Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis
Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis
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DOI：
10.1001/jama.2019.5791
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发表时间：
2019-05-28
影响因子：
120.7
通讯作者：
Angus, Derek C.
中科院分区：
文献类型：
--
作者：
Seymour, Christopher W.;Kennedy, Jason N.;Angus, Derek C.
重要性：脓毒症是一种异质性综合征。识别不同的临床表型可能允许更精准的治疗并改善医疗护理。
目的：从临床数据中推导出脓毒症表型，确定其可重复性以及与宿主反应生物标志物和临床结局的相关性，并评估其与随机临床试验（RCT）结果的潜在因果关系。
设计、环境和参与者：使用统计学、机器学习和模拟工具对数据集进行回顾性分析。在宾夕法尼亚州12家医院（2010 - 2012年）入院6小时内符合脓毒症 - 3标准的20189名患者（16552名独特患者）中，通过对29个变量应用一致性k均值聚类推导出表型。在第二个数据库（2013 - 2014年；共43086名患者，其中31160名独特患者）、一项肺炎所致脓毒症的前瞻性队列研究（n = 583）以及3项脓毒症RCT（n = 4737）中评估可重复性以及与生物学参数和临床结局的相关性。
暴露因素：电子健康记录中的所有临床和实验室变量。
主要结局和指标：推导出的表型（α、β、γ和δ）频率、宿主反应生物标志物、28天和365天死亡率以及RCT模拟结果。
结果：推导队列包括20189名脓毒症患者（平均年龄64[标准差，17]岁；10022[50%]为男性；平均最高24小时序贯器官衰竭评估[SOFA]评分3.9[标准差，2.4]）。验证队列包括43086名患者（平均年龄67[标准差，17]岁；21993[51%]为男性；平均最高24小时SOFA评分3.6[标准差，2.0]）。在4种推导出的表型中，α表型最常见（n = 6625；33%），包括血管升压药使用量最低的患者；β表型（n = 5512；27%）患者年龄较大，慢性疾病和肾功能障碍更多；γ表型（n = 5385；27%）患者炎症和肺功能障碍更多；δ表型（n = 2667；13%）患者肝功能障碍和感染性休克更多。验证队列中的表型分布相似。不同表型的生物标志物模式存在一致差异。在推导队列中，α表型的5691名独特患者中有287人死亡（5%）；β表型的4420人中有561人死亡（13%）；γ表型的4318人中有1031人死亡（24%）；δ表型的2223人中有897人死亡（40%）。在所有队列和试验中，δ表型的28天和365天死亡率高于其他3种表型（P <.001）。模拟结果表明，在脓毒症RCT中，α表型患者从治疗中获益的可能性最高（>60%），而δ表型患者从治疗中获益的可能性最低（<33%），甚至有>60%的有害可能性。
结论和相关性：在这项对脓毒症患者数据集的回顾性分析中，确定了4种与宿主反应模式和临床结局相关的临床表型，模拟结果表明这些表型可能有助于理解治疗效果的异质性。需要进一步研究以确定这些表型在临床护理中的实用性以及对试验设计和解释的指导作用。
IMPORTANCE Sepsis is a heterogeneous syndrome. Identification of distinct clinical phenotypes may allow more precise therapy and improve care.OBJECTIVE To derive sepsis phenotypes from clinical data, determine their reproducibility and correlation with host-response biomarkers and clinical outcomes, and assess the potential causal relationship with results from randomized clinical trials (RCTs).DESIGN, SETTINGS, AND PARTICIPANTS Retrospective analysis of data sets using statistical, machine learning, and simulation tools. Phenotypes were derived among 20 189 total patients (16 552 unique patients) who met Sepsis-3 criteria within 6 hours of hospital presentation at 12 Pennsylvania hospitals (2010-2012) using consensus k means clustering applied to 29 variables. Reproducibility and correlation with biological parameters and clinical outcomes were assessed in a second database (2013-2014; n = 43 086 total patients and n = 31 160 unique patients), in a prospective cohort study of sepsis due to pneumonia (n = 583), and in 3 sepsis RCTs (n = 4737).EXPOSURES All clinical and laboratory variables in the electronic health record.MAIN OUTCOMES AND MEASURES Derived phenotype (alpha, beta, gamma, and delta) frequency, host-response biomarkers, 28-day and 365-day mortality, and RCT simulation outputs.RESULTS The derivation cohort included 20 189 patients with sepsis (mean age, 64 [SD, 17] years; 10 022 [50%] male; mean maximum 24-hour Sequential Organ Failure Assessment [SOFA] score, 3.9 [SD, 2.4]). The validation cohort included 43 086 patients (mean age, 67 [SD, 17] years; 21 993 [51%] male; mean maximum 24-hour SOFA score, 3.6 [SD, 2.0]). Of the 4 derived phenotypes, the a phenotype was the most common (n = 6625; 33%) and included patients with the lowest administration of a vasopressor; in the beta phenotype (n = 5512; 27%), patients were older and had more chronic illness and renal dysfunction; in the gamma phenotype (n = 5385; 27%), patients had more inflammation and pulmonary dysfunction; and in the delta phenotype (n = 2667; 13%), patients had more liver dysfunction and septic shock. Phenotype distributions were similar in the validation cohort. There were consistent differences in biomarker patterns by phenotype. In the derivation cohort, cumulative 28-day mortality was 287 deaths of 5691 unique patients (5%) for the alpha phenotype; 561 of 4420 (13%) for the beta phenotype; 1031 of 4318 (24%) for the gamma phenotype; and 897 of 2223 (40%) for the delta phenotype. Across all cohorts and trials, 28-day and 365-day mortality were highest among the delta phenotype vs the other 3 phenotypes (P33% chance of benefit to >60% chance of harm).CONCLUSIONS AND RELEVANCE In this retrospective analysis of data sets from patients with sepsis, 4 clinical phenotypes were identified that correlated with host-response patterns and clinical outcomes, and simulations suggested these phenotypes may help in understanding heterogeneity of treatment effects. Further research is needed to determine the utility of these phenotypes in clinical care and for informing trial design and interpretation.