A nomogram prediction model for predicting the risk of type 2 diabetes mellitus in patients with obstructive sleep apnea based on triglyceride-glucose index_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

HONG Xueling ,  LI Yongxia

Second Ward, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Kunming Medical University, Kuning, Yunnan 650000, P. R. China;

Corresponding author：

LI Yongxia, Email: yongxiali999@163.com

Keywords：

Obstructive sleep apnea; type 2 diabetes mellitus; insulin resistance; nomogram; apnea hypopnea index; triglyceride-glucose index

DOI：

10.7507/1671-6205.202409084

Video：

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Objective To construct, validate and evaluate a nomogram prediction model based on triglyceride-glucose index for predicting the risk of type 2 diabetes mellitus (T2DM) in patients with obstructive sleep apnea (OSA). Methods A total of 414 patients diagnosed with OSA who were hospitalized in the Second Affiliated Hospital of Kunming Medical University from July 2013 to July 2023 were retrospectively analyzed. They were randomly divided into training set (n=289) and validation set (n=125) at a ratio of 7:3 using R software. In the training set, univariate logistic regression, best subsets regression (BSR) and multivariate Logistic regression were used to determine the independent predictors of OSA combined with T2DM and construct a nomogram. The area under the receiver operating characteristic curve (AUC), calibration curve, Hosmer-Lemeshow goodness of fit test, decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the discrimination, calibration and clinical applicability of the nomogram prediction model. Finally, the internal validation of the nomogram prediction model was carried out on the validation set. Results In the training set, the results of univariate logistic regression, BSR and multivariate logistic regression analysis showed that hypertension (OR=2.413, 95%CI 1.276-4.563, P=0.007), apnea hypopnea index (OR=1.034, 95%CI 1.014-1.053, P=0.001), triglyceride-glucose index( OR=12.065, 95%CI 5.735-25.379, P<0.001), triglyceride/high density lipoprotein cholesterol (OR=0.736, 95%CI 0.634-0.855, P<0.001) were independent predictors of T2DM in OSA patients. A nomogram prediction model was constructed based on the above four predictors. In the training set and validation set, the AUC, sensitivity, and specificity of the nomogram prediction model for predicting the risk of T2DM in OSA patients were 0.820 (95%CI 0.771-0.869), 75.7%, 75.9% and 0.778 (95%CI 0.696-0.861), 74.5%, 73.0%, respectively, indicating that the nomogram had good discrimination. The calibration curve showed that the nomogram had a good calibration for predicting T2DM in OSA patients. DCA and CIC also showed that the nomogram prediction model had certain clinical utility. Conclusions A simple, fast and effective nomogram prediction model with good discrimination, calibration and clinical applicability was successfully constructed, validated and evaluated. It can be used to predict the risk of T2DM in OSA patients and help clinicians to identify patients with high risk of T2DM in OSA patients.

1.	Abbasi A, Gupta SS, Sabharwal N, et al. A comprehensive review of obstructive sleep apnea. Sleep Sci, 2021, 14(2): 142-154.
2.	Wang C, Tan J, Miao Y, et al. Obstructive sleep apnea, prediabetes and progression of type 2 diabetes: A systematic review and meta‐analysis. J Diabetes Investig, 2022, 13(8): 1396-1411.
3.	Zhang J, Tian L, Guo L. Changes of aldosterone levels in patients with type 2 diabetes complicated by moderate to severe obstructive sleep apnea–hypopnea syndrome before and after treatment with continuous positive airway pressure. J Int Med Res, 2019, 47(10): 4723-4733.
4.	Alterki A, Abu-Farha M, Al Shawaf E, et al. Investigating the relationship between obstructive sleep apnoea, inflammation and cardio-metabolic diseases. Int J Mol Sci, 2023, 24(7): 6807.
5.	Pugliese G, Barrea L, Laudisio D, et al. Sleep Apnea, obesity, and disturbed glucose homeostasis: epidemiologic evidence, biologic insights, and therapeutic strategies. Curr Obes Rep, 2020, 9(1): 30-38.
6.	Bakker JP, Baltzis D, Tecilazich F, et al. The effect of continuous positive airway pressure on vascular function and cardiac structure in diabetes and sleep apnea. a randomized controlled trial. Ann Am Thorac Soc, 2020, 17(4): 474-483.
7.	Sasaki N, Ozono R, Higashi Y, et al. Association of insulin resistance, plasma glucose level, and serum insulin level with hypertension in a population with different stages of impaired glucose metabolism. J Am Heart Assoc, 2020, 9(7): e015546.
8.	Luo P, Cao Y, Li P, et al. TyG index performs better than HOMA-IR in Chinese type 2 diabetes mellitus with a BMI<35 kg/m²: a hyperglycemic clamp validated study. Medicina (Kaunas), 2022, 58(7): 876.
9.	Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 1985, 28(7): 412-419.
10.	Jog KS, Eagappan S, Santharam RK, et al. Comparison of novel biomarkers of insulin resistance with homeostasis model assessment of insulin resistance, its correlation to metabolic syndrome in South Indian population and proposition of population specific cutoffs for these indices. Cureus, 2023, 15(1): e33653.
11.	Shi Y, Ma L, Chen X, et al. Prediction model of obstructive sleep apnea–related hypertension: machine learning–based development and interpretation study. Front Cardiovasc Med, 2022, 9: 1042996.
12.	Zeng Y, Zhao J, Zhang J, et al. Development of a Nomogram That predicts the risk of coronary heart disease in patients with hyperlipidemia. J Cardiovasc Pharmacol Ther, 2023, 28: 107424842311677.
13.	Guo J, Zhou Y, Zhou B. Development and validation of a new nomogram model for predicting acute ischemic stroke in elderly patients with non-valvular atrial fibrillation: a single-center cross-sectional study. Clin Interv Aging, 2024, 19: 67-79.
14.	Hu H, Nakagawa T, Honda T, et al. Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models. BMJ Open Diabetes Res Care, 2024, 12(1): e003680.
15.	Xue M, Liu L, Wang S, et al. A simple nomogram score for screening patients with type 2 diabetes to detect those with hypertension: a cross-sectional study based on a large community survey in China. PLoS One, 2020, 15(8): e0236957.
16.	Nie Q, Qin L, Yan W, et al. Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies. Front Endocrinol (Lausanne), 2023, 14: 1118620.
17.	Che B, Zhong C, Zhang R, et al. Triglyceride-glucose index and triglyceride to high-density lipoprotein cholesterol ratio as potential cardiovascular disease risk factors: an analysis of UK biobank data. Cardiovasc Diabetol, 2023, 22(1): 34.
18.	Berry RB, Budhiraja R, Gottlieb DJ, et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events: Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med, 2012, 8(5): 597-619.
19.	中国高血压防治指南修订委员会, 高血压联盟(中国), 中华医学会心血管病学分会, 等. 中国高血压防治指南(2018年修订版). 中国心血管杂志, 2019, 24(1): 24-56.
20.	Knuuti J, Wijns W, Saraste A, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes: The Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC). Eur Heart J, 2020, 41(3): 407-477.
21.	中华医学会, 中华医学会杂志社, 中华医学会全科医学分会, 等. 缺血性卒中基层诊疗指南(2021年). 中华全科医师杂志, 2021, 20(09): 927-946.
22.	中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2020年版)(上). 中国实用内科杂志, 2021, 41(8): 668-695.
23.	Michalek-Zrabkowska M, Macek P, Martynowicz H, et al. Obstructive sleep apnea as a risk factor of insulin resistance in nondiabetic adults. Life (Basel), 2021, 11(1): 50.
24.	Behnoush AH, Khalaji A, Ghondaghsaz E, et al. Triglyceride-glucose index and obstructive sleep apnea: a systematic review and meta-analysis. Lipids Health Dis, 2024, 23(1): 4.
25.	Zhang M, Wang B, Liu Y, et al. Cumulative increased risk of incident type 2 diabetes mellitus with increasing triglyceride glucose index in normal-weight people: The Rural Chinese Cohort Study. Cardiovasc Diabetol, 2017, 16: 30.
26.	Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, et al. Triglyceride–glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN cohort. Prev Med, 2016, 86: 99-105.
27.	Liu H, Yan S, Chen G, et al. Association of the ratio of triglycerides to high-density lipoprotein cholesterol levels with the risk of type 2 diabetes: a retrospective cohort study in beijing. J Diabetes Res, 2021, 2021: e5524728.
28.	Lin D, Qi Y, Huang C, et al. Associations of lipid parameters with insulin resistance and diabetes: a population-based study. Clin Nutr, 2018, 37(4): 1423-1429.
29.	Lim TK, Lee HS, Lee YJ. Triglyceride to HDL-cholesterol ratio and the incidence risk of type 2 diabetes in community dwelling adults: a longitudinal 12-year analysis of the Korean Genome and Epidemiology Study. Diabetes Res Clin Pr, 2020, 163: 108150.
30.	Li X, Xue Y, Dang Y, et al. Association of non-insulin-based insulin resistance indices with risk of incident prediabetes and diabetes in a Chinese rural population: a 12-year prospective study. Diabetes Metab Syndr Obes, 2022, 15: 3809.
31.	Mokhlesi B, Tjaden AH, Temple KA, et al. Obstructive sleep apnea, glucose tolerance, and β-cell function in adults with prediabetes or untreated type 2 diabetes in the Restoring Insulin Secretion (RISE) Study. Diabetes Care, 2021, 44(4): 993-1001.
32.	夏露, 李镇圻, 谢治年, 等. 阻塞性睡眠呼吸暂停和2型糖尿病: 一项双向孟德尔随机化研究. 中华耳鼻咽喉头颈外科杂志, 2023, 58(10): 974-979.
33.	Oscullo G, Torres G, Campos-Rodriguez F, et al. Resistant/refractory hypertension and sleep apnoea: current knowledge and future challenges. J Clin Med, 2019, 8(11): 1872.
34.	Bikov A, Frent S, Pleava R, et al. The burden of associated comorbidities in patients with obstructive sleep apnea-regional differences in two Central-Eastern European sleep centers. J Clin Med, 2020, 9(11): 3583.
35.	Alsaadon H, Afroz A, Karim A, et al. Hypertension and its related factors among patients with type 2 diabetes mellitus - a multi-hospital study in Bangladesh. BMC public health, 2022, 22(1): 198.
36.	Wang B, Yang Y, Li X. Interaction of Hypertension and insulin resistance exacerbates the occurrence of diabetes mellitus in healthy individuals. J Diabetes Res, 2022, 2022: 9289812.
37.	Archontogeorgis K, Papanas N, Nena E, et al. Insulin sensitivity and insulin resistance in non-diabetic middle-aged patients with obstructive sleep apnoea syndrome. Open Cardiovasc Med J, 2017, 11: 159-168.
38.	Knutson KL, Van Cauter E, Zee P, et al. Cross-sectional associations between measures of sleep and markers of glucose metabolism among subjects with and without diabetes. Diabetes Care, 2011, 34(5): 1171-1176.

1. Abbasi A, Gupta SS, Sabharwal N, et al. A comprehensive review of obstructive sleep apnea. Sleep Sci, 2021, 14(2): 142-154.
2. Wang C, Tan J, Miao Y, et al. Obstructive sleep apnea, prediabetes and progression of type 2 diabetes: A systematic review and meta‐analysis. J Diabetes Investig, 2022, 13(8): 1396-1411.
3. Zhang J, Tian L, Guo L. Changes of aldosterone levels in patients with type 2 diabetes complicated by moderate to severe obstructive sleep apnea–hypopnea syndrome before and after treatment with continuous positive airway pressure. J Int Med Res, 2019, 47(10): 4723-4733.
4. Alterki A, Abu-Farha M, Al Shawaf E, et al. Investigating the relationship between obstructive sleep apnoea, inflammation and cardio-metabolic diseases. Int J Mol Sci, 2023, 24(7): 6807.
5. Pugliese G, Barrea L, Laudisio D, et al. Sleep Apnea, obesity, and disturbed glucose homeostasis: epidemiologic evidence, biologic insights, and therapeutic strategies. Curr Obes Rep, 2020, 9(1): 30-38.
6. Bakker JP, Baltzis D, Tecilazich F, et al. The effect of continuous positive airway pressure on vascular function and cardiac structure in diabetes and sleep apnea. a randomized controlled trial. Ann Am Thorac Soc, 2020, 17(4): 474-483.
7. Sasaki N, Ozono R, Higashi Y, et al. Association of insulin resistance, plasma glucose level, and serum insulin level with hypertension in a population with different stages of impaired glucose metabolism. J Am Heart Assoc, 2020, 9(7): e015546.
8. Luo P, Cao Y, Li P, et al. TyG index performs better than HOMA-IR in Chinese type 2 diabetes mellitus with a BMI<35 kg/m²: a hyperglycemic clamp validated study. Medicina (Kaunas), 2022, 58(7): 876.
9. Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 1985, 28(7): 412-419.
10. Jog KS, Eagappan S, Santharam RK, et al. Comparison of novel biomarkers of insulin resistance with homeostasis model assessment of insulin resistance, its correlation to metabolic syndrome in South Indian population and proposition of population specific cutoffs for these indices. Cureus, 2023, 15(1): e33653.
11. Shi Y, Ma L, Chen X, et al. Prediction model of obstructive sleep apnea–related hypertension: machine learning–based development and interpretation study. Front Cardiovasc Med, 2022, 9: 1042996.
12. Zeng Y, Zhao J, Zhang J, et al. Development of a Nomogram That predicts the risk of coronary heart disease in patients with hyperlipidemia. J Cardiovasc Pharmacol Ther, 2023, 28: 107424842311677.
13. Guo J, Zhou Y, Zhou B. Development and validation of a new nomogram model for predicting acute ischemic stroke in elderly patients with non-valvular atrial fibrillation: a single-center cross-sectional study. Clin Interv Aging, 2024, 19: 67-79.
14. Hu H, Nakagawa T, Honda T, et al. Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models. BMJ Open Diabetes Res Care, 2024, 12(1): e003680.
15. Xue M, Liu L, Wang S, et al. A simple nomogram score for screening patients with type 2 diabetes to detect those with hypertension: a cross-sectional study based on a large community survey in China. PLoS One, 2020, 15(8): e0236957.
16. Nie Q, Qin L, Yan W, et al. Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies. Front Endocrinol (Lausanne), 2023, 14: 1118620.
17. Che B, Zhong C, Zhang R, et al. Triglyceride-glucose index and triglyceride to high-density lipoprotein cholesterol ratio as potential cardiovascular disease risk factors: an analysis of UK biobank data. Cardiovasc Diabetol, 2023, 22(1): 34.
18. Berry RB, Budhiraja R, Gottlieb DJ, et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events: Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med, 2012, 8(5): 597-619.
19. 中国高血压防治指南修订委员会, 高血压联盟(中国), 中华医学会心血管病学分会, 等. 中国高血压防治指南(2018年修订版). 中国心血管杂志, 2019, 24(1): 24-56.
20. Knuuti J, Wijns W, Saraste A, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes: The Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC). Eur Heart J, 2020, 41(3): 407-477.
21. 中华医学会, 中华医学会杂志社, 中华医学会全科医学分会, 等. 缺血性卒中基层诊疗指南(2021年). 中华全科医师杂志, 2021, 20(09): 927-946.
22. 中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2020年版)(上). 中国实用内科杂志, 2021, 41(8): 668-695.
23. Michalek-Zrabkowska M, Macek P, Martynowicz H, et al. Obstructive sleep apnea as a risk factor of insulin resistance in nondiabetic adults. Life (Basel), 2021, 11(1): 50.
24. Behnoush AH, Khalaji A, Ghondaghsaz E, et al. Triglyceride-glucose index and obstructive sleep apnea: a systematic review and meta-analysis. Lipids Health Dis, 2024, 23(1): 4.
25. Zhang M, Wang B, Liu Y, et al. Cumulative increased risk of incident type 2 diabetes mellitus with increasing triglyceride glucose index in normal-weight people: The Rural Chinese Cohort Study. Cardiovasc Diabetol, 2017, 16: 30.
26. Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, et al. Triglyceride–glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN cohort. Prev Med, 2016, 86: 99-105.
27. Liu H, Yan S, Chen G, et al. Association of the ratio of triglycerides to high-density lipoprotein cholesterol levels with the risk of type 2 diabetes: a retrospective cohort study in beijing. J Diabetes Res, 2021, 2021: e5524728.
28. Lin D, Qi Y, Huang C, et al. Associations of lipid parameters with insulin resistance and diabetes: a population-based study. Clin Nutr, 2018, 37(4): 1423-1429.
29. Lim TK, Lee HS, Lee YJ. Triglyceride to HDL-cholesterol ratio and the incidence risk of type 2 diabetes in community dwelling adults: a longitudinal 12-year analysis of the Korean Genome and Epidemiology Study. Diabetes Res Clin Pr, 2020, 163: 108150.
30. Li X, Xue Y, Dang Y, et al. Association of non-insulin-based insulin resistance indices with risk of incident prediabetes and diabetes in a Chinese rural population: a 12-year prospective study. Diabetes Metab Syndr Obes, 2022, 15: 3809.
31. Mokhlesi B, Tjaden AH, Temple KA, et al. Obstructive sleep apnea, glucose tolerance, and β-cell function in adults with prediabetes or untreated type 2 diabetes in the Restoring Insulin Secretion (RISE) Study. Diabetes Care, 2021, 44(4): 993-1001.
32. 夏露, 李镇圻, 谢治年, 等. 阻塞性睡眠呼吸暂停和2型糖尿病: 一项双向孟德尔随机化研究. 中华耳鼻咽喉头颈外科杂志, 2023, 58(10): 974-979.
33. Oscullo G, Torres G, Campos-Rodriguez F, et al. Resistant/refractory hypertension and sleep apnoea: current knowledge and future challenges. J Clin Med, 2019, 8(11): 1872.
34. Bikov A, Frent S, Pleava R, et al. The burden of associated comorbidities in patients with obstructive sleep apnea-regional differences in two Central-Eastern European sleep centers. J Clin Med, 2020, 9(11): 3583.
35. Alsaadon H, Afroz A, Karim A, et al. Hypertension and its related factors among patients with type 2 diabetes mellitus - a multi-hospital study in Bangladesh. BMC public health, 2022, 22(1): 198.
36. Wang B, Yang Y, Li X. Interaction of Hypertension and insulin resistance exacerbates the occurrence of diabetes mellitus in healthy individuals. J Diabetes Res, 2022, 2022: 9289812.
37. Archontogeorgis K, Papanas N, Nena E, et al. Insulin sensitivity and insulin resistance in non-diabetic middle-aged patients with obstructive sleep apnoea syndrome. Open Cardiovasc Med J, 2017, 11: 159-168.
38. Knutson KL, Van Cauter E, Zee P, et al. Cross-sectional associations between measures of sleep and markers of glucose metabolism among subjects with and without diabetes. Diabetes Care, 2011, 34(5): 1171-1176.

Chinese Journal of Respiratory and Critical Care Medicine

Latest ArticlesA nomogram prediction model for predicting the risk of type 2 diabetes mellitus in patients with obstructive sleep apnea based on triglyceride-glucose index

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