Abstract

Rhabdomyolysis is often encountered in austere environments where the diagnosis can be challenging due to the expense or unavailability of creatine phosphokinase (CPK) testing. CPK concentration ≥5,000 U/L has previously been found to be a sensitive marker for progression to renal failure. This study sought to propose a model utilizing an alternate biomarker to allow for the diagnosis and monitoring of clinically significant rhabdomyolysis in the absence of CPK. We performed a retrospective chart review of 77 patients admitted to a tertiary medical center with a primary diagnosis of rhabdomyolysis. A linear regression model with aspartate aminotransferase (AST) as the independent variable was developed and used to predict CPK ≥5,000 U/L on admission and CPK values on subsequent hospital days. The study was approved and monitored by the Institutional Review Board at Walter Reed National Military Medical Center. Ln(AST) explained over 80% of the variance in ln(CPK) (adjusted R2 = 0.802). The diagnostic accuracy to predict CPK ≥5,000 U/L was high (AUC 0.959; 95% CI: 0.921-0.997, P < 0.001). A cut point of AST ≥110 U/L in our study population had a 97.1% sensitivity and an 85.7% specificity for the detection of a CPK value ≥5,000 U/L. The agreement between actual CPK and predicted CPK for subsequent days of hospitalization was fair with an intraclass correlation coefficient of 0.52 (95% CI: 0.38-0.63). The developed model based on day 1 data tended to overpredict CPK values on subsequent hospital days. We propose a threshold concentration of AST that has an excellent sensitivity for detecting CPK concentration ≥5,000 U/L on day of admission in a patient population with a diagnosis of rhabdomyolysis. A formula with a fair ability to predict CPK levels based on AST concentrations on subsequent hospital days was also developed.

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