Two-Hour Algorithm for Triage toward Rule-Out and Rule-In of Acute Myocardial Infarction by Use of High-Sensitivity Cardiac Troponin I

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1 Clinical Chemistry 62: (2016) Proteomics and Protein Markers Two-Hour Algorithm for Triage toward Rule-Out and Rule-In of Acute Myocardial Infarction by Use of High-Sensitivity Cardiac Troponin I Jasper Boeddinghaus, 1,2,3 Tobias Reichlin, 1,2 Louise Cullen, 4,5 Jaimi H. Greenslade, 4,5 William A. Parsonage, 5,6 Christopher Hammett, 6 John W. Pickering, 7,8 Tracey Hawkins, 4,5 Sally Aldous, 8 Raphael Twerenbold, 1,2 Karin Wildi, 1 Thomas Nestelberger, 1,2,3 Karin Grimm, 1,2,3 Maria Rubini Gimenez, 1,2 Christian Puelacher, 1 Vera Kern, 1 Katharina Rentsch, 9 Martin Than, 8 and Christian Mueller 1,2* BACKGROUND: The early triage of patients toward ruleout and rule-in of acute myocardial infarction (AMI) is challenging. Therefore, we aimed to develop a 2-h algorithm that uses high-sensitivity cardiac troponin I (hs-ctni). METHODS: We prospectively enrolled 1435 (derivation cohort) and 1194 (external validation cohort) patients presenting with suspected AMI to the emergency department. The final diagnosis was adjudicated by 2 independent cardiologists. hs-ctni was measured at presentation and after 2hinablinded fashion. We derived and validated a diagnostic algorithm incorporating hsctni values at presentation and absolute changes within the first 2 h. RESULTS: AMI was the final diagnosis in 17% of patients in the derivation and 13% in the validation cohort. The 2-h algorithm developed in the derivation cohort classified 56% of patients as rule-out, 17% as rule-in, and 27% as observation. Resulting diagnostic sensitivity and negative predictive value (NPV) were 99.2% and 99.8% for rule-out; specificity and positive predictive value (PPV) were 95.2% and 75.8% for rule-in. Applying the 2-h algorithm in the external validation cohort, 60% of patients were classified as rule-out, 13% as rule-in, and 27% as observation. Diagnostic sensitivity and NPV were 98.7% and 99.7% for rule-out; specificity and PPV were 97.4% and 82.2% for rule-in. Thirty-day survival was 100% for rule-out patients in both cohorts. CONCLUSIONS: A simple algorithm incorporating hsctni baseline values and absolute 2-h changes allowed a triage toward safe rule-out or accurate rule-in of AMI in the majority of patients American Association for Clinical Chemistry Sensitive and high-sensitivity cardiac troponin assays enable measurement of lower cardiac troponin concentrations (1 17), improve the diagnostic accuracy for acute myocardial infarction (AMI) 10 at presentation, and allow the development of novel early rule-out algorithms (3 11, 18 22). Several algorithms have been validated in large multicenter studies and, when used in conjunction with the electrocardiogram (ECG) and clinical information, allow safe rule-out of AMI. These algorithms differ substantially in the percentage of patients that can be assigned to rule-out (efficacy) (3 11, 18 22). In addition, only the high-sensitivity cardiac troponin T/I (hsctnt/hs-ctni) 1-h algorithms and the hs-ctnt 2-h algorithm also provide guidance for rule-in. Given the rather low positive predictive value (PPV) of mildly increased high-sensitivity cardiac troponin concentrations for AMI (3, 4, 12, 23), guidance for rule-in is of particular importance when using high-sensitivity cardiac troponin in clinical practice (24). Very high negative predictive value (NPV) for rule-out ( 99.5%), very high efficacy of about 80%, detailed guidance for rule-in, and independent external validation are currently the unique 1 Cardiovascular Research Institute Basel (CRIB), 2 Department of Cardiology, and 3 Department of Internal Medicine, University Hospital Basel, Basel, Switzerland; 4 Department of Emergency Medicine, Royal Brisbane and Women s Hospital, Brisbane, Australia; 5 School of Public Health, The Queensland University of Technology, Brisbane, Australia; 6 School of Medicine, The University of Queensland, Brisbane, Australia; 7 Department of Medicine, University of Otago, Christchurch, New Zealand; 8 Emergency Department, Christchurch Hospital, Christchurch, New Zealand; 9 Laboratory Medicine, University Hospital Basel, Basel, Switzerland. J. Boeddinghaus, T. Reichlin, and L. Cullen contributed equally to this manuscript and should be considered first authors. * Address correspondence to this author at: Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, Petersgraben 4, CH-4031 Basel, Switzerland. Fax ; christian.mueller@usb.ch. Received September 30, 2015; accepted December 23, Previously published online at DOI: /clinchem American Association for Clinical Chemistry 10 Nonstandard abbreviations: AMI, acute myocardial infarction; ECG, electrocardiogram; hs-ctnt, high-sensitivity cardiac troponin T; hs-ctni, high-sensitivity cardiac troponin I; PPV, positive predictive value; NPV, negative predictive value; ED, emergency department; APACE, Advantageous Predictors of Acute Coronary Syndrome Evaluation; ADAPT, 2-h Accelerated Diagnostic Protocol to Assess Patients With Chest Pain Symptoms Using Contemporary Troponins as the Only Biomarker; CAD, coronary artery disease; IQR, interquartile range; TIMI, Thrombolysis in Myocardial Infarction. 494

2 Use of hs-ctni for 2-h Diagnosis of AMI features of the hs-ctnt 2-h algorithm (18). On the basis of patient flow and emergency department (ED) and laboratory logistics related to sampling at this short interval, a 2-h protocol may be preferable for many institutions. We hypothesized that a similar 2-h algorithm could be developed for the only currently approved hs-ctni assay, which has been shown to have even higher analytical sensitivity than the hs-ctnt assay (15, 25). Proper derivation and validation are required before such an accelerated hs-ctni algorithm can be recommended for use in clinical practice. The aim of this study was to develop an hs-ctni algorithm for rapid rule-in and rule-out of AMI from a European multicenter cohort that uses hs-ctni concentrations and absolute changes within the first 2 h. We then sought to externally validate the derived algorithm in a non-european cohort. We also compared the performance of this new hs-ctni 2-h algorithm with the recently published hs-ctnt 2-h algorithm in the derivation and validation cohorts. Methods The study design and population of the derivation and validation cohorts, as well as routine clinical assessment, adjudication of final diagnosis, and follow-up and clinical endpoints are described in the Data Supplement, which accompanies the online version of this article at INVESTIGATIONAL hs-ctni ANALYSIS Blood samples for determination of hs-ctni (Architect STAT high-sensitivity troponin I, Abbott Laboratories) were collected in serum tubes at presentation to the ED and after 2 h. After centrifugation (30 min, 3000g,4 C for serum), samples were frozen at 80 C until assayed in a blinded fashion in a dedicated core laboratory. According to the manufacturer, the hs-ctni assay has a 99th percentile concentration of 26.2 ng/l with a corresponding CV of 5% and a limit of detection of 1.9 ng/l (14 16). The lowest ctni concentration corresponding to a total CV of 10% is 5.6 ng/l; total CVs are 20%, 15%, and 5% at 2.2, 3.6, and 9 ng/l, respectively (16). ALGORITHM DEVELOPMENT AND VALIDATION The algorithm for use of hs-ctni was developed in the derivation cohort [Advantageous Predictors of Acute Coronary Syndrome Evaluation (APACE)]. The algorithm incorporates hs-ctni concentrations at presentation and absolute hs-ctni changes within the first 2 h. Selection of these 2 parameters was based on the previously published high diagnostic accuracy of the combination of absolute concentrations and absolute changes (26, 27). Optimal thresholds for rule-out were selected to allow for a minimal diagnostic sensitivity and NPV of 99%. Optimal thresholds for rule-in were selected to allow for the highest diagnostic specificity and positive predictive value (PPV) possible. The algorithm developed in the derivation cohort was then tested for diagnostic accuracy in the validation cohort [2-h Accelerated Diagnostic Protocol to Assess Patients With Chest Pain Symptoms Using Contemporary Troponins as the Only Biomarker (ADAPT)]. Subgroup analyses focused on differences according to sex, age, presence of known coronary artery disease (CAD), early presenters (patients with an onset of chest pain 3 h), and patients with renal dysfunction (estimated glomerular filtration rate 60 ml min 1 (1.73 m 2 ) 1 ). Continuous variables are presented as mean (SD) or median [interquartile range (IQR)] and categorical variables as numbers and percentages. Differences in baseline characteristics between patients with and without AMI and between patients in the derivation and validation cohorts were assessed with the Mann Whitney U test for continuous variables and the Pearson 2 test for categorical variables. Survival during 30 days and 360 days of follow-up according to the classification provided by the hs-ctni algorithm was plotted in Kaplan Meier curves, and the log-rank test was used to assess differences in survival between groups. All hypothesis testing was 2-tailed, and P values 0.05 were considered statistically significant. Statistical analyses were performed with SPSS for Windows 22.0 (SPSS) in the derivation sample and Stata version 12 (StataCorp) in the validation sample. Results CHARACTERISTICS OF PATIENTS Baseline characteristics of the patients in the derivation cohort (n 1435) and the validation cohort (n 1194) are shown in Tables 1 and 2. Baseline characteristics of the patients in the derivation cohort and validation cohort with missing samples are shown in Supplemental Tables 1 and 2. AMI was the final diagnosis in 17% of patients in the derivation cohort (14.3% type 1 AMI, 2.4% type 2 AMI) and 13% in the validation cohort (all type 1 AMI). Of all patients, discharge within 24 h occurred in 48% of patients in the derivation cohrt and 26% in the validation cohort. Time from onset of symptoms to first study blood draw was 3 h (2 6 h) in the derivation cohort and 3.5 h (2 7 h) in the validation cohort. hs-ctni concentrations at presentation and after 2 h are provided in the online Supplemental Appendix. DERIVATION OF THE hs-ctni ALGORITHM FOR THE DIAGNOSIS OF AMI Rule-out criteria were defined as a maximal hs-ctni concentration within the first 2hof 6 ng/l and an Clinical Chemistry 62:3 (2016) 495

3 Table 1. Baseline characteristics of the patients in the derivation cohort. a Characteristic All patients AMI Others P n Age, years 62 (49 74) 71 (59 79) 60 (48 72) <0.001 Male sex 996 (69) 180 (75) 816 (68) 0.03 Risk factors Hypertension 889 (62) 195 (82) 694 (58) <0.001 Hypercholesterolemia 739 (51) 165 (69) 574 (48) <0.001 Diabetes 257 (18) 69 (29) 188 (16) <0.001 Current smoking 372 (26) 57 (24) 315 (26) 0.44 History of smoking 530 (37) 103 (43) 427 (36) 0.03 History CAD 509 (35) 123 (51) 386 (32) <0.001 Previous myocardial infarction 343 (24) 86 (36) 257 (21) <0.001 Previous revascularization 410 (29) 89 (37) 321 (27) Peripheral artery disease 92 (6) 33 (14) 59 (5) <0.001 Previous stroke 78 (5) 25 (10) 53 (4) <0.001 Creatinine clearance, ml min 1 m 2 85 (70 102) 77 (58 95) 87 (73 103) <0.001 ECG findings Left bundle branch block 43 (3) 13 (6) 30 (3) 0.01 ST-segment elevation 24 (2) 3 (1) 21 (2) 0.63 ST-segment depression 118 (8) 59 (26) 59 (5) <0.001 T-wave inversion 115 (8) 26 (11) 89 (8) 0.05 No significant abnormalities 1135 (79) 138 (58) 997 (83) <0.001 a Data are mean (IQR) or n (%). absolute change within the first 2hof 2 ng/l. For rule-in of AMI, the optimal thresholds were either a maximal hs-ctni value within the first 2hof 64 ng/l or an absolute change in hs-ctni within the first 2hof 15 ng/l. Patients fulfilling neither of the above criteria for rule-in or for rule-out were classified in a third group called observe. The diagnostic performance of the algorithm in the derivation cohort is shown in Fig. 2A. The algorithm classified 804 (56%) patients as rule-out, 240 (17%) as rule-in, and 391 (27%) for observation. Further details on the patients classified for observation are given in the online Supplemental Appendix. Two patients with AMI were missed by the algorithm (see online Supplemental Table 3 for detailed patient characteristics), which resulted in a diagnostic sensitivity and NPV of 99.2% (95% CI, 97% 99.8%) and 99.8% (95% CI, 99.1% 99.9%) for rule-out. Specificity and PPV for rule-in were 95.2% (95% CI, 93.8% 96.2%) and 75.8% (95% CI, 70% 80.8%). Predefined subgroup analyses are shown in the online Supplemental Appendix and Fig. 3A. VALIDATION OF THE hs-ctni ALGORITHM FOR THE DIAGNOSIS OF AMI The algorithm was tested in the external validation cohort (Fig. 2B). Applying the hs-ctni algorithm to the validation cohort, 715 (60%) patients were classified as rule-out. Two patients with AMI were missed (see online Supplemental Table 3 for detailed patient characteristics), resulting in diagnostic sensitivity and NPV of 98.7% (95% CI, 95.5% 99.9%) and 99.7% (99% 100%), respectively. Additionally, 152 (13%) patients were classified as rule-in, which resulted in a diagnostic specificity and PPV of 97.4% (95% CI, 96.2% 98.3%) and 82.2% (95% CI, 75.2% 88%). Taken together, the algorithm allowed a definite diagnosis (either rule-in or rule-out) after 2 h in 73% of patients. The remaining 327 (27%) patients were classified as observe. Further details on the patients classified for observation are provided in the online Supplemental Appendix. The final adjudicated diagnoses in patients falsely ruled in for AMI (n 27) on the basis of the algorithm were acute heart failure (n 2), stable CAD (n 1), perimyocarditis (n 2), cardiomyopathy (n 2), pulmonary disease (n 3), 496 Clinical Chemistry 62:3 (2016)

4 Use of hs-ctni for 2-h Diagnosis of AMI Table 2. Baseline characteristics of the patients in the validation cohort. a Characteristic All patients AMI Others P n Age, years 61 (50 73) 70.5 (59 79) 60 (49 71) <0.001 Male sex 707 (59) 106 (67) 601 (58) Risk factors Hypertension 664 (56) 100 (63) 564 (54) Hypercholesterolemia 629 (53) 92 (58) 537 (52) Diabetes 173 (14) 27 (17) 146 (14) Current smoking 220 (18) 23 (15) 197 (19) History of smoking 520 (44) 71 (45) 449 (43) History CAD 246 (21) 46 (29) 200 (19) Previous myocardial infarction 308 (26) 52 (33) 256 (25) Previous revascularization 285 (24) 46 (29) 239 (23) Peripheral artery disease 44 (4) 10 (6) 34 (3) Previous stroke 140 (12) 20 (13) 120 (12) Creatinine, μmol/l 83 (72 98) 94 (80 115) 82 (71 95) <0.001 ECG findings Indicative of AMI 11 (1) 2 (1) 9 (1) Indicative of ischemia not 103 (9) 44 (28) 59 (6) <0.001 known to be old Indicative of ischemia known 85 (7) 18 (11) 67 (6) to be old No significant abnormalities 995 (83) 94 (59) 901 (87) <0.001 a Data are mean (IQR) or n (%). Classification of ECG was performed as suggested by Forest et al. (41). Eleven patients were missing creatinine values. sinus venous thrombosis (n 2), Wolff Parkinson White syndrome (n 1), atrial fibrillation (n 2), vasovagal (n 1), palpitations (n 1), possible unstable angina (n 4), unspecified cardiovascular problem (n 2), and noncardiovascular problem (n 4). Predefined subgroup analyses are shown in the online Supplemental Appendix and Fig. 3B. DIRECT COMPARISON WITH THE hs-ctnt 2-h ALGORITHM Patient flow in the derivation and the validation cohorts is shown in online Supplemental Fig. 1A. In the derivation cohort (n 1435), 1372 patients (96%) also had measurements of hs-ctnt at presentation and after 2 h. Of these patients, 876 (64%) were classified as rule-out, 281 (20%) as observe, and 215 (16%) as rule-in according to the predefined hs-ctnt 2-h algorithm (see online Supplemental Fig. 1B). The resulting diagnostic sensitivity, NPV, specificity, and PPV were 99.6% (95% CI, 97.6% 100%), 99.9% (99.4% 100%), 96.3% (95% 97.3%), and 80.5% (74.5% 85.5%). In the validation cohort (n 1194), 1153 patients (97%) also had measurements of hs-ctnt at presentation and after 2 h. Of these patients, 780 (68%) were classified as rule-out, 238 (20%) as observe, and 135 (12%) as rule-in, which resulted in a diagnostic sensitivity, NPV, specificity, and PPV of 96.6% (95% CI, 92.1% 98.9%), 99.4% (98.5% 99.8%), 96.5% (95.2% 97.6%), and 74% (65.8% 81.2%) (see online Supplemental Fig. 1B). Accordingly, the performance of the hs-ctni and hs-ctnt 2-h algorithms overall were comparable in both the derivation and the validation cohorts. Differences included a higher percentage of patients ruled out with the hs-ctnt 2-h algorithm in the derivation cohort and the validation cohort and an accordingly lower percentage of patients remaining in the observation group with the hs-ctnt 2-h algorithm vs the hs-ctni 2-h algorithm in both cohorts. Although in the derivation cohort the PPV tended to be higher in the rule-in group according to the hs-ctnt 2-h algorithm (hs-ctnt: 80.5% vs hs-ctni: 75.8%), the PPV was higher in the rule-in group according to the hsctni 2-h algorithm (hs-ctnt: 74.1% vs hs-ctni: 82.2%) in the validation cohort. Clinical Chemistry 62:3 (2016) 497

5 Fig. 1. hs-ctni concentrations at presentation to the emergency department and after 2 h, and absolute changes in patients with and without AMI in the derivation (A) and validation (B) cohorts. Boxes are IQRs; whiskers are ranges (without outliers further than 1.5 IQR from the respective end of the box). PROGNOSTIC PERFORMANCE OF THE hs-ctni ALGORITHM TO PREDICT DEATH DURING FOLLOW-UP In the derivation cohort, there were 18 deaths within 30 days and 66 within 1 year. Cumulative 30-day survival rates in Kaplan Meier curves were 100%, 98%, and 95.8% (P 0.001) in rule-out, observe, and rulein, respectively (Fig. 4). This pattern continued up to a follow-up of 1 year, with cumulative survival rates of 98.5%, 92.3%, and 90.4% (P 0.001). Similar findings were seen in the validation cohort (online appendix). PROGNOSTIC PERFORMANCE OF THE hs-ctnt ALGORITHM TO PREDICT DEATH DURING FOLLOW-UP In the derivation cohort, there were 17 deaths within 30 days and 62 within 1 year. Cumulative 30-day survival rates in Kaplan Meier curves were 100%, 97.5%, and 95.3% (P 0.001) in rule-out, observe, and rule-in (see online Supplemental Fig. 2). This pattern continued up to a follow-up of 1 year, with cumulative survival rates of 98.6%, 91.1%, and 88.4% (P 0.001). Similar findings were seen in the validation cohort (see online Supplemental Fig. 2). Accordingly, the performance of the hs-ctni 2-h algorithm and the hs-ctnt 2-h algorithm were also comparable regarding the prediction of death during follow-up. Discussion With the use of 2 large, independent, and wellcharacterized prospective cohorts of unselected patients presenting with symptoms suggestive of AMI, this study derived and validated an hs-ctni algorithm for triage toward rapid rule-out and rule-in of AMI. The algorithm was derived from a European cohort by use of hs-ctni baseline concentrations and absolute changes within the first 2 h and was externally validated in a non-european cohort. Furthermore, we compared the performance of the hs-ctni with the hs-ctnt 2-h algorithm. Our findings help to extend the previously unique features of the hs-ctnt 2-h algorithm (18) to this novel hs-ctni 2halgorithm: very high NPV for rule-out ( 99.5%), high efficacy of about 80%, detailed guidance for rule-in, and independent external validation. This important extension and corroboration further highlights the suitability and attractiveness of these assay-specific high-sensitivity cardiac troponin 2-h algorithms for routine clinical care. We report 6 major findings. First, safety as quantified by the NPV in the rule-out zone, efficacy as quantified by the percentage of patients assigned a definite pathway (either rule-out or rule-in) by 2 h, and PPV in the rule-in zone were very high and similar to those observed for the hs-ctnt 2-h algorithm (18). In the validation cohort, a safe rule-out and accu- 498 Clinical Chemistry 62:3 (2016)

6 Use of hs-ctni for 2-h Diagnosis of AMI Fig. 2. Performance of the 2-h algorithm classifying patients into rule-out, observational zone, and rule-in for the derivation (A) and validation (B) cohorts. hs-ctni values are presented in ng/l. 0 h/2 h, hs-ctni at presentation and after 2 h; Δ 2 h, absolute change of hs-ctni within the first 2 h. rate rule-in of AMI could be performed within 2 h with a diagnostic sensitivity and NPV of 98.7% (95% CI, 95.5% 99.9%) and 99.7% (99% 100%) and a specificity and PPV of 97.4% (96.2% 98.3%) and 82.2% (75.2% 88%). Second, the assay-specific cutoff values for rule-out with this hs-ctni 2-h algorithm (6 and 2 ng/l for 0/2 h concentrations and absolute change, respectively) were lower than those found for the hs-ctnt 2-h algorithm (14 and 4 ng/l for 0/2 h concentrations and absolute change, respectively) (18). In contrast, both the 0/2 h and the absolute change cutoff for rule-in were slightly higher than the ones found for the hs-ctnt 2-h algorithm. Third, 30-day survival was 100% (both cohorts), and 360-day survival was 98.5% (derivation cohort) and 99.7% (validation cohort) in patients ruled-out for AMI, which underscores the safety of early discharge from the ED for the majority of patients assigned rule-out, with further outpatient management as clinically appropriate. Fourth, although the hs-ctni 2-h algorithm had a nearly perfect NPV, it should be used only in conjunction with all other clinical information including an assessment of pretest probability for AMI and the ECG. In each cohort, 2 AMI patients were missed by the algorithm. Potential reasons include a delayed increase in hs-ctni concentrations after 2 h, errors in the handling of study blood samples, and analytical discrepancies between hs-ctni (used as part of the algorithm) and the ctn assays (hs-ctnt in APACE and s-ctni in ADAPT) used for adjudication. The latter are rare, but have been consistently found to occur in some patients (28, 29). Fifth, subgroup analyses confirmed consistent and very high NPV ( 99.5%) for rule-out of AMI in all predefined subgroups in both the derivation and the validation cohort. In contrast, for rule-in, some differences Clinical Chemistry 62:3 (2016) 499

7 Fig. 3. Forest plots indicating NPV and PPV of the 2-h algorithm in study subgroups of the derivation (A) and validation (B) cohorts. cpo, Chest pain onset; egfr, estimated glomerular filtration rate. 500 Clinical Chemistry 62:3 (2016)

8 Use of hs-ctni for 2-h Diagnosis of AMI Fig. 4. Kaplan Meier curves displaying survival during 30 and 360 days of follow-up in the derivation (A,C) and validation (B,D) cohorts according to the classification into rule-out, observational zone, and rule-in provided by the hs-ctni 2-h algorithm. Differences in survival were assessed using the log-rank test. emerged, with lower PPV in women and patients with known CAD, and higher PPV in men and patients without known CAD in the derivation cohort. These findings are in line with previous studies documenting that female patients with suspected AMI are about 10 years older than male patients and that cardiac comorbidities such as hypertensive heart disease increase with increasing age (30 33). This hypothesis is further supported by the observation that the final adjudicated diagnosis of cardiac but non-cad cause of acute chest discomfort (such as tako-tsubo cardiomyopathy, perimyocarditis, or tachyarrhythmias) was more common in women. Similarly, pa- Clinical Chemistry 62:3 (2016) 501

9 tients with known CAD more often have preexisting cardiomyocyte injury, which results in chronically increased concentrations of cardiac troponin (30 32, 34) and thereby a lower PPV for the rule-in of AMI of this 2-h algorithm. These differences were not of statistical significance in the validation cohort, which had a lower number of AMI patients. Six, despite substantial differences in analytical sensitivity favoring the hs-ctni assay, overall the clinical performance of the hs-ctni and hs-ctnt 2-h algorithms were similar in both the derivation and the validation cohorts. Because hs-ctnt was used for the adjudication in the derivation cohort and s-ctni was used for the adjudication in the validation cohort, the consistent finding of comparable clinical performance of the hs-ctni 2-h algorithm and the hs-ctnt 2-h algorithm is methodologically very strong. The comparable clinical performance was seen irrespective of whether ctnt or ctni was used for the adjudication. This finding corroborates and extends previous studies indicating that beyond analytical sensitivity, other assay characteristics also seem to affect the clinical performance of ctn assays (25, 32). Although high-sensitivity cardiac troponin assays have been shown to increase diagnostic accuracy at presentation (3, 4), simple how-to-use instructions for clinical decision making are lacking. These are critically needed to take advantage of high-sensitivity cardiac troponin and to shorten the time to rule-in and rule-out of AMI (24, 30 32). The hs-ctni 2-h algorithm derived and validated in this study and its hs-ctnt 2-h algorithm counterpart are not the only such tools. They must be seen in the context of several other recently developed early diagnostic algorithms for AMI, most notably highsensitivity cardiac troponin 1-h algorithms (20, 22, 35). For example, the recently derived and validated hs-ctni 1-h algorithm assigned 50.5% of patients to rule-out, with an NPV of 99.6% (95% CI, 98.4% 100%), and 19% of patients to rule-in, with a PPV of 73.9% (95% CI, 66.7% 80.2%) in the validation cohort; 30.5% of patients remained in the observational zone. Thereby, the hs-ctni 2-h algorithm seems to have even more favorable performance characteristics than the hs-ctni 1-h algorithm owing to a slightly higher percentage of patients assigned to rule-out. Local patient flow characteristics and institution/physician preferences will help decide whether having the second high-sensitivity cardiac troponin measurement performed at 1 h (for the 0/1 h algorithm) or at 2 h (for the 0/2 h algorithm) is preferable. The other extensively validated strategy combines the TIMI risk score, ECG, and high-sensitivity cardiac troponin measured at 0 and 2 h (6, 7, 19, 21). Another attractive emergent rapid rule-out strategy uses a single measurement of a very low blood concentration of hs-ctnt or hs-ctni (8 11, 13). The hs-ctni assay examined in this study, with a single cutoff value of 2 ng/l (the limit of detection), allowed us to rule-out AMI in 12.6% of patients with a NPV of 100% (95% CI, 98.2% 100%) with an adjudication of the final diagnosis (type 1 and type 2 AMI) by use of serial measurements of hs-ctnt (9). The use of a cutoff value of 5 ng/l allowed to rule-out AMI in 61% of patients with a NPV of 99.6% (95% CI, %) with an adjudication of the final diagnosis (only type 1 MI, type 2 MI were not counted as events) and a limited number of patients with serial sampling (13). While simple and attractive, this approach only seems to achieve sufficient high NPV in patients presenting with at least 2 3 h from chest pain onset (9, 13). With older ctn assays, the terms troponin positive and troponin negative were often used and resulted in high PPV and specificity but low sensitivity for AMI because of the low analytical sensitivity of previousgeneration assays for detection of the troponin molecule. The high-sensitivity cardiac troponin assays are analytically more sensitive and detect smaller amounts of cardiomyocyte damage more rapidly (2) A one-size-fits-all single cutoff criterion for simultaneous rule-in and ruleout, however, would either result in the identification of too many patients with increased troponin values with various acute and chronic conditions associated with cardiac involvement other than AMI or would not take advantage of the sensitivity of the high-sensitivity cardiac troponin assays and continue to miss small AMIs. Our study, in line with other recent studies (18, 20, 22, 35), rather proposes the use of two different criteria for ruleout and rule-in, resulting in three diagnostic groups, with only approximately 25% of the patients being classified to observe, requiring prolonged monitoring and serial blood sampling. This concept of a gray zone is well known from other fields of acute cardiac care, such as the use of natriuretic peptides for the diagnosis of acute heart failure (36). The proportion of chest pain patients in an ED indeed suffering from AMI can vary remarkably according to the organization of the emergency medical services. Accordingly, AMI proportions reported from recent large chest pain cohort studies have ranged from 3% to 23% (1, 3, 21). It is important for the generalizability of the algorithm that its performance was equally good in both cohorts. For some, but not all, of the high-sensitivity cardiac troponin assays, differences in the 99th percentile between women and men have been reported (15), which has recently brought up the option of possibly using sexspecific 99th percentiles vs the standard practice of the last 2 decades of using a general 99th percentile (37 39). In our study, concentrations of hs-ctni in patients with symptoms suggestive of AMI were similar in men and women, and the accuracy of the algorithm was very similar for men and women, which may be seen as an argu- 502 Clinical Chemistry 62:3 (2016)

10 Use of hs-ctni for 2-h Diagnosis of AMI ment in favor of continuing the use of a general cutoff level. Additional analyses from high-quality diagnostic and prognostic studies are necessary to better quantify the possible net effects of using sex-specific cutoffs, both in the community and in acute hospitalized populations (40). It is important to highlight that AMI remains a clinical diagnosis and that in clinical practice, hs-ctni concentrations are interpreted in conjunction with all other available information including 12-lead ECG, patient history and examination, and other diagnostic investigations. Accordingly, only about 75% 80% of patients triaged toward rule-in will have an adjudicated diagnosis of AMI. The immediate clinical consequence of triage toward rule-in in general is early coronary angiography, which is essential, for instance, to differentiate AMI from tako-tsubo cardiomyopathy or myocarditis. The accuracy of the algorithm in clinical practice, when used in conjunction with the above information and supported ideally by an automated electronic laboratory reporting system, will likely be even higher than reported in this hs-ctni only analysis and will particularly further increase the PPV. Potential limitations of the current study merit consideration. First, our study was conducted in ED patients with symptoms suggestive of AMI. Further studies are required to quantify the performance of this hs-ctni 2-h algorithm in patients with lower (e.g., general practitioner setting) or higher (e.g., coronary care unit setting) pretest probability, as well as in the inherently challenging group of critically ill patients. Second, the data presented were obtained from prospective diagnostic studies. Studies applying the diagnostic algorithm prospectively for clinical decision-making are warranted. Third, we used a specific hs-ctni assay for derivation and validation of the algorithm (Abbott Architect STAT hsctni). We hypothesize that similar algorithms can be developed for other high-sensitivity cardiac troponin assays that have shown similar diagnostic accuracy for AMI (9, 22). However, this hypothesis requires testing and derivation of the assay-specific cutoff values in a large diagnostic study. Fourth, the adjudication process for AMI was similar, but not identical, in the derivation and validation cohorts. This can be seen as both a strength and a limitation. For example, the derivation cohort adjudicated type 1 and type 2 AMI, whereas type 2 AMI was assigned to the cardiac other group in the validation cohort. Fifth, although having an overall large sample size, the number of patients with an adjudicated diagnosis of AMI in several subgroups, such as patients presenting very early and women, was only moderate. This highlights the need for further large studies. In conclusion, with a simple algorithm incorporating hs-ctni values at presentation and after 2 h as well as absolute changes within the first 2 h, a safe rule-out or accurate rule-in of AMI could be performed within 2 h in a majority of patients presenting with chest pain. The use of this algorithm is safe, substantially shortens the time needed for rule-out and rule-in of AMI, and leaves only one-quarter of chest pain patients requiring more prolonged monitoring and serial blood sampling. Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article. Authors Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest: Employment or Leadership: None declared. Consultant or Advisory Role: C. Mueller, Abbott, Alere, AstraZeneca, biomérieux, BG Medicine, BMS, Brahms, Cardiorentis, Daiichi Sankyo, Novartis, Radiometer, Roche, Sanofi, Siemens, and Singulex. Stock Ownership: None declared. Honoraria: L. Cullen, Abbott Diagnostics; W.A. Parsonage, Abbott Laboratories; M. Than, Alere and Abbott; C. Mueller, Abbott, Alere, AstraZeneca, biomérieux, BG Medicine, BMS, Brahms, Cardiorentis, Daiichi Sankyo, Novartis, Radiometer, Roche, Sanofi, Siemens, and Singulex. Research Funding: L. Cullen, research grants from the Queensland Emergency Medical Research Foundation (QEMRF PROJ ); C. Mueller, the Swiss National Science Foundation, the Swiss Heart Foundation, Abbott, Alere, AstraZeneca, biomérieux, Beckman Coulter, Brahms, Nanosphere, Roche, Siemens, Singulex, Sphingotec, 8sense, Nanosphere, and the Department of Internal Medicine, University Hospital Basel. Expert Testimony: None declared. Patents: None declared. Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript. Acknowledgments: We are indebted to the patients who participated in the study and to the emergency department staff as well as the laboratory technicians of all participating sites for their most valuable efforts. In addition, we thank Claudia Stelzig, MS; Michael Freese, RN; Melanie Wieland, RN; Irina Klimmeck, RN; Fausta Chiaverio, RN; Sabine Hartwiger, MD; Julia Meissner, MD; Willibald Hochholzer, MD; Roland Bingisser, MD; and Stefano Bassetti, MD (University Hospital Basel, Switzerland); Esther Garrido, MD; Federico Peter, MD; Isabel Campodarve, MD; and Joachim Gea, MD (Hospital del Mar, IMIM, Barcelona, Spain); Stefan Steuer, MD (Limmattalspital Zuerich, Switzerland); Shanen O Kane, RN; Kimberley Ryan, RN; Kate Parker, RN; and Jennifer Bilesky, BSc, for help with data acquisition; and valuable contributions from Geoff Morangie-Newnam and Jadwiga Chabrowska (Hons Maths) (all Royal Brisbane and Women s Hospital). Clinical Chemistry 62:3 (2016) 503

11 References 1. Thygesen K, Mair J, Mueller C, Huber K, Weber M, Plebani M, et al. Recommendations for the use of natriuretic peptides in acute cardiac care: a position statement from the Study Group on Biomarkers in Cardiology of the ESC Working Group on Acute Cardiac Care. Eur Heart J 2012;33: Giannitsis E, Kurz K, Hallermayer K, Jarausch J, Jaffe AS, Katus HA. Analytical validation of a high-sensitivity cardiac troponin T assay. Clin Chem 2010;56: Reichlin T, Hochholzer W, Bassetti S, Steuer S, Stelzig C, Hartwiger S, et al. Early diagnosis of myocardial infarctionwithsensitivecardiactroponinassays. NEnglJMed 2009;361: Keller T, Zeller T, Peetz D, Tzikas S, Roth A, Czyz E, et al. Sensitive troponin I assay in early diagnosis of acute myocardial infarction. N Engl J Med 2009;361: Keller T, Zeller T, Ojeda F, Tzikas S, Lillpopp L, Sinning C, et al. Serial changes in highly sensitive troponin I assay and early diagnosis of myocardial infarction. JAMA 2011;306: Cullen L, Mueller C, Parsonage W a, Wildi K, Greenslade JH, Twerenbold R, et al. Validation of high-sensitivity troponin I in a 2-hour diagnostic strategy to assess 30- day outcomes in emergency department patients with possible acute coronary syndrome. J Am Coll Cardiol 2013;62: Meller B, Cullen L, Parsonage W, Greenslade JH, Aldous S, Reichlin T, et al. Accelerated diagnostic protocol using high-sensitivity cardiac troponin T in acute chest pain patients. Int J Cardiol 2015;184: Body R, Carley S, McDowell G, Jaffe AS, France M, Cruickshank K, et al. Rapid exclusion of acute myocardial infarction in patients with undetectable troponin using a high-sensitivity assay. J Am Coll Cardiol 2011; 58: Rubini Giménez M, Hoeller R, Reichlin T, Zellweger C, Twerenbold R, Reiter M, et al. Rapid rule-out of acute myocardial infarction using undetectable levels of highsensitivity cardiac troponin. Int J Cardiol 2013;168: Bandstein N, Ljung R, Johansson M, Holzmann MJ. Undetectable high-sensitivity cardiac troponin T level in the emergency department and risk of myocardial infarction. J Am Coll Cardiol 2014;63: Zhelev Z, Hyde C, Youngman E, Rogers M, Fleming S, Slade T, et al. Diagnostic accuracy of single baseline measurement of Elecsys Troponin T high-sensitive assayfordiagnosisofacutemyocardialinfarctioninemergency department: systematic review and metaanalysis. BMJ 2015;350:h Kavsak P a, Wang X, Ko DT, MacRae AR, Jaffe AS. Shortand long-term risk stratification using a nextgeneration, high-sensitivity research cardiac troponin I (hs-ctni) assay in an emergency department chest pain population. Clin Chem 2009;55: Shah AS V, Anand A, Sandoval Y, Lee KK, Smith SW, Adamson PD, et al. High-sensitivity cardiac troponin I at presentation in patients with suspected acute coronary syndrome: a cohort study. Lancet 2015;6736: Koerbin G, Tate J, Potter JM, Cavanaugh J, Glasgow N, Hickman PE. Characterisation of a highly sensitive troponin I assay and its application to a cardio-healthy population. Clin Chem Lab Med 2012;50: Apple FS, Ler R, Murakami MM. Determination of 19 cardiac troponin I and T assay 99th percentile values from a common presumably healthy population. Clin Chem 2012;58: Krintus M, Kozinski M, Boudry P, Capell NE, Köller U, Lackner K, et al. European multicenter analytical evaluation of the Abbott ARCHITECT STAT high sensitive troponin I immunoassay. Clin Chem Lab Med 2014;52: Apple FS, Jesse RL, Newby LK, Wu AHB, Christenson RH. National Academy of Clinical Biochemistry and IFCC Committee for Standardization of Markers of Cardiac Damage Laboratory Medicine Practice Guidelines: Analytical issues for biochemical markers of acute coronary syndromes. Circulation 2007;115:e Reichlin T, Cullen L, Parsonage W, Greenslade J, Twerenbold R, Moehring B, et al. Two-hour algorithm for triage toward rule-out and rule-in of acute myocardial infarction using high-sensitivity cardiac troponin T. Am J Med 2014;128: Than M, Cullen L, Aldous S, Parsonage W, Reid CM, Greenslade J, et al. 2-Hour accelerated diagnostic protocol to assess patients with chest pain symptoms using contemporary troponins as the only biomarker: the ADAPT trial. J Am Coll Cardiol 2012;59: Rubini Gimenez M, Twerenbold R, Jaeger C, Schindler C, Puelacher C, Wildi K, et al. One-hour rule-in and ruleout of acute myocardial infarction using highsensitivity cardiac troponin I. Am J Med 2015;128: Than M, Cullen L, Reid CM, Lim SH, Aldous S, Ardagh MW, et al. A 2-h diagnostic protocol to assess patients with chest pain symptoms in the Asia-Pacific region (ASPECT): a prospective observational validation study. Lancet 2011;377: Reichlin T, Schindler C, Drexler B, Twerenbold R, Reiter M, Zellweger C, et al. One-hour rule-out and rule-in of acute myocardial infarction using high-sensitivity cardiac troponin T. Arch Intern Med 2012;172: Zahid M, Good CB, Singla I, Sonel AF. Clinical significance of borderline elevated troponin I levels across different assays in patients with suspected acute coronary syndrome. Am J Cardiol 2009;104: Jesse RL. On the relative value of an assay versus that of a test: a history of troponin for the diagnosis of myocardial infarction. J Am Coll Cardiol 2010;55: Rubini Gimenez M, Twerenbold R, Reichlin T, Wildi K, Haaf P, Schaefer M, et al. Direct comparison of highsensitivity-cardiac troponin I vs. T for the early diagnosis of acute myocardial infarction. Eur Heart J 2014;35: Reichlin T, Irfan A, Twerenbold R, Reiter M, Hochholzer W, Burkhalter H, et al. Utility of absolute and relative changes in cardiac troponin concentrations in the early diagnosis of acute myocardial infarction. Circulation 2011;124: Mueller M, Biener M, Vafaie M, Doerr S, Keller T, Blankenberg S, et al. Absolute and relative kinetic changes of high-sensitivity cardiac troponin T in acute coronary syndrome and in patients with increased troponin in the absence of acute coronary syndrome. Clin Chem 2012;58: Wildi K, Rubini Gimenez M, Twerenbold R, Reichlin T, Jaeger C, Heinzelmann A, et al. Misdiagnosis of myocardial infarction related to limitations of the current regulatory approach to define clinical decision values for cardiac troponin. Circulation 2015;131: Lindahl B, Eggers KM, Venge P, James S. Evaluation of four sensitive troponin assays for risk assessment in acute coronary syndromes using a new clinically oriented approach for comparison of assays. Clin Chem Lab Med 2013;51: ThygesenK, AlpertJS, WhiteHD. Universaldefinitionof myocardial infarction. Eur Heart J 2007;28: Roffi M, Patrono C, Collet J-P, Mueller C, Valgimigli M, Andreotti F, et al ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J 2015;ehv Thygesen K, Mair J, Giannitsis E, Mueller C, Lindahl B, Blankenberg S, et al. How to use high-sensitivity cardiac troponins in acute cardiac care. Eur Heart J 2012; 33: Reiter M, Twerenbold R, Reichlin T, Haaf P, Peter F, Meissner J, et al. Early diagnosis of acute myocardial infarction in the elderly using more sensitive cardiac troponin assays. Eur Heart J 2011;32: Reiter M, Twerenbold R, Reichlin T, Benz B, Haaf P, Meissner J, et al. Early diagnosis of acute myocardial infarction in patients with pre-existing coronary artery disease using more sensitive cardiac troponin assays. Eur Heart J 2012;33: Reichlin T, Twerenbold R, Wildi K, Gimenez MR, Bergsma N, Haaf P, et al. Prospective validation of a 1-hour algorithm to rule-out and rule-in acute myocardial infarction using a high-sensitivity cardiac troponin T assay. CMAJ 2015;187:E Fonarow GC, Adams KF, Abraham WT, Yancy CW, Boscardin WJ. Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis. JAMA 2005;293: Shah AS V, Griffiths M, Lee KK, McAllister DA, Hunter AL, Ferry A V, et al. High sensitivity cardiac troponin and the under-diagnosis of myocardial infarction in women: prospective cohort study. BMJ 2015;350:g Eggers KM, Johnston N, Lind L, Venge P, Lindahl B. Cardiac troponin I levels in an elderly population from the community the implications of sex. Clin Biochem 2015;48: Bohula May E, Bonaca MP, Jarolim P, Antman EM, Braunwald E, Giugliano RP, et al. Prognostic performance of a high-sensitivity cardiac troponin I assay in patients with non-st-elevation acute coronary syndrome. Clin Chem 2014;60: Mueller C, Kavsak P. Sex-specific cutoffs for cardiac troponin using high-sensitivity assays is there clinical equipoise? Clin Biochem 2015;48: Forest RS, Shofer FS, Sease KL, Hollander JE. Assessment of the standardized reporting guidelines ECG classification system: the presenting ECG predicts 30- day outcomes. Ann Emerg Med 2004;44: Clinical Chemistry 62:3 (2016)