scispace - formally typeset
Journal ArticleDOI

The value of serum creatine kinase in predicting the risk of rhabdomyolysis-induced acute kidney injury: a systematic review and meta-analysis

TLDR
The significant role of rhabdomyolysis etiology (traumatic/non-traumatic) in predictive performance of CK was declared and there was a significant correlation between mean CK level and risk of crush-induced AKI.
Abstract
Identifying the potential effective factors of rhabdomyolysis-induced acute kidney injury (AKI) is of major importance for both treatment and logistic concerns. The present study aimed to evaluate the value of creatine kinase (CK) in predicting the risk of rhabdomyolysis-induced AKI through meta-analysis. Two reviewers searched the electronic databases of Medline, EMBASE, Cochrane library, Scopus, and Google Scholar. Data regarding study design, patient characteristics, number of cases, mean and screening characteristics of CK, and final patient outcome were extracted from relevant studies. Pooled measures of standardized mean difference, OR, and diagnostic accuracy were calculated using STATA version 11.0. 5997 non-redundant studies were found (143 potentially relevant). 27 articles met the inclusion criteria but 9 were excluded due to lack of data. The correlation between serum CK and AKI occurrence was stronger in traumatic cases (SMD = 1.34, 95 % CI = 1.25–1.42, I 2 = 94 %; p < 0.001). This correlation was more prominent in crush-induced AKI (adjusted OR = 14.7, 95 % CI = 7.63–28.52, I 2 = 0.0 %; p = 0.001). Area under the ROC curve of CK in predicting AKI occurrence was 0.75 (95 % CI = 0.71–0.79). The results of this meta-analysis declared the significant role of rhabdomyolysis etiology (traumatic/non-traumatic) in predictive performance of CK. There was a significant correlation between mean CK level and risk of crush-induced AKI. The pooled OR of CK was considerable, but its screening performance characteristics were not desirable.

read more

Citations
More filters
Journal ArticleDOI

Non-traumatic rhabdomyolysis: Background, laboratory features, and acute clinical management.

TL;DR: The pathophysiological and clinical features of non-traumatic rhabdomyolysis, focusing specifically on Emergency Department (ED) management, are presented and discussed.
Journal ArticleDOI

Prevention of rhabdomyolysis-induced acute kidney injury - A DASAIM/DSIT clinical practice guideline

TL;DR: The available evidence onhabdomyolysis‐induced acute kidney injury is summarized and recommendations according to current standards for trustworthy guidelines are provided.
Journal ArticleDOI

Blood purification with a cytokine adsorber for the elimination of myoglobin in critically ill patients with severe rhabdomyolysis

TL;DR: In this article, the authors evaluated the effect of cytokine adsorber Cytosorb® (CS) on reducing myoglobin levels in patients with severe rhabdomyolysis.
References
More filters
Journal ArticleDOI

Systematic Review: Process of Forming Academic Service Partnerships to Reform Clinical Education

TL;DR: This study’s findings can provide practical guidelines to steer partnership programs within the academic and clinical bodies, with the aim of providing a collaborative partnership approach to clinical education.
Journal ArticleDOI

Bias in meta-analysis detected by a simple, graphical test

TL;DR: Funnel plots, plots of the trials' effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials.
Journal ArticleDOI

Meta-analysis of observational studies in epidemiology - A proposal for reporting

TL;DR: A checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion should improve the usefulness ofMeta-an analyses for authors, reviewers, editors, readers, and decision makers.
Journal ArticleDOI

Estimating the mean and variance from the median, range, and the size of a sample.

TL;DR: Two simple formulas are found that estimate the mean using the values of the median, low and high end of the range, and n (the sample size) and these hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported.
Related Papers (5)