In a real-life setting, risk factors, coronary artery calcium score, and coronary stenosis at computed tomography angiography are associated with major adverse cardiovascular events and all-cause mortality among kidney transplant candidates

Nielsen, Mette; Dahl, Jonathan Nørtoft; Laursen, Rasmus; Jespersen, Bente; Ivarsen, Per; Winther, Simon; Birn, Henrik

doi:10.1016/j.ajt.2023.05.001

Cited by 6 publications

(8 citation statements)

References 30 publications

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“…No major adverse effects of contrast administration were observed. Contradictory to the previous study, 18 radiographic findings did not affect the transplant candidacy of any patients, drawing into question the benefit of regular cardiac CT screening in this population. 19 Serial myocardial perfusion imaging (MPI) was found to be a useful diagnostic tool for assessing the risk of MACE in asymptomatic kidney transplant candidates in 2 studies.…”

Section: Kidney Transplantationmentioning

confidence: 54%

Section: Kidney Transplantationmentioning

confidence: 54%

“…In patients undergoing both CACS and coronary CTA who had lower risk for cardiovascular disease, only positive CACS and coronary CTA findings but not risk factors were associated with increased risk of MACE. 18 The authors suggested a possible benefit of cardiac CT screening in low cardiovascular risk (asymptomatic) kidney transplant candidates. This notion was subsequently explored in an observational cohort study of 473 candidates.…”

Section: Kidney Transplantationmentioning

confidence: 99%

See 2 more Smart Citations

Abdominal Organ Transplantation: Noteworthy Literature in 2023

Katayama,

Maffucci,

Domanski

et al. 2024

Semin Cardiothorac Vasc Anesth

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This review highlights noteworthy literature published in 2023 and pertinent to anesthesiologists and critical care physicians caring for patients undergoing abdominal organ transplantation. We feature 9 studies from 593 peer-reviewed papers on pancreatic transplantation, 3 from 194 on intestinal transplantation, and 28 from over 4513 on kidney transplantation. The liver transplantation section includes a special focus on 20 studies from 5666 clinical trial publications. We explore a broad range of topics, including donor management, perioperative recipient management, and innovative pharmacologic and mechanical interventions tested for the improvement of patient and graft outcomes and survival.

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Section: Kidney Transplantationmentioning

confidence: 54%

Section: Kidney Transplantationmentioning

confidence: 54%

Section: Kidney Transplantationmentioning

confidence: 99%

See 1 more Smart Citation

Abdominal Organ Transplantation: Noteworthy Literature in 2023

Katayama,

Maffucci,

Domanski

et al. 2024

Semin Cardiothorac Vasc Anesth

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“…Previous works have identi ed scoring of coronary calcium using software to be accurate and reliable [12,13] . Further, these scores have been used to assess cardiovascular disease progression risk and related outcomes such as mortality [14] .…”

Section: Introductionmentioning

confidence: 99%

Unraveling the Impact of Abdominal Arterial Calcifications on Kidney Transplant Waitlist Mortality Through Ensemble Machine Learning

Salehinejad,

Spaulding,

Hanouneh

et al. 2023

Preprint

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The scarcity of organ donors relative to the number of patients with End Stage Kidney Disease (ESKD) has led to prolonged waiting times for kidney transplants, contributing to elevated cardiovascular mortality risk. Transplant professionals are tasked with the complex allocation of limited organs to a vulnerable patient group facing heightened morbidity and mortality risk. The need for continuous re-evaluation of waitlisted patients is evident due to the significant number who perish while awaiting transplantation. Among individuals with ESKD, vascular calcification, particularly Abdominal Arterial Calcifications (AAC), holds predictive value for cardiovascular events and mortality. However, a standardized method to quantify AAC's prognostic potential remains lacking, especially for kidney transplant evaluations. This study presents an ensemble machine learning (ML) approach to study the relationship between AAC score and mortality in patients on the waitlist and triage patients needing transplantation. Using the AAC score, the proposed ML model can predict kidney transplant waitlist morality with an accuracy of 78% while its accuracy is 68% without using this score. This study leverages explainable ML to explore the relationship between predictors and mortality in waitlisted patients, aiming to improve patient triage accuracy.

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“…To provide such external validation, we applied the AHA‐2022 algorithm to an observational cohort of PKTCs. The cohort was systematically referred to anatomic evaluation using cardiac computed tomography (CT), which allowed for evaluation of CHD in all PKTCs 10 and correlated findings with the classification according to both the AHA‐2022 and AHA‐2012 algorithms. In addition, we characterized the cohort with respect to the number of PKTCs undergoing revascularization after initial screening as well as risk of major adverse cardiovascular events (MACEs) and all‐cause death depending on the classification.…”

mentioning

confidence: 99%

External Validation of Proposed American Heart Association Algorithm for Cardiovascular Screening Before Kidney Transplantation

Nielsen,

Dahl,

Jespersen

et al. 2023

JAHA

Self Cite

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Background Screening for cardiovascular disease is currently recommended before kidney transplantation. The present study aimed to validate the proposed algorithm by the American Heart Association (AHA‐2022) considering cardiovascular findings and outcomes in kidney transplant candidates, and to compare AHA‐2022 with the previous recommendation (AHA‐2012). Methods and Results We applied the 2 screening algorithms to an observational cohort of kidney transplant candidates (n=529) who were already extensively screened for coronary heart disease by referral to cardiac computed tomography between 2014 and 2019. The cohort was divided into 3 groups as per the AHA‐2022 algorithm, or into 2 groups as per AHA‐2012. Outcomes were degree of coronary heart disease, revascularization rate following screening, major adverse cardiovascular events, and all‐cause death. Using the AHA‐2022 algorithm, 69 (13%) patients were recommended for cardiology referral, 315 (60%) for cardiac screening, and 145 (27%) no further screening. More patients were recommended cardiology referral or screening compared with the AHA‐2012 (73% versus 53%; P <0.0001). Patients recommended cardiology referral or cardiac screening had a higher risk of major adverse cardiovascular events (hazard ratio [HR], 5.5 [95% CI, 2.8–10.8]; and HR, 2.1 [95% CI, 1.2–3.9]) and all‐cause death (HR, 12.0 [95% [CI, 4.6–31.4]; and HR, 5.3 [95% CI, 2.1–13.3]) compared with patients recommended no further screening, and were more often revascularized following initial screening (20% versus 7% versus 0.7%; P <0.001). Conclusions The AHA‐2022 algorithm allocates more patients for cardiac referral and screening compared with AHA‐2012. Furthermore, the AHA‐2022 algorithm effectively discriminates between kidney transplant candidates at high, intermediate, and low risk with respect to major adverse cardiovascular events and all‐cause death.

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In a real-life setting, risk factors, coronary artery calcium score, and coronary stenosis at computed tomography angiography are associated with major adverse cardiovascular events and all-cause mortality among kidney transplant candidates

Cited by 6 publications

References 30 publications

Abdominal Organ Transplantation: Noteworthy Literature in 2023

Abdominal Organ Transplantation: Noteworthy Literature in 2023

Unraveling the Impact of Abdominal Arterial Calcifications on Kidney Transplant Waitlist Mortality Through Ensemble Machine Learning

External Validation of Proposed American Heart Association Algorithm for Cardiovascular Screening Before Kidney Transplantation

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