针对 PCI 患者长期风险预测的临床和冠状动脉病变功能评估整合模型的开发与验证。

IF 1.8 4区 医学 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS
Shao-Yu Wu, Rui Zhang, Sheng Yuan, Zhong-Xing Cai, Chang-Dong Guan, Tong-Qiang Zou, Li-Hua Xie, Ke-Fei Dou
{"title":"针对 PCI 患者长期风险预测的临床和冠状动脉病变功能评估整合模型的开发与验证。","authors":"Shao-Yu Wu, Rui Zhang, Sheng Yuan, Zhong-Xing Cai, Chang-Dong Guan, Tong-Qiang Zou, Li-Hua Xie, Ke-Fei Dou","doi":"10.26599/1671-5411.2024.01.007","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>To establish a scoring system combining the ACEF score and the quantitative blood flow ratio (QFR) to improve the long-term risk prediction of patients undergoing percutaneous coronary intervention (PCI).</p><p><strong>Methods: </strong>In this population-based cohort study, a total of 46 features, including patient clinical and coronary lesion characteristics, were assessed for analysis through machine learning models. The ACEF-QFR scoring system was developed using 1263 consecutive cases of CAD patients after PCI in PANDA III trial database. The newly developed score was then validated on the other remaining 542 patients in the cohort.</p><p><strong>Results: </strong>In both the Random Forest Model and the DeepSurv Model, age, renal function (creatinine), cardiac function (LVEF) and post-PCI coronary physiological index (QFR) were identified and confirmed to be significant predictive factors for 2-year adverse cardiac events. The ACEF-QFR score was constructed based on the developmental dataset and computed as age (years)/EF (%) + 1 (if creatinine ≥ 2.0 mg/dL) + 1 (if post-PCI QFR ≤ 0.92). The performance of the ACEF-QFR scoring system was preliminarily evaluated in the developmental dataset, and then further explored in the validation dataset. The ACEF-QFR score showed superior discrimination (C-statistic = 0.651; 95% CI: 0.611-0.691, <i>P</i> < 0.05 versus post-PCI physiological index and other commonly used risk scores) and excellent calibration (Hosmer-Lemeshow χ<sup>2</sup> = 7.070; <i>P</i> = 0.529) for predicting 2-year patient-oriented composite endpoint (POCE). The good prognostic value of the ACEF-QFR score was further validated by multivariable Cox regression and Kaplan-Meier analysis (adjusted HR = 1.89; 95% CI: 1.18-3.04; log-rank <i>P <</i> 0.01) after stratified the patients into high-risk group and low-risk group.</p><p><strong>Conclusions: </strong>An improved scoring system combining clinical and coronary lesion-based functional variables (ACEF-QFR) was developed, and its ability for prognostic prediction in patients with PCI was further validated to be significantly better than the post-PCI physiological index and other commonly used risk scores.</p>","PeriodicalId":51294,"journal":{"name":"Journal of Geriatric Cardiology","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10908582/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development and validation of a model integrating clinical and coronary lesion-based functional assessment for long-term risk prediction in PCI patients.\",\"authors\":\"Shao-Yu Wu, Rui Zhang, Sheng Yuan, Zhong-Xing Cai, Chang-Dong Guan, Tong-Qiang Zou, Li-Hua Xie, Ke-Fei Dou\",\"doi\":\"10.26599/1671-5411.2024.01.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>To establish a scoring system combining the ACEF score and the quantitative blood flow ratio (QFR) to improve the long-term risk prediction of patients undergoing percutaneous coronary intervention (PCI).</p><p><strong>Methods: </strong>In this population-based cohort study, a total of 46 features, including patient clinical and coronary lesion characteristics, were assessed for analysis through machine learning models. The ACEF-QFR scoring system was developed using 1263 consecutive cases of CAD patients after PCI in PANDA III trial database. The newly developed score was then validated on the other remaining 542 patients in the cohort.</p><p><strong>Results: </strong>In both the Random Forest Model and the DeepSurv Model, age, renal function (creatinine), cardiac function (LVEF) and post-PCI coronary physiological index (QFR) were identified and confirmed to be significant predictive factors for 2-year adverse cardiac events. The ACEF-QFR score was constructed based on the developmental dataset and computed as age (years)/EF (%) + 1 (if creatinine ≥ 2.0 mg/dL) + 1 (if post-PCI QFR ≤ 0.92). The performance of the ACEF-QFR scoring system was preliminarily evaluated in the developmental dataset, and then further explored in the validation dataset. The ACEF-QFR score showed superior discrimination (C-statistic = 0.651; 95% CI: 0.611-0.691, <i>P</i> < 0.05 versus post-PCI physiological index and other commonly used risk scores) and excellent calibration (Hosmer-Lemeshow χ<sup>2</sup> = 7.070; <i>P</i> = 0.529) for predicting 2-year patient-oriented composite endpoint (POCE). The good prognostic value of the ACEF-QFR score was further validated by multivariable Cox regression and Kaplan-Meier analysis (adjusted HR = 1.89; 95% CI: 1.18-3.04; log-rank <i>P <</i> 0.01) after stratified the patients into high-risk group and low-risk group.</p><p><strong>Conclusions: </strong>An improved scoring system combining clinical and coronary lesion-based functional variables (ACEF-QFR) was developed, and its ability for prognostic prediction in patients with PCI was further validated to be significantly better than the post-PCI physiological index and other commonly used risk scores.</p>\",\"PeriodicalId\":51294,\"journal\":{\"name\":\"Journal of Geriatric Cardiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-01-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10908582/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Geriatric Cardiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.26599/1671-5411.2024.01.007\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geriatric Cardiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.26599/1671-5411.2024.01.007","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

目的建立一个结合 ACEF 评分和定量血流比(QFR)的评分系统,以改善经皮冠状动脉介入治疗(PCI)患者的长期风险预测:在这项基于人群的队列研究中,通过机器学习模型对包括患者临床和冠状动脉病变特征在内的共 46 个特征进行了评估分析。ACEF-QFR 评分系统是利用 PANDA III 试验数据库中 1263 例PCI 后的连续 CAD 患者开发的。然后在队列中剩余的 542 例患者身上验证了新开发的评分系统:结果:在随机森林模型和 DeepSurv 模型中,年龄、肾功能(肌酐)、心功能(LVEF)和 PCI 后冠状动脉生理指数(QFR)均被确定为 2 年不良心脏事件的重要预测因素。ACEF-QFR 评分是根据发育数据集构建的,计算公式为年龄(岁)/EF(%)+1(如果肌酐≥ 2.0 mg/dL)+1(如果PCI 后 QFR ≤ 0.92)。在开发数据集中对 ACEF-QFR 评分系统的性能进行了初步评估,然后在验证数据集中进行了进一步探讨。ACEF-QFR评分与PCI后生理指数和其他常用风险评分相比,显示出卓越的区分度(C统计量=0.651;95% CI:0.611-0.691,P < 0.05)和出色的校准性(Hosmer-Lemeshow χ2 = 7.070;P = 0.529),可预测2年患者导向复合终点(POCE)。将患者分为高危组和低危组后,多变量考克斯回归和卡普兰-梅耶分析进一步验证了 ACEF-QFR 评分的良好预后价值(调整后 HR = 1.89;95% CI:1.18-3.04;log-rank P 0.01):结论:结合临床和基于冠状动脉病变的功能变量(ACEF-QFR)开发了一种改进的评分系统,其对PCI患者的预后预测能力得到了进一步验证,明显优于PCI后生理指数和其他常用的风险评分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development and validation of a model integrating clinical and coronary lesion-based functional assessment for long-term risk prediction in PCI patients.

Objectives: To establish a scoring system combining the ACEF score and the quantitative blood flow ratio (QFR) to improve the long-term risk prediction of patients undergoing percutaneous coronary intervention (PCI).

Methods: In this population-based cohort study, a total of 46 features, including patient clinical and coronary lesion characteristics, were assessed for analysis through machine learning models. The ACEF-QFR scoring system was developed using 1263 consecutive cases of CAD patients after PCI in PANDA III trial database. The newly developed score was then validated on the other remaining 542 patients in the cohort.

Results: In both the Random Forest Model and the DeepSurv Model, age, renal function (creatinine), cardiac function (LVEF) and post-PCI coronary physiological index (QFR) were identified and confirmed to be significant predictive factors for 2-year adverse cardiac events. The ACEF-QFR score was constructed based on the developmental dataset and computed as age (years)/EF (%) + 1 (if creatinine ≥ 2.0 mg/dL) + 1 (if post-PCI QFR ≤ 0.92). The performance of the ACEF-QFR scoring system was preliminarily evaluated in the developmental dataset, and then further explored in the validation dataset. The ACEF-QFR score showed superior discrimination (C-statistic = 0.651; 95% CI: 0.611-0.691, P < 0.05 versus post-PCI physiological index and other commonly used risk scores) and excellent calibration (Hosmer-Lemeshow χ2 = 7.070; P = 0.529) for predicting 2-year patient-oriented composite endpoint (POCE). The good prognostic value of the ACEF-QFR score was further validated by multivariable Cox regression and Kaplan-Meier analysis (adjusted HR = 1.89; 95% CI: 1.18-3.04; log-rank P < 0.01) after stratified the patients into high-risk group and low-risk group.

Conclusions: An improved scoring system combining clinical and coronary lesion-based functional variables (ACEF-QFR) was developed, and its ability for prognostic prediction in patients with PCI was further validated to be significantly better than the post-PCI physiological index and other commonly used risk scores.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Geriatric Cardiology
Journal of Geriatric Cardiology CARDIAC & CARDIOVASCULAR SYSTEMS-GERIATRICS & GERONTOLOGY
CiteScore
3.30
自引率
4.00%
发文量
1161
期刊介绍: JGC focuses on both basic research and clinical practice to the diagnosis and treatment of cardiovascular disease in the aged people, especially those with concomitant disease of other major organ-systems, such as the lungs, the kidneys, liver, central nervous system, gastrointestinal tract or endocrinology, etc.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信