Carotid plaque thickness predicts cardiovascular events and death in patients with chronic kidney disease.
Humans
Male
Female
Renal Insufficiency, Chronic
/ complications
Middle Aged
Aged
Cardiovascular Diseases
/ diagnostic imaging
Plaque, Atherosclerotic
/ diagnostic imaging
Predictive Value of Tests
Carotid Artery Diseases
/ diagnostic imaging
Cohort Studies
Risk Factors
Carotid Intima-Media Thickness
CACS
Cardiovascular events
Cardiovascular risk
Carotid ultrasound imaging
Chronic kidney disease
Coronary artery calcium score
MACE
Maximal carotid plaque thickness
Plaque progression
cPTmax
Journal
BMC nephrology
ISSN: 1471-2369
Titre abrégé: BMC Nephrol
Pays: England
ID NLM: 100967793
Informations de publication
Date de publication:
31 Oct 2024
31 Oct 2024
Historique:
received:
17
09
2023
accepted:
21
10
2024
medline:
1
11
2024
pubmed:
1
11
2024
entrez:
1
11
2024
Statut:
epublish
Résumé
Classical risk scoring systems underestimate the risk of cardiovascular disease in chronic kidney disease (CKD). Coronary artery calcium score (CACS) has improved prediction of cardiovascular events in patients with CKD. The maximal carotid plaque thickness (cPTmax) measured in ultrasound scans of the carotid arteries has demonstrated similar predictive value as CACS in the general population. This is the first study to investigate whether cPTmax can predict cardiovascular events in CKD and to compare the predictive value of cPTmax and CACS in CKD. Two hundred patients with CKD stage 3 from the Copenhagen CKD Cohort underwent ultrasound scanning of the carotid arteries. The assessment consisted of locating plaque and measuring the thickest part of the plaque, cPTmax. Based on the distribution of cPTmax, the participants were divided into 3 groups: No plaques, cPTmax 1.0-1.9 mm and cPTmax > 1.9 mm (median cPTmax = 1.9 mm among patients with plaques). To measure CACS, 175 of the patients underwent a non-contrast CT scan of the coronary arteries. The follow-up time spanned between the ultrasound scan and a predefined end-date or the time of first event, defined as a composite of major cardiovascular events or death of any cause (MACE). The median follow-up time was 5.4 years during which 45 patients (22.5%) developed MACE. In a Cox-regression adjusted for classical cardiovascular risk factors, patients with cPTmax > 1.9 mm had a significantly increased hazard ratio of MACE (HR 3.2, CI: 1.1-9.3), p = 0.031) compared to patients without plaques. C-statistics was used to evaluate models for predicting MACE. The improvement in C-statistics was similar for the two models including classical cardiovascular risk factors plus cPTmax (0.247, CI: 0.181-0.312) and CACS (0.243, CI: 0.172-0.315), respectively, when compared to a model only controlled for time since baseline (a Cox model with no covariates). Our results indicate that cPTmax may be useful for predicting MACE in CKD. cPTmax and CACS showed similar ability to predict MACE.
Sections du résumé
BACKGROUND
BACKGROUND
Classical risk scoring systems underestimate the risk of cardiovascular disease in chronic kidney disease (CKD). Coronary artery calcium score (CACS) has improved prediction of cardiovascular events in patients with CKD. The maximal carotid plaque thickness (cPTmax) measured in ultrasound scans of the carotid arteries has demonstrated similar predictive value as CACS in the general population. This is the first study to investigate whether cPTmax can predict cardiovascular events in CKD and to compare the predictive value of cPTmax and CACS in CKD.
METHOD
METHODS
Two hundred patients with CKD stage 3 from the Copenhagen CKD Cohort underwent ultrasound scanning of the carotid arteries. The assessment consisted of locating plaque and measuring the thickest part of the plaque, cPTmax. Based on the distribution of cPTmax, the participants were divided into 3 groups: No plaques, cPTmax 1.0-1.9 mm and cPTmax > 1.9 mm (median cPTmax = 1.9 mm among patients with plaques). To measure CACS, 175 of the patients underwent a non-contrast CT scan of the coronary arteries. The follow-up time spanned between the ultrasound scan and a predefined end-date or the time of first event, defined as a composite of major cardiovascular events or death of any cause (MACE).
RESULTS
RESULTS
The median follow-up time was 5.4 years during which 45 patients (22.5%) developed MACE. In a Cox-regression adjusted for classical cardiovascular risk factors, patients with cPTmax > 1.9 mm had a significantly increased hazard ratio of MACE (HR 3.2, CI: 1.1-9.3), p = 0.031) compared to patients without plaques. C-statistics was used to evaluate models for predicting MACE. The improvement in C-statistics was similar for the two models including classical cardiovascular risk factors plus cPTmax (0.247, CI: 0.181-0.312) and CACS (0.243, CI: 0.172-0.315), respectively, when compared to a model only controlled for time since baseline (a Cox model with no covariates).
CONCLUSION
CONCLUSIONS
Our results indicate that cPTmax may be useful for predicting MACE in CKD. cPTmax and CACS showed similar ability to predict MACE.
Identifiants
pubmed: 39482658
doi: 10.1186/s12882-024-03831-4
pii: 10.1186/s12882-024-03831-4
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
389Informations de copyright
© 2024. The Author(s).
Références
Hill NR, Fatoba ST, Oke JL, Hirst JA, Callaghan AO, Lasserson DS et al. Global prevalence of chronic kidney disease – A systematic review and Meta-analysis. 2016; 1–18. https://doi.org/10.5061/dryad.3s7rd.Funding
Gansevoort RT, Correa-Rotter R, Hemmelgarn BR, Jafar TH, Heerspink HJL, Mann JF, et al. Chronic kidney disease and cardiovascular risk: Epidemiology, mechanisms, and prevention. Lancet. 2013;382:339–52. https://doi.org/10.1016/S0140-6736(13)60595-4 .
doi: 10.1016/S0140-6736(13)60595-4
pubmed: 23727170
Bikbov B, Purcell CA, Levey AS, Smith M, Abdoli A, Abebe M, et al. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the global burden of Disease Study 2017. Lancet. 2020;395:709–33. https://doi.org/10.1016/S0140-6736(20)30045-3 .
doi: 10.1016/S0140-6736(20)30045-3
Go AS, Chertow GM, Fan D, McCulloch CE, Hsu C. Chronic kidney Disease and the risks of Death, Cardiovascular events, and hospitalization. N Engl J Med. 2004;351:1296–305. https://doi.org/10.1056/nejmoa041031 .
doi: 10.1056/nejmoa041031
pubmed: 15385656
Keith DS, Nichols GA, Gullion CM, Brown JB, Smith DH. Longitudinal follow-up and outcomes among a Population with chronic kidney disease in a large Managed Care Organization. Arch Intern Med. 2004;164:659–63. https://doi.org/10.1001/archinte.164.6.659 .
doi: 10.1001/archinte.164.6.659
pubmed: 15037495
Sosnov J, Lessard D, Goldberg RJ, Yarzebski J, Gore JM. Differential symptoms of acute myocardial infarction in patients with kidney disease: a community-wide perspective. Am J Kidney Dis. 2006;47:378–84. https://doi.org/10.1053/j.ajkd.2005.11.017 .
doi: 10.1053/j.ajkd.2005.11.017
pubmed: 16490615
Chen J, Budoff MJ, Reilly MP, Yang W, Rosas SE, Rahman M, et al. Coronary artery calcification and risk of cardiovascular disease and death among patients with chronic kidney disease. JAMA Cardiol. 2017;2:635–43. https://doi.org/10.1001/jamacardio.2017.0363 .
doi: 10.1001/jamacardio.2017.0363
pubmed: 28329057
pmcid: 5798875
Lee JH, Rizvi A, Hartaigh B, Han D, Park MW, Roudsari HM, et al. The predictive value of coronary artery calcium scoring for major adverse cardiac events according to renal function (from the Coronary computed tomography angiography evaluation for clinical outcomes: an International Multicenter [CONFIRM] Registry). Am J Cardiol. 2019;123:1435–42. https://doi.org/10.1016/j.amjcard.2019.01.055 .
doi: 10.1016/j.amjcard.2019.01.055
pubmed: 30850210
Matsushita K, Sang Y, Ballew SH, Shlipak M, Katz R, Rosas SE, et al. Subclinical atherosclerosis measures for cardiovascular prediction in CKD. J Am Soc Nephrol. 2015;26:439–47. https://doi.org/10.1681/ASN.2014020173 .
doi: 10.1681/ASN.2014020173
pubmed: 25145930
Sørensen IMH, Bjergfelt SS, Hjortkjær HØ, Kofoed KF, Lange T, Feldt-Rasmussen B, et al. Coronary and extra-coronary artery calcium scores as predictors of cardiovascular events and mortality in chronic kidney disease stages 1–5: a prospective cohort study. Nephrol Dial Transpl. 2022;1–13. https://doi.org/10.1093/ndt/gfac252 .
Valdivielso JM, Betriu A, Martinez-Alonso M, Arroyo D, Bermudez-Lopez M, Fernandez E. Factors predicting cardiovascular events in chronic kidney disease patients. Role of subclinical atheromatosis extent assessed by vascular ultrasound. PLoS ONE. 2017;12(10):e0186665. https://doi.org/10.1371/journal.pone.0186665 .
doi: 10.1371/journal.pone.0186665
pubmed: 29045466
pmcid: 5646852
Avramovski P, Avramovska M, Sikole A. B-flow imaging estimation of carotid and femoral atherosclerotic plaques: vessel walls rheological damage or strong predictor of cardiovascular mortality in chronic dialysis patients. Int Urol Nephrol. 2016;48:1713–20. https://doi.org/10.1007/s11255-016-1393-x .
doi: 10.1007/s11255-016-1393-x
pubmed: 27515315
Sillesen H, Sartori S, Sandholt B, Baber U, Mehran R, Fuster V. Carotid plaque thickness and carotid plaque burden predict future cardiovascular events in asymptomatic adult americans. Eur Hear J - Cardiovasc Imaging. 2017;19:1042–50. https://doi.org/10.1093/ehjci/jex239 .
doi: 10.1093/ehjci/jex239
Bjergfelt SS, Sørensen IMH, Hjortkjær H, Landler N, Ballegaard ELF, Biering-Sørensen T, et al. Carotid plaque thickness is increased in chronic kidney disease and associated with carotid and coronary calcification. PLoS ONE. 2021;16:1–16. https://doi.org/10.1371/journal.pone.0260417 .
doi: 10.1371/journal.pone.0260417
Sørensen IMH, Saurbrey SAK, Hjortkjær HØ, Brainin P, Carlson N, Ballegaard ELF, et al. Regional distribution and severity of arterial calcification in patients with chronic kidney disease stages 1–5: a cross-sectional study of the Copenhagen chronic kidney disease cohort. BMC Nephrol. 2020;21:534. https://doi.org/10.1186/s12882-020-02192-y .
doi: 10.1186/s12882-020-02192-y
pubmed: 33297991
pmcid: 7726904
Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604–12. https://doi.org/10.7326/0003-4819-150-9-200905050-00006 .
doi: 10.7326/0003-4819-150-9-200905050-00006
pubmed: 19414839
pmcid: 2763564
Of OJOS, Kidney Disease. Improving global outcomes (KDIGO) CKD Work Group. KDIGO 2012 Clinical Practice Guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013;3:4–4. https://doi.org/10.1038/kisup.2012.76 .
doi: 10.1038/kisup.2012.76
Touboul PJ, Hennerici MG, Meairs S, Adams H, Amarenco P, Bornstein N et al. Mannheim carotid intima-media thickness consensus (2004–2006): An update on behalf of the advisory board of the 3rd and 4th Watching the Risk Symposium 13th and 15th European Stroke Conferences, Mannheim, Germany, 2004, and Brussels, Belgium, 2006. Cerebrovasc Dis. 2007;23: 75–80. https://doi.org/10.1159/000097034
Johri AM, Nambi V, Naqvi TZ, Feinstein SB, Kim ESH, Park MM, et al. Recommendations for the Assessment of Carotid arterial plaque by Ultrasound for the characterization of atherosclerosis and evaluation of Cardiovascular Risk: from the American Society of Echocardiography. J Am Soc Echocardiogr. 2020;33:917–33. https://doi.org/10.1016/j.echo.2020.04.021 .
doi: 10.1016/j.echo.2020.04.021
pubmed: 32600741
Ferreira-Divino L. Association Between Carotid Artery Plaque and Albuminuria in Individuals With Type 2 Diabetes and No Clinical Cardiovascular Disease in: In: JASN, editor. Abstract Supplement - Kidney Week. 2022. p. 913. https://doi.org/10.1097/rhu.0b013e3182557a66
Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15:827–32. https://doi.org/10.1016/0735-1097(90)90282-T .
doi: 10.1016/0735-1097(90)90282-T
pubmed: 2407762
Pletcher MJ, Tice JA, Pignone M, Browner WS. Using the coronary artery calcium score to Predict Coronary Heart Disease events. Arch Intern Med. 2004;164:1285. https://doi.org/10.1001/archinte.164.12.1285 .
doi: 10.1001/archinte.164.12.1285
pubmed: 15226161
Wenning C, Vrachimis A, Pavenstädt HJ, Reuter S, Schäfers M. Coronary artery calcium burden, carotid atherosclerotic plaque burden, and myocardial blood flow in patients with end-stage renal disease: a non-invasive imaging study combining PET/CT and 3D ultrasound. J Nucl Cardiol. 2021;28:2660–70. https://doi.org/10.1007/s12350-020-02080-w .
doi: 10.1007/s12350-020-02080-w
pubmed: 32140994
Gracia M, Betriu À, Martínez-Alonso M, Arroyo D, Abajo M, Fernández E, et al. Predictors of subclinical atheromatosis progression over 2 years in patients with different stages of CKD. Clin J Am Soc Nephrol. 2016;11:287–96. https://doi.org/10.2215/CJN.01240215 .
doi: 10.2215/CJN.01240215
pubmed: 26668022
Palanca A, Castelblanco E, Perpiñán H, Betriu À, Soldevila B, Valdivielso JM, et al. Prevalence and progression of subclinical atherosclerosis in patients with chronic kidney disease and diabetes. Atherosclerosis. 2018;276:50–7. https://doi.org/10.1016/j.atherosclerosis.2018.07.018 .
doi: 10.1016/j.atherosclerosis.2018.07.018
pubmed: 30032025
Golan R, Shai I, Gepner Y, Harman-Boehm I, Schwarzfuchs D, Spence JD, et al. Effect of wine on carotid atherosclerosis in type 2 diabetes: a 2-year randomized controlled trial. Eur J Clin Nutr. 2018;72:871–8. https://doi.org/10.1038/s41430-018-0091-4 .
doi: 10.1038/s41430-018-0091-4
pubmed: 29379143
Mortensen MB, Fuster V, Muntendam P, Mehran R, Baber U, Sartori S, et al. A simple disease-guided Approach to personalize ACC/AHA-Recommended statin allocation in Elderly people: the BioImage Study. J Am Coll Cardiol. 2016;68:881–91. https://doi.org/10.1016/j.jacc.2016.05.084 .
doi: 10.1016/j.jacc.2016.05.084
pubmed: 27561760
Stein JH, Smith SS, Hansen KM, Korcarz CE, Piper ME, Fiore MC, et al. Longitudinal effects of smoking cessation on carotid artery atherosclerosis in contemporary smokers: the Wisconsin smokers Health Study. Atherosclerosis. 2020;315:62–7. https://doi.org/10.1016/j.atherosclerosis.2020.11.010 .
doi: 10.1016/j.atherosclerosis.2020.11.010
pubmed: 33227549
pmcid: 7736540
Baber U, Mehran R, Sartori S, Schoos MM, Sillesen H, Muntendam P, et al. Prevalence, impact, and predictive value of detecting subclinical coronary and carotid atherosclerosis in asymptomatic adults: the bioimage study. J Am Coll Cardiol. 2015;65:1065–74. https://doi.org/10.1016/j.jacc.2015.01.017 .
doi: 10.1016/j.jacc.2015.01.017
pubmed: 25790876
Moody WE, Edwards NC, Chue CD, Ferro CJ, Townend JN. Arterial disease in chronic kidney disease. Heart. 2013;99:365–72. https://doi.org/10.1136/heartjnl-2012-302818 .
doi: 10.1136/heartjnl-2012-302818
pubmed: 23118349