The use of visceral adiposity variables in the prediction of obstructive sleep apnea: evidence from a large cross-sectional study

A Machine Learning Prediction Model of Adult Obstructive Sleep Apnea Based on Systematically Evaluated Common Clinical Biochemical Indicators

Objective

Obstructive sleep apnea (OSA) is a common and potentially fatal sleep disorder. The purpose of this study was to construct an objective and easy-to-promote model based on common clinical biochemical indicators and demographic data for OSA screening.

Methods

The study collected the clinical data of patients who were referred to the Sleep Medicine Center of the Second Affiliated Hospital of Fujian Medical University from December 1, 2020, to July 31, 2023, including data for demographics, polysomnography (PSG), and 30 biochemical indicators. Univariate and multivariate analyses were performed to compare the differences between groups, and the Boruta method was used to analyze the importance of the predictors. We selected and compared 10 predictors using 4 machine learning algorithms which were "Gaussian Naive Bayes (GNB)", "Support Vector Machine (SVM)", "K Neighbors Classifier (KNN)", and "Logistic Regression (LR)". Finally, the optimal algorithm was selected to construct the final prediction model.

Results

Among all the predictors of OSA, body mass index (BMI) showed the best predictive efficacy with an area under the receiver operating characteristic curve (AUC) = 0.699; among the predictors of biochemical indicators, triglyceride-glucose (TyG) index represented the best predictive performance (AUC = 0.656). The LR algorithm outperformed the 4 established machine learning (ML) algorithms, with an AUC (F1 score) of 0.794 (0.841), 0.777 (0.827), and 0.732 (0.788) in the training, validation, and testing cohorts, respectively.

Conclusion

We have constructed an efficient OSA screening tool. The introduction of biochemical indicators in ML-based prediction models can provide a reference for clinicians in determining whether patients with suspected OSA need PSG.

Application Value of Cardiometabolic Index for the Screening of Obstructive Sleep Apnea with or Without Metabolic Syndrome

Background

Obstructive sleep apnea (OSA) is a common chronic disease with various comorbidities. The cardiometabolic index (CMI) reflects visceral fat tissue distribution and function, assessing the risk of obesity-related conditions such as metabolic syndrome (MetS) and stroke, which are strongly connected to OSA. The relationship between CMI with OSA and OSA combined with MetS (OMS) remains unclear. This study aims to evaluate the screening value of CMI for OSA and OMS, compared to the lipid accumulation product (LAP).

Methods

A total of 280 participants who underwent polysomnography were finally included, with the measurements of metabolic-related laboratory test results such as total cholesterol and triglyceride. Receiver operating curve (ROC) analysis and calculation of the area under the curve (AUC) were conducted to assess the screening potential of CMI, LAP, and the logistic regression models established based on them for OSA and OMS. The Youden index, sensitivity, and specificity were used to determine the optimal cutoff points.

Results

ROC curve analysis revealed that the AUCs for CMI in screening OSA and OMS were 0.808 and 0.797, and the optimal cutoff values were 0.71 (sensitivity 0.797, specificity 0.776) and 0.89 (sensitivity 0.830, specificity 0.662), respectively, showing higher Youden index than LAP. The AUCs of screening models based on CMI for OSA and OMS were 0.887 and 0.824, respectively.

Conclusion

CMI and LAP can effectively screen for OSA and OMS, while CMI has more practical cutoff values for identifying the diseased states. Screening models based on CMI demonstrate a high discriminatory ability for OSA and OMS, which needs verification in a large-scale population.

Triglyceride-glucose index and obstructive sleep apnea: a systematic review and meta-analysis

BACKGROUND

Obstructive sleep apnea (OSA) has a bidirectional association with metabolic syndrome, and insulin resistance (IR). The triglyceride-glucose (TyG) index could be a simply calculated marker of IR in OSA. However, its clinical application appears still limited. Hence, this systematic review and meta-analysis aimed to respond to this question by analyzing all the existing studies showing an association between OSA and the TyG index.

METHODS

Four online databases, including PubMed, Scopus, the Web of Science, and Embase were searched for studies evaluating the TyG index in OSA. After screening and data extraction, a random-effect meta-analysis was performed to compare the TyG index in OSA patients vs. healthy controls by calculating standardized mean difference (SMD) and 95% confidence interval (CI) and pooling the area under the curves (AUCs) for diagnosis of OSA based on this index.

RESULTS

Ten studies involving 16,726 individuals were included in the current systematic review. Meta-analysis indicated that there was a significantly higher TyG index in patients with OSA, compared with the healthy controls (SMD 0.856, 95% CI 0.579 to 1.132, P < 0.001). Also, TyG had a diagnostic ability for OSA representing a pooled AUC of 0.681 (95% CI 0.627 to 0.735). However, based on the two studies' findings, no difference between different severities of OSA was observed. Finally, our data showed that the TyG index is a good potential predictor of adverse outcomes in these patients.

CONCLUSION

Our study revealed that the TyG index is an easy-to-measure marker of IR for assessing OSA, both in diagnosis and prognosis. Our study supports its implementation in routine practice to help clinicians in decision-making and patient stratification.

The use of the sleep apnea-specific hypoxic burden to predict obstructive sleep apnea hypopnea syndrome: Evidence from a large cross-sectional study

OBJECTIVES

Obstructive sleep apnea hypopnea syndrome (OSA) is an independent risk factor for neurocognitive and behavioral problems and cardiovascular and metabolic morbidities, ultimately increasing mortality. However, OSA diagnosis is time-consuming, labor-intensive, and expensive. We evaluated the predictive utility of the sleep apnea-specific hypoxic burden (SASHB) in terms of OSA and the severity thereof in Han Chinese individuals.

METHODS

From January 2019 to July 2022, subjects with suspected OSA were recruited in the sleep center of the Shanghai Sixth People's Hospital during sleep evaluation via standard polysomnography. Basic anthropometric measurements and polysomnographic indicators were collected; SASHB was calculated based on the SpO2 trends of apnea or hypopnea events. Models predictive of OSA were established via logistic regression in the experimental group and verified in an independent group by drawing receiver operating characteristic (ROC) curves.

RESULTS

A total of 2303 subjects with suspected OSA (1200 in the experimental group and 1103 in the validation group) were included. SASHB was positively correlated with the apnea-hyponea index (AHI) in all subjects (r = 0.823, P < 0.001). SASHB distinguished OSA from non-OSA subjects in both the experimental group {area under the curve (AUC) 0.948 [0.934∼0.962]} and the validation group (AUC 0.931 [0.913∼0.949]). SASHB predicted OSA severity well, better than did the neck, waist, or hip circumference; the lowest or mean oxygen saturation; and the Epworth sleepiness scale score.

CONCLUSION

SASHB predicted OSA both accurately and efficiently in a Chinese Han population. Further studies are warranted to verify our findings in community samples.

Triglyceride-glucose index as a predictor of obstructive sleep apnoea severity in the absence of traditional risk factors

OBJECTIVE

We evaluated the association between the triglyceride-glucose (TG) index, a marker of insulin resistance, and obstructive sleep apnoea (OSA) severity in patients without diabetes mellitus, obesity, and metabolic syndrome.

METHODS

This retrospective cohort study included 1,527 patients. We used univariate and multivariate analyses to identify the independent predictors associated with OSA.

RESULTS

Most patients were males (81.5%) with a mean age of 43.9 ± 11.1 (15-90) years. Based on the apnoea-hypopnea index (AHI), 353 (23.1%) patients were included in the control group, whereas 32.4%, 23.5%, and 21% had mild, moderate, and severe OSA, respectively. The TG index values demonstrated significant associations with OSA patients compared with the control group (p = 0.001). In addition, the mean values of the oxygen desaturation index (ODI), AHI, minimum oxygen saturation, and total sleep time percentage with saturation below 90% demonstrated statistically significant differences among the TG index groups (p: 0.001; p:0.001; p:0.001; p:0.003). The optimal TG index cutoff value to predict OSA was 8.615 (AUC = 0.638, 95% CI = 0.606-0.671, p = 0.001). In multivariate logistic regression analysis, after adjusting for age, sex, and body mass index, the TG index was independently associated with OSA patients.

CONCLUSION

The TG index is independently associated with increased risk for OSA. This indicates that this index, a marker for disease severity, can be used to identify severe OSA patients on waiting lists for PSG.

Association of adiposity with risk of obstructive sleep apnea: a population-based study

BACKGROUND

Obesity is a crucial risk factor for obstructive sleep apnea (OSA), but the association between adiposity deposition and OSA risk has not reached a consistent conclusion. This study sought to reveal the association of multiple adiposity indicators with OSA risk.

METHODS

This cross-sectional study included 9,733 participants aged 35-74 years, recruited from an ongoing population-based cohort. OSA was assessed by the Berlin Questionnaire. Six adiposity indicators, including neck circumference (NC), body fat percentage (BF%), waist-to-hip ratio (WHR), visceral adiposity index (VAI), lipid accumulation product (LAP), and resting metabolic rate (RMR), were selected. Multivariate logistic regression models were used to examine the association of adiposity indicators with OSA risk.

RESULTS

One thousand six hundred twenty-six participants (16.71%) were classified into the OSA group. NC, BF%, WHR, VAI, LAP, and RMR were all positively associated with the risk of OSA after adjusting for confounders, regardless of age, sex, and history of dyslipidemia. Every 1-unit increment of NC, BF%, and VAI was associated with a 13%, 9%, and 14% increased risk of OSA, respectively; every 0.01-unit increment of WHR was associated with a 3% increased risk of OSA; every 10-unit increment of LAP and RMR was associated with 2% and 4% increased risk of OSA, respectively.

CONCLUSIONS

NC, BF%, WHR, VAI, LAP, and RMR were all independently and positively associated with OSA risk, regardless of age, sex, history of dyslipidemia, and menopausal status. Application of these new indicators could help to more comprehensively reflect and predict the risk of OSA in the general population.

Composite lipid indices in patients with obstructive sleep apnea: a systematic review and meta-analysis

BACKGROUND

One of the most prevalent sleep disorders affecting the individual's daily life is obstructive sleep apnea (OSA), for which obesity is a major risk factor. Several novel lipid indices have been suggested to have associations with OSA, among which visceral adiposity index (VAI), atherogenic index of plasma (AIP), and lipid accumulation product (LAP) are the most important ones. Herein, the current study aimed to systematically investigate the association between these indices and OSA.

METHODS

Four international databases, including PubMed, Scopus, the Web of Science, and Embase were searched in order to find relevant studies that investigated LAP, VAI, or AIP in OSA and compared them with non-OSA cases or within different severities of OSA. Random-effect meta-analysis was used to generate the standardized mean difference (SMD) and 95% confidence interval (CI) of the difference in lipid indices between OSA and non-OSA cases. Moreover, the pooled area under the receiver operating characteristic curves (AUCs) observed in individual studies for diagnosis of OSA based on these lipid indices were calculated by random-effect meta-analysis.

RESULTS

Totally 14 original studies were included, comprised of 14,943 cases. AIP, LAP, and VAI were assessed in eight, five, and five studies, respectively. Overall, these lipid indices had acceptable diagnostic ability (AUC 0.70, 95% CI 0.67 to 073). Meta-analysis revealed that AIP was significantly higher in patients with OSA (SMD 0.71, 95% CI 0.45 to 0.97, P < 0.01). Moreover, AIP also increased in higher severities of OSA. Regarding LAP, a higher LAP was observed in OSA/patients with high risk for OSA rather than in controls/low risk for OSA (SMD 0.53, 95% CI 0.25 to 0.81, P < 0.01). VAI was also increased in OSA based on results from two studies.

CONCLUSION

These findings suggest that composite lipid indices are increased in OSA. Also, these indices can have the potential beneficiary diagnostic and prognostic ability in OSA. Future studies can confirm these findings and enlighten the role of lipid indices in OSA.

Prognostic significance of multiple triglycerides-derived metabolic indices in patients with acute coronary syndrome

BACKGROUND

Triglyceride (TG) and its related metabolic indices, all recognized as surrogates of insulin resistance, have been demonstrated to be relevant to clinical prognosis. However, the relative value of these TG-related indices for predicting cardiovascular events among patients with acute coronary syndrome (ACS) has not been examined.

METHODS

The TG, the triglyceride-glucose (TyG) index, the atherogenic index of plasma, TG to high-density lipoprotein cholesterol ratio, and the lipoprotein combine index were assessed in 1694 ACS patients undergoing percutaneous coronary intervention. The primary endpoint was major adverse cardiovascular event (MACE), which was the composite of all-cause mortality, stroke, myocardial infarction, or unplanned repeat revascularization.

RESULTS

During a median follow-up of 31 months, 345 patients (20.4%) had MACE. The risk of the MACE was increased with higher TG and the four TG-derived metabolic indices [TG-adjusted hazard ratio (HR) = 1.002, 95% CI: 1.001-1.003; TyG index-adjusted HR = 1.736, 95% CI: 1.398-2.156; atherogenic index of plasma-adjusted HR = 2.513, 95% CI: 1.562-4.043; TG to high-density lipoprotein cholesterol ratio-adjusted HR = 1.148, 95% CI: 1.048-1.258; and lipoprotein combine index-adjusted HR = 1.009, 95% CI: 1.004-1.014; P < 0.001 for all indices]. TG and all the four indices significantly improved the predictive ability for MACE in addition to the baseline model. Among them, TyG index showed the best ability for predicting MACE compared with the other three indices from all the three measurements ( P < 0.05 for all comparison).

CONCLUSIONS

TG and TG-derived metabolic indices were all strongly associated with MACE among ACS patients undergoing percutaneous coronary intervention. Among all the indices, TyG index showed the best ability to predict the risk of MACE.

Sex-specific association of sleep duration with subclinical indicators of metabolic diseases among asymptomatic adults

Background

Accumulating evidence suggests sleep duration may be involved in metabolic regulation. However, studies regarding the association with the early stage of the metabolic disease are limited, and the findings were inconsistent.

Methods

A study among 4922 asymptomatic adults was conducted based on a Chinese national survey in 2009. The early stage of metabolic diseases was evaluated using three proxies: triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C), the product of triglyceride and fasting glucose (TyG), and lipid accumulation product (LAP). Multivariable linear and logistic regression models were used to explore the associations of sleep duration with the three indicators.

Results

The linear regression models revealed that, among females, sleep duration <7 h per day, compared with 7-9 h, was associated with an increased value of LAP and TyG by 25.232% (95%CI: 10.738%, 41.623%) and 0.104 (95%CI: 0.024, 0.185), respectively, in the crude model. The effects were attenuated but remained significant for LAP (11.405%; 95%CI: 1.613%, 22.262%). Similarly, the logistic regression models further found that sleep duration <7 h per day could increase the risk of elevated LAP (OR: 1.725, 95CI%:1.042, 2.856) after adjusting for multiple covariates. By contrast, no associations were found among males.

Conclusions

Short sleep duration was associated with subclinical indicators of metabolic diseases, and females were more susceptible to the association.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-022-01626-w.

Comparison of Composite Lipid Indices in Patients with Obstructive Sleep Apnoea

PURPOSE

Obstructive sleep apnoea (OSA) is a recognised risk factor for cardiovascular disease. However, it is difficult to evaluate the risk of cardiovascular disease in patients with OSA due to multiple shared risk factors. Composite lipid indices, such as atherogenic index of plasma (AIP), visceral adiposity index (VAI) and lipid accumulation product (LAP) have been shown to predict cardiovascular disease better than their individual lipid components. This study aimed to evaluate these indices in patients with OSA.

PATIENTS AND METHODS

Six hundred sixty-seven (667) patients with OSA and 139 non-OSA control volunteers participated in the study. Fasting serum triglycerides, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C) levels were measured, and AIP, LAP and VAI were calculated following cardiorespiratory polygraphy. The relationship between lipid parameters, OSA and its comorbidities was evaluated using receiver operating curve (ROC) analysis.

RESULTS

We found a significant difference in all lipid parameters between OSA patients and controls. Comparing ROCs, LAP was significantly more strongly associated with OSA compared to all the other parameters. The optimal cut-off value for LAP to detect OSA was 76.4, with a sensitivity of 63% and a specificity of 76%. In addition, LAP was the best parameter to predict hypertension and diabetes in patients with OSA, and it was predictive for ischaemic heart disease together with HDL-C.

CONCLUSION

Our results support the use of LAP in clinical practice when evaluating cardiovascular risk in patients with OSA. However, the optimal cut-off value should be determined in large-scale follow-up studies.

Association Between Triglyceride Glucose Index-Waist Circumference and Risk of First Myocardial Infarction in Chinese Hypertensive Patients with Obstructive Sleep Apnoea: An Observational Cohort Study

PURPOSE

This study aimed to investigate the association between triglyceride glucose index-waist circumference (TyG-WC) and the risk of first myocardial infarction (MI) in Chinese hypertensive patients with obstructive sleep apnoea (OSA).

METHODS

This study was an observational cohort study. A total of 2224 Chinese hypertensive patients with OSA without a history of MI were included in this study. Hazard ratio (HR) and 95% confidence interval (CI) were estimated using multivariable Cox proportion hazard models. A generalized additive model was used to identify nonlinear relationships. Additionally, we performed hierarchical analysis and test for interaction.

RESULTS

During a median follow-up of 7.15 years, 85 incidents of MI developed. Overall, there was a positive association between TyG-WC and the risk of first MI. In the multivariable-adjusted model, the risk of MI increased with quartiles of the TyG-WC, the HR in quartile 4 versus quartile 1 was 4.29. A generalized additive model and a smooth curve fitting showed that there existed a similar J-shaped association between TyG-WC and the risk of first MI, with an inflection point at about 785.

CONCLUSION

Elevated levels of the baseline TyG-WC are associated with an increased risk of first MI. This finding indicates that the TyG-WC might be useful to identify the high risk of first MI in Chinese hypertensive patients with OSA.

Triglyceride-Glucose Index in Non-Diabetic, Non-Obese Patients with Obstructive Sleep Apnoea

Obstructive sleep apnoea (OSA) is associated with increased insulin resistance. Triglyceride-glucose index (TyG) is a simple marker of insulin resistance; however, it has been investigated only by two studies in OSA. The aim of this study was to evaluate TyG in non-diabetic, non-obese patients with OSA. A total of 132 patients with OSA and 49 non-OSA control subjects were included. Following a diagnostic sleep test, fasting blood was taken for the analysis of the lipid profile and glucose concentrations. TyG was calculated as ln(triglyceride [mg/dL] × glucose [mg/dL]/2). Comparison analyses between OSA and control groups were adjusted for age, gender, body mass index (BMI) and smoking. TyG was higher in men (p < 0.01) and in ever-smokers (p = 0.02) and it was related to BMI (ρ = 0.33), cigarette pack-years (ρ = 0.17), apnoea–hypopnoea index (ρ = 0.38), oxygen desaturation index (ρ = 0.40), percentage of total sleep time spent with oxygen saturation below 90% (ρ = 0.34), and minimal oxygen saturation (ρ = −0.29; all p < 0.05). TyG values were significantly higher in OSA (p = 0.02) following adjustment for covariates. OSA is independently associated with higher TyG values which are related to disease severity in non-obese, non-diabetic subjects. However, the value of TyG in clinical practice should be evaluated in follow-up studies in patients with OSA.

Body Fat Indices as Effective Predictors of Insulin Resistance in Obstructive Sleep Apnea: Evidence from a Cross-Sectional and Longitudinal Study : BFI as Predictors of IR in OSA

PURPOSE

Body fat indices serve as predictive markers of insulin resistance (IR) in metabolic diseases. IR is common in obstructive sleep apnea (OSA). However, whether body fat indices have utility as predictors of IR in OSA remain unknown.

MATERIALS AND METHODS

A longitudinal study was conducted in 46 patients undergoing bariatric surgery to explore the relationship between IR and body fat indices. Then, a cross-sectional study was performed to evaluate the relationships between body fat indices and IR, and receiver operating characteristic (ROC) curves were generated. Body indices, homeostasis model assessment index of insulin resistance (HOMA-IR), biological indicators, and polysomnographic variables were collected.

RESULTS

In the longitudinal study, significant relationships were found between remission of IR and changes in visceral adiposity index (VAI) (r = 0.452, P < 0.05) and triglyceride-glucose index (TyG) (r = 0.650, P < 0.01). In the cross-sectional study, lipid accumulation product (LAP) (best cutoff value: 30.16, area under the curve (AUC) = 0.728, P < 0.001) and TyG (best cutoff value: 8.54, AUC = 0.740, P < 0.001) were indicators of IR in normal weight group. In overweight/obese group, body mass index (BMI) (best cutoff value: 27.69 AUC = 0.707, P < 0.001) and waist circumference (WC) (best cutoff value: 97.25, AUC = 0.708, P < 0.001) were markers of IR. TyG showed better ability to predict IR in normal weight females (best cutoff value: 8.39 AUC = 0.813, P < 0.001).

CONCLUSIONS

Body fat indices are predictive markers of IR in patients with OSA.

Association of Hypertriglyceridemic Waist Phenotype with Obstructive Sleep Apnea: A Cross-Sectional Study

OBJECTIVE

Hypertriglyceridemic waist (HTGW) phenotype is an independent risk factor for metabolic disorders. Although obstructive sleep apnea (OSA) is associated with metabolic disorders, it is unclear whether there is an association between HTGW phenotype and OSA.

METHODS

We enrolled consecutive participants presenting to a sleep center in Shanghai, China. Full-night polysomnography was performed, and serum triglyceride (TG) levels and waist circumference (WC) were calculated. HTGW phenotype was defined as increased WC (men > 90 cm, women > 80 cm) and elevated TG levels (> 1.7 mmol/L). Participants were classified into four groups: normal TG with normal WC (NTNW); normal TG with increased WC (NTGW); elevated TG with normal WC (HTNW); and elevated TG with enlarged WC, namely HTGW. The relationships between HTGW phenotypes and OSA were assessed using binary (apnea hypopnea index, [AHI]≥5/hr) and multinomial logistic regression analyses (clinical AHI severity categories).

RESULTS

We included 3190 participants in this cross-sectional study. Compared to the NTNW phenotype, participants with NTGW and HTGW phenotypes had the significantly higher risk of OSA (AHI ≥5/hr, odds ratio [OR] = 2.51, 95% confidence interval [CI] = 1.91-3.31; OR = 3.76, 95% CI = 2.67-5.31, respectively), after adjustment for confounders. In subgroup analyses categorised by age, sex, and BMI, the aforementioned associations remained significant. The association between the NTGW, HTGW phenotype and OSA risk remained significant across the OSA severity groups. Multinomial logistic regression also revealed that the mild (OR = 1.63, 95% CI = 1.07-2.50), moderate (OR = 1.875, 95% CI = 1.22-2.88), and severe OSA (OR = 3.18, 95% CI = 2.14-4.73) were associated with HTGW phenotype.

CONCLUSION

Both NTGW and HTGW phenotype were positively associated with OSA risk in all subgroups. Further longitudinal follow-up studies are needed to determine the causal link and prognostic role of these metabolic factors.

Lipid accumulation product (LAP) was independently associatedwith obstructive sleep apnea in patients with type 2 diabetes mellitus

BACKGROUND

Lipid accumulation product (LAP) is a new index based on a combination of waist circumference (WC) and serum triglycerides (TG) reflecting lipid accumulation. In this cross-sectional study, we aimed to explore whether LAP was independently associated with obstructive sleep apnea (OSA) in Type 2 diabetes mellitus (T2DM) patients.

METHODS

A cross-sectional study of 317 T2DM patients who underwent overnight polysomnography (PSG) tests was conducted. The clinical data between non-OSA group and OSA group were compared. Multivariable linear regression and multivariable logistic regression analyses were performed to determine associations of LAP, with apnea-hypopnea index (AHI) and OSA.

RESULTS

Among 317 patients, 219 (69.1%) were men, and the mean ages (±SD) were 51.4 (±13.5) years for men and 54.6 (±15.1) years for women (p = 0.067). The prevalence rates of OSA were 63.0% for men and 68.4% for women (p = 0.357). LAP (log-transformed) was significantly correlated with AHI (log-transformed), with the Pearson's correlation coefficient of 0.170 (p = 0.002). With adjustment for potential confounding factors, multivariate linear regression analyses showed the association of LAP with AHI was not statistically significant, with the adjusted linear regression coefficients (95% CI) of per SD increase of LAP for AHI (log-transformed) was 0.092 (- 0.011-0.194, p = 0.080). Multivariate logistic regression analyses showed LAP was significantly associated with increased risk of OSA, with the adjusted OR (95%CI) of per SD increase of LAP of 1.639 (1.032-2.604, p = 0.036). However, as constituents of LAP, neither TG nor WC was significantly associated with AHI and OSA.

CONCLUSION

LAP was independently associated with OSA and might be used as a potential OSA risk marker in T2DM patients, beyond the general index of obesity.

Discordance between the triglyceride glucose index and fasting plasma glucose or HbA1C in patients with acute coronary syndrome undergoing percutaneous coronary intervention predicts cardiovascular events: a cohort study from China

Background

Previous studies have investigated the relationship of the triglyceride glucose (TyG) index with the incidence of cardiovascular events. However, to date, there have been no studies comparing the predictive values of fasting plasma glucose (FPG), glycosylated hemoglobin A (HbA1C) and the TyG index for the risk of cardiovascular events. This study aimed to use discordance analysis to evaluate and compare the effectiveness of FPG, HbA1C and the TyG index to predict the risk of cardiovascular events.

Methods

Patients diagnosed with acute coronary disease (ACS) undergoing percutaneous coronary intervention (PCI) were enrolled in this study. The TyG index was computed using the following formula: ln [fasting triglycerides (mg/dL) × FPG (mg/dL)/2]. We categorized patients into 4 concordance/discordance groups. Discordance was defined as a TyG index equal to or greater than the median and an FPG or HbA1C less than the median, or vice versa. The primary outcome was the composite of death, nonfatal myocardial infarction, nonfatal stroke and unplanned repeat revascularization. A Cox proportional hazards regression model was performed to estimate the risk of cardiovascular events according to the concordance/discordance groups. Sensitivity analysis was performed on each patient group divided into high or low categories for HbA1C or FPG and were repeated according to diabetes status.

Results

In total, 9285 patients were included in the final statistical analysis (male: 75.3%, age: 59.9 ± 10.05 years, BMI: 26.2 ± 9.21 kg/m², diabetes: 43.9% and dyslipidemia: 76.8%). The medians defining concordance/discordance were 6.19 mmol/L for FPG, 6.1% for HbA1C and 8.92 for the TyG index. The TyG index was strongly related to triglycerides and HDL-C (r = 0.881 and -0.323, respectively; both P < 0.001). During the 17.4 ± 2.69 months of follow-up, there were 480 (5.1%) incident cardiovascular events. Among patients with a lower HbA1C or FPG, 15.6% and 16.3%, respectively, had a discordantly high TyG index and a greater risk of cardiovascular events compared with patients with a concordantly low TyG index after full adjustment (HR: 1.92, 95% CI 1.33–2.77; HR: 1.89, 95% CI 1.38–2.59; for HbA1C and FPG, respectively). Repeat risk estimation using high or low categories for FPG or HbA1C and diabetes status confirmed the results.

Conclusions

Patients with a discordantly high TyG index had a significantly greater risk of cardiovascular events regardless of diabetes status. The TyG index might be a better predictor of cardiovascular risk than FPG or HbA1C for patients with ACS undergoing PCI. This discordance may support better cardiovascular risk management regardless of diabetes status.