請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91824完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 杜裕康 | zh_TW |
| dc.contributor.advisor | Yu-Kang Tu | en |
| dc.contributor.author | 黃暉凱 | zh_TW |
| dc.contributor.author | Huei-Kai Huang | en |
| dc.date.accessioned | 2024-02-22T16:53:24Z | - |
| dc.date.available | 2024-02-23 | - |
| dc.date.copyright | 2024-02-22 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-02-04 | - |
| dc.identifier.citation | References
1. Zheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol. 2018;14(2):88-98. 2. International Diabetes Federation. IDF Diabetes Atlas, 10th edn. Brussels, Belgium: 2021. Available at: https://www.diabetesatlas.org. 3. Zimmet PZ. Diabetes and its drivers: the largest epidemic in human history? Clinical Diabetes and Endocrinology. 2017;3(1):1. 4. Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Research and Clinical Practice. 2010;87(1):4-14. 5. Zheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nature Reviews Endocrinology. 2018;14(2):88-98. 6. Murea M, Ma L, Freedman BI. Genetic and environmental factors associated with type 2 diabetes and diabetic vascular complications. Rev Diabet Stud. 2012;9(1):6-22. 7. Kolb H, Martin S. Environmental/lifestyle factors in the pathogenesis and prevention of type 2 diabetes. BMC Medicine. 2017;15(1):131. 8. Banday MZ, Sameer AS, Nissar S. Pathophysiology of diabetes: An overview. Avicenna J Med. 2020;10(4):174-188. 9. Avramidis I, Apsemidou A, Lalia AZ, et al. Lessons From a Diabetes Clinic: Achieving Glycemic Goals and Clinical Use of Antidiabetic Agents in Patients With Type 2 Diabetes. Clinical Diabetes. 2020;38(3):248-255. 10. Presley CA, Khodneva Y, Juarez LD, et al. Trends and Predictors of Glycemic Control Among Adults With Type 2 Diabetes Covered by Alabama Medicaid, 2011-2019. Prev Chronic Dis. 2023;20:E81. 11. Deshpande AD, Harris-Hayes M, Schootman M. Epidemiology of diabetes and diabetes-related complications. Phys Ther. 2008;88(11):1254-1264. 12. Umpierrez G, Korytkowski M. Diabetic emergencies - ketoacidosis, hyperglycaemic hyperosmolar state and hypoglycaemia. Nat Rev Endocrinol. 2016;12(4):222-232. 13. Litwak L, Goh SY, Hussein Z, Malek R, Prusty V, Khamseh ME. Prevalence of diabetes complications in people with type 2 diabetes mellitus and its association with baseline characteristics in the multinational A1chieve study. Diabetol Metab Syndr. 2013;5(1):57. 14. Raptis SA, Dimitriadis GD. Oral hypoglycemic agents: insulin secretagogues, alpha-glucosidase inhibitors and insulin sensitizers. Exp Clin Endocrinol Diabetes. 2001;109 Suppl 2:S265-287. 15. Cryer PE. Minireview: Glucagon in the pathogenesis of hypoglycemia and hyperglycemia in diabetes. Endocrinology. 2012;153(3):1039-1048. 16. Heller SR, Peyrot M, Oates SK, Taylor AD. Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen. BMJ Open Diabetes Res Care. 2020;8(1). 17. Chow E, Bernjak A, Williams S, et al. Risk of Cardiac Arrhythmias During Hypoglycemia in Patients With Type 2 Diabetes and Cardiovascular Risk. Diabetes. 2014;63(5):1738-1747. 18. Andersen A, Bagger JI, Baldassarre MPA, et al. Acute hypoglycemia and risk of cardiac arrhythmias in insulin-treated type 2 diabetes and controls. Eur J Endocrinol. 2021;185(2):343-353. 19. Chugh SS, Havmoeller R, Narayanan K, et al. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study. Circulation. 2014;129(8):837-847. 20. Zoni-Berisso M, Lercari F, Carazza T, Domenicucci S. Epidemiology of atrial fibrillation: European perspective. Clin Epidemiol. 2014;6:213-220. 21. Chao TF, Liu CJ, Tuan TC, et al. Lifetime Risks, Projected Numbers, and Adverse Outcomes in Asian Patients With Atrial Fibrillation: A Report From the Taiwan Nationwide AF Cohort Study. Chest. 2018;153(2):453-466. 22. Escudero-Martínez I, Morales-Caba L, Segura T. Atrial fibrillation and stroke: A review and new insights. Trends Cardiovasc Med. 2023;33(1):23-29. 23. Wutzler A, Krogias C, Grau A, Veltkamp R, Heuschmann PU, Haeusler KG. Stroke prevention in patients with acute ischemic stroke and atrial fibrillation in Germany - a cross sectional survey. BMC Neurology. 2019;19(1):25. 24. Lacoste JL, Szymanski TW, Avalon JC, et al. Atrial Fibrillation Management: A Comprehensive Review with a Focus on Pharmacotherapy, Rate, and Rhythm Control Strategies. Am J Cardiovasc Drugs. 2022;22(5):475-496. 25. Katsanos AH, Kamel H, Healey JS, Hart RG. Stroke Prevention in Atrial Fibrillation: Looking Forward. Circulation. 2020;142(24):2371-2388. 26. Hatem SN, Redheuil A, Gandjbakhch E. Cardiac adipose tissue and atrial fibrillation: the perils of adiposity. Cardiovascular Research. 2016;109(4):502-509. 27. Sun Y, Hu D. The link between diabetes and atrial fibrillation: cause or correlation? J Cardiovasc Dis Res. 2010;1(1):10-11. 28. Wang A, Green JB, Halperin JL, Piccini JP, Sr. Atrial Fibrillation and Diabetes Mellitus: JACC Review Topic of the Week. J Am Coll Cardiol. 2019;74(8):1107-1115. 29. Plitt A, McGuire DK, Giugliano RP. Atrial Fibrillation, Type 2 Diabetes, and Non-Vitamin K Antagonist Oral Anticoagulants: A Review. JAMA Cardiol. 2017;2(4):442-448. 30. Fangel MV, Nielsen PB, Kristensen JK, et al. Glycemic Status and Thromboembolic Risk in Patients With Atrial Fibrillation and Type 2 Diabetes Mellitus: A Danish Cohort Study. Circ Arrhythm Electrophysiol. 2019;12(5):e007030. 31. Chan YH, Chuang C, Chan CC, et al. Glycemic status and risks of thromboembolism and major bleeding in patients with atrial fibrillation. Cardiovasc Diabetol. 2020;19(1):30. 32. Maruhashi T, Higashi Y. Pathophysiological Association between Diabetes Mellitus and Endothelial Dysfunction. Antioxidants. 2021;10(8):1306. 33. Tabit CE, Chung WB, Hamburg NM, Vita JA. Endothelial dysfunction in diabetes mellitus: molecular mechanisms and clinical implications. Rev Endocr Metab Disord. 2010;11(1):61-74. 34. Carr ME. Diabetes mellitus: A hypercoagulable state. Journal of Diabetes and its Complications. 2001;15(1):44-54. 35. Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest. 2010;137(2):263-272. 36. Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJ, Lip GY. A novel user-friendly score (HAS-BLED) to assess 1-year risk of major bleeding in patients with atrial fibrillation: the Euro Heart Survey. Chest. 2010;138(5):1093-1100. 37. Pengo V, Denas G. Optimizing quality care for the oral vitamin K antagonists (VKAs). Hematology Am Soc Hematol Educ Program. 2018;2018(1):332-338. 38. Jin C, Cui C, Seplowe M, et al. Anticoagulation for Atrial Fibrillation: A Review of Current Literature and Views. Cardiol Rev. 2022. 39. Mekaj YH, Mekaj AY, Duci SB, Miftari EI. New oral anticoagulants: their advantages and disadvantages compared with vitamin K antagonists in the prevention and treatment of patients with thromboembolic events. Ther Clin Risk Manag. 2015;11:967-977. 40. Manning WJ, Singer DE, Lip GY. Atrial fibrillation in adults: Use of oral anticoagulants. UpToDate. 2023. Retrieved January 1, 2024, from https://www.uptodate.com/contents/atrial-fibrillation-in-adults-use-of-oral-anticoagulants. 41. Qamar A, Vaduganathan M, Greenberger NJ, Giugliano RP. Oral Anticoagulation in Patients With Liver Disease. Journal of the American College of Cardiology. 2018;71(19):2162-2175. 42. Li Y, Chen JP, Duan L, Li S. Effect of vitamin K2 on type 2 diabetes mellitus: A review. Diabetes Res Clin Pract. 2018;136:39-51. 43. Manna P, Kalita J. Beneficial role of vitamin K supplementation on insulin sensitivity, glucose metabolism, and the reduced risk of type 2 diabetes: A review. Nutrition. 2016;32(7-8):732-739. 44. Karamzad N, Maleki V, Carson-Chahhoud K, Azizi S, Sahebkar A, Gargari BP. A systematic review on the mechanisms of vitamin K effects on the complications of diabetes and pre-diabetes. Biofactors. 2020;46(1):21-37. 45. Rasekhi H, Karandish M, Jalali MT, et al. Phylloquinone supplementation improves glycemic status independent of the effects of adiponectin levels in premonopause women with prediabetes: a double-blind randomized controlled clinical trial. J Diabetes Metab Disord. 2015;14(1):1. 46. Yoshida M, Jacques PF, Meigs JB, et al. Effect of vitamin K supplementation on insulin resistance in older men and women. Diabetes Care. 2008;31(11):2092-2096. 47. Beulens JW, van der AD, Grobbee DE, Sluijs I, Spijkerman AM, van der Schouw YT. Dietary phylloquinone and menaquinones intakes and risk of type 2 diabetes. Diabetes Care. 2010;33(8):1699-1705. 48. Huang HK, Liu PP, Lin SM, et al. Risk of developing diabetes in patients with atrial fibrillation taking non-vitamin K antagonist oral anticoagulants or warfarin: A nationwide cohort study. Diabetes Obes Metab. 2021;23(2):499-507. 49. Cheung CL, Sing CW, Lau WCY, et al. Treatment with direct oral anticoagulants or warfarin and the risk for incident diabetes among patients with atrial fibrillation: a population-based cohort study. Cardiovasc Diabetol. 2021;20(1):71. 50. Esmon CT. Targeting factor Xa and thrombin: impact on coagulation and beyond. Thromb Haemost. 2014;111(4):625-633. 51. Licari LG, Kovacic JP. Thrombin physiology and pathophysiology. J Vet Emerg Crit Care (San Antonio). 2009;19(1):11-22. 52. ten Cate H. Tissue factor-driven thrombin generation and inflammation in atherosclerosis. Thromb Res. 2012;129 Suppl 2:S38-40. 53. Ezekowitz JA, Lewis BS, Lopes RD, et al. Clinical outcomes of patients with diabetes and atrial fibrillation treated with apixaban: results from the ARISTOTLE trial. Eur Heart J Cardiovasc Pharmacother. 2015;1(2):86-94. 54. Baker WL, Beyer-Westendorf J, Bunz TJ, et al. Effectiveness and safety of rivaroxaban and warfarin for prevention of major adverse cardiovascular or limb events in patients with non-valvular atrial fibrillation and type 2 diabetes. Diabetes Obes Metab. 2019;21(9):2107-2114. 55. Korgaonkar S, Yang Y, Banahan B, 3rd, Bentley JP. Comparative effectiveness and safety of non-vitamin-K antagonist oral anticoagulants and warfarin in older adults with atrial fibrillation and diabetes. Curr Med Res Opin. 2021;37(3):343-356. 56. Brambatti M, Darius H, Oldgren J, et al. Comparison of dabigatran versus warfarin in diabetic patients with atrial fibrillation: Results from the RE-LY trial. Int J Cardiol. 2015;196:127-131. 57. Bansilal S, Bloomgarden Z, Halperin JL, et al. Efficacy and safety of rivaroxaban in patients with diabetes and nonvalvular atrial fibrillation: the Rivaroxaban Once-daily, Oral, Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF Trial). Am Heart J. 2015;170(4):675-682.e678. 58. Giugliano RP, Ruff CT, Braunwald E, et al. Edoxaban versus warfarin in patients with atrial fibrillation. N Engl J Med. 2013;369(22):2093-2104. 59. Hsu CC, Hsu PF, Sung SH, et al. Is There a Preferred Stroke Prevention Strategy for Diabetic Patients with Non-Valvular Atrial Fibrillation? Comparing Warfarin, Dabigatran and Rivaroxaban. Thromb Haemost. 2018;118(1):72-81. 60. Yao X, Tangri N, Gersh BJ, et al. Renal Outcomes in Anticoagulated Patients With Atrial Fibrillation. J Am Coll Cardiol. 2017;70(21):2621-2632. 61. Hernandez AV, Bradley G, Khan M, et al. Rivaroxaban vs. warfarin and renal outcomes in non-valvular atrial fibrillation patients with diabetes. Eur Heart J Qual Care Clin Outcomes. 2020;6(4):301-307. 62. Dimakos J, Cui Y, Platt RW, Renoux C, Filion KB, Douros A. Concomitant Use of Sulfonylureas and Warfarin and the Risk of Severe Hypoglycemia: Population-Based Cohort Study. Diabetes Care. 2022;45(10):e131-e133. 63. Chao TF, Chiang CE, Liao JN, Chen TJ, Lip GYH, Chen SA. Comparing the Effectiveness and Safety of Nonvitamin K Antagonist Oral Anticoagulants and Warfarin in Elderly Asian Patients With Atrial Fibrillation: A Nationwide Cohort Study. Chest. 2020;157(5):1266-1277. 64. Tsai CT, Liao JN, Chen SJ, Jiang YR, Chen TJ, Chao TF. Non-vitamin K antagonist oral anticoagulants versus warfarin in AF patients ≥ 85 years. Eur J Clin Invest. 2021:e13488. 65. Triplitt C. Drug Interactions of Medications Commonly Used in Diabetes. Diabetes Spectrum. 2006;19(4):202-211. 66. Romley JA, Gong C, Jena AB, Goldman DP, Williams B, Peters A. Association between use of warfarin with common sulfonylureas and serious hypoglycemic events: retrospective cohort analysis. Bmj. 2015;351:h6223. 67. Nam YH, Brensinger CM, Bilker WB, Leonard CE, Han X, Hennessy S. Serious Hypoglycemia and Use of Warfarin in Combination With Sulfonylureas or Metformin. Clin Pharmacol Ther. 2019;105(1):210-218. 68. Alwafi H, Wong ICK, Naser AY, et al. Concurrent Use of Oral Anticoagulants and Sulfonylureas in Individuals With Type 2 Diabetes and Risk of Hypoglycemia: A UK Population-Based Cohort Study. Front Med (Lausanne). 2022;9:893080. 69. Hsieh CY, Su CC, Shao SC, et al. Taiwan''s National Health Insurance Research Database: past and future. Clin Epidemiol. 2019;11:349-358. 70. Hsing AW, Ioannidis JP. Nationwide Population Science: Lessons From the Taiwan National Health Insurance Research Database. JAMA Intern Med. 2015;175(9):1527-1529. 71. Matthews AA, Danaei G, Islam N, Kurth T. Target trial emulation: applying principles of randomised trials to observational studies. Bmj. 2022;378:e071108. 72. Hernán MA, Robins JM. Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available. Am J Epidemiol. 2016;183(8):758-764. 73. Kutcher SA, Brophy JM, Banack HR, Kaufman JS, Samuel M. Emulating a Randomised Controlled Trial With Observational Data: An Introduction to the Target Trial Framework. Can J Cardiol. 2021;37(9):1365-1377. 74. García-Albéniz X, Hsu J, Hernán MA. The value of explicitly emulating a target trial when using real world evidence: an application to colorectal cancer screening. Eur J Epidemiol. 2017;32(6):495-500. 75. Hernán MA, Sauer BC, Hernández-Díaz S, Platt R, Shrier I. Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses. J Clin Epidemiol. 2016;79:70-75. 76. Maringe C, Benitez Majano S, Exarchakou A, et al. Reflection on modern methods: trial emulation in the presence of immortal-time bias. Assessing the benefit of major surgery for elderly lung cancer patients using observational data. Int J Epidemiol. 2020;49(5):1719-1729. 77. Chen A, Stecker E, B AW. Direct Oral Anticoagulant Use: A Practical Guide to Common Clinical Challenges. J Am Heart Assoc. 2020;9(13):e017559. 78. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43(11):1130-1139. 79. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. 80. Pamukcu B, Lip GY, Lane DA. Simplifying stroke risk stratification in atrial fibrillation patients: implications of the CHA2DS2-VASc risk stratification scores. Age Ageing. 2010;39(5):533-535. 81. Austin PC. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate Behav Res. 2011;46(3):399-424. 82. Rubin DB. Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation. Health Services and Outcomes Research Methodology. 2001;2(3):169-188. 83. Elze MC, Gregson J, Baber U, et al. Comparison of Propensity Score Methods and Covariate Adjustment: Evaluation in 4 Cardiovascular Studies. J Am Coll Cardiol. 2017;69(3):345-357. 84. Austin PC, Xin Yu AY, Vyas MV, Kapral MK. Applying Propensity Score Methods in Clinical Research in Neurology. Neurology. 2021;97(18):856-863. 85. Brookhart MA, Wyss R, Layton JB, Stürmer T. Propensity score methods for confounding control in nonexperimental research. Circ Cardiovasc Qual Outcomes. 2013;6(5):604-611. 86. Desai RJ, Franklin JM. Alternative approaches for confounding adjustment in observational studies using weighting based on the propensity score: a primer for practitioners. Bmj. 2019;367:l5657. 87. Robins JM, Hernán MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11(5):550-560. 88. Xu S, Ross C, Raebel MA, Shetterly S, Blanchette C, Smith D. Use of stabilized inverse propensity scores as weights to directly estimate relative risk and its confidence intervals. Value Health. 2010;13(2):273-277. 89. Austin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Stat Med. 2015;34(28):3661-3679. 90. Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm Stat. 2011;10(2):150-161. 91. Heinze G, Jüni P. An overview of the objectives of and the approaches to propensity score analyses. Eur Heart J. 2011;32(14):1704-1708. 92. Austin PC. The relative ability of different propensity score methods to balance measured covariates between treated and untreated subjects in observational studies. Med Decis Making. 2009;29(6):661-677. 93. Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med. 2009;28(25):3083-3107. 94. Austin PC, Lee DS, Fine JP. Introduction to the Analysis of Survival Data in the Presence of Competing Risks. Circulation. 2016;133(6):601-609. 95. Austin PC. A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications. Int Stat Rev. 2017;85(2):185-203. 96. Balan TA, Putter H. A tutorial on frailty models. Stat Methods Med Res. 2020;29(11):3424-3454. 97. Andrade SE, Kahler KH, Frech F, Chan KA. Methods for evaluation of medication adherence and persistence using automated databases. Pharmacoepidemiol Drug Saf. 2006;15(8):565-574. 98. Seeger JD, Bykov K, Bartels DB, Huybrechts K, Schneeweiss S. Propensity Score Weighting Compared to Matching in a Study of Dabigatran and Warfarin. Drug Saf. 2017;40(2):169-181. 99. Haneuse S, VanderWeele TJ, Arterburn D. Using the E-Value to Assess the Potential Effect of Unmeasured Confounding in Observational Studies. Jama. 2019;321(6):602-603. 100. VanderWeele TJ, Ding P. Sensitivity Analysis in Observational Research: Introducing the E-Value. Ann Intern Med. 2017;167(4):268-274. 101. Lipsitch M, Tchetgen Tchetgen E, Cohen T. Negative controls: a tool for detecting confounding and bias in observational studies. Epidemiology. 2010;21(3):383-388. 102. Gianchandani RY, Neupane S, Iyengar JJ, Heung M. Pathophysiology and management of hypoglycemiain end-stage renal disease patients: a review. Endocr Pract. 2017;23(3):353-362. 103. Chesnaye NC, Stel VS, Tripepi G, et al. An introduction to inverse probability of treatment weighting in observational research. Clin Kidney J. 2022;15(1):14-20. 104. Yu HY, Tsai HE, Chen YS, Hung KY. Comparison of warfarin dosage fluctuation with time in therapeutic range for bleeding or thromboembolism rate in Chinese patients. J Formos Med Assoc. 2019;118(2):611-618. 105. Copeland KT, Checkoway H, McMichael AJ, Holbrook RH. Bias due to misclassification in the estimation of relative risk. Am J Epidemiol. 1977;105(5):488-495. 106. Höfler M. The effect of misclassification on the estimation of association: a review. Int J Methods Psychiatr Res. 2005;14(2):92-101. 107. Chen HL, Hsiao FY. Risk of hospitalization and healthcare cost associated with Diabetes Complication Severity Index in Taiwan''s National Health Insurance Research Database. J Diabetes Complications. 2014;28(5):612-616. 108. Hernán MA. Causal analyses of existing databases: no power calculations required. J Clin Epidemiol. 2022;144:203-205. 109. Group IHS. Hypoglycaemia, cardiovascular disease, and mortality in diabetes: epidemiology, pathogenesis, and management. Lancet Diabetes Endocrinol. 2019;7(5):385-396. 110. Shafiee G, Mohajeri-Tehrani M, Pajouhi M, Larijani B. The importance of hypoglycemia in diabetic patients. J Diabetes Metab Disord. 2012;11(1):17. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91824 | - |
| dc.description.abstract | 引言:
心房顫動和糖尿病是全球性的重要公共衛生問題,隨著人口老化,其盛行率和發病率皆不斷上升。患有心房顫動的病人,尤其又同時患有糖尿病的病人,有相當高的中風發生風險,因此往往需要長期使用口服抗凝血藥物來預防中風。先前有研究指出,維生素K可能對於改善胰島素敏感性和葡萄糖耐受性有所助益。亦有研究進一步指出,非維生素K拮抗劑口服抗凝血劑(non-vitamin K antagonist oral anticoagulants, NOAC)和維生素K拮抗劑華法林(warfarin),對維生素K功能抑制與否之不同,可能導致其使用者,在葡萄糖耐受性和糖尿病控制方面存在差異。然而,目前有關NOAC與warfarin的使用,對於心房顫動和糖尿病病患其各種糖尿病相關併發症發生風險的潛在影響,臨床證據仍然不足。此外,先前曾有研究指出,warfarin與某些糖尿病藥物之間可能有潛在的藥物交互作用,併用時可能增加低血糖風險,但關於NOAC與warfarin的使用對於低血糖風險影響之比較,相關證據仍相當缺乏。在心房顫動和糖尿病病患中,選擇適當的口服抗凝血藥物以最小化糖尿病併發症和低血糖的風險,是重要的臨床問題,然而相關研究證據有限,仍需要進一步探討。 研究目的: 我們的第一項研究旨在探討心房顫動和糖尿病病患使用NOAC相較於warfarin,對糖尿病各項相關併發症和死亡風險的影響。我們的第二項研究旨在探討病患在使用各種糖尿病藥物時,併用NOAC相較於併用warfarin,對於嚴重低血糖風險的影響。 方法: 我們使用台灣全人口健保資料庫,進行回顧性世代研究。我們納入了健保資料庫中曾診斷有心房顫動和糖尿病,並有使用NOAC或warfarin的患者。在研究一中,我們使用目標試驗模擬設計,比較NOAC與warfarin使用者在糖尿病相關併發症(包含大血管併發症、小血管併發症和血糖急症)和死亡風險的差異。我們使用穩定治療權重倒數機率(stabilized inverse probability of treatment weighting, IPTW),來建立一個在不同治療組之間具有相似患者特性的假想族群進行分析。我們採用Cox比例風險模型來估計風險比(hazard ratio, HR)。在研究二中,我們使用泊松回歸模型估計嚴重低血糖的發生率比(incidence rate ratio, IRR)。同樣使用穩定治療權重倒數機率來平衡治療組之間的特徵,以進行分析比較。 結果: 在研究一中,共有19847名NOAC使用者和10372名warfarin使用者被納入分析。與使用warfarin的病患相比,使用NOAC的病患在發展大血管併發症(HR=0.84,95% CI:0.78-0.91,p<0.001)、小血管併發症(HR=0.79,95% CI:0.73-0.85,p<0.001)、血糖急症(HR=0.91,95% CI:0.83-0.99,p=0.043)和死亡(HR=0.78,95% CI:0.75-0.82,p<0.001)的風險皆顯著較低。針對個別NOAC(dabigatran, rivaroxaban, apixaban, and edoxaban)的分析顯示,與warfarin相比,各NOAC的使用者在併發症和死亡風險方面,都有一致的減少趨勢。各項敏感性分析和負對照指標的分析,也都支持我們的研究發現。 在研究二中,我們共納入56774名診斷有心房顫動和糖尿病且有併用糖尿病藥物和口服抗凝血劑之患者進行分析。總體而言,與糖尿病藥物併用warfarin相比,併用NOAC其嚴重低血糖風險顯著較低(IRR=0.73,95% CI:0.63–0.85,p<0.001)。在根據不同糖尿病藥物的次族群分析中,發現在服用糖尿病藥物二甲雙胍(metformin)(IRR=0.73, 95% CI: 0.59–0.89, p=0.002)、二肽基肽酶-4抑制劑(dipeptidyl peptidase-4 inhibitor, DPP-4i)(IRR=0.73, 95% CI: 0.59–0.92, p=0.007)或磺脲類藥物(sulfonylurea)(IRR=0.68, 95% CI: 0.56–0.81, p<0.001)的次族群患者中,併用NOAC者其嚴重低血糖風險顯著較併用warfarin者低。 結論: 在患有心房顫動和糖尿病之患者中,與warfarin相比,使用NOAC與較低的糖尿病相關併發症(例如大血管併發症、小血管併發症、血糖急症)和死亡風險相關。與糖尿病藥物同時使用時,NOAC使用者也比warfarin使用者有顯著較低的嚴重低血糖風險。因此,對於需要使用口服抗凝血劑治療的心房顫動和糖尿病患者而言,NOAC可能是一個比warfarin更好的治療選擇,以降低這些糖尿病相關併發症和死亡風險。 | zh_TW |
| dc.description.abstract | Introduction:
Atrial fibrillation (AF) and diabetes mellitus (DM) are significant public health issues, with rising prevalence and incidence in the aging population worldwide. Patients with AF, particularly those with DM, are more likely to experience stroke during their lifetime, necessitating long-term oral anticoagulant use for stroke prevention. Previous evidence suggests that vitamin K may play a beneficial role in improving insulin sensitivity and glucose tolerance. Some studies have further indicated potential differences in glucose tolerance and diabetes control between non-vitamin K antagonist oral anticoagulants (NOACs) use and warfarin use due to their varying effects on vitamin K function. However, current clinical evidence regarding the potential effects of NOACs versus warfarin on the risks of developing various diabetes-related complications in patients with AF and DM remains limited. Furthermore, a few previous studies have suggested potential drug-drug interactions between warfarin and some specific antidiabetic drugs, which may increase the risk of hypoglycemia, but evidence comparing NOACs and warfarin on this issue is scarce. Identifying an optimal oral anticoagulant to minimize the risk of diabetes complications and hypoglycemia in patients with AF and DM is a critical clinical concern, yet relevant evidence is limited and requires further investigation. Study Aims: Our first study aimed to investigate the risk of diabetes-related complications and mortality in patients with AF and DM taking NOACs compared to those taking warfarin. In our second study (Study 2), we aimed to specifically investigate the risk of serious hypoglycemia when taking various antidiabetic medications with concurrent NOACs compared to those with concurrent warfarin. Methods: We conducted retrospective cohort studies using nationwide data from Taiwan''s National Health Insurance Research Database (NHIRD). Patients with AF and DM taking either NOACs or warfarin in the NHIRD were identified. In Study 1, we investigated the risks of diabetes-related complications (macrovascular complications, microvascular complications, and glycemic emergencies) and mortality in NOAC versus warfarin users using a target trial emulation framework. Stabilized inverse probability of treatment weighting (IPTW) was used to create a pseudo-population with balance patient characteristics between treatment groups for analyses. Cox proportional hazard models were employed to estimate hazard ratios (HRs). In Study 2, we estimated the incidence rate ratios (IRRs) of serious hypoglycemia using Poisson regression models. Stabilized IPTW was also utilized to balance characteristics between treatment groups for comparisons. Various sensitivity analyses were further performed in both Study 1 and Study 2. Results: In Study 1, a total of 19847 NOAC users and 10372 warfarin users were included. Patients taking NOACs had significantly lower risks of developing macrovascular complications (HR=0.84, 95% CI: 0.78-0.91, p<0.001), microvascular complications (HR=0.79, 95% CI: 0.73-0.85, p<0.001), glycemic emergency (HR=0.91, 95% CI: 0.83-0.99, p=0.043), and mortality (HR=0.78, 95% CI: 0.75-0.82, p<0.001) than those taking warfarin. The analyses for individual NOACs (dabigatran, rivaroxaban, apixaban, and edoxaban) revealed a consistent trend of decreased complication and mortality risks for NOAC users compared to warfarin users. Several sensitivity analyses and the analyses for negative control outcomes also supported our study findings. In Study 2, a total of 56,774 patients with AF and DM taking antidiabetic drugs with concurrent use of NOACs or warfarin were included for analyses. Overall, concurrent use of NOACs with antidiabetic drugs had a significantly lower risk of serious hypoglycemia than concurrent use of warfarin with antidiabetic drugs (IRR=0.73, 95% CI: 0.63–0.85, p<0.001). In the subgroup analyses according to different antidiabetic drugs, the significantly lower risk of serious hypoglycemia associated with concurrent NOAC use was found in patients taking metformin (IRR=0.73, 95% CI: 0.59–0.89, p=0.002), DPP-4i (IRR=0.73, 95% CI: 0.59–0.92, p=0.007), or sulfonylurea (IRR=0.68, 95% CI: 0.56–0.81, p<0.001). Conclusions: Among patients with AF and DM, NOAC use was associated with lower risks of diabetes-related complications (e.g., macrovascular complications, microvascular complications, glycemic emergencies) and mortality compared with warfarin use. Patients taking antidiabetic drugs with concurrent use of NOACs also had a significantly lower risk of serious hypoglycemia than those with concurrent use of warfarin. Therefore, NOAC may be a better therapeutic choice than warfarin for decreasing these complications and mortality in diabetic AF patients requiring oral anticoagulant treatment. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-02-22T16:53:24Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-02-22T16:53:24Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Contents
致謝 i 摘要 ii Abstract v Abbreviation list viii Contents ix Contents of Tables xiv Contents of Figures xviii Chapter 1. Introduction 1 1.1 Diabetes mellitus 1 1.2 Diabetes-related macrovascular complications, microvascular complications, and glycemic emergency 2 1.3 Severe hypoglycemia: a dangerous side-effect of antidiabetic medications 4 1.4 Atrial fibrillation 4 1.5 Diabetes mellitus and atrial fibrillation 5 1.6 Oral anticoagulant use in patients with atrial fibrillation 6 1.7 Oral anticoagulant types – warfarin and NOACs 7 1.8 Vitamin K, warfarin, and glucose metabolism 11 1.9 NOACs, inflammation and atherosclerotic plaque formation 12 Chapter 2. Literature review and study aims 13 2.1 Potential effect of NOACs versus warfarin on development of diabetes-related complications 13 2.1.1 Preexisting evidence on macrovascular complications 13 2.1.2 Preexisting evidence on microvascular complications 14 2.1.3 Preexisting evidence on glycemic emergencies 15 2.1.4 Preexisting evidence on mortality 16 2.2 Potential differences in serious hypoglycemia risk between NOAC and warfarin use in patients on antidiabetic drugs 16 2.3 Study aims 18 Chapter 3. Methods 20 3.1 Methods of Study 1 20 3.1.1 Data source 20 3.1.2 Target trial emulation 21 3.1.3 Study population and exposure 28 3.1.4 Study outcomes, comparison, and follow-up 29 3.1.5 Covariates and confounders 32 3.1.6 Subgroup and stratified analyses 34 3.1.7 Propensity score methods 34 3.1.8 Propensity score methods used in our analyses 38 3.1.9 Statistical analyses 40 3.1.10 Sensitivity analyses 41 3.2 Methods of Study 2 44 3.2.1 Data source 44 3.2.2 Study population, exposure, and follow-up time 44 3.2.3 Study outcome and comparison 45 3.2.4 Covariates and confounders 46 3.2.5 Subgroup and stratified analyses 47 3.2.6 Stabilized inverse probability of treatment weighting using propensity score 47 3.2.7 Statistical analyses 48 3.2.8 Sensitivity analyses 48 Chapter 4. Results 51 4.1 Results of Study 1 51 4.1.1 Patient characteristics 51 4.1.2 Distribution of propensity scores and the weights calculated by stabilized IPTW 72 4.1.3 Risks of diabetes complications and mortality in patients taking NOACs versus warfarin 79 4.1.4 Results of sensitivity analyses: on-treatment design, focusing on patients with high medication possession ratio, and exclusion of patients with chronic kidney disease 87 4.1.5 Results of sensitivity analyses applying stabilized IPTW with weight truncation 91 4.1.6 Results of sensitivity analyses applying propensity score matching 93 4.1.7 Results of sensitivity analyses using multivariable regression models to adjust covariates without propensity score methods 107 4.1.8 E-values and negative control outcomes 109 4.2 Results of Study 2 113 4.2.1 Patient characteristics 113 4.2.2 Distribution of propensity scores and the weights calculated by stabilized IPTW 121 4.2.3 Risk of serious hypoglycemia in patients taking antidiabetic drugs with concurrent use of NOACs versus warfarin 125 4.2.4 Risk of serious hypoglycemia according to each antidiabetic drug with concurrent use of NOACs versus warfarin 131 4.2.5 Results of sensitivity analyses 135 4.2.6 E-values and negative control outcomes 148 Chapter 5. Discussion 151 5.1 Discussion of Study 1 151 5.1.1 Summary of findings 151 5.1.2 Comparison with previous studies 151 5.1.3 Sensitivity analyses 154 5.1.4 The choices of propensity score methods in our study 155 5.1.5 Evaluation of potential unmeasured confounders 155 5.1.6 Possible underlying mechanisms 157 5.1.7 Clinical implications 158 5.1.8 Strengths and limitations 159 5.2 Discussion of Study 2 163 5.2.1 Summary of findings 163 5.2.2 Comparison with previous studies 163 5.2.3 Sensitivity analyses 165 5.2.4 Unavailability of diabetes severity and the issue of potential unmeasured confounders 166 5.2.5 Challenges in conducting randomized controlled trials and the sample size issue for this investigation 167 5.2.6 Potential underlying mechanisms 169 5.2.7 Clinical implications 170 5.2.8 Strengths and limitations 170 Chapter 6. Conclusion 173 References 175 Appendix 187 Contents of Appendix 187 I. Supplemental Tables 188 II. Published Articles 195 | - |
| dc.language.iso | en | - |
| dc.subject | 心房顫動 | zh_TW |
| dc.subject | 糖尿病 | zh_TW |
| dc.subject | 非維生素K拮抗劑口服抗凝血劑 | zh_TW |
| dc.subject | 華法林 | zh_TW |
| dc.subject | 併發症 | zh_TW |
| dc.subject | 低血糖 | zh_TW |
| dc.subject | 世代研究 | zh_TW |
| dc.subject | diabetes mellitus | en |
| dc.subject | cohort study | en |
| dc.subject | hypoglycemia | en |
| dc.subject | complication | en |
| dc.subject | warfarin | en |
| dc.subject | non-vitamin K antagonist oral anticoagulants | en |
| dc.subject | atrial fibrillation | en |
| dc.title | 比較非維生素K拮抗劑口服抗凝血劑與warfarin在心房顫動和糖尿病患者中對糖尿病相關併發症及嚴重低血糖風險的影響 | zh_TW |
| dc.title | Comparative Effectiveness of Non-Vitamin K Antagonist Oral Anticoagulants and Warfarin on the Risks of Diabetes-related Complications and Serious Hypoglycemia in Patients with Atrial Fibrillation and Diabetes Mellitus | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-1 | - |
| dc.description.degree | 博士 | - |
| dc.contributor.oralexamcommittee | 簡國龍;張慶國;蕭斐元;東雅惠 | zh_TW |
| dc.contributor.oralexamcommittee | Kuo-Liong Chien;Chin-Kuo Chang;Fei-Yuan Hsiao;Yaa-Hui Dong | en |
| dc.subject.keyword | 心房顫動,糖尿病,非維生素K拮抗劑口服抗凝血劑,華法林,併發症,低血糖,世代研究, | zh_TW |
| dc.subject.keyword | atrial fibrillation,diabetes mellitus,non-vitamin K antagonist oral anticoagulants,warfarin,complication,hypoglycemia,cohort study, | en |
| dc.relation.page | 195 | - |
| dc.identifier.doi | 10.6342/NTU202400538 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-02-05 | - |
| dc.contributor.author-college | 公共衛生學院 | - |
| dc.contributor.author-dept | 流行病學與預防醫學研究所 | - |
| 顯示於系所單位: | 流行病學與預防醫學研究所 | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-112-1.pdf | 6.36 MB | Adobe PDF | 檢視/開啟 |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
