Bernstein L H, Qamar A, McPherson C, Zarich S, Rudolph R
Department of Pathology and Laboratory Medicine, Bridgeport Hospital, Connecticut 06610, USA.
Yale J Biol Med. 1999 Jan-Feb;72(1):5-13.
We examine the use of information theory applied to a single cardiac troponin T (cTnT) (first generation monoclonal; Boehringer Mannheim Corp., Indianapolis, Indiana) used with the character of chest pain, electrocardiography (ECG) and serial ECG changes in the evaluation of acute myocardial infarction (AMI). We combined a single measure of cTnT (blinded to the investigators) with a creatine kinase MB isoenzyme (CK-MB) measurement to discover the best decision value for this test in a study of 293 consecutive patients presenting to the emergency department with symptoms warranting exclusion of AMI.
The decision value for determining whether cTnT is positive or negative was determined independently of the final diagnosis by examining the information in the cTnT and CKMB data. Using information theory, an autocorrelation matrix with a one-to-one pairing of the CKMB and troponin T was constructed. The effective information, also known as Kullback entropy, assigned the values for troponin T and for CKMB that have the lowest frequency of misclassification error. The Kullback entropy is determined by subtracting the data entropy from the maximum entropy of the data set in which the information has been destroyed. The assignment of the optimum decision values was made independently of the clinical diagnoses without the construction of a receiver-operator characteristic curve (ROC). The final diagnosis of AMI was independently determined by the clinicians and entered into the medical record.
The decision value for cTnT was 0.1 ng/ml as determined by the the information in the data. The method was validated within the same study by mapping the results so obtained into the diagnoses obtained independently by the clinicians using all of the methods at their disposal. The cTnT was different in AMI (n = 60) compared with non-AMI patients (n = 233) (2.08 +/- 0.21 vs. 0.07 +/- 0.10; p < .0001).
Information theory provides a strong framework and methodology for determining the decision value for cTnT which minimizes misclassification errors at 0.1 ng/ml. The result has a strong correlation with other features in detecting AMI in patients presenting with chest pain.
我们研究了信息论在评估急性心肌梗死（AMI）时的应用，将其应用于单一的心肌肌钙蛋白T（cTnT）（第一代单克隆抗体；勃林格殷格翰公司，印第安纳波利斯，印第安纳州），并结合胸痛特征、心电图（ECG）及系列心电图变化进行分析。在一项对293例因症状需排除AMI而就诊于急诊科的连续患者的研究中，我们将单一的cTnT测量值（研究者不知情）与肌酸激酶MB同工酶（CK-MB）测量值相结合，以找出该检测的最佳判定值。
通过检查cTnT和CKMB数据中的信息，独立于最终诊断来确定cTnT呈阳性或阴性的判定值。利用信息论，构建了一个CKMB和肌钙蛋白T一一配对的自相关矩阵。有效信息，也称为库尔贝克熵，为肌钙蛋白T和CKMB赋予了错误分类频率最低的值。库尔贝克熵通过从信息已被破坏的数据集中的最大熵中减去数据熵来确定。最佳判定值的赋值独立于临床诊断，无需构建受试者操作特征曲线（ROC）。AMI的最终诊断由临床医生独立确定并记录在病历中。
根据数据中的信息，cTnT的判定值为0.1 ng/ml。通过将如此获得的结果映射到临床医生使用所有可用方法独立获得的诊断中，该方法在同一研究中得到了验证。与非AMI患者（n = 233）相比，AMI患者（n = 60）的cTnT不同（2.08 +/- 0.21 vs. 0.07 +/- 0.10；p <.0001）。
信息论为确定cTnT的判定值提供了一个强大的框架和方法，该判定值在0.1 ng/ml时可将错误分类误差降至最低。该结果与胸痛患者检测AMI的其他特征具有很强的相关性。
