Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury.

IF 4.9 2区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Chun-Fu Lai, Jung-Hua Liu, Li-Jung Tseng, Chun-Hao Tsao, Nai-Kuan Chou, Shuei-Liong Lin, Yung-Ming Chen, Vin-Cent Wu
{"title":"Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury.","authors":"Chun-Fu Lai, Jung-Hua Liu, Li-Jung Tseng, Chun-Hao Tsao, Nai-Kuan Chou, Shuei-Liong Lin, Yung-Ming Chen, Vin-Cent Wu","doi":"10.1080/07853890.2023.2197290","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Heterogeneity exists in sepsis-associated acute kidney injury (SA-AKI). This study aimed to perform unsupervised consensus clustering in critically ill patients with dialysis-requiring SA-AKI.</p><p><strong>Patients and methods: </strong>This prospective observational cohort study included all septic patients, defined by the Sepsis-3 criteria, with dialysis-requiring SA-AKI in surgical intensive care units in Taiwan between 2009 and 2018. We employed unsupervised consensus clustering based on 23 clinical variables upon initializing renal replacement therapy. Multivariate-adjusted Cox regression models and Fine-Gray sub-distribution hazard models were built to test associations between cluster memberships with mortality and being free of dialysis at 90 days after hospital discharge, respectively.</p><p><strong>Results: </strong>Consensus clustering among 999 enrolled patients identified three sub-phenotypes characterized with distinct clinical manifestations upon renal replacement therapy initiation (<i>n</i> = 352, 396 and 251 in cluster 1, 2 and 3, respectively). They were followed for a median of 48 (interquartile range 9.5-128.5) days. Phenotypic cluster 1, featured by younger age, lower Charlson Comorbidity Index, higher baseline estimated glomerular filtration rate but with higher severity of acute illness was associated with an increased risk of death (adjusted hazard ratio of 3.05 [95% CI, 2.35-3.97]) and less probability to become free of dialysis (adjusted sub-distribution hazard ratio of 0.55 [95% CI, 0.38-0.8]) than cluster 3. By examining distinct features of the sub-phenotypes, we discovered that pre-dialysis hyperlactatemia ≥3.3 mmol/L was an independent outcome predictor. A clinical model developed to determine high-risk sub-phenotype 1 in this cohort (C-static 0.99) can identify a sub-phenotype with high in-hospital mortality risk (adjusted hazard ratio of 1.48 [95% CI, 1.25-1.74]) in another independent multi-centre SA-AKI cohort.</p><p><strong>Conclusions: </strong>Our data-driven approach suggests sub-phenotypes with clinical relevance in dialysis-requiring SA-AKI and serves an outcome predictor. This strategy represents further development toward precision medicine in the definition of high-risk sub-phenotype in patients with SA-AKI.Key messagesUnsupervised consensus clustering can identify sub-phenotypes of patients with SA-AKI and provide a risk prediction.Examining the features of patient heterogeneity contributes to the discovery of serum lactate levels ≥ 3.3 mmol/L upon initializing RRT as an independent outcome predictor.This data-driven approach can be useful for prognostication and lead to a better understanding of therapeutic strategies in heterogeneous clinical syndromes.</p>","PeriodicalId":8371,"journal":{"name":"Annals of medicine","volume":null,"pages":null},"PeriodicalIF":4.9000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10101673/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/07853890.2023.2197290","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Heterogeneity exists in sepsis-associated acute kidney injury (SA-AKI). This study aimed to perform unsupervised consensus clustering in critically ill patients with dialysis-requiring SA-AKI.

Patients and methods: This prospective observational cohort study included all septic patients, defined by the Sepsis-3 criteria, with dialysis-requiring SA-AKI in surgical intensive care units in Taiwan between 2009 and 2018. We employed unsupervised consensus clustering based on 23 clinical variables upon initializing renal replacement therapy. Multivariate-adjusted Cox regression models and Fine-Gray sub-distribution hazard models were built to test associations between cluster memberships with mortality and being free of dialysis at 90 days after hospital discharge, respectively.

Results: Consensus clustering among 999 enrolled patients identified three sub-phenotypes characterized with distinct clinical manifestations upon renal replacement therapy initiation (n = 352, 396 and 251 in cluster 1, 2 and 3, respectively). They were followed for a median of 48 (interquartile range 9.5-128.5) days. Phenotypic cluster 1, featured by younger age, lower Charlson Comorbidity Index, higher baseline estimated glomerular filtration rate but with higher severity of acute illness was associated with an increased risk of death (adjusted hazard ratio of 3.05 [95% CI, 2.35-3.97]) and less probability to become free of dialysis (adjusted sub-distribution hazard ratio of 0.55 [95% CI, 0.38-0.8]) than cluster 3. By examining distinct features of the sub-phenotypes, we discovered that pre-dialysis hyperlactatemia ≥3.3 mmol/L was an independent outcome predictor. A clinical model developed to determine high-risk sub-phenotype 1 in this cohort (C-static 0.99) can identify a sub-phenotype with high in-hospital mortality risk (adjusted hazard ratio of 1.48 [95% CI, 1.25-1.74]) in another independent multi-centre SA-AKI cohort.

Conclusions: Our data-driven approach suggests sub-phenotypes with clinical relevance in dialysis-requiring SA-AKI and serves an outcome predictor. This strategy represents further development toward precision medicine in the definition of high-risk sub-phenotype in patients with SA-AKI.Key messagesUnsupervised consensus clustering can identify sub-phenotypes of patients with SA-AKI and provide a risk prediction.Examining the features of patient heterogeneity contributes to the discovery of serum lactate levels ≥ 3.3 mmol/L upon initializing RRT as an independent outcome predictor.This data-driven approach can be useful for prognostication and lead to a better understanding of therapeutic strategies in heterogeneous clinical syndromes.

Abstract Image

Abstract Image

Abstract Image

无监督聚类确定了需要透析的败血症相关急性肾损伤患者的亚表型,并揭示了新的预后预测因素。
引言:败血症相关性急性肾损伤(SA-AKI)存在异质性。本研究旨在对需要SA-AKI透析的危重患者进行无监督一致性聚类。患者和方法:这项前瞻性观察性队列研究包括了台湾2009年至2018年期间外科重症监护室中所有根据Sepsis-3标准定义的透析需求SA-AKI的败血症患者。我们在启动肾脏替代治疗时,基于23个临床变量采用了无监督一致性聚类。建立了多变量调整的Cox回归模型和Fine Gray亚分布风险模型,以检验聚类成员与90岁时死亡率和无透析之间的相关性 出院后第天。结果:999名入选患者的一致聚类确定了三种亚表型,其特征是在肾脏替代治疗开始时具有不同的临床表现(n = 分别在簇1、2和3中的352、396和251)。他们被随访了48天(四分位间距9.5-128.5)。表型簇1,以年龄较小、Charlson共病指数较低为特征,基线估计的肾小球滤过率越高,但急性疾病的严重程度越高,与第3组相比,死亡风险增加(调整后的危险比为3.05[95%CI,2.35-3.97])和免于透析的可能性越小(调整后亚分布危险比为0.55[95%CI、0.38-0.8])。通过检查亚表型的不同特征,我们发现透析前高乳血症≥3.3 mmol/L是一个独立的预后预测指标。为确定该队列中的高危亚表型1而开发的临床模型(C静态0.99)可以在另一个独立的多中心SA-AKI队列中确定具有高住院死亡率风险(调整后的危险比为1.48[95%CI,1.25-1.74])的亚表型。结论:我们的数据驱动方法表明,在需要SA-AKI的透析中,亚表型具有临床相关性,并可作为结果预测指标。这一策略代表着在定义SA-AKI患者的高危亚表型方面向精准医学的进一步发展。关键信息无监督一致性聚类可以识别SA-AKI患者的亚表型,并提供风险预测。检查患者异质性的特征有助于发现血清乳酸水平≥3.3 mmol/L作为独立的结果预测因子。这种数据驱动的方法可用于预测,并有助于更好地了解异质性临床综合征的治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Annals of medicine
Annals of medicine 医学-医学:内科
CiteScore
4.90
自引率
0.00%
发文量
292
审稿时长
3 months
期刊介绍: Annals of Medicine is one of the world’s leading general medical review journals, boasting an impact factor of 5.435. It presents high-quality topical review articles, commissioned by the Editors and Editorial Committee, as well as original articles. The journal provides the current opinion on recent developments across the major medical specialties, with a particular focus on internal medicine. The peer-reviewed content of the journal keeps readers updated on the latest advances in the understanding of the pathogenesis of diseases, and in how molecular medicine and genetics can be applied in daily clinical practice.
×
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