Predictors of Renal Replacement Therapy in Acute Kidney Injury

被引：3

作者：

Koziolek, Michael J. ^{[1
]}

Datta, Rabi R. ^{[1
]}

Mattes, Harry ^{[1
]}

Jung, Klaus ^{[2
]}

Heise, Daniel ^{[3
]}

Streich, Jan H. ^{[1
]}

Muehlhausen, Johannes ^{[1
]}

Mueller, Gerhard A. ^{[1
]}

Dihazi, Hassan ^{[1
]}

机构：

[1] Georg August Univ Gottingen, Dept Nephrol & Rheumatol, Robert Koch Str 40, DE-37075 Gottingen, Germany

[2] Georg August Univ Gottingen, Dept Med Stat, Gottingen, Germany

[3] Georg August Univ Gottingen, Dept Anaesthesiol, Gottingen, Germany

来源：

NEPHRON EXTRA | 2012年 / 2卷 / 01期

关键词：

Acute kidney injury; Dialysis; Logistic regression model; Renal failure; Renal replacement therapy;

D O I：

10.1159/000342257

中图分类号：

R5 [内科学]; R69 [泌尿科学（泌尿生殖系疾病）];

学科分类号：

1002 ; 100201 ;

摘要：

Backgrounds: Criteria that may guide early renal replacement therapy (RRT) initiation in patients with acute kidney injury (AKI) currently do not exist. Methods: In 120 consecutive patients with AKI, clinical and laboratory data were analyzed on admittance. The prognostic power of those parameters which were significantly different between the two groups was analyzed by receiver operator characteristic curves and by leave-1-out cross validation. Results: Six parameters (urine albumin, plasma creatinine, blood urea nitrogen, daily urine output, fluid balance and plasma sodium) were combined in a logistic regression model that estimates the probability that a particular patient will need RRT. Additionally, a second model without daily urine output was established. Both models yielded a higher accuracy (89 and 88% correct classification rate, respectively) than the best single parameter, cystatin C (correct classification rate 74%). Conclusions: The combined models may help to better predict the necessity of RRT using clinical and routine laboratory data in patients with AKI. Copyright (C) 2012 S. Karger AG, Basel.

引用

页码：247 / 255

页数：9

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