肌钙蛋白T水平可确认或排除急性心梗

瑞士巴塞尔大学医院的Tobias Reichlin博士及其同事8月13日在《内科学文献》在线发表的一项前瞻性多中心研究结果显示，利用高敏感心肌肌钙蛋白T(hs-cTnT)基线水平及其绝对变化值，可简便快速确认和排除大多数胸痛急诊患者是否患有急性心肌梗死(AMI)(Arch. Intern. Med. 2012 Aug. 13 [doi: 10.1001/archinternmed.2012.3698])。

研究者称，基于对随机筛选的436例患者的分析而建立的这一方法，在436例APACE(急性冠脉综合症评估有益预测因素)研究受试者中得到了验证，可在1 h内可靠地排除或确认77%的胸痛患者是否为AMI。在验证队列中，该方法排除AMI的敏感性和阴性预测值均为100%，确诊AMI的特异性和阳性预测值分别为97%和84%。应用该方法可避免对3/4的胸痛患者进行长时间监测和系列血样采集。

APACE研究受试者为2006年4月~2009年6月因胸痛就诊的AMI疑似患者，分别在基线和1 h后测定心肌坏死高度特异生物标志物—血清hs-cTnT水平。结果显示，AMI患者基线hs-cTnT水平明显高于其他最终诊断患者， 不同hs-cTnT定量水平的急性胸痛患者AMI患病率差异显著。基线hs-cTnT水平<14 ng/L(健康个体第99百分位)的胸痛患者，其AMI患病率为3.2%，hs-cTnT水平介于14~49 ng/L、50~99 ng/L和100~199 ng/L胸痛患者的AMI发病率则分别升至21%、65%和88%，而hs-cTnT水平≥200 ng/L患者的发病率高达93%。AMI最佳排除阈值为基线hs-cTnT水平<12 ng/L，且第1小时绝对变化值<3 ng/L；最佳确诊阈值为基线hs-cTnT水平≥52 ng/L或第1小时绝对变化值≥5 ng/L。

259例AMI排除患者、76例确诊患者和101例不符合排除或确认标准的患者(被认为属于“观察区”)累计30天生存率分别为99.8%、95.3%和98.6%。研究者认为，AMI排除患者0.2%较低的30天死亡率“提示这些患者适合早期出院” 。

研究者指出， 该研究扩展并证实了有关hs-cTnT分析研究的最新结果，阐明了如何将这些分析方法用于日常临床实践决策，具有重大临床意义。鉴于AMI患者比例随hs-cTnT水平增高而增大，定量而非定性说明hs-cTnT水平非常重要，可避免笼统使用hs-cTnT阳性和阴性的说法。但鉴于受试者均为有症状的疑似AMI急诊患者(应在预测试概率的医院应用该方法)以及MI患者比例(17%)高于其他有关胸痛患者研究等潜在局限性，上述判断方法还需要在针对低风险队列的第二项多中心研究中加以证实和外部验证。

随刊述评：新计算方法迈出了重要一步

杜克临床研究所心脏病科的L. Kristin Newby博士指出，上述方法在hs-cTnT用于疑似MI急诊患者分诊方面取得了重要进展，随着该方法的进一步完善，将大幅提升对这类患者的评估水平，但尚需进一步提供可用于临床实践的证据。最为重要的是，上述方法需要在前瞻性研究中加以验证，除评估敏感性和阴性预测值、特异性和阳性预测值外，还应评估其对临床结局的影响，这还将有助于确认上述阈值是否适用于不同年龄段的患者，以及是否还应考虑性别和症状发作时间等因素。此外，如果将检测结果和判断结论加入患者电子病历中，将促进医生在患者分诊和治疗中全面应用(Arch. Intern. Med. 2012 Aug. 13 [doi: 10/1001/archinternmed.2012.1808])。

该研究由瑞士国家科学基金会、瑞士心脏病基金会、雅培、罗氏、西门子以及巴塞尔大学医院内科部基金资助。hs-cTnT试剂由罗氏提供。Reichlin博士和共同作者Christian Mueller博士均披露与雅培等多家公司和基金会存在经济利益，Newby博士也报告与安进、阿斯利康等公司以及国立心肺血液研究所存在利益关系。

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By: SHARON WORCESTER, Cardiology News Digital Network

A simple algorithm using baseline values and absolute changes in high-sensitivity cardiac troponin T allows for rapid rule-in and rule-out of acute myocardial infarction in most patients who present with chest pain, according to findings from a prospective, multicenter study.

The algorithm, which was developed in a randomly selected derivation cohort of 436 patients and validated in an additional 436 subjects from the APACE (Advantageous Predictors of Acute Coronary Syndrome Evaluation) study, safely ruled out and accurately ruled in acute myocardial infarction within 1 hour in 77% of patients with chest pain, Dr. Tobias Reichlin of University Hospital Basel (Switzerland) and his colleagues reported online Aug. 13 in Archives of Internal Medicine.

In the validation cohort, the algorithm had 100% sensitivity and negative predictive value for ruling out acute myocardial infarction, and 97% specificity and 84% positive predictive value for ruling in AMI, the investigators said (Arch. Intern. Med. 2012 Aug. 13 [doi: 10.1001/archinternmed.2012.3698]).

Use of the algorithm "may obviate the need for prolonged monitoring and serial blood sampling in 3 of 4 patients with chest pain," they noted.

APACE participants presented during April 2006-June 2009 with acute chest pain symptoms suggestive of AMI, and were tested at baseline and after 1 hour for serum levels of high-sensitivity cardiac troponin T (hs-cTnT), a highly specific biomarker of myocardial necrosis.

Baseline levels of hs-cTnT were significantly higher in patients with AMI, compared with patients having other final diagnoses, and the prevalence of AMI in those presenting with acute chest pain differed significantly based on quantitative levels of hs-cTnT.

"In patients with hs-cTnT levels lower than 14 ng/L (99th percentile of healthy individuals) at presentation, the incidence of AMI was 3.2%, and there was a rise to 21% in patients with levels between 14 and 49 ng/L, 65% in patients with levels between 50 and 99 ng/L, 88% in patients with levels between 100 and 199 ng/L, and 93% in patients with levels of 200 ng/L or higher," the investigators said.

The optimal rule-out threshold was determined to be a baseline hs-cTnT level lower than 12 ng/L, and an absolute change of less than 3 ng/L in the first hour; the optimal rule-in threshold for AMI was either a baseline hs-cTnT of 52 ng/L or higher at presentation, or an absolute change of 5 ng/L or higher in the first hour.

The cumulative 30-day survival rates among 259 patients in whom AMI was ruled out, 76 in whom AMI was ruled in, and 101 who did not meet criteria for rule-in or rule-out (those considered to be in an "observational zone") were 99.8%, 95.3%, and 98.6%, respectively.

The low 30-day mortality of 0.2% in patients ruled out for AMI "underscores the suitability of these patients for early discharge," the investigators wrote.

"Our findings extend and corroborate recent results regarding hs-cTnT assays and are of great clinical importance," they said, explaining that they provide some clarification about how to use the assays for decision making in daily clinical practice. Because the proportion of patients with AMI continuously increases with increasing hs-cTnT values, it is important to interpret levels as quantitative rather than qualitative, avoiding the terms positive and negative with respect to the levels.

Given the potential limitations of the study – including the fact that it was conducted in emergency department patients with symptoms suggestive of AMI (the pretest probability setting where the algorithm should be used), and the fact that the proportion of patients with MI (17%) was high compared with other chest pain studies – the algorithm requires confirmation and external validation in a second multicenter study in a lower-risk cohort, the investigators said.

This study was supported by research grants from the Swiss National Science Foundation, the Swiss Heart Foundation, Abbott, Roche, Siemens, and the department of internal medicine at University Hospital Basel. The hs-cTnT assay was donated by Roche. Dr. Reichlin and coauthor Dr. Christian Mueller each disclosed receiving speaker honoraria from Abbott, Biosite, and other companies. In addition, Dr. Reichlin disclosed receiving grant support from the Professor Max Cloetta Foundation, and Dr. Mueller reported receiving research support from the Novartis Foundation, the Krokus Foundation, Abbott, AstraZeneca, and other companies.

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Algorithmic Approach Provides Important Step Forward

The algorithmic approach to ruling in and ruling out AMI in patients presenting with chest pain as presented by Dr. Reichlin and his colleagues provides an important step forward in the application of high-sensitivity cardiac troponin as a tool for the triage of emergency department patients with possible MI, and could – with continued development – substantially improve the evaluation of such patients, Dr. L. Kristin Newby wrote in an accompanying editorial.

"However, much work remains to develop the evidence to bring hsTn testing and the algorithms they have developed to use in clinical practice," she wrote.

Most importantly, the algorithm requires validation in prospective studies that assess implications for clinical outcomes in addition to the sensitivity and negative predictive value, and specificity and positive predictive value, she noted.

Such studies will help confirm that the thresholds used in the current study are satisfactory across age groups, and help determine whether factors such as sex and time from symptom onset should also be considered.

"Finally, although touted as ‘simple’ by the authors, the need for multi-component algorithms that are different for rule-in and rule-out and that vary by age group or other parameters will challenge application by busy clinicians unlikely to remember or accurately process the proposed algorithm. As such, it will be imperative that hsTn algorithms, if validated, are built into clinical decision support layered onto electronic health records so that testing results are provided electronically to physicians along with the algorithmic interpretation to allow systematic application in triage and treatment," she wrote.

DR. NEWBY is with the division of cardiology at the Duke Clinical Research Institute in Durham, N.C. She reported receiving personal income from consulting or other service, and/or support from research grants or contracts from Amgen, AstraZeneca, and other companies, as well as the National Heart, Lung, and Blood Institute.