使用简化临床数据算法识别以脂蛋白代谢失调为特征的脓毒症亚表型。

IF 2.9 3区 医学 Q2 CRITICAL CARE MEDICINE
SHOCK Pub Date : 2025-08-01 Epub Date: 2025-04-23 DOI:10.1097/SHK.0000000000002605
Guillaume Labilloy, Sébastien Tanaka, Lauren Page Black, Beulah Augustin, Charlotte Hopson, Joanne Bethencourt, Dongyuan Wu, Dawoud Sulaiman, Andrew Bertrand, Reinaldo Salomão, Kiley Graim, Susmita Datta, Srinivasa Reddy, Faheem W Guirgis, Daniel A Hofmaenner
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引用次数: 0

摘要

背景:在脓毒症中胆固醇代谢失调导致患者异质性。描述了低脂蛋白水平和高死亡率(HYPO)或高脂蛋白水平和低死亡率(NORMO)的亚表型。我们开发了一种简化的临床算法用于床边亚表型识别。方法:我们分析了四项前瞻性研究(内部数据集)的数据,重点关注HYPO和NORMO亚表型。建立了1000树随机森林分类器和逻辑回归模型,利用临床特征预测亚表型。通过将预测结果与来自机器学习模型的实际亚表型进行比较来评估性能。该模型应用于来自三个法国研究的281名患者的外部数据集。结果:内部队列包括386例患者(中位年龄63岁,46%为女性)。四个临床特征[肝脏SOFA、心血管SOFA、低(LDL-C)和高密度脂蛋白胆固醇(HDL-C)]预测HYPO与NORMO亚表型的AUC为0.86,敏感性为0.771,特异性为0.779。在内部数据集中,HYPO和NORMO患者的28天死亡率分别为26%和15%,在外部队列中,分别为30%和10%。HYPO内部与外部数据集LDL-C水平相似(p = 0.99),但HDL-C水平不同(p = 0.02)。内部与外部数据集的NORMO中位数LDL-C (p = 0.99)和HDL-C (p = 0.12)水平相似。在内部和外部数据集中,HYPO患者的LDL-C、HDL-C和总胆固醇均低于NORMO患者。结论:我们简化的临床数据算法可能允许对显示脂质失调亚表型的脓毒症患者进行床边识别。需要外部验证来验证这些结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

IDENTIFYING A SEPSIS SUBPHENOTYPE CHARACTERIZED BY DYSREGULATED LIPOPROTEIN METABOLISM USING A SIMPLIFIED CLINICAL DATA ALGORITHM.

IDENTIFYING A SEPSIS SUBPHENOTYPE CHARACTERIZED BY DYSREGULATED LIPOPROTEIN METABOLISM USING A SIMPLIFIED CLINICAL DATA ALGORITHM.

IDENTIFYING A SEPSIS SUBPHENOTYPE CHARACTERIZED BY DYSREGULATED LIPOPROTEIN METABOLISM USING A SIMPLIFIED CLINICAL DATA ALGORITHM.

IDENTIFYING A SEPSIS SUBPHENOTYPE CHARACTERIZED BY DYSREGULATED LIPOPROTEIN METABOLISM USING A SIMPLIFIED CLINICAL DATA ALGORITHM.

Abstract: Background: Cholesterol metabolism is dysregulated in sepsis contributing to patient heterogeneity. Subphenotypes displaying lower lipoprotein levels and higher mortality (previously subphenotyped hypolipoprotein phenotype [HYPO]) or higher lipoprotein levels and lower mortality (previously subphenotyped normolipoprotein phenotype [NORMO]) were described. We developed a simplified clinical algorithm for bedside subphenotype recognition. Methods: We analyzed data from four prospective studies (internal dataset), focusing on HYPO and NORMO subphenotypes. A 1,000-tree random forest classifier and logistic regression models were built, using clinical features to predict subphenotypes. Performance was evaluated by comparing predictions to actual subphenotypes derived from a machine learning model. The model was applied to an external dataset of 281 patients from three French studies. Results: The internal cohort consisted of 386 patients (median age, 63 years; 46% female). Four clinical features (hepatic SOFA, cardiovascular SOFA, low [low-density lipoprotein cholesterol {LDL-C}] and high-density lipoprotein cholesterol [high-density lipoprotein cholesterol {HDL-C}]) predicted HYPO versus NORMO subphenotypes with an area under the receiver operating characteristic curve of 0.86, a sensitivity of 0.771, and a specificity of 0.779. In the internal dataset, 28-day mortality for HYPO versus NORMO patients was 26% versus 15%, and in the external cohort, 30% versus 10%. HYPO internal versus external dataset LDL-C levels were similar ( P = 0.99), but HDL-C ( P = 0.02) levels were different. Median NORMO internal versus external dataset LDL-C ( P = 0.99) and HDL-C ( P = 0.12) levels were similar. HYPO patients had lower LDL-C, HDL-C and total cholesterol than NORMO patients in both internal and external datasets. Conclusions: Our simplified clinical data algorithm may allow for bedside recognition of septic patients displaying lipid dysregulation subphenotypes. External validation is needed to verify these results.

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来源期刊
SHOCK
SHOCK 医学-外科
CiteScore
6.20
自引率
3.20%
发文量
199
审稿时长
1 months
期刊介绍: SHOCK®: Injury, Inflammation, and Sepsis: Laboratory and Clinical Approaches includes studies of novel therapeutic approaches, such as immunomodulation, gene therapy, nutrition, and others. The mission of the Journal is to foster and promote multidisciplinary studies, both experimental and clinical in nature, that critically examine the etiology, mechanisms and novel therapeutics of shock-related pathophysiological conditions. Its purpose is to excel as a vehicle for timely publication in the areas of basic and clinical studies of shock, trauma, sepsis, inflammation, ischemia, and related pathobiological states, with particular emphasis on the biologic mechanisms that determine the response to such injury. Making such information available will ultimately facilitate improved care of the traumatized or septic individual.
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