2DM patients, but also in early stage of diabetes, indicating that subjects with pre-diabetes present increased platelets reactivity. Moreover, our results suggest that MPV is associated with increased arterial stiffness and subclinical myocardial damage, indicating MPV as new marker of CV risk.

Assessing the association between triglyceride-glucose index and atrial fibrillation: a systematic review and meta-analysis

BACKGROUND

An essential relationship between insulin resistance (IR) and atrial fibrillation (AF) has been demonstrated. Among the methods used to assess IR, the triglyceride-glucose (TyG) index is the more straightforward, dimensionless, and low-cost tool. However, the possible usage of this index in clinical practice to predict and diagnose AF has yet to be determined and consolidated.

OBJECTIVE AND RATIONALE

Herein, we performed a systematic review and meta-analysis to assess the association between the TyG index and AF.

METHODS

Databases (PubMed, Embase, Scopus, and Web of Science) were systematically searched for studies evaluating the TyG index in AF. The inclusion criteria were observational studies investigating AF and TyG index correlation in individuals older than 18 years, while preclinical studies and those without the relevant data were excluded. Random effect meta-analyses comparing TyG levels between AF and non-AF cases, AF recurrence after radiofrequency ablation, and post-procedural AF were performed using standardized mean differences (SMD) with their matching 95% confidence intervals (CIs).

RESULTS

Our screening identified nine studies to be analyzed, including 6,171 participants including 886 with AF. The meta-analysis demonstrated that the TyG index resulted higher in patients with AF than non-AF counterparts (SMD 1.23, 95% CI 0.71 to 1.75, I2 98%, P < 0.001). Subgroup analysis showed the same results for post-procedure AF (SMD 0.99, 95% CI 0.78 to 1.20, I2 10%, P < 0.001) and post-ablation AF (SMD 1.25, 95% CI 1.07 to 1.43, I2 46%, P < 0.001), while no difference was found in population-based cohorts (SMD 1.45, 95% CI - 0.41 to 3.31, I2 100%, P = 0.13). Publication year (P = 0.036) and sample size (P = 0.003) showed significant associations with the effect size, using multivariable meta-regression.

CONCLUSION

The TyG index is an easy-to-measure surrogate marker of IR in patients with AF. Further clinical studies are warranted to demonstrate its ability for routine clinical use and as a screening tool.

Relationship between Triglyceride-Glucose Index and Disease Activity and Subclinical Atherosclerosis in Rheumatoid Arthritis

BACKGROUND

In rheumatoid arthritis (RA), insulin resistance (IR) is related to inflammatory markers, disease activity, and progression of atherosclerotic changes. Triglyceride-glucose (TyG) index is a relatively new indicator of IR.

AIMS

The present study aimed to investigate the relationship between TyG index, disease activity and subclinical atherosclerosis (SCA) in RA patients.

METHODS

The present case-control study included 100 RA patients and 50 age- and sex-matched healthy controls. All participants were subjected to careful history taking through clinical examination and standard laboratory assessment. The TyG index was calculated as TyG index = ln (Fasting triglyceride (mg/dL) × fasting glucose (mg/dL))/2. Carotid intima-media thickness (CIMT) measurement was done using B-mode ultrasound.

RESULTS

Patients had significantly higher TyG index as compared to controls. Patients with high disease activity had significantly higher frequency of extraarticular manifestations (39.6% versus 51.6%, p = 0.028), higher Larsen score (3.8 ± 1.3 versus 2.8 ± 1.2, p < 0.001), higher anti-cyclic citrullinated peptide (anti-CCP) levels (median (IQR): 243.1 (205.0-408.0) U/ml versus 99.0 (78.0-332.5), p < 0.001), higher TyG index (4.8 ± 0.22 versus 4.67 ± 0.24, p = 0.006), and higher CIMT (0.87 ± 0.22 versus 0.77 ± 0.17 mm, p = 0.018). Patients with SCA had higher BMI (34.6 ± 6.2 versus 30.5 ± 5.3 Kg/m2, p < 0.001), higher Larsen score (3.7 ± 1.4 versus 3.1 ± 1.3, p = 0.028) and higher TyG index (4.89 ± 0.23 versus 4.64 ± 0.19, p < 0.001). Binary logistic regression analysis identified patients' age (OR (95% CI): 0.94 (0.89-0.99), p = 0.018), Larsen score (OR (95% CI): 1.93 (1.32-2.82), p = <0.001), anti-CCP (OR (95%): 1.04 (1.02-1.07), p = 0.032), and TyG index (OR (95% CI): 22.67 (2.14-240.4), p = 0.01) as significant predictors of high disease activity in multivariate analysis.

CONCLUSION

IR estimated by the TyG index is related to disease activity and SCA in RA patients.

Association of cardiometabolic factors and insulin resistance surrogates with mortality in participants from the Korean Genome and Epidemiology Study

BACKGROUND

Simple biochemical and anthropometric measurements such as fasting blood glucose (FBG), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), waist circumference (WC), and body mass index (BMI) are used to formulate insulin resistance (IR) indices. Whether these indices provide new predictive information for mortality remains unknown. This study examined the relationships of biochemical, anthropometric, and IR indices with mortality risk, as well as their predictive performance.

METHODS

The data source was the Korean Genome and Epidemiology Study (2004-2020) involving 114,957 participants whose data were linked to death records. The IR indices- triglyceride-glucose index (TyG), TyG-BMI, TyG-WC, visceral adiposity index (VAI), lipid accumulation product (LAP), and metabolic score for insulin resistance (METS-IR) were computed using standard formulae. The associations were examined using restricted cubic splines. The predictive performance was compared using the log-likelihood ratio chi-square test.

RESULTS

Body mass index was U-shaped, HDL-C was reverse J-shaped, and FBG and TG levels were J-shaped associated with all-cause mortality. Results showed U-shaped (TyG), J-shaped (TyG-BMI, VAI, LAP, and METS-IR), and reverse J-shaped (TyG-WC) associations with all-cause mortality. The percentages of new predictive information for all-cause mortality explained by the FBG level, BMI, TyG-BMI, and METIR were 3.34%, 2.33%, 1.47%, and 1.37%, respectively. Other IR indices and biochemical and anthropometric measurements provided < 1.0% of new predictive information. For cardiovascular disease mortality, the FBG, BMI, METIR, TyG-BMI, and HDL-C levels explained 2.57%, 2.12%, 1.59%, 1.30%, and 1.27% of new predictive information respectively. Moreover, the risks of cancer mortality explained by FBG level, VAI, and HDL-C level were 2.05%, 1.49%, and 1.28%, respectively.

CONCLUSIONS

Fasting blood glucose level is a superior predictor of mortality risk and may be used as a simple predictive and preventative factor.

Triglyceride glucose index as a predictor of mortality in middle-aged and elderly patients with type 2 diabetes in the US

Despite a wealth of research linking the triglyceride glucose index (TyG index) to metabolic diseases. However, little evidence links the TyG index to all-cause or CVD mortality in middle-aged and elderly individuals with type 2 diabetes (T2D). This study analyzed data from 2998 patients with T2D who participated in the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. The TyG index and mortality in middle-aged and elderly T2D patients were investigated using Cox regression models. The nonlinear association between the TyG index and mortality can be understood with the help of a restricted cubic spline (RCS). During a median follow-up period of 82 months, 883 fatalities were observed from all causes and 265 from CVD. The TyG index was found to have a U-shaped relationship with all-cause and CVD mortality in T2D, with cutoffs of 8.95 and 9, respectively, according to the RCS. After controlling for other factors, an increase of 1 unit in the TyG index was related to an increase of 33% in all-cause mortality and 50% in CVD mortality when TyG was ≥ 8.95 and 9. When TyG < 8.95 and 9, with the change in the TyG index, the change in all-cause and CVD death was insignificant. Patients with T2D who are middle-aged or older, especially elderly patients, have higher TyG levels associated with increased mortality. In middle-aged and elderly patients with T2D, the TyG index may predict the probability of death from any cause and death from CVD.

Triglyceride-glucose index and heart failure: a systematic review and meta-analysis

BACKGROUND

Insulin resistance (IR) is a major metabolic disorder observed in heart failure (HF) and is tightly associated with patients' poor prognosis. The triglyceride-glucose index (TyG) has been proposed as a surrogate marker of IR in HF. Yet, whether TyG is a reliable clinical marker is still under debate. Hence, we aimed to respond to this relevant question via a systematic review and meta-analysis of existing studies.

METHODS

A systematic search was conducted in PubMed, Embase, Scopus, and Web of Science to find studies investigating the TyG index in patients with HF or its association with the incidence of HF. Adjusted hazard ratios (HR) and 95% confidence intervals (CI) were pooled through random-effect meta-analysis. HRs were calculated using TyG as a continuous variable (1 unit increase) and by comparing the group with the highest TyG to the lowest TyG group.

RESULTS

Thirty studies, involving 772,809 participants, were included in this systematic review. Meta-analysis of seven studies comparing the highest-TyG to the lowest-TyG group showed a significantly increased risk of HF in the former group (HR 1.21, 95% CI 1.14 to 1.29, P < 0.01). The same result was found when pooling the HRs for a one-unit increase in the TyG index (HR 1.17, 95% CI 1.08 to 1.26). Similarly, a more elevated TyG index was associated with a higher incidence of HF in patients with type 2 diabetes or coronary artery disease. Additionally, the incidence of adverse events (readmission and mortality) in patients with HF was associated with TyG.

CONCLUSION

Our findings support the TyG index as a valuable marker to assess the risk of HF incidence in different populations and as a prognostic marker in patients with HF. Further studies should be conducted to confirm these associations and investigate the clinical utility of the TyG index.

The triglyceride-glucose index is associated with atherosclerosis in patients with symptomatic coronary artery disease, regardless of diabetes mellitus and hyperlipidaemia

BACKGROUND

Diabetes and hyperlipidaemia are both risk factors for coronary artery disease, and both are associated with a high triglyceride-glucose index (TyG index). The TyG index has been presented as a marker of insulin resistance (IR). Its utility in predicting and detecting cardiovascular disease has been reported. However, few studies have found it to be a helpful marker of atherosclerosis in patients with symptomatic coronary artery disease (CAD). The purpose of this study was to demonstrate that the TyG index can serve as a valuable marker for predicting coronary and carotid atherosclerosis in symptomatic CAD patients, regardless of diabetes mellitus and hyperlipidaemia.

METHODS

This study included 1516 patients with symptomatic CAD who underwent both coronary artery angiography and carotid Doppler ultrasound in the Department of Cardiology at Tianjin Union Medical Center from January 2016 to December 2022. The TyG index was determined using the Ln formula. The population was further grouped and analysed according to the presence or absence of diabetes and hyperlipidaemia. The Gensini score and carotid intima-media thickness were calculated or measured, and the patients were divided into four groups according to TyG index quartile to examine the relationship between the TyG index and coronary or carotid artery lesions in symptomatic CAD patients.

RESULTS

In symptomatic CAD patients, the TyG index showed a significant positive correlation with both coronary lesions and carotid plaques. After adjusting for sex, age, smoking, BMI, hypertension, diabetes, and the use of antilipemic and antidiabetic agents, the risk of developing coronary lesions and carotid plaques increased across the baseline TyG index. Compared with the lowest quartile of the TyG index, the highest quartile (quartile 4) was associated with a greater incidence of coronary heart disease [OR = 2.55 (95% CI 1.61, 4.03)] and carotid atherosclerotic plaque [OR = 2.31 (95% CI 1.27, 4.20)] (P < 0.05). Furthermore, when compared to the fasting blood glucose (FBG) or triglyceride (TG) level, the TyG index had a greater area under the ROC curve for predicting coronary lesions and carotid plaques. The subgroup analysis demonstrated the TyG index to be an equally effective predictor of coronary and carotid artery disease, regardless of diabetes and hyperlipidaemia.

CONCLUSION

The TyG index is a useful marker for predicting coronary and carotid atherosclerosis in patients with symptomatic CAD, regardless of diabetes mellitus and hyperlipidaemia. The TyG index is of higher value for the identification of both coronary and carotid atherosclerotic plaques than the FBG or TG level alone.

Machine Learning as a Support for the Diagnosis of Type 2 Diabetes

Diabetes is a chronic, metabolic disease characterized by high blood sugar levels. Among the main types of diabetes, type 2 is the most common. Early diagnosis and treatment can prevent or delay the onset of complications. Previous studies examined the application of machine learning techniques for prediction of the pathology, and here an artificial neural network shows very promising results as a possible valuable aid in the management and prevention of diabetes. Additionally, its superior ability for long-term predictions makes it an ideal choice for this field of study. We utilized machine learning methods to uncover previously undiscovered associations between an individual’s health status and the development of type 2 diabetes, with the goal of accurately predicting its onset or determining the individual’s risk level. Our study employed a binary classifier, trained on scratch, to identify potential nonlinear relationships between the onset of type 2 diabetes and a set of parameters obtained from patient measurements. Three datasets were utilized, i.e., the National Center for Health Statistics’ (NHANES) biennial survey, MIMIC-III and MIMIC-IV. These datasets were then combined to create a single dataset with the same number of individuals with and without type 2 diabetes. Since the dataset was balanced, the primary evaluation metric for the model was accuracy. The outcomes of this study were encouraging, with the model achieving accuracy levels of up to 86% and a ROC AUC value of 0.934. Further investigation is needed to improve the reliability of the model by considering multiple measurements from the same patient over time.