p.88 抽出テキスト
182. Kessous R, Shoham-Vardi I, Pariente G, Holcberg G, Sheiner E. An association between preterm delivery and long-term maternal cardiovascular morbidity. Am J Obstet Gynecol 2013;209:368.e1–8. https://doi.org/10.1016/j.ajog.2013.05.041 183. Markovitz AR, Stuart JJ, Horn J, Williams PL, Rimm EB, Missmer SA, et al. Does pregnancy complication history improve cardiovascular disease risk prediction? Findings from the HUNT study in Norway. Eur Heart J 2019;40:1113–20. https://doi.org/10. 1093/eurheartj/ehy863 184. Saei Ghare Naz M, Sheidaei A, Aflatounian A, Azizi F, Ramezani Tehrani F. Does adding adverse pregnancy outcomes improve the Framingham cardiovascular risk score in women? Data from the Tehran Lipid and Glucose Study. J Am Heart Assoc 2022;11: e022349. https://doi.org/10.1161/jaha.121.022349 185. Gladstone RA, Pudwell J, Nerenberg KA, Grover SA, Smith GN. Cardiovascular risk assessment and follow-up of women after hypertensive disorders of pregnancy: a prospective cohort study. J Obstet Gynaecol Can 2019;41:1157–67.e1. https://doi.org/10. 1016/j.jogc.2018.10.024 186. Patel AP, Wang M, Kartoun U, Ng K, Khera AV. Quantifying and understanding the higher risk of atherosclerotic cardiovascular disease among South Asian individuals: results from the UK Biobank prospective cohort study. Circulation 2021;144:410–22. https://doi.org/10.1161/circulationaha.120.052430 187. Tillin T, Hughes AD, Whincup P, Mayet J, Sattar N, McKeigue PM, et al. Ethnicity and prediction of cardiovascular disease: performance of QRISK2 and Framingham scores in a U.K. tri-ethnic prospective cohort study (SABRE—Southall And Brent REvisited). Heart 2014;100:60–7. https://doi.org/10.1136/heartjnl-2013-304474 188. Rabanal KS, Igland J, Tell GS, Jenum AK, Klemsdal TO, Ariansen I, et al. Validation of the cardiovascular risk model NORRISK 2 in South Asians and people with diabetes. Scand Cardiovasc J 2021;55:56–62. https://doi.org/10.1080/14017431.2020.1821909 189. Veronesi G, Gianfagna F, Giampaoli S, Chambless LE, Mancia G, Cesana G, et al. Improving long-term prediction of first cardiovascular event: the contribution of family history of coronary heart disease and social status. Prev Med 2014;64:75–80. https:// doi.org/10.1016/j.ypmed.2014.04.007 190. Sivapalaratnam S, Boekholdt SM, Trip MD, Sandhu MS, Luben R, Kastelein JJP, et al. Family history of premature coronary heart disease and risk prediction in the EPIC-Norfolk prospective population study. Heart 2010;96:1985–9. https://doi.org/ 10.1136/hrt.2010.210740 191. Kimenai DM, Pirondini L, Gregson J, Prieto D, Pocock SJ, Perel P, et al. Socioeconomic deprivation: an important, largely unrecognized risk factor in primary prevention of cardiovascular disease. Circulation 2022;146:240–8. https://doi.org/10.1161/ circulationaha.122.060042 192. Avina-Zubieta JA, Thomas J, Sadatsafavi M, Lehman AJ, Lacaille D. Risk of incident cardiovascular events in patients with rheumatoid arthritis: a meta-analysis of observational studies. Ann Rheum Dis 2012;71:1524–9. https://doi.org/10.1136/annrheumdis- 2011-200726 193. Crowson CS, Matteson EL, Roger VL, Therneau TM, Gabriel SE. Usefulness of risk scores to estimate the risk of cardiovascular disease in patients with rheumatoid arthritis. Am J Cardiol 2012;110:420–4. https://doi.org/10.1016/j.amjcard.2012.03.044 194. Arts EE, Popa C, Den Broeder AA, Semb A G, Toms T, Kitas G D, et al. Performance of four current risk algorithms in predicting cardiovascular events in patients with early rheumatoid arthritis. Ann Rheum Dis 2015;74:668–74. https://doi.org/10.1136/ annrheumdis-2013-204024 195. Arts EE, Popa CD, Den Broeder AA, Donders R, Sandoo A, Toms T, et al. Prediction of cardiovascular risk in rheumatoid arthritis: performance of original and adapted SCORE algorithms. Ann Rheum Dis 2016;75:674–80. https://doi.org/10.1136/ annrheumdis-2014-206879 196. Gelfand JM, Neimann AL, Shin DB, Wang X, Margolis DJ, Troxel AB. Risk of myocardial infarction in patients with psoriasis. JAMA 2006;296:1735–41. https://doi.org/10.1001/ jama.296.14.1735 197. Miller IM, Ellervik C, Yazdanyar S, Jemec GB. Meta-analysis of psoriasis, cardiovascular disease, and associated risk factors. J Am Acad Dermatol 2013;69:1014–24. https://doi. org/10.1016/j.jaad.2013.06.053 198. Eder L, Chandran V, Gladman DD. The Framingham risk score underestimates the extent of subclinical atherosclerosis in patients with psoriatic disease. Ann Rheum Dis 2014;73:1990–6. https://doi.org/10.1136/annrheumdis-2013-203433 199. Armstrong EJ, Harskamp CT, Armstrong AW. Psoriasis and major adverse cardiovascular events: a systematic review and meta-analysis of observational studies. J Am Heart Assoc 2013;2:e000062. https://doi.org/10.1161/jaha.113.000062 200. Elmets CA, Leonardi CL, Davis DMR, Gelfand JM, Lichten J, Mehta NN, et al. Joint AAD-NPF guidelines of care for the management and treatment of psoriasis with awareness and attention to comorbidities. J Am Acad Dermatol 2019;80:1073–113. https://doi.org/10.1016/j.jaad.2018.11.058 201. Lu X, Wang Y, Zhang J, Pu D, Hu N, Luo J, et al. Patients with systemic lupus erythematosus face a high risk of cardiovascular disease: a systematic review and meta-analysis. Int Immunopharmacol 2021;94:107466. https://doi.org/10.1016/j.intimp.2021.107466 202. Drosos GC, Konstantonis G, Sfikakis PP, Tektonidou MG. Underperformance of clinical risk scores in identifying vascular ultrasound-based high cardiovascular risk in systemic lupus erythematosus. Eur J Prev Cardiol. 2020. https://doi.org/10.1177/ 2047487320906650 203. Shah ASV, Stelzle D, Lee KK, Beck EJ, Alam S, Clifford S, et al. Global burden of atherosclerotic cardiovascular disease in people living with HIV: systematic review and meta-analysis. Circulation 2018;138:1100–12. https://doi.org/10.1161/circulationaha.117.033369 204. Triant VA, Perez J, Regan S, Massaro JM, Meigs JB, Grinspoon SK, et al. Cardiovascular risk prediction functions underestimate risk in HIV infection. Circulation 2018;137: 2203–14. https://doi.org/10.1161/circulationaha.117.028975 205. Triant VA, Lyass A, Hurley LB, Borowsky LH, Ehrbar RQ, H W, et al. Cardiovascular Risk Estimation Is Suboptimal in People With HIV. J Am Heart Assoc. 2024;13:e029228. https://doi.org/10.1161/JAHA.123.029228 206. Correll CU, Solmi M, Veronese N, Bortolato B, Rosson S, Santonastaso P, et al. Prevalence, incidence and mortality from cardiovascular disease in patients with pooled and specific severe mental illness: a large-scale meta-analysis of 3,211,768 patients and 113,383,368 controls. World Psychiatry 2017;16:163–80. https://doi.org/10.1002/wps.20420 207. Lambert AM, Parretti HM, Pearce E, Price MJ, Riley M, Ryan R, et al. Temporal trends in associations between severe mental illness and risk of cardiovascular disease: a systematic review and meta-analysis. PLoS Med 2022;19:e1003960. https://doi.org/10.1371/ journal.pmed.1003960 208. Cunningham R, Poppe K, Peterson D, Every-Palmer S, Soosay I, Jackson R. Prediction of cardiovascular disease risk among people with severe mental illness: a cohort study. PLoS One 2019;14:e0221521. https://doi.org/10.1371/journal.pone.0221521 209. Yeboah J, Young R, McClelland RL, Delaney JC, Polonsky TS, Dawood FZ, et al. Utility of nontraditional risk markers in atherosclerotic cardiovascular disease risk assessment. J Am Coll Cardiol 2016;67:139–47. https://doi.org/10.1016/j.jacc.2015.10.058 210. Akintoye E, Afonso L, Bengaluru Jayanna M, Bao W, Briasoulis A, Robinson J, et al. Prognostic utility of risk enhancers and coronary artery calcium score recommended in the 2018 ACC/AHA multisociety cholesterol treatment guidelines over the pooled cohort equation: insights from 3 large prospective cohorts. J Am Heart Assoc 2021;10: e019589. https://doi.org/10.1161/jaha.120.019589 211. Peters SA, den Ruijter HM, Bots ML, Moons KG. Improvements in risk stratification for the occurrence of cardiovascular disease by imaging subclinical atherosclerosis: a systematic review. Heart 2012;98:177–84. https://doi.org/10.1136/heartjnl-2011-300747 212. Nicolaides AN, Panayiotou AG, Griffin M, Tyllis T, Bond D, Georgiou N, et al. Arterial ultrasound testing to predict atherosclerotic cardiovascular events. J Am Coll Cardiol 2022;79:1969–82. https://doi.org/10.1016/j.jacc.2022.03.352 213. Laclaustra M, Casasnovas JA, Fernández-Ortiz A, Fuster V, León-Latre M, Jiménez-Borreguero LJ, et al. Femoral and carotid subclinical atherosclerosis association with risk factors and coronary calcium: the AWHS study. J Am Coll Cardiol 2016;67:1263–74. https://doi.org/10.1016/j.jacc.2015.12.056 214. López-Melgar B, Fernández-Friera L, Oliva B, García-Ruiz JM, Peñalvo JL, Gómez-Talavera S, et al. Subclinical atherosclerosis burden by 3D ultrasound in midlife: the PESA study. J Am Coll Cardiol 2017;70:301–13. https://doi.org/10.1016/j.jacc. 2017.05.033 215. Ben-Shlomo Y, Spears M, Boustred C, May M, Anderson SG, Benjamin EJ, et al. Aortic pulse wave velocity improves cardiovascular event prediction: an individual participant meta-analysis of prospective observational data from 17,635 subjects. J Am Coll Cardiol 2014;63:636–46. https://doi.org/10.1016/j.jacc.2013.09.063 216. Ohkuma T, Ninomiya T, Tomiyama H, Kario K, Hoshide S, Kita Y, et al. Brachial-Ankle pulse wave velocity and the risk prediction of cardiovascular disease: an individual participant data meta-analysis. Hypertension 2017;69:1045–52. https://doi.org/10.1161/ hypertensionaha.117.09097 217. Stone K, Veerasingam D, Meyer ML, Heffernan KS, Higgins S, Maria Bruno R, et al. Reimagining the value of brachial-ankle pulse wave velocity as a biomarker of cardiovascular disease risk-a call to action on behalf of VascAgeNet. Hypertension 2023;80: 1980–92. https://doi.org/10.1161/hypertensionaha.123.21314 218. An DW, Hansen TW, Aparicio LS, Chori B, Huang Q-F, Wei F-F, et al. Derivation of an outcome-driven threshold for aortic pulse wave velocity: an individual-participant meta-analysis. Hypertension 2023;80:1949–59. https://doi.org/10.1161/hypertensionaha. 123.21318 219. de Lemos JA, Ayers CR, Levine BD, deFilippi CR, Wang TJ, Hundley W, et al. Multimodality strategy for cardiovascular risk assessment: performance in 2 population-based cohorts. Circulation 2017;135:2119–32. https://doi.org/10.1161/ circulationaha.117.027272 220. Hageman SHJ, Petitjean C, Pennells L, Kaptoge S, Pajouheshnia R, Tillmann T, et al. Improving 10-year cardiovascular risk prediction in apparently healthy people: flexible addition of risk modifiers on top of SCORE2. Eur J Prev Cardiol 2023;30:1705–14. https://doi.org/10.1093/eurjpc/zwad187 221. McEvoy JW, Chen Y, Nambi V, Ballantyne CM, Sharrett AR, Appel LJ, et al. High-sensitivity cardiac troponin T and risk of hypertension. Circulation 2015;132: 825–33. https://doi.org/10.1161/circulationaha.114.014364 222. Hussain A, Sun W, Deswal A, de Lemos JA, McEvoy JW, Hoogeveen RC, et al. Association of NT-ProBNP, blood pressure, and cardiovascular events: the ARIC study. J Am Coll Cardiol 2021;77:559–71. https://doi.org/10.1016/j.jacc.2020.11.063 223. Stuart JJ, Tanz LJ, Cook NR, Spiegelman D, Missmer SA, Rimm EB, et al. Hypertensive disorders of pregnancy and 10-year cardiovascular risk prediction. J Am Coll Cardiol 2018;72:1252–63. https://doi.org/10.1016/j.jacc.2018.05.077 ESC Guidelines 3999 Downloaded from academic.oup.com/eurheartj/article/45/38/3912/7741010 by guest on 07 October 2026