Inclusion Criteria and Assessment of Study Quality
We included studies in the analysis if, after a review of the full article, they met the following inclusion criteria:
- The study design was prospective data collection, consecutive or nonconsecutive patient enrollment (but not case-control), and the physician determining whether the patient had an AMI was blinded to the troponin results.
- The study population was of adult patients with acute chest pain.
- The WHO reference standard or similar criteria was used to diagnose AMI.
- The authors reported data for calculating sensitivity or specificity for at least one point from the onset of pain or presentation to the ED for troponin T or I.
The WHO criteria for diagnosing AMI require 2 of the following: clinical history, typical electrocardiogram changes, and an increase of CK and CK-MB activity. Case-series studies of only patients with AMI were included for the calculation of sensitivity. We further classified studies meeting these basic criteria as level I or II depending on whether the patient enrollment was clearly stated as consecutive (level I), or nonconsecutive or unspecified (level II).
Data Abstraction
Two independent investigators (either ME and DF or CF and DF) reviewed each article for study quality and inclusion criteria. We resolved any discrepancies by consensus decision. Two articles were in French or German, and only one investigator reviewed each of these. Neither study met inclusion criteria.
We abstracted the following data from each article: setting, variables required for evaluation of study quality, time from onset of chest pain or admission to the ED, and cutoff value(s) for abnormal levels of troponin T or I. If a range of 4 hours or less was reported for the time from onset of pain or the time from arrival at the ED, the mean time was used as a point estimate. Ranges of greater than 4 hours were discarded. For example, if a study reported the specificity for blood drawn between 4 and 6 hours after presentation to the ED, this range was recorded as a point estimate of 5 hours. We compared the data abstracted by each of the 2 reviewers, and all discrepancies were resolved by consensus decision. If it appeared that additional data might have been collected but not reported, we contacted the authors of the articles by postal or electronic mail.
Statistical Analysis
The primary outcomes were the test characteristics (sensitivity, specificity, predictive values, and positive and negative likelihood ratios) for each test at different points in time. Sensitivity is the proportion of patients with AMI who have an abnormal troponin test result, and specificity is the proportion without AMI who have a normal troponin test result. The positive and negative likelihood ratios are calculated using the following equations:
Positive likelihood ratio=sensitivity/(100-specificity)
Negative likelihood ratio=(100-sensitivity)/specificity
The positive and negative likelihood ratios correspond to the clinical concepts of ruling in and ruling out disease. Thus, a higher positive likelihood ratio means that a test result is better for ruling in disease when positive, and a lower negative likelihood ratio means that a test result is better for ruling out disease when negative. When possible, we made summary estimates of sensitivity and specificity using a DerSimonian and Laird random effects model. Sensitivity and specificity were pooled independently and weighted by the inverse of the variance using the MetaTest software (Joseph Lau, MD, New England Medical Center, Boston, Mass). If a fixed effects model (Mantel-Haenszel, chi-square) and a random effects model (DerSimonian and Laird) calculated similar estimates of sensitivity or specificity the studies were homogenous, and we reported the more conservative random effects model result. If the fixed effects model and random effects model gave estimates that were different in a clinically meaningful way, the studies were heterogeneous, and only a range was reported.
We drew summary receiver operating characteristic (ROC) curves, and calculated the weighted area under the curve by the method of Moses5 using the MetaTest software. The area under the ROC curve is a measure of the ability of a test to discriminate between healthy and diseased individuals, and it is equal to the proportion of patients correctly classified in a forced-choice comparison. Models for sensitivity and specificity versus hours from the onset of chest pain and models for sensitivity and specificity versus cutoff level were fitted using SPSS 9.0 software (SPSS, Chicago, Ill). The choice of linear or logarithmic model was based on inspection of the data.
Results
Eleven studies met level I criteria for quality,6-16 and an additional 8 met level II criteria.17-24 Study characteristics are summarized in Table 1. Most studies only reported data for the time from presentation to the ED, rather than the time from onset of chest pain.