Abstract
Background
For evaluation of patients with chest pain and suspected acute coronary syndrome (ACS), consensus guidelines recommend use of a cardiac troponin cut-point that corresponds to the 99th percentile of a healthy population. Most conventional troponin methods lack sufficient precision at this very low level.
Methods and results
In a cross-sectional study, 377 patients (mean age 53.7 years, 64.2% male) with chest pain and low-to-intermediate likelihood for ACS were enrolled in the emergency department. Blood was tested using a pre-commercial high sensitivity troponin T assay (hsTnT) and compared to a conventional cardiac troponin T method (cTnT). Patients underwent a 64-slice coronary computed tomography (CT) coronary angiogram at the time of phlebotomy, on average 4 hours from initial presentation. Among patients with acute chest pain, 37 (9.8%) had an ACS. Using the 99th percentile cut-point for a healthy population (13 pg/mL), hsTnT had 62% sensitivity, 89% specificity, 38% positive predictive value, and 96% negative predictive value for ACS. Compared to cTnT, hsTnT detected 27% more ACS cases (P =.001), and an hsTnT above the 99th percentile strongly predicted ACS (odds ratio 9.0, 95% confidence interval 3.9–20.9; P <.001). Independent of ACS diagnosis, CT angiography demonstrated concentrations of hsTnT were determined by numerous factors including the presence and severity of coronary artery disease as well as left ventricular mass, left ventricular ejection fraction, and regional left ventricular dysfunction.
Conclusions
Among low-to-intermediate risk patients with chest pain, hsTnT provides good sensitivity and specificity for ACS. Elevation of hsTnT identifies patients with myocardial injury and significant structural heart disease, irrespective of the diagnosis of ACS.
Keywords: myocardial infarction, troponin, diagnosis, imaging
Since the advent of testing for cardiac troponins for the diagnosis of myocardial infarction (MI), the use of these assays continues to evolve. Over the past two decades, troponins have been adopted as the preferred biomarker for the diagnosis of acute MI, a position reaffirmed in recent consensus guidelines1, 2. As part of this consensus for the preferred use of troponins for the diagnostic evaluation of the patient with suspected or proven acute coronary syndrome (ACS), the use of a troponin cut-point for acute MI that equals the 99th percentile of a healthy population has been endorsed, as long as the assay used delivers acceptable precision at this very low threshold, as risk for adverse outcome (including death) has been repeatedly demonstrated in the context of values above this level 3–10. However, most commercial assays for troponin were inadequate to deliver such performance, due either to a limit of detection above that of reference populations, or to unacceptable imprecision (by consensus, more than 10% variation from test to test) at very low concentrations11.
Recently, however, newer assays for troponin have been developed, which, through multiple methodologic modifications, are now able to detect changes in concentration of the marker at or below the 99th percentile for a normal population. While these “high sensitivity” troponin assays may now achieve consensus guideline recommended precision of <10% imprecision at this low reference limit1, 2, a degree of uncertainty regarding their clinical application exists however, particularly with respect to the specificity of these tests for the clinical syndrome of acute MI, as they are able to detect even minor degrees of myocardial injury, even in the absence of ACS. Indeed, despite consensus for their adoption for clinical use, only preliminary data exist supporting the use of “high sensitivity” troponin assays in populations of patients with chest pain and suspected ACS3, 4, 12, 13. Furthermore, the anatomical causes of elevation of “high sensitivity” troponin or the clinical ramification of an elevated level of such markers in a patient without an ACS remains undefined.
With these issues in mind, among a group of patients presenting with chest discomfort and suspected ACS, we examined the diagnostic performance of a new pre-clinical “high sensitivity” test for troponin T (hsTnT) using the 99th percentile cut-point for this assay, and correlated hsTnT results both with clinical syndrome, as well as cardiac structure and function as demonstrated by 64-slice computed tomography (CT) angiography at the time of blood measurement.
Methods
All study methods were approved by the local Institutional Review Board.
Patient population
A description of the patient population in this study was recently reported14. In brief, between May of 2005 and May of 2007, a convenience sample of 377 low to intermediate risk subjects presenting to the Massachusetts General Hospital emergency department between the weekday hours of 7 AM and 7 PM with a chief complaint of chest discomfort and clinical suspicion for ACS were enrolled; detailed inclusion/exclusion criteria are provided in Supplemental Table 1. Following enrollment, patients were followed for 6 months for clinical course, and endpoints were ascertained. A final diagnosis of ACS (including either acute MI or unstable angina) was retrospectively made, and based on the judgment of two physicians with access to the history and nature of the presenting symptoms, past medical history, results of physical examination, and all medical records available from index hospitalization (including the results of standard troponin testing) through 180 days from presentation. Events subsequent to 180 days from enrollment did not influence the final diagnosis. Disagreement in final diagnosis occurred in 4% of cases, and was resolved by consensus, using a third reviewer15. For the purposes of this analysis, patients were categorized as having unstable angina using a cTnT value of <.03 ng/mL measured at any time during hospitalization, as per consensus guidelines2.
Cardiac biomarker testing
A sample of blood for biomarker testing (hsTnT and cTnT) was taken at the time of CT angiography, at a median of 4.2 hours from initial presentation. Blood was immediately processed and frozen at −80° C, until it was assayed with a pre-commercial hsTnT method (Roche Diagnostics, Penzberg, Germany) on an Elecsys® 2010 platform. Given enhanced sensitivity, this assay is reported with units of pg/mL (rather than ng/mL for conventional troponin T, cTnT) and is reported to have a coefficient of variation of 8% at 10 pg/mL16; the 99th percentile for a normal reference population is reported to be 13 pg/mL17, which was the cut-point used for this analysis. For the present analysis, hsTnT had an inter-run coefficient of variation of 3.6% and 2.9% at concentrations of 42 and 2820 pg/mL.
In addition to hsTnT, conventional cTnT (Stat T, Roche Diagnostics, Penzberg, Germany) was measured using a 4th generation immunoassay on an Elecsys® 2010 platform. This assay is reported in ng/mL, has a 99th percentile of 0.01 ng/mL and recommended diagnostic threshold for acute MI of 0.03 ng/mL. For the present analysis, cTnT had an inter-run coefficient of variation of 6.6% and 3.8% at concentrations of 0.07 and 2.2 ng/mL. Lastly, amino-terminal pro-B type natriuretic peptide (NT-proBNP; Roche Diagnostics, Penzberg, Germany), and Cystatin C (cys-C; Siemens Diagnostics, Eschborn, Germany) were also measured. All blood was tested on the first freeze thaw cycle.
CT Angiography
Cardiac CT imaging and interpretation was performed using a 64-slice scanner (Sensation 64, Siemens Medical Solutions, Forcheim, Germany) as previously described14.
Interpretation of the CT angiogram included assessment for presence and extent of coronary artery disease (CAD) according to the American Heart Association 17-segment coronary artery model; the number of segments affected by atherosclerotic plaque was noted, and plaque was further coded as calcified or non-calcified. The presence of significant coronary stenosis was defined as a luminal obstruction of >50% of the diameter of the reference coronary segment. In addition cardiac structure and function was assessed, including measures of chamber volume in end-systole and end-diastole, left ventricular ejection fraction, left ventricular mass, and regional left ventricular dysfunction.
Statistical Methods
Baseline demographics of patients with and without ACS were compared using the χ2 test for dichotomous variables, and the student’s T-test or the Wilcoxon Rank Sum test for continuous variables, as appropriate. For comparisons of concentrations of hsTnT between multiple diagnostic groups (no ACS, unstable angina, and acute MI), the Kruskal-Wallis test was used.
The diagnostic performance of the hsTnT assay was assessed using receiver operator characteristic (ROC) curves, with area under the curve (AUC) estimated as a function of the gold standard diagnosis of ACS (including both unstable angina and acute MI); curves for hsTnT versus cTnT were compared for significant differences; net reclassification improvement (NRI) and integrated discrimation improvement (IDI) were performed as described by Pencina et al 18. The optimal cut-point for hsTnT was identified in the ROC curve using the value providing maximal sensitivity and specificity. Further, sensitivity and specificity, as well as positive and negative predictive value (PPV and NPV; all with 95 % confidence intervals, CI) for unstable angina, acute MI, or all ACS using an hsTnT of 13 pg/mL (the 99th percentile cut-point) was evaluated, and compared to a cTnT of 0.01 ng/mL (the 99th percentile, and limit of detection for this method) and 0.03 ng/mL (the lowest cTnT cut-point delivering <10% imprecision). The sensitivity and specificity for ACS from an hsTnT ≥13 pg/mL was compared to that of a cTnT ≥0.03 ng/mL using the McNemar test.
To better understand the association between hsTnT and ACS diagnosis, logistic regression analyses was performed examining the final gold standard diagnosis as a function of hsTnT tertiles; two models were used in this analysis, the first adjusted for age and sex, the second fully-adjusted for age, sex, hypertension, hyperlipidemia, diabetes mellitus, and prior CAD. In both models, the first tertile served as referent, with odds ratios (OR) and 95% CIs generated for the second and third tertile. Furthermore, using a hsTnT cut-off of 13 pg/mL, OR and 95% CI for a final diagnosis of ACS was generated in a similar fashion with models including age and sex as well as the fully-adjusted model described above.
In an effort to better understand the meaning of hsTnT concentrations (especially with respect to the presence and extent of CAD as well as ventricular structure and function), continuous variables and log-transformed concentrations of hsTnT were correlated using Spearman analysis; following, independent predictors of hsTnT concentrations were identified using multivariable linear regression including candidate variables with a P ≤.10 in univariable analysis. Only those variables with a P value <.05 were retained in the final model. In addition, associations between hsTnT above and below the 99th percentile in those without ACS were examined. Finally, linear regression analysis was then repeated, constrained to only those patients without ACS and an hsTnT above 13 pg/mL.
All statistical analyses were performed using SAS software (Version 9.2, Cary, NC, USA). All P values are two-sided, with a value <.05 considered significant.
Results
Baseline Characteristics
The mean (± standard deviation; SD) age of the study population overall was 53.7 ± 12.0 years; 242 (64.1%) were male. Of the overall study population, 37 (9.8%) were judged to have ACS, of whom 25 had unstable angina using standard criteria. Baseline characteristics of study subjects as a function of ACS, including CT angiogram results are detailed in table 1.
Table 1.
Characteristics of study population categorized as a function of ACS.
| Characteristic | ACS | No ACS | P* | ||
|---|---|---|---|---|---|
| All (N=37) | MI (N=8) | UAP (N=29) | All (N=340) | ||
| Age | 61 (±12) | 55 (±10) | 63 (±12) | 53 (±12) | <.001 |
| Male sex | 30 (81%) | 8 (100%) | 22 (78%) | 212 (62%) | .02 |
| Past medical history | |||||
| Diabetes mellitus | 9 (24%) | 0 (0%) | 9 (31%) | 37 (11%) | .02 |
| Hypertension | 25 (67%) | 4 (50%) | 21 (72%) | 134 (39%) | .001 |
| Hyperlipidemia | 24 (65%) | 3 (38%) | 21 (72%) | 132 (39%) | .002 |
| Family history of CAD | 10 (27%) | 3 (38%) | 7 (24%) | 83 (24%) | .73 |
| Personal history of CAD | 12 (32%) | 1 (13%) | 11 (38%) | 35 (10%) | <.001 |
| Prior myocardial infarction | 9 (24%) | 1 (13%) | 8 (28%) | 26 (8%) | <.001 |
| Tobacco use | 14 (38%) | 4 (50%) | 10 (34%) | 172 (51%) | .14 |
| Medications at presentation | |||||
| Aspirin | 21 (57%) | 2 (25%) | 19 (66%) | 116 (34%) | .006 |
| Statin | 21 (57%) | 2 (25%) | 18 (62%) | 101 (30%) | <.001 |
| Nitroglycerine | 4 (11%) | 0 (0%) | 4 (14%) | 19 (6%) | .21 |
| β blocker | 18 (49%) | 2 (25%) | 16 (55%) | 81 (24%) | .001 |
| Vital signs | |||||
| Systolic blood pressure, mmHg | 136 (±22) | 138 (±18) | 135 (±23) | 139.6 (±23) | .48 |
| Diastolic blood pressure, mmHg | 73 (±13) | 83 (±6) | 71 (±14) | 80.4 (±13) | .002 |
| Heart rate, beats/minute | 63 (±8) | 61 (±11) | 63 (±7) | 66 (±9) | .04 |
| Body-mass index, Kg/m2 | 29 (±5) | 28 (±6) | 29 (±4) | 29 (±6) | .80 |
| Coronary CT angiography | |||||
| Segments with calcified plaque | 6.6 (±3.5) | 5.8 (±4.0) | 6.8 (±3.5) | 1.7 (±3.0) | <.001 |
| Segments with non-calcified plaque | 3.8 (±3.0) | 4.0 (±2.7) | 3.7 (±3.3) | 0.9 (±1.8) | <.001 |
| Segments with mixed plaque | 2.8 (±2.7) | 3.4 (±2.4) | 2.7 (±2.8) | 0.6 (±1.5) | <.001 |
| Segments with any plaque | 7.5 (±3.5) | 6.4 (±4.0) | 7.8 (±3.4) | 2 (±3.0) | <.001 |
| Segments with significant stenosis | 1.4 (±1.4) | 1.3 (±1.7) | 1.4 (±1.5) | 0.1 (±0.4) | <.001 |
| Vessels with any plaque | 3.0 (±1.0) | 2.8 (±1.1) | 3.1 (±1.0) | 1.0 (±1.3) | <.001 |
| Vessels with significant stenosis | 0.9 (±0.9) | 1.0 (±0.9) | 0.9 (±1.0) | 0.06 (±0.3) | <.001 |
| Cardiac chamber size and function | |||||
| Left atrial diastolic volume, mL | 109 (±31) | 99 (±31) | 111 (±31) | 96 (±26) | .006 |
| Left atrial systolic volume, mL | 69 (±30) | 63 (±27) | 71 (±31) | 57 (±20) | <.001 |
| LV end diastolic volume, mL | 126 (±37) | 133 (±40) | 124 (±37) | 118 (±32) | .17 |
| LV end systolic volume, mL | 48 (±31) | 51 (±26) | 47 (±32) | 39 (±20) | .02 |
| LV mass | 161 (±40) | 161 (±25) | 161 (±43) | 151 (±42) | .16 |
| LV ejection fraction, % | 64 (±13) | 63 (±9) | 64 (±14) | 68 (±9) | .04 |
| Regional LV dysfunction | 27 (73%) | 8 (100%) | 19 (66%) | 32 (10%) | <.001 |
| Biomarkers besides TnT | |||||
| NT-proBNP, pg/mL, median (IQR) | 115 (53–426) | 81 (60–143) | 145 (53–482) | 47 (24–111) | .19 |
| Cystatin-C, mg/L, median (IQR) | 0.90 (0.81–0.97) | 0.83 (0.73–0.87) | 0.93 (0.84–0.99) | 0.82 (0.73–0.93) | .35 |
Continuous variables are expressed as mean ± standard deviation unless otherwise specified.
p-value for the difference comparing patients with and without ACS. ACS denotes: acute coronary syndrome; MI denotes: myocardial infarction; UAP debnotes: unstable angina pectoris; CAD denotes: coronary artery disease; LV denotes: left ventricular; NT-proBNP denotes: amino-terminal pro-B type natriuretic peptide; IQR denotes: interquartile range.
Troponin Results
The median hsTnT value for the group as a whole was 5.4 pg/mL (interquartile range [IQR] = 2.7–9.0]. Overall, 62 (16.4%) had an hsTnT ≥13 pg/mL. Median concentrations of hsTnT were significantly higher among those patients judged to have an ACS, compared to those without (28.0 [interquartile range, IQR = 8.6–68.7] versus 7.0 [IQR = 2.5–8.1] pg/mL; P >.001). When categorized as acute MI, unstable angina, and non-cardiac chest pain, median concentration of hsTnT were highest in those with acute MI (112.0 [IQR = 60.7–211.5] pg/mL), intermediate in those with unstable angina (12.3 [IQR = 4.9–31.9] pg/mL), and lowest in those without ACS (7.0 [IQR = 2.7–9.0] pg/mL; P <.001 for trend across groups).
ROC testing demonstrated an AUC for the diagnosis of ACS of 0.79 for hsTnT, compared to 0.74 for cTnT (P =.28). The NRI from adding hsTnT to cTnT was 0.74 (95% CI=0.49–0.99; P <.001), while the IDI was 0.24 (95% CI = 0.14–0.33; P<.001). The probability of correctly identifying ACS when adding hsTnT to cTnT improved from 18.7% to 40.7% (probability change for events = 22.0%). The probability of nonevents from adding hsTnT to cTnT changed from 8.6% to 6.6% (probability change for nonevents is −2.0%); the relative IDI overall was 2.37, which translates to a 237% improvement by adding hsTnT to cTnT.
Compared to the cTnT cut-point of 0.03 ng/mL, an hsTnT ≥13 pg/mL had statistically superior sensitivity (Table 2; P =.002), detecting nearly 50% more cases of ACS (23 of 37 cases, versus 12 of 37 cases); this relates to the identification of patients judged to have unstable angina (by definition, with a conventional cTnT <0.03 ng/mL) using hsTnT. On the other hand, although an hsTnT had excellent specificity for ACS (89%), it was significantly less specific than cTnT (Table 2; P <.001). The PPV and NPV of an hsTnT of 13 pg/mL were 38% and 96% respectively. The ROC-optimal cut-point for hsTnT was 8.62 pg/mL, which delivered 76% sensitivity, 78% specificity and 27% PPV for ACS.
Table 2.
Results of troponin testing for diagnosis of ACS.
| Analyte, cut-point | Sensitivity (95% CI) | Specificity (95% CI) | PPV (95% CI) | NPV (95% CI) |
|---|---|---|---|---|
|
Diagnostic accuracy for acute coronary syndrome in all patients (AUChsTNT: 0.79) | ||||
| hsTnT, 13 pg/mL | 62% (47–78)* | 89% (85–92) | 38% (26–50) | 96% (93–98) |
| cTnT, 0.01 ng/mL | 49% (33–65) | 97% (96–99)† | 67% (49–84) | 95% (92–97) |
| cTnT, 0.03 ng/mL | 35% (20–50) | 99% (96–99)† | 72% (52–93) | 93% (90–95) |
|
Diagnostic accuracy for myocardial infarction in all patients (AUChsTNT: 0.86) | ||||
| hsTnT, 13 pg/mL | 88% (47–100) | 85% (81–89) | 11% (5–22) | 100% (98–100) |
| cTnT, 0.01 ng/mL | 88% (47–100) | 94% (92–97)† | 26% (11–46) | 100% (98–100) |
| cTnT, 0.03 ng/mL | 88% (47–100) | 97% (95–98)† | 39% (17–46) | 100% (98–100) |
|
Diagnostic accuracy for unstable angina pectoris in patients without myocardial infarction (AUChsTNT: 0.72) | ||||
| hsTnT, 13 pg/mL | 55% (37–74)* | 89% (85–92) | 30% (18–44) | 96% (93–98) |
| cTnT, 0.01 ng/mL | 38% (21–58) | 97% (95–99)† | 55% (32–77) | 95% (92–97) |
| cTnT, 0.03 ng/mL | 21% (8–40) | 99% (97–100)† | 55% (23–83) | 94% (90–96) |
P<.001 versus cTnT;
P<.001 versus hsTnT
Considering hsTnT tertiles, a graded association with ACS was found; compared to the first tertile (referent), in age and sex adjusted models, the second (OR 2.6; 95% CI 1.4–4.6; P =.002 ) and third tertiles (OR 5.1, 95% CI=2.2–11.9; P <.001) had higher likelihood for ACS. A similar pattern was observed in fully adjusted models (Tertile 2: OR 2.4, 95% CI = 1.3–4.3; P =.005; Tertile 3: OR 4.7, 95% CI = 2.0–11.2; P <.001).
Considering hsTnT as a function of the 99th percentile cut-point of 13 pg/mL and using a final diagnosis of ACS as the dependent variable, a similar independent association with ACS was noted in both models (age and sex adjusted: OR=9.3, 95% CI=4.2–20.5, P <.001; fully adjusted: OR 9.0, 95% CI = 3.9–20.9, P <.001).
Correlations and Predictors of hsTnT in Patients with Chest Pain
All Subjects
Table 3 details predictors of log-transformed hsTnT in all subjects. In multivariable analyses, independent predictors of hsTnT included age, presence/extent of CAD, cardiac structure, cardiac function, and NT-proBNP values.
Table 3.
Univariable and multivariable predictors of log-transformed hsTnT concentrations.
| Univariable | Multivariable | |||
|---|---|---|---|---|
| Characteristic | Spearman correlation |
P | β | P |
| Age | 0.29 | <.001 | 0.019 | .005 |
| Physical examination | ||||
| Body-mass index, Kg/m2 | 0.05 | .30 | - | - |
| Systolic blood pressure, mm Hg | 0.09 | .07 | - | - |
| Diastolic blood pressure, mm Hg | − 0.075 | .14 | - | - |
| Heart rate, beats/minute | −0.09 | .08 | - | - |
| Coronary CT angiography | ||||
| Segments with calcified plaque | 0.31 | <.001 | - | - |
| Segments with non-calcified plaque | 0.25 | <.001 | - | - |
| Segments with mixed plaque | 0.25 | <.001 | - | - |
| Segments with any plaque | 0.32 | <.001 | - | - |
| Segments with significant stenosis | 0.20 | .005 | − 0.324 | .03 |
| Vessels with significant stenosis | 0.22 | <.001 | 0.634 | .004 |
| Vessels with plaque | 0.30 | <.001 | - | - |
| Cardiac chamber size and function | ||||
| Left atrial diastolic volume | 0.20 | .001 | - | - |
| Left atrial systolic volume | 0.20 | .001 | - | - |
| Left ventricular end diastolic volume | 0.13 | .01 | − 0.012 | .06 |
| Left ventricular end systolic volume | 0.16 | .003 | 0.028 | .06 |
| Left ventricular mass | 0.30 | <.001 | 0.008 | <.001 |
| Left ventricular ejection fraction | −0.06 | .24 | 0.042 | .04 |
| Regional left ventricular dysfunction | - | - | 0.669 | <.001 |
| Biomarkers besides Troponin T | ||||
| NT-proBNP | 0.26 | <.001 | 0.001 | .009 |
| Cystatin-C | 0.13 | .009 | - | - |
NT-proBNP denotes: amino-terminal pro-B type natriuretic peptide.
Subjects With Elevated hsTnT but Without ACS
Considering only those patients with an hsTnT above 13 pg/mL (N=61), 38 (62%) did not have an ACS. Compared to those patients without ACS and with negative hsTnT, patients with an elevated value were more likely to have more complex medical histories (including prior CAD), as well as more cardiac abnormalities, with more prevalent and extensive CAD as well as larger cardiac chamber sizes and greater left ventricular mass (Table 4).
Table 4.
Comparison of patients without ACS as a function of hsTnT result.
| No ACS | |||
|---|---|---|---|
| Characteristic | hsTnT ≥13 pg/mL (N=38) |
hsTnT <13 pg/mL (N=302) |
P |
| Age | 61.5 (±14.0) | 52 (±11.0) | <.001 |
| Male sex | 26 (68%) | 186 (62%) | .40 |
| Past medical history | |||
| Diabetes mellitus | 10 (26%) | 27 (9%) | .001 |
| Hypertension | 21 (55%) | 113 (37%) | .03 |
| Hyperlipidemia | 21 (55%) | 111 (37%) | .03 |
| Family history of coronary artery disease | 10 (26%) | 73 (24%) | .80 |
| Personal history of coronary artery disease | 10 (26%) | 25 (8%) | <.001 |
| Prior myocardial infarction | 7 (18%) | 19 (6%) | .008 |
| Tobacco use | 15 (39%) | 157 (52%) | .10 |
| Medications at presentation | |||
| Aspirin | 17 (45%) | 99 (33%) | .10 |
| Statin | 17 (45%) | 84 (28%) | .03 |
| Nitroglycerine | 5 (13%) | 14 (5%) | .03 |
| β blocker | 16 (42%) | 65 (21%) | .005 |
| Vital signs | |||
| Systolic blood pressure, mm Hg | 137 (±23.0) | 139 (±23.0) | .60 |
| Diastolic blood pressure, mm Hg | 77 (±18.0) | 81 (±13.0) | .20 |
| Heart rate, beats/minute | 65 (±7.0) | 67 (±10.0) | .30 |
| Body-mass index, Kg/m2 | 29 (±6.0) | 29 (±6.0) | .40 |
| Coronary CT angiography | |||
| Segments with calcified plaque | 4.4 (±4.0) | 1.5 (±3.0) | <.001 |
| Segments with non-calcified plaque | 1.8 (±3.0) | 0.8 (±2.0) | .05 |
| Segments with mixed plaque | 1.4 (±2.5) | 0.5 (±1.4) | .04 |
| Segments with plaque | 4.8 (±5.0) | 1.7 (±3.0) | .001 |
| Segments with significant stenosis | 0.4 (±1.0) | 0.06 (±0.3) | .04 |
| Vessels with significant stenosis | 0.2 (±0.5) | 0.05 (±0.3) | .09 |
| Vessels with plaque | 2 (±1.8) | 0.9 (±1.3) | .001 |
| Cardiac chamber size and function | |||
| Left atrial diastolic volume, mL | 107 (±33.0) | 95 (±24.0) | .02 |
| Left atrial systolic volume, mL | 69 (±31.0) | 55 (17.0) | .01 |
| Left ventricular end diastolic volume, mL | 122 (±45.0) | 117 (±30.0) | .50 |
| Left ventricular end systolic volume, mL | 48 (±41.0) | 38 (±16.0) | .20 |
| Left ventricular mass | 173 (±60.0) | 147 (±39.0) | .01 |
| Left ventricular ejection fraction, % | 65 (±14.0) | 68 (±9.0) | .30 |
| Regional left ventricular dysfunction | 8 (22%) | 24 (8%) | .008 |
| Biomarkers besides Troponin T | |||
| NT-proBNP, pg/mL, median (interquartile range) | 248 (92–492) | 42 (23–86) | <.001 |
| Cystatin-C, mg/L, median (interquartile range) | 0.93 (0.75–1.07) | 0.82 (0.73–0.92) | .05 |
Continuous variables are expressed as mean ± standard deviation unless otherwise specified. hsTnT denotes: high sensitivity troponin T; NT-proBNP denotes: amino-terminal pro-B type natriuretic peptide.
In patients without ACS, stepwise selection of significant variables identified age (β coefficient = 0.0399; P <.001), left ventricular mass (β coefficient = 0.0117; P <.001), and NT-proBNP (β coefficient = 0.00110; P = .03) as predictors of hsTnT values.
Discussion
The decision to adopt the 99th percentile of troponin from a normal population for the evaluation of patients with suspected ACS was based primarily on the enhanced risk stratification associated with such lower cut-points3–10. Furthermore, use of the 99th percentile for troponin appears to be associated with more robust prediction of benefit from early-invasive strategies for ACS management, when compared to higher cut-points8, 10. Complicating the situation was the fact that until recently, troponin methods were unable to deliver the requisite analytical performance at the 99th percentile11, an extremely low cut-point in a range that is in the range of analytical “noise” for most conventional assays. Furthermore, these assays are well-recognized to be able to detect myocardial injury in the absence of a clinical ACS, such as in heart failure16. Indeed, the diagnostic ramification of a troponin result above the 99th percentile—reflective of significant myocardial injury—in those without a clinically manifest ACS requires further definition.
We have shown, in a population of low-to-intermediate risk patients with chest discomfort, that hsTnT was able more sensitively detect ACS than a corresponding conventional cTnT method, and the hsTnT assay delivered excellent specificity as well. Furthermore, as each patient underwent concomitant cardiac CT (including angiography of the coronary arteries), we were able to show that myocardial injury (reflected by concentrations of hsTnT)—independent of the presence or absence of ACS—was associated with the presence and severity of a wide range of cardiac abnormalities, including more prevalent CAD and greater left ventricular mass. Importantly, such associations were present in those without ACS, which illustrates the importance of considering hsTnT values not only as a marker of ACS presence, but also as a marker of underlying structural heart disease.
Recent data have been published demonstrating the augmented sensitivity of hsTn methods for acute MI (and ACS overall)3, 4, 12, 13. In each of these analyses, a hsTn method consistently demonstrated augmented sensitivity compared to conventional assays for these analytes, much as we found in our analysis, in which nearly 50% more cases of ACS were diagnosed at the time of sampling. These results are consistent with data suggesting use of the 99th troponin percentile provides earlier recognition of myocardial injury19–23, with a significant percentage of patients reclassified from unstable angina to acute MI. Although superior to cTnT for diagnosis, it is necessary to note that hsTnT was not universally elevated in those judged to have ACS, suggesting that even with enhanced sensitivity, many patients with unstable angina or transient myocardial ischemia may still have troponin results below the 99th percentile for a normal population17.
As a counter observation to increased sensitivity, we did see a 10% reduction in specificity for ACS compared to conventional cTnT, reminiscent of other reports3, 4, 12, 13. This is not surprising, as the “gold standard” for acute MI diagnosis used all studies was a conventional cTn method, which partially explains the superior specificity of conventional assays; on the other hand, the specificity for ACS of 89% observed with hsTnT is excellent, and is expected to be accompanied by enhanced risk stratification, as suggested by other studies examining the advantages conferred by use of the 99th percentile for cTn interpretation 3–10.
More to this point, looking beyond the specificity or PPV of hsTnT for “acute MI” (and in comparisons to other studies of its kind), a strength of our study is the mechanistic association between hsTnT and prevalent cardiovascular disease as detected by universal CT angiography in our study subjects. This finding was present not only in subjects with an ACS, but also in those without. Our data suggest that an elevated “high sensitivity” troponin result reflects myocardial injury—irrespective of an ACS—and thus reflects a true signal for structural heart disease, even in the absence of an acute cardiac event. This mechanistically explains their proven ability to prognosticate adverse outcomes across the wide spectrum of patients evaluated with these assays, from “apparently well” subjects24, to those with chronic CAD6, ACS9, 10, and heart failure16.
It remains yet unclear whether myocardial ischemia in the absence of necrosis can be detected using hsTnT or hsTnI. Although a small amount of cTn is found in the cytosol of myocytes, and could theoretically be released without frank myocyte death, such a phenomenon remains yet unproven. In this setting, however, it is quite probable that hsTn methods will be superior to conventional troponin methods for detection of such a process. Indeed, in a model of exercise stress testing, hsTnI elevation was detected in parallel with the presence and severity of ischemia25. Whether this is proof of concept that ischemia—without necrosis—may lead to elevated hsTn is speculative, without histologic evidence to corroborate.
Our results indicate that clinicians should recognize that elevation of either hsTnT or hsTnI likely identifies a patient with significant heart disease, at higher risk for adverse outcome, irrespective of the presence or absence of ACS. Given the ability of these assays to detect myocardial injury above and beyond any other methods currently available, more than ever, we emphasize the crucial need to consider each patient as a function not only of their troponin value but also with respect to their clinical presentation, in order to avoid over-diagnosis of “acute MI” with these highly-sensitive assays. Indeed, hsTn methods should be considered very accurate tests for myocardial injury, rather than a test for “acute MI”, and only in the correct context should a positive result for these assays be interpreted as consistent with ACS. The growing use of hsTn methods will require a rethinking of the current guidelines for ACS management, as well as how exactly to manage the patient with an unexpectedly elevated hsTn value. Ultimately, the correct interpretation of hsTn methods should be based on Bayesian considerations, integrating pre-test likelihood with post-test result, and the recognition that higher hsTn values are more likely to reflect higher risk myocardial injury states, such as acute MI.
Our study has limitations worthy of comment. First, the cohort studied was small, yet the demographics and overall rate of ACS is comparable to “real world” analyses of patients presenting to the emergency department with chest discomfort26. In addition, given the low-to-intermediate risk nature of our population, a low 6-month event rate subsequent to presentation was observed, which limits our ability to examine the prognostic value of hsTnT versus cTnT. With respect to comparative performance of hsTnT relative to cTnT, similar data have recently been published by Reichlin and colleagues describing a cohort of 786 subjects with a much higher rate of ACS (33% overall)13; despite the overall higher risk of the study subjects in this latter analysis, the performance of hsTnT for ACS diagnosis in our study was quite similar. Moreover, although smaller than the Reichlin study (or a similar analysis of hsTnI by Keller and colleagues12), our study is set apart by the morphological correlation of hsTnT results with cardiac structure and function using cardiac CT. This aspect of our study adds a depth of understanding to the results of hsTnT above and beyond clinical analyses of ACS etiology. Indeed, mechanistic understanding of the predictors of hsTn release is crucially important. Another issue is the timing of the blood draw: the blood samples assayed for hsTnT and cTnT were drawn contemporaneously with the CT scan, yet they were obtained some 4 hours after presentation. Whether an earlier sample for hsTnT would have been less sensitive for diagnosis is possible, particularly if within the first hour of ischemia. Additionally, we only have one measurement of hsTnT; serial measures would have provided more data regarding the performance of hsTnT versus cTnT, and would have allowed for a better assessment of the ramifications of an elevated hsTnT in the absence of ACS. Indeed, serial measurement of hsTnT or I has been advocated3, 5, 20, to detect a change in troponin concentration (rising or falling), which would more likely represent an ischemic syndrome. Lastly, our subjects were low-to-intermediate risk, thus our results may not necessarily apply to such medically complex or unstable patients. Nonetheless, our data are applicable to a large population of patients26 where troponin assays are particularly important, given their lack of significant electrocardiographic changes or clinical instability.
Clinical Summary
Given the fact that in the context of an acute coronary syndrome (ACS) very low level cardiac troponin (cTn) release is associated with an increase in the risk for adverse outcomes, current consensus guidelines define acute myocardial infarction using cTn values in excess of the 99th percentile of a healthy population, assuming the assay used is sufficiently precise at this very low threshold value. Most conventional cTn assays are not able to deliver this performance. However, newly developed “high sensitivity” troponin (hsTn) assays are now able to detect very low levels of cTn, with acceptable precision at very low concentrations, meeting specifications from consensus guidelines. Among 377 low-to-intermediate risk patients with chest pain and suspected ACS, we compared results of an hsTnT method to that of a conventional cTnT assay. We found the hsTnT method increased sensitivity for ACS compared to cTnT; furthermore, as every patient had a cardiac computerized tomography angiogram, we demonstrated that hsTnT concentrations strongly correlated with abnormalities in cardiac structure and function, independent of a diagnosis of ACS.
Supplementary Material
Acknowlegements
The authors would like to thank Kevin F. Kennedy, MS for providing assistance with calculation of NRI and IDI, as well as Mrs. Gerlinde Trischler for excellent technical assistance. Reagents for troponin assays were provided by Roche Diagnostics.
Funding sources: Sponsored by the National Institutes of Health (RO1 HL080053). Dr. Januzzi is partially supported by the Balson Scholar Fund. Dr. Truong is supported by National Institutes of Health grants T32HL076136 and L30HL093896. Dr. Mohammed is supported by the Dennis and Marilyn Barry Cardiology Fellowship, and Mr. Schlett is supported in part by grants from the German Federal Ministry of Education and Research, as well as the Foundation of German Business.
Footnotes
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Subject codes: [3] acute coronary syndromes, [4] acute myocardial infarction, [30] CT and MR, [33] other diagnostic testing
Disclosures: Dr. Januzzi reports having received significant (>$10,000) research grant support from Roche Diagnostics.
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