Development of model to predict end-stage renal disease after coronary artery bypass grafting

The ACHE score

Yeonhee Lee, Jiwon Park, Myoung Jin Jang, Hong Ran Moon, Dong Ki Kim, Kook-Hwan Oh, Kwon-Wook Joo, Chun Soo Lim, Yon Su Kim, Ki Young Na, Seung Seok Han

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Because end-stage renal disease (ESRD) increases the risks of morbidity and mortality, early detection and prevention of ESRD is a critical issue in clinical practice. However, no ESRD-prediction models have been developed or validated in patients undergoing coronary artery bypass grafting (CABG).This is a retrospective multicenter cohort study, recruited between January 2004 and December 2015. A cohort of 3089 patients undergoing CABG in two tertiary referral centers was analyzed to derive a risk-prediction model. The model was developed using Cox proportional hazard analyses, and its performance was assessed using C-statistics. The model was externally validated in an independent cohort of 279 patients.During the median follow-up of 6 years (maximum 13 years), ESRD occurred in 60 patients (2.0%). Through stepwise selection multivariate analyses, the following three variables were finally included in the ESRD-prediction model: postoperative Acute kidney injury, underlying Chronic kidney disease, and the number of antiHypertensive drugs (ACHE score). This model showed good performance in predicting ESRD with the following C-statistics: 0.89 (95% confidence interval [CI] 0.84-0.94) in the development cohort and 0.82 (95% CI 0.60-1.00) in the external validation cohort.The present ESRD-prediction model may be applicable to patients undergoing CABG, with the advantage of simplicity and preciseness.

Original languageEnglish
Pages (from-to)e15789
JournalMedicine
Volume98
Issue number21
DOIs
StatePublished - 1 May 2019

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Coronary Artery Bypass
Chronic Kidney Failure
Confidence Intervals
Chronic Renal Insufficiency
Acute Kidney Injury
Tertiary Care Centers
Antihypertensive Agents
Multicenter Studies
Cohort Studies
Multivariate Analysis
Morbidity
Mortality

Cite this

@article{1eaac50cff6a415488e78321c8e6b642,
title = "Development of model to predict end-stage renal disease after coronary artery bypass grafting: The ACHE score",
abstract = "Because end-stage renal disease (ESRD) increases the risks of morbidity and mortality, early detection and prevention of ESRD is a critical issue in clinical practice. However, no ESRD-prediction models have been developed or validated in patients undergoing coronary artery bypass grafting (CABG).This is a retrospective multicenter cohort study, recruited between January 2004 and December 2015. A cohort of 3089 patients undergoing CABG in two tertiary referral centers was analyzed to derive a risk-prediction model. The model was developed using Cox proportional hazard analyses, and its performance was assessed using C-statistics. The model was externally validated in an independent cohort of 279 patients.During the median follow-up of 6 years (maximum 13 years), ESRD occurred in 60 patients (2.0{\%}). Through stepwise selection multivariate analyses, the following three variables were finally included in the ESRD-prediction model: postoperative Acute kidney injury, underlying Chronic kidney disease, and the number of antiHypertensive drugs (ACHE score). This model showed good performance in predicting ESRD with the following C-statistics: 0.89 (95{\%} confidence interval [CI] 0.84-0.94) in the development cohort and 0.82 (95{\%} CI 0.60-1.00) in the external validation cohort.The present ESRD-prediction model may be applicable to patients undergoing CABG, with the advantage of simplicity and preciseness.",
author = "Yeonhee Lee and Jiwon Park and Jang, {Myoung Jin} and Moon, {Hong Ran} and Kim, {Dong Ki} and Kook-Hwan Oh and Kwon-Wook Joo and Lim, {Chun Soo} and Kim, {Yon Su} and Na, {Ki Young} and Han, {Seung Seok}",
year = "2019",
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doi = "10.1097/MD.0000000000015789",
language = "English",
volume = "98",
pages = "e15789",
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issn = "0025-7974",
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Development of model to predict end-stage renal disease after coronary artery bypass grafting : The ACHE score. / Lee, Yeonhee; Park, Jiwon; Jang, Myoung Jin; Moon, Hong Ran; Kim, Dong Ki; Oh, Kook-Hwan; Joo, Kwon-Wook; Lim, Chun Soo; Kim, Yon Su; Na, Ki Young; Han, Seung Seok.

In: Medicine, Vol. 98, No. 21, 01.05.2019, p. e15789.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Development of model to predict end-stage renal disease after coronary artery bypass grafting

T2 - The ACHE score

AU - Lee, Yeonhee

AU - Park, Jiwon

AU - Jang, Myoung Jin

AU - Moon, Hong Ran

AU - Kim, Dong Ki

AU - Oh, Kook-Hwan

AU - Joo, Kwon-Wook

AU - Lim, Chun Soo

AU - Kim, Yon Su

AU - Na, Ki Young

AU - Han, Seung Seok

PY - 2019/5/1

Y1 - 2019/5/1

N2 - Because end-stage renal disease (ESRD) increases the risks of morbidity and mortality, early detection and prevention of ESRD is a critical issue in clinical practice. However, no ESRD-prediction models have been developed or validated in patients undergoing coronary artery bypass grafting (CABG).This is a retrospective multicenter cohort study, recruited between January 2004 and December 2015. A cohort of 3089 patients undergoing CABG in two tertiary referral centers was analyzed to derive a risk-prediction model. The model was developed using Cox proportional hazard analyses, and its performance was assessed using C-statistics. The model was externally validated in an independent cohort of 279 patients.During the median follow-up of 6 years (maximum 13 years), ESRD occurred in 60 patients (2.0%). Through stepwise selection multivariate analyses, the following three variables were finally included in the ESRD-prediction model: postoperative Acute kidney injury, underlying Chronic kidney disease, and the number of antiHypertensive drugs (ACHE score). This model showed good performance in predicting ESRD with the following C-statistics: 0.89 (95% confidence interval [CI] 0.84-0.94) in the development cohort and 0.82 (95% CI 0.60-1.00) in the external validation cohort.The present ESRD-prediction model may be applicable to patients undergoing CABG, with the advantage of simplicity and preciseness.

AB - Because end-stage renal disease (ESRD) increases the risks of morbidity and mortality, early detection and prevention of ESRD is a critical issue in clinical practice. However, no ESRD-prediction models have been developed or validated in patients undergoing coronary artery bypass grafting (CABG).This is a retrospective multicenter cohort study, recruited between January 2004 and December 2015. A cohort of 3089 patients undergoing CABG in two tertiary referral centers was analyzed to derive a risk-prediction model. The model was developed using Cox proportional hazard analyses, and its performance was assessed using C-statistics. The model was externally validated in an independent cohort of 279 patients.During the median follow-up of 6 years (maximum 13 years), ESRD occurred in 60 patients (2.0%). Through stepwise selection multivariate analyses, the following three variables were finally included in the ESRD-prediction model: postoperative Acute kidney injury, underlying Chronic kidney disease, and the number of antiHypertensive drugs (ACHE score). This model showed good performance in predicting ESRD with the following C-statistics: 0.89 (95% confidence interval [CI] 0.84-0.94) in the development cohort and 0.82 (95% CI 0.60-1.00) in the external validation cohort.The present ESRD-prediction model may be applicable to patients undergoing CABG, with the advantage of simplicity and preciseness.

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U2 - 10.1097/MD.0000000000015789

DO - 10.1097/MD.0000000000015789

M3 - Article

VL - 98

SP - e15789

JO - Medicine (United States)

JF - Medicine (United States)

SN - 0025-7974

IS - 21

ER -