Abstract：
UNASSIGNED: Identifying risk factors and improving prognostication for mortality among patients with sepsis-associated acute kidney injury (AKI) undergoing continuous kidney replacement therapy (CKRT) is important in improving the adverse prognosis of this patient population. This study aimed to compare the prognostic value of existing systemic inflammation biomarkers and determine the optimal systemic inflammation biomarker in patients with sepsis-associated AKI receiving CKRT.
UNASSIGNED: This multi-center, retrospective, observational cohort study included 1,500 patients with sepsis-associated AKI treated with intensive care and CKRT. The main predictor was a panel of 13 different systemic inflammation biomarkers. The primary outcome was 28-day mortality after CKRT initiation. Secondary outcomes included 90-day mortality after CKRT initiation, CKRT duration, kidney replacement therapy dependence at discharge, and lengths of intensive care unit (ICU) and hospital stays.
UNASSIGNED: When added to the widely accepted Acute Physiology and Chronic Health Evaluation II score, platelet-to-albumin ratio (PAR) and neutrophil-platelet score (NPS) had the highest improvements in prognostication of 28-day mortality, where the corresponding increases in C-statistic were 0.01 (95% confidence interval [CI], 0.00-0.02) and 0.02 (95% CI, 0.01-0.03). Similar findings were observed for 90-day mortality. The 28- and 90-day mortality rates were significantly lower for the higher PAR and NPS quartiles. These associations remained significant even after adjustment for potential confounding variables in multivariable Cox proportional hazards models.
UNASSIGNED: Of the available systemic inflammation biomarkers, the addition of PAR or NPS to conventional ICU prediction models improved the prognostication of patients with sepsis-associated AKI receiving intensive care and CKRT.
UNASSIGNED: This multi-center, retrospective, observational cohort study included 1,500 patients with sepsis-associated AKI treated with intensive care and CKRT. The main predictor was a panel of 13 different systemic inflammation biomarkers. The primary outcome was 28-day mortality after CKRT initiation. Secondary outcomes included 90-day mortality after CKRT initiation, CKRT duration, kidney replacement therapy dependence at discharge, and lengths of intensive care unit (ICU) and hospital stays.
UNASSIGNED: When added to the widely accepted Acute Physiology and Chronic Health Evaluation II score, platelet-to-albumin ratio (PAR) and neutrophil-platelet score (NPS) had the highest improvements in prognostication of 28-day mortality, where the corresponding increases in C-statistic were 0.01 (95% confidence interval [CI], 0.00-0.02) and 0.02 (95% CI, 0.01-0.03). Similar findings were observed for 90-day mortality. The 28- and 90-day mortality rates were significantly lower for the higher PAR and NPS quartiles. These associations remained significant even after adjustment for potential confounding variables in multivariable Cox proportional hazards models.
UNASSIGNED: Of the available systemic inflammation biomarkers, the addition of PAR or NPS to conventional ICU prediction models improved the prognostication of patients with sepsis-associated AKI receiving intensive care and CKRT.
摘要：
确定脓毒症相关急性肾损伤(AKI)患者的危险因素并改善其死亡率预测，对于改善该患者人群的不良预后非常重要。本研究旨在比较现有全身性炎症生物标志物的预后价值，并确定接受CKRT的脓毒症相关AKI患者的最佳全身性炎症生物标志物。
■这个多中心，回顾性,观察性队列研究纳入1,500例脓毒症相关AKI患者,接受重症监护和CKRT治疗.主要预测因子是一组13种不同的全身性炎症生物标志物。主要结果是CKRT开始后28天的死亡率。次要结果包括开始CKRT后90天死亡率，CKRT持续时间,出院时依赖肾脏替代疗法，以及重症监护病房（ICU）和住院时间的长短。
■添加到广泛接受的急性生理学和慢性健康评估II评分中时，血小板与白蛋白比值(PAR)和中性粒细胞-血小板评分(NPS)对28天死亡率的预测改善最大,其中C统计量的相应增加为0.01(95%置信区间[CI]，0.00-0.02)和0.02(95%CI,0.01-0.03)。对于90天死亡率观察到类似的发现。对于较高的PAR和NPS四分位数，28天和90天的死亡率显着降低。即使在多变量Cox比例风险模型中调整了潜在的混杂变量后，这些关联仍然显着。
■在可用的全身性炎症生物标志物中，在常规ICU预测模型中增加PAR或NPS可改善接受重症监护和CKRT的脓毒症相关AKI患者的预后.
■这个多中心，回顾性,观察性队列研究纳入1,500例脓毒症相关AKI患者,接受重症监护和CKRT治疗.主要预测因子是一组13种不同的全身性炎症生物标志物。主要结果是CKRT开始后28天的死亡率。次要结果包括开始CKRT后90天死亡率，CKRT持续时间,出院时依赖肾脏替代疗法，以及重症监护病房（ICU）和住院时间的长短。
■添加到广泛接受的急性生理学和慢性健康评估II评分中时，血小板与白蛋白比值(PAR)和中性粒细胞-血小板评分(NPS)对28天死亡率的预测改善最大,其中C统计量的相应增加为0.01(95%置信区间[CI]，0.00-0.02)和0.02(95%CI,0.01-0.03)。对于90天死亡率观察到类似的发现。对于较高的PAR和NPS四分位数，28天和90天的死亡率显着降低。即使在多变量Cox比例风险模型中调整了潜在的混杂变量后，这些关联仍然显着。
■在可用的全身性炎症生物标志物中，在常规ICU预测模型中增加PAR或NPS可改善接受重症监护和CKRT的脓毒症相关AKI患者的预后.
