Chandel Abhimanyu, Brusher Kara, Hall Victoria, Howard Robin S, Clark Paul A
Department of Internal Medicine, Walter Reed National Military Medical Center, 8901 Rockville Pike, Bethesda, MD 20889.
F. Edward Herbert School of Medicine, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Rd, Bethesda, MD 20814.
Mil Med. 2019 Dec 1;184(11-12):820-825. doi: 10.1093/milmed/usz101.
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.
横纹肌溶解症在严峻环境中经常出现,由于肌酸磷酸激酶(CPK)检测费用高昂或无法进行检测,其诊断颇具挑战性。此前已发现CPK浓度≥5000 U/L是进展为肾衰竭的敏感标志物。本研究旨在提出一种利用替代生物标志物的模型,以便在没有CPK检测的情况下诊断和监测具有临床意义的横纹肌溶解症。
我们对一家三级医疗中心收治的77例初步诊断为横纹肌溶解症的患者进行了回顾性病历审查。建立了以天冬氨酸转氨酶(AST)为自变量的线性回归模型,并用于预测入院时CPK≥5000 U/L以及随后住院天数的CPK值。该研究得到了沃尔特里德国家军事医疗中心机构审查委员会的批准和监督。
Ln(AST)解释了Ln(CPK)中超过80%的方差(调整后R2 = 0.802)。预测CPK≥5000 U/L的诊断准确性较高(AUC 0.959;95% CI:0.921 - 0.997,P < 0.001)。在我们的研究人群中,AST≥110 U/L的切点对于检测CPK值≥5000 U/L的敏感性为97.1%,特异性为85.7%。住院后续天数实际CPK与预测CPK之间的一致性一般,组内相关系数为0.52(95% CI:0.38 - 0.63)。基于第1天数据建立的模型往往会高估后续住院天数的CPK值。
我们提出了一个AST阈值浓度,其对于诊断为横纹肌溶解症的患者群体入院当天检测CPK浓度≥5000 U/L具有出色的敏感性。还开发了一个基于后续住院天数AST浓度预测CPK水平能力一般的公式。