Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP

被引:26
|
作者
Matsushita, Kunihiro [1 ]
Kaptoge, Stephen [2 ]
Hageman, Steven H. J. [3 ]
Sang, Yingying [1 ]
Ballew, Shoshana H. [1 ]
Grams, Morgan E. [1 ]
Surapaneni, Aditya [1 ]
Sun, Luanluan [2 ]
Arnlov, Johan [4 ]
Bozic, Milica [5 ,6 ]
Brenner, Hermann [7 ,8 ]
Brunskill, Nigel J. [9 ]
Chang, Alex R. [10 ,11 ]
Chinnadurai, Rajkumar [12 ]
Cirillo, Massimo [13 ]
Correa, Adolfo [14 ]
Ebert, Natalie [15 ]
Eckardt, Kai Uwe [16 ,17 ]
Gansevoort, Ron T. [18 ]
Gutierrez, Orlando [19 ]
Hadaegh, Farzad [20 ]
He, Jiang [21 ]
Hwang, Shih Jen [22 ]
Jafar, Tazeen H. [23 ,24 ,25 ]
Jassal, Simerjot K. [26 ,27 ]
Kayama, Takamasa [28 ]
Kovesdy, Csaba P. [29 ,30 ]
Landman, Gijs W. [31 ]
Levey, Andrew S. [32 ]
Lloyd-Jones, Donald M. [33 ]
Major, Rupert W. [9 ]
Miura, Katsuyuki [34 ]
Muntner, Paul [19 ]
Nadkarni, Girish N. [35 ]
Nowak, Christoph [4 ]
Ohkubo, Takayoshi [36 ]
Pena, Michelle J. [37 ]
Polkinghorne, Kevan R. [38 ]
Sairenchi, Toshimi [39 ]
Schaeffner, Elke [15 ]
Schneider, Markus P. [16 ]
Shalev, Varda [40 ,41 ]
Shlipak, Michael G. [42 ,43 ]
Solbu, Marit D. [44 ,45 ]
Stempniewicz, Nikita [46 ,47 ]
Tollitt, James [12 ,48 ]
Valdivielso, Jose M. [5 ,6 ]
van der Leeuw, Joep [3 ]
Wang, Angela Yee Moon [49 ]
Wen, Chi Pang [50 ]
机构
[1] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD 21205 USA
[2] Univ Cambridge, Dept Publ Hlth & Primary Care, Cambridge, England
[3] Univ Med Ctr Utrecht, Dept Vasc Med, Utrecht, Netherlands
[4] Karolinska Inst, Dept Neurobiol Care Sci & Soc, Stockholm, Sweden
[5] IRBLleida, Vasc & Renal Translat Res Grp, Lleida, Spain
[6] Spanish Res Network Renal Dis RedInRen ISCIII, Lleida, Spain
[7] Heidelberg Univ, German Canc Res Ctr DKFZ, Div Clin Epidemiol & Aging Res, Heidelberg, Germany
[8] Heidelberg Univ, Network Aging Res, Heidelberg, Germany
[9] Univ Leicester, Univ Hosp Leicester NHS Trust, Leicester Gen Hosp, Dept Cardiovasc Sci,John Walls Renal Unit, Leicester, Leics, England
[10] Geisinger Med Ctr, Dept Nephrol, Danville, PA 17822 USA
[11] Geisinger Med Ctr, Kidney Hlth Res Inst Geisinger, Danville, PA 17822 USA
[12] Northern Care Alliance NHS Fdn Trust, Dept Renal Med, Salford Care Org, Salford, Lancs, England
[13] Univ Naples Federico II, Dept Publ Hlth, Naples, Italy
[14] Univ Mississippi Med Ctr, Jackson, MS USA
[15] Charite Univ Med Berlin, Inst Publ Hlth, Berlin, Germany
[16] Friedrich Alexander Univ Erlangen Nurnberg, Dept Nephrol & Hypertens, Erlangen, Germany
[17] Charite Univ Med Berlin, Dept Nephrol & Med Intens Care, Berlin, Germany
[18] Univ Groningen, Univ Med Ctr Groningen, Dept Nephrol, Groningen, Netherlands
[19] Univ Alabama Birmingham, Dept Epidemiol, Birmingham, AL USA
[20] Shahid Beheshti Univ Med Sci, Res Inst Endocrine Sci, Tehran, Iran
[21] Tulane Univ, Dept Epidemiol, Sch Publ Hlth & Trop Med, New Orleans, LA USA
[22] Natl Heart Lung & Blood Inst, Framingham, MA USA
[23] Duke Natl Univ Singapore Med Sch, Program Hlth Serv & Syst Res, Singapore, Singapore
[24] Aga Khan Univ, Dept Med, Karachi, Pakistan
[25] Duke Univ, Duke Global Hlth Inst, Durham, NC USA
[26] Univ Calif San Diego, Div Gen Internal Med, San Diego, CA 92103 USA
[27] VA San Diego Healthcare, San Diego, CA USA
[28] Yamagata Univ, Global Ctr Excellence, Fac Med, Yamagata, Japan
[29] Memphis Vet Affairs Med Ctr, Med Nephrol, Memphis, TN USA
[30] Univ Tennessee, Hlth Sci Ctr, Memphis, TN USA
[31] Gelre Hosp Locat, Apeldoorn, Netherlands
[32] Tufts Med Ctr, Div Nephrol, Boston, MA 02111 USA
[33] Northwestern Univ, Dept Prevent Med, Chicago, IL 60611 USA
[34] Shiga Univ Med Sci, NCD Epidemiol Res Ctr, Otsu, Shiga, Japan
[35] Icahn Sch Med Mt Sinai, Div Nephrol, Dept Med, New York, NY 10029 USA
[36] Teikyo Univ, Dept Hyg & Publ Hlth, Sch Med, Tokyo, Japan
[37] Univ Groningen, Univ Med Ctr Groningen, Dept Clin Pharm & Pharmacol, Groningen, Netherlands
[38] Monash Univ, Clayton, Vic, Australia
[39] Dokkyo Med Univ, Med Sci Nursing, Sch Nursing, Mibu, Tochigi, Japan
[40] Maccabi Healthcare Serv, Inst Hlth & Res & Innovat, Tel Aviv, Israel
[41] Tel Aviv Univ, Tel Aviv, Israel
[42] Univ Calif San Francisco, Kidney Hlth Res Collaborat, San Francisco, CA 94143 USA
[43] San Francisco VA Healthcare Syst, San Francisco, CA USA
[44] Univ Hosp North Norway, Sect Nephrol, Tromso, Norway
[45] UiT Arctic Univ Norway, Tromso, Norway
[46] AMGA Amer Med Grp Assoc, Alexandria, VA USA
[47] OptumLabs, Alexandria, VA USA
[48] Univ Manchester, Renal Dept, Oxford Rd, Manchester, Lancs, England
[49] Univ Hong Kong, Queen Mary Hosp, Dept Med, Hong Kong, Peoples R China
[50] China Med Univ Hosp, Taichung, Taiwan
关键词
Chronic kidney disease; Cardiovascular disease; Risk prediction; Meta-analysis; GLOMERULAR-FILTRATION-RATE; EPIDEMIOLOGY; ALBUMINURIA; MODEL;
D O I
10.1093/eurjpc/zwac176
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Aims The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an 'Add-on' to incorporate CKD measures into these algorithms, using a validated approach. Methods In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP. We validated C-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997 719 participants from 34 different datasets. Results In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved C-statistic by 0.006 (95%CI 0.004-0.008) and 0.016 (0.010-0.023), respectively, for SCORE2 and 0.012 (0.009-0.015) and 0.024 (0.014-0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57 485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI [e.g. 0.100 (0.062-0.138) for SCORE2] compared to the qualitative approach in the ESC guideline. Conclusion Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD.
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收藏
页码:8 / 16
页数:9
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