Baysan Meryem, Baroni Gianluca D, van Boekel Anna M, Steyerberg Ewout W, Arbous Mendi S, van der Bom Johanna G
Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands.
Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Crit Care Explor. 2020 Mar 24;2(3):e0087. doi: 10.1097/CCE.0000000000000087. eCollection 2020 Mar.
We investigated the added predictive value of lactate and lactate clearance to the Acute Physiology and Chronic Health Evaluation IV model for predicting in-hospital mortality in critically ill patients with sepsis.
Retrospective observational cohort study.
Mixed ICU of Leiden University Medical Center, The Netherlands.
Critically ill patients adult patients with sepsis who have been admitted to the ICU of Leiden University Medical Center, The Netherlands, from 2006 to January 2018.
None.
We fitted a baseline model with the Acute Physiology and Chronic Health Evaluation IV predictors and added 13 prespecified combinations of lactate and lactate clearance at 0, 6 and 24 hours after admission to create a set of extended models to compare with the baseline Acute Physiology and Chronic Health Evaluation IV model. Among 603 ICU admissions, 451 patients met the inclusion criteria. A total of 160 patients died in-hospital, of which 106 died in the ICU. Their lactate and lactate clearance measurements were higher at all time points than those of survivors. The Akaike Information Criterion score improved in 10 of 13 prespecified extended models, with best performance for models that included lactate at 24 hours, alone or in combination with lactate at admission or lactate clearance at 24 hours. We compared the observed and predicted probabilities of in-hospital mortality of the baseline Acute Physiology and Chronic Health Evaluation IV model with the best model in our data, lactate at 24 hours added to the Acute Physiology and Chronic Health Evaluation IV model. This resulted in an increase in specificity of 29.9% (95% CI, 18.9-40.9%).
Lactate measurements at 24 hours after admission add predictive value to the prediction of mortality with Acute Physiology and Chronic Health Evaluation IV among ICU patients with sepsis. External validation is needed to develop extended prediction models.
我们研究了乳酸和乳酸清除率对急性生理学与慢性健康状况评估IV模型（APACHE IV）预测脓毒症重症患者院内死亡率的附加预测价值。
回顾性观察队列研究。
荷兰莱顿大学医学中心综合重症监护病房。
2006年至2018年1月入住荷兰莱顿大学医学中心重症监护病房的脓毒症成年重症患者。
无。
我们构建了一个包含急性生理学与慢性健康状况评估IV预测指标的基线模型，并在入院后0、6和24小时添加了13种预先设定的乳酸和乳酸清除率组合，以创建一组扩展模型，与基线急性生理学与慢性健康状况评估IV模型进行比较。在603例入住重症监护病房的患者中，451例符合纳入标准。共有160例患者在院内死亡，其中106例在重症监护病房死亡。他们在所有时间点的乳酸和乳酸清除率测量值均高于幸存者。在13种预先设定的扩展模型中，有10种模型的赤池信息准则评分有所改善，其中包含入院24小时乳酸单独或与入院时乳酸或24小时乳酸清除率联合使用的模型表现最佳。我们将基线急性生理学与慢性健康状况评估IV模型的院内死亡观察概率和预测概率与我们数据中的最佳模型（即急性生理学与慢性健康状况评估IV模型添加入院24小时乳酸）进行了比较。这使得特异性提高了29.9%（95%CI，18.9 - 40.9%）。
入院24小时后的乳酸测量值为APACHE IV预测脓毒症重症监护病房患者死亡率增加了预测价值。需要进行外部验证以开发扩展预测模型。
