Department of Critical Care Medicine, The Second Hospital of Lanzhou University, Lanzhou, China.
Shock. 2024 May 1;61(5):718-727. doi: 10.1097/SHK.0000000000002335. Epub 2024 Feb 5.
Purpose : The objective of this study is to establish a nomogram that correlates optimized Acute Physiology and Chronic Health Evaluation II (APACHE II) score with sepsis-related indicators, aiming to provide a robust model for early prediction of sepsis prognosis in clinical practice and serve as a valuable reference for improved diagnosis and treatment strategies. Methods : This retrospective study extracted sepsis patients meeting the inclusion criteria from the MIMIC-IV database to form the training group. An optimized APACHE II score integrated with relevant indicators was developed using a nomogram for predicting the prognosis of sepsis patients. External validation was conducted using data from the intensive care unit at Lanzhou University Second Hospital. Results : The study enrolled 1805 patients in the training cohort and 203 patients in the validation cohort. A multifactor analysis was conducted to identify factors affecting patient mortality within 28 days, resulting in the development of an optimized score by simplifying evaluation indicators from APACHE II score. The results showed that the optimized score (area under the ROC curve [AUC] = 0.715) had a higher area under receiver operating characteristic curve than Sequential Organ Failure Assessment score (AUC = 0.637) but slightly lower than APACHE II score (AUC = 0.720). Significant indicators identified through multifactor analysis included platelet count, total bilirubin level, albumin level, prothrombin time, activated partial thromboplastin time, mechanical ventilation use and renal replacement therapy use. These seven indicators were combined with optimized score to construct a nomogram based on these seven indicators. The nomogram demonstrated good clinical predictive value in both training cohort (AUC = 0.803) and validation cohort (AUC = 0.750). Calibration curves and decision curve analyses also confirmed its good predictive ability, surpassing the APACHE II score and Sequential Organ Failure Assessment score in identifying high-risk patients. Conclusions : The nomogram was established in this study using the MIMIC-IV database and validated with external data, demonstrating its robust discriminability, calibration, and clinical practicability for predicting 28-day mortality in sepsis patients. These findings aim to provide substantial support for clinicians' decision making.
本研究旨在建立一个与脓毒症相关指标相关的优化急性生理学和慢性健康评估 II(APACHE II)评分的列线图,旨在为临床实践中脓毒症预后的早期预测提供一个稳健的模型,并为改进诊断和治疗策略提供有价值的参考。
本回顾性研究从 MIMIC-IV 数据库中提取符合纳入标准的脓毒症患者,形成训练组。使用列线图开发了一种预测脓毒症患者预后的优化 APACHE II 评分与相关指标的整合方法。使用兰州大学第二医院重症监护室的数据进行外部验证。
该研究纳入了 1805 例患者的训练队列和 203 例患者的验证队列。通过多因素分析确定了影响 28 天内患者死亡率的因素,从而通过简化 APACHE II 评分的评估指标来开发优化评分。结果表明,优化评分(ROC 曲线下面积 [AUC] = 0.715)比序贯器官衰竭评估评分(AUC = 0.637)具有更高的 AUC,但略低于 APACHE II 评分(AUC = 0.720)。通过多因素分析确定的显著指标包括血小板计数、总胆红素水平、白蛋白水平、凝血酶原时间、活化部分凝血活酶时间、机械通气使用和肾脏替代治疗使用。这七个指标与优化评分相结合,构建了一个基于这七个指标的列线图。该列线图在训练队列(AUC = 0.803)和验证队列(AUC = 0.750)中均显示出良好的临床预测价值。校准曲线和决策曲线分析也证实了其良好的预测能力,在识别高危患者方面优于 APACHE II 评分和序贯器官衰竭评估评分。
本研究使用 MIMIC-IV 数据库建立了列线图,并通过外部数据进行了验证,证明其对预测脓毒症患者 28 天死亡率具有稳健的区分能力、校准能力和临床实用性。这些发现旨在为临床医生的决策提供有力支持。