Reweighting and validation of the hospital frailty risk score using electronic health records in Germany: a retrospective observational study.

BACKGROUND: In the hospital setting, frailty is a significant risk factor, but difficult to measure in clinical practice. We propose a reweighting of an existing diagnoses-based frailty score using routine data from a tertiary care teaching hospital in southern Germany. METHODS: The dataset includes patient characteristics such as sex, age, primary and secondary diagnoses and in-hospital mortality. Based on this information, we recalculate the existing Hospital Frailty Risk Score. The cohort includes patients aged ≥ 75 and was divided into a development cohort (admission year 2011 to 2013, N = 30,525) and a validation cohort (2014, N = 11,202). A limited external validation is also conducted in a second validation cohort containing inpatient cases aged ≥ 75 in 2022 throughout Germany (N = 491,251). In the development cohort, LASSO regression analysis was used to select the most relevant variables and to generate a reweighted Frailty Score for the German setting. Discrimination is assessed using the area under the receiver operating characteristic curve (AUC). Visualization of calibration curves and decision curve analysis were carried out. Applicability of the reweighted Frailty Score in a non-elderly population was assessed using logistic regression models. RESULTS: Reweighting of the Frailty Score included only 53 out of the 109 frailty-related diagnoses and resulted in substantially better discrimination than the initial weighting of the score (AUC = 0.89 vs. AUC = 0.80, p < 0.001 in the validation cohort). Calibration curves show a good agreement between score-based predictions and actual observed mortality. Additional external validation using inpatient cases aged ≥ 75 in 2022 throughout Germany (N = 491,251) confirms the results regarding discrimination and calibration and underlines the geographic and temporal validity of the reweighted Frailty Score. Decision curve analysis indicates that the clinical usefulness of the reweighted score as a general decision support tool is superior to the initial version of the score. Assessment of the applicability of the reweighted Frailty Score in a non-elderly population (N = 198,819) shows that discrimination is superior to the initial version of the score (AUC = 0.92 vs. AUC = 0.87, p < 0.001). In addition, we observe a fairly age-stable influence of the reweighted Frailty Score on in-hospital mortality, which does not differ substantially for women and men. CONCLUSIONS: Our data indicate that the reweighted Frailty Score is superior to the original Frailty Score for identification of older, frail patients at risk for in-hospital mortality. Hence, we recommend using the reweighted Frailty Score in the German in-hospital setting.

Diagnostic and prognostic value of the sex-specific 99th percentile of four high-sensitivity cardiac troponin assays in patients with suspected myocardial infarction.

AIMS: High-sensitivity cardiac troponin (hs-cTn) assays are used for detection of myocardial infarction (MI). Ninety-ninth percentiles show wide inter-assay variation. The use of sex-specific cut-offs is recommended as definitory cut-off for MI. We compared diagnostic performance and prognostic value of sex-specific 99th percentiles of four hs-cTn assays in patients with suspected MI. METHODS AND RESULTS: Concentrations of four hs-cTn assays were measured at presentation and after 3 h in patients with suspected MI. Final diagnoses were adjudicated according to the 4th Universal Definition of MI. Unisex and sex-specific 99th percentiles were evaluated as diagnostic cut-offs following the ESC 0/3 h algorithm. These cut-offs were used in Cox-regression analyses to investigate the association with a composite endpoint of MI, revascularization, cardiac rehospitalization, and death. Non-ST-elevation MI was diagnosed in 368 of 2718 patients. Applying the unisex 99th percentile, Elecsys hs-cTnT provided highest negative predictive value (NPV) of 99.7 and a positive predictive value (PPV) of 75.9. The analysed hs-cTnI assays showed slightly lower NPVs and comparable PPVs [Architect (NPV 98.0, PPV of 71.4); Atellica (NPV 97.7, PPV of 76.1); Pathfast (NPV 97.7, PPV of 66.6)]. Application of sex-specific 99th percentiles did not significantly affect diagnostic performance. Concentrations above 99th percentile were independent predictors for impaired long-term outcome (hazard ratios 1.2-1.5, P < 0.001). CONCLUSION: We describe a good diagnostic accuracy of four hs-cTn assays using the assay-specific 99th percentile for detection of MI. Application of sex-specific 99th percentiles did neither affect diagnostic performance nor prognostic value significantly. Finally, values above the 99th percentile were associated with poor long-term outcome.

Prognostic utility of a multi-biomarker panel in patients with suspected myocardial infarction.

BACKGROUND: The accurate identification of patients with high cardiovascular risk in suspected myocardial infarction (MI) is an unmet clinical need. Therefore, we sought to investigate the prognostic utility of a multi-biomarker panel with 29 different biomarkers in in 748 consecutive patients with symptoms indicative of MI using a machine learning-based approach. METHODS: Incident major cardiovascular events (MACE) were documented within 1 year after the index admission. The selection of the best multi-biomarker model was performed using the least absolute shrinkage and selection operator (LASSO). The independent and additive utility of selected biomarkers was compared to a clinical reference model and the Global Registry of Acute Coronary Events (GRACE) Score, respectively. Findings were validated using internal cross-validation. RESULTS: Median age of the study population was 64 years. At 1 year of follow-up, 160 cases of incident MACE were documented. 16 of the investigated 29 biomarkers were significantly associated with 1-year MACE. Three biomarkers including NT-proBNP (HR per SD 1.24), Apolipoprotein A-I (Apo A-I; HR per SD 0.98) and kidney injury molecule-1 (KIM-1; HR per SD 1.06) were identified as independent predictors of 1-year MACE. Although the discriminative ability of the selected multi-biomarker model was rather moderate, the addition of these biomarkers to the clinical reference model and the GRACE score improved model performances markedly (∆C-index 0.047 and 0.04, respectively). CONCLUSION: NT-proBNP, Apo A-I and KIM-1 emerged as strongest independent predictors of 1-year MACE in patients with suspected MI. Their integration into clinical risk prediction models may improve personalized risk stratification. Prognostic utility of a multi-biomarker approach in suspected myocardial infarction. In a cohort of 748 patients with symptoms indicative of myocardial infarction (MI) to the emergency department, we measured a 29-biomarker panel and performed regressions, machine learning (ML)-based variable selection and discriminative/reclassification analyses. We identified three biomarkers as top predictors for 1-year major adverse cardiovascular events (MACE). Their integration into a clinical risk prediction model and the Global Registry of Acute Coronary Events (GRACE) Score allowed for marked improvement in discrimination and reclassification for 1-year MACE. Apo apolipoprotein; CRP C-reactive protein; CRS clinical risk score; ECG electrocardiogram; EN-RAGE extracellular newly identified receptor for advanced glycation end-products binding protein; FABP fatty acid-binding protein; GS Grace Score; hs-cTnI high-sensitivity cardiac troponin I; KIM-1 kidney injury molecule-1; LASSO least absolute shrinkage and selection operator; MACE major adverse cardiovascular events; MI myocardial infarction; NRI net reclassification improvement; NT-proBNP N-terminal prohormone of brain natriuretic peptide.

Long-term outcome of patients presenting with myocardial injury or myocardial infarction.

AIMS: Patients with acute or chronic myocardial injury are frequently identified in the context of suspected myocardial infarction (MI). We aimed to investigate their long-term follow-up. METHODS AND RESULTS: We prospectively enrolled 2714 patients with suspected MI and followed them for all-cause mortality and a composite cardiovascular endpoint (CVE; cardiovascular death, MI, unplanned revascularization) for a median of 5.1 years. Final diagnoses were adjudicated by two cardiologists according to the Fourth Universal Definition of MI, including 143 (5.3%) ST-elevation MI, 236 (8.7%) non-ST-elevation MI (NSTEMI) Type 1 (T1), 128 (4.7%) NSTEMI T2, 86 (3.2%) acute and 677 (24.9%) with chronic myocardial injury, and 1444 (53.2%) with other reasons for chest pain (reference). Crude event rates per 1000 patient-years for all-cause mortality were highest in patients with myocardial injury (81.6 [71.7, 92.3]), and any type of MI (55.9 [46.3, 66.7]), compared to reference (12.2 [9.8, 15.1]). Upon adjustment, all diagnoses were significantly associated with all-cause mortality. Moreover, patients with acute (adj-HR 1.92 [1.08, 3.43]) or chronic (adj-HR 1.59 [1.16, 2.18]) myocardial injury, and patients with NSTEMI T1 (adj-HR 2.62 [1.85, 3.69]) and ST-elevation MI (adj-HR 3.66 [2.41, 5.57]) were at increased risk for cardiovascular events. CONCLUSION: Patients with myocardial injury are at a similar increased risk for death and cardiovascular events compared to patients with acute MI. Further studies need to determine appropriate management strategies for patients with myocardial injury. REGISTRATION: Clinicaltrials.gov (NCT02355457).

Rising and Falling High-Sensitivity Cardiac Troponin in Diagnostic Algorithms for Patients With Suspected Myocardial Infarction.

Background High-sensitivity cardiac troponin (hs-cTn)-based diagnostic algorithms are recommended for the management of patients with suspected myocardial infarction (MI) without ST elevation. Although mirroring different phases of myocardial injury, falling and rising troponin patterns (FPs and RPs, respectively) are equally considered by most algorithms. We aimed to compare the performance of diagnostic protocols for RPs and FPs, separately. Methods and Results We pooled 2 prospective cohorts of patients with suspected MI and stratified patients to stable, FP, and RP during serial sampling separately for hs-cTnI and hs-cTnT and applied the European Society of Cardiology 0/1- and 0/3-hour algorithms comparing the positive predictive values to rule in MI. Overall, 3523 patients were included in the hs-cTnI study population. The positive predictive value for patients with an FP was significantly reduced compared with patients with an RP (0/1-hour: FP, 53.3% [95% CI, 45.0-61.4] versus RP, 76.9 [95% CI, 71.6-81.7]; 0/3-hour: FP, 56.9% [95% CI, 42.2-70.7] versus RP, 78.1% [95% CI, 74.0-81.8]). The proportion of patients in the observe zone was larger in the FP using 0/1-hour (31.3% versus 55.8%) and 0/3-hour (14.6% versus 38.6%) algorithms. Alternative cutoffs did not improve algorithm performances. Compared with stable hs-cTn, the risk for death or MI was highest in those with an FP (adjusted hazard ratio [HR], hs-cTnI 2.3 [95% CI, 1.7-3.2]; RP adjusted HR, hs-cTnI 1.8 [95% CI, 1.4-2.4]). Findings were similar for hs-cTnT tested in 3647 patients overall. Conclusions The positive predictive value to rule in MI by the European Society of Cardiology 0/1- and 0/3-hour algorithms is significantly lower in patients with FP than RP. These are at highest risk for incident death or MI. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT02355457, NCT03227159.

Role of Copeptin and hs-cTnT to Discriminate AHF from Uncomplicated NSTE-ACS with Baseline Elevated hs-cTnT-A Derivation and External Validation Study.

BACKGROUND: In light of overlapping symptoms, discrimination between non-ST-elevation (NSTE) acute coronary syndrome (ACS) and acute heart failure (HF) is challenging, particularly in patients with equivocal clinical presentation for suspected ACS. We sought to evaluate the diagnostic and prognostic properties of copeptin in this scenario. METHODS: Data from 1088 patients from a single-center observational registry were used to test the ability of serial high sensitivity cardiac troponin T (hs-cTnT)-compared to copeptin, or a combination of copeptin with hs-cTnT-to discriminate acute HF from uncomplicated non-ST-elevation myocardial infarction (NSTEMI) and to evaluate all-cause mortality after 365 days. Patients with STEMI, those with unstable angina and either normal or undetectable hs-cTnT concentrations were excluded. The findings were validated in an independent external NSTE-ACS cohort. RESULTS: A total of 219 patients were included in the analysis. The final diagnosis was acute HF in 56 and NSTE-ACS in 163, with NSTEMI in 78 and unstable angina having stable elevation of hs-cTnT >ULN in 85. The rate of all-cause death at 1 year was 9.6% and occurred significantly more often in acute HF than in NSTE-ACS (15 vs. 6%, p < 0.001). In the test cohort, the area under the receiver operator curve (AUC) for the discrimination of acute HF vs. NSTE-ACS without HF was 0.725 (95% confidence interval [CI] 0.625-0.798) for copeptin and significantly higher than for hs-cTnT at 0 h (AUC = 0.460, 0.370-0.550) or at 3 h (AUC = 0.441, 0.343-0.538). Copeptin and hs-cTnT used either as continuous values or at cutoffs optimized to yield 90% specificity for acute HF were associated with significantly higher age- and sex-adjusted risk for all-cause mortality at 365 days. The findings from the test cohort were consistently replicated in the independent external NSTE-ACS validation cohort. CONCLUSIONS: High concentrations of copeptin in patients with suspected NSTE-ACS and equivocal clinical presentation suggest the presence of acute HF compared to uncomplicated NSTE-ACS and are associated with higher rates of all-cause death at 365 days.

Advances in rapid diagnostic tests for myocardial infarction patients.

INTRODUCTION: A rapid diagnosis of myocardial infarction (MI) is of utmost importance in order to provide adequate therapy for patients that suffer from acute ischemic cardiac injury. Cardiac troponin has evolved as the most significant biomarker in the diagnostic assessment of MI, but its evaluation and management can be challenging. Different troponin-based diagnostic protocols have been suggested for the diagnosis of MI and they have been validated and further developed over the years. AREAS COVERED: This review highlights the advances, characteristics, and challenges of rapid diagnostic protocols for MI and summarizes recent findings of investigations in the field. EXPERT OPINION: Although high-sensitivity troponin assays and rapid diagnostic protocols have revolutionized the assessment of suspected MI, we are still facing challenges that must be overcome in order to improve the outcome of patients with MI.

Validation of a 0/1 h Algorithm for Rapid Diagnosis of Myocardial Infarction Using a High-Sensitivity Troponin I Assay.

BACKGROUND: Current guidelines recommend 0/1 h algorithms using high-sensitivity cardiac troponin (hs-cTn) for fast diagnosis of myocardial infarction (MI). Yet, for some assays, existing data is limited. We aimed to evaluate the diagnostic performance and the prognostic value of a rapid 0/1 h algorithm for the Access hs-cTnI assay. METHODS: In consecutive patients presenting with suspected MI, we measured concentrations of Access hs-cTnI at presentation and after 1 hour. Final diagnosis was adjudicated independently by 2 cardiologists. Parameters for diagnostic performance were calculated, applying the recently derived European Society of Cardiology (ESC) 0/1 h algorithm for Access hs-cTnI. Additionally, we assessed the prognostic utility of Access hs-cTnI for the composite end point of all-cause mortality and incident MI at 3 years. RESULTS: In 1879 patients, 257 non-ST-elevation MIs occurred. Application of the 0/1 h algorithm classified 44.5% as rule-out, 20.3% as rule-in, and triaged 35.1% to the observe group. High rule-out safety was confirmed with a sensitivity of 97.7% (95% CI, 95.0%-99.1%) and a negative predictive value of 99.3% (95% CI, 98.4%-99.7%). Rule-in capacity was moderate with a specificity of 88.0% (95% CI, 86.3%-89.6%) and a positive predictive value of 50.8% (95% CI, 45.7%-55.9%). After exclusion of patients with ST-elevation MI the results showed strong prognostic value, even after adjustment for cardiovascular risk factors and comorbidities, with adjusted hazard ratios of 2.51 (95% CI, 1.56-4.04) in the observe and 3.55 (95% CI, 2.18-5.79) in the rule-in group for the composite end point of all-cause mortality and incident MI at 3 years, compared to ruled-out patients. CONCLUSION: The ESC 0/1 h algorithm for Access hs-cTnI allows safe and efficient triage of patients with suspected MI and has strong prognostic utility up to 3 years after the initial evaluation.

Serial measurements of protein and microRNA biomarkers to specify myocardial infarction subtypes.

Background: While cardiac-specific troponin (cTn) allows for rapid diagnosis of acute type 1 myocardial infarction (T1MI), its performance to differentiate acute myocardial injury (AI) or type 2 myocardial infarction (T2MI) is limited. The objective was to combine biomarkers to improve discrimination of different myocardial infarction (MI) aetiologies. Methods: We determined levels of cardiac troponin T and I (cTnT, cTnI), cardiac myosin-binding protein C (cMyBP-C), NT-proBNP and ten miRNAs, known to be associated with cardiac pathology in a total of n = 495 serial plasma samples at three time points (on admission, after 1 h and 3 h) from 57 NSTEMI (non-ST-elevation myocardial infarction), 18 AI, and 31 STEMI patients, as defined by fourth universal definition of MI (UDMI4) and 59 control individuals. We then applied linear mixed effects model to compare the kinetics of all molecules in these MI sub-types. Results: Established (cTnT, cTnI) and novel (cMyBP-C) cardiac necrosis markers failed in differentiating T1MI vs T2MI at early time points. All cardiac necrosis markers were higher in T1MI than in T2MI at 3 h after admission. Muscle-enriched miRNAs (miR-1 and miR-133a) were correlated with cardiac necrosis protein markers and did not offer better discrimination. Established cardiac strain marker NT-proBNP differentiated AI and T1MI at all time points but failed to discriminate T2MI from T1MI. However, the combination of NT-proBNP and cTnT along with age returned an overall AUC of 0.76 [95 % CI 0.67-0.84] for differentiating T1MI, T2MI and AI. Conclusions: Rather than using single biomarkers of myocardial necrosis, a combination of clinical biomarkers for cardiac necrosis (troponin) and cardiac strain (NT-proBNP) might aid in differentiating T1MI, T2MI and AI.

High-sensitivity troponin I with or without ultra-sensitive copeptin for the instant rule-out of acute myocardial infarction.

Background: The instant, single-sampling rule-out of acute myocardial infarction (AMI) is still an unmet clinical need. We aimed at testing and comparing diagnostic performance and prognostic value of two different single-sampling biomarker strategies for the instant rule-out of AMI. Methods: From the Biomarkers in Acute Cardiac Care (BACC) cohort, we recruited consecutive patients with acute chest pain and suspected AMI presenting to the Emergency Department of the University Medical Center Hamburg-Eppendorf, Hamburg, Germany. We compared safety, effectiveness and 12-month incidence of the composite endpoint of all-cause death and myocardial infarction between (i) a single-sampling, dual-marker pathway combining high-sensitivity cardiac troponin I (hs-cTnI) and ultra-sensitive copeptin (us-Cop) at presentation (hs-cTnI ≤ 27 ng/L, us-Cop < 10 pmol/L and low-risk ECG) and (ii) a single-sampling pathway based on one-off hs-cTnI determination at presentation (hs-cTnI < 5 ng/L and low-risk ECG). As a comparator, we used the European Society of Cardiology (ESC) 0/1-h dual-sampling algorithm. Results: We enrolled 1,136 patients (male gender 65%) with median age of 64 years (interquartile range, 51-75). Overall, 228 (20%) patients received a final diagnosis of AMI. The two single-sampling instant rule-out pathways yielded similar negative predictive value (NPV): 97.4% (95%CI: 95.4-98.7) and 98.7% (95%CI: 96.9-99.6) for dual-marker and single hs-cTnI algorithms, respectively (P = 0.11). Both strategies were comparably safe as the ESC 0/1-h dual-sampling algorithm and this was consistent across subgroups of early-comers, low-intermediate risk (GRACE-score < 140) and renal dysfunction. Despite a numerically higher rate of false-negative results, the dual-marker strategy ruled-out a slightly but significantly higher percentage of patients compared with single hs-cTnI determination (37.4% versus 32.9%; P < 0.001). There were no significant between-group differences in 12-month composite outcome. Conclusions: Instant rule-out pathways based on one-off determination of hs-cTnI alone or in combination with us-Cop are comparably safe as the ESC 0/1 h algorithm for the instant rule-out of AMI, yielding similar prognostic information. Instant rule-out strategies are safe alternatives to the ESC 0/1 h algorithm and allow the rapid and effective triage of suspected AMI in patients with low-risk ECG. However, adding copeptin to hs-cTn does not improve the safety of instant rule-out compared with the single rule-out hs-cTn at very low cut-off concentrations.

A Biomarker Model to Distinguish Types of Myocardial Infarction and Injury.

BACKGROUND: Discrimination among patients with type 1 myocardial infarction (T1MI), type 2 myocardial infarction (T2MI), and myocardial injury is difficult. OBJECTIVES: The aim of this study was to investigate the discriminative value of a 29-biomarker panel in an emergency department setting. METHODS: Patients presenting with suspected myocardial infarction (MI) were recruited. The final diagnosis in all patients was adjudicated on the basis of the fourth universal definition of MI. A panel of 29 biomarkers was measured, and multivariable logistic regression analysis was used to evaluate the associations of these biomarkers with the diagnosis of MI or myocardial injury. Biomarkers were chosen using backward selection. The model was internally validated using bootstrapping. RESULTS: Overall, 748 patients were recruited (median age 64 years), of whom 138 had MI (107 T1MI and 31 T2MI) and 221 had myocardial injury. In the multivariable model, 4 biomarkers (apolipoprotein A-II, N-terminal prohormone of brain natriuretic peptide, copeptin, and high-sensitivity cardiac troponin I) remained significant discriminators between T1MI and T2MI. Internal validation of the model showed an area under the curve of 0.82. For discrimination between MI and myocardial injury, 6 biomarkers (adiponectin, N-terminal prohormone of brain natriuretic peptide, pulmonary and activation-regulated chemokine, transthyretin, copeptin, and high-sensitivity troponin I) were selected. Internal validation showed an area under the curve of 0.84. CONCLUSIONS: Among 29 biomarkers, 7 were identified to be the most relevant discriminators between subtypes of MI or myocardial injury. Regression models based on these biomarkers allowed good discrimination. (Biomarkers in Acute Cardiac Care [BACC]; NCT02355457).

The association of anaemia and high-sensitivity cardiac troponin and its effect on diagnosing myocardial infarction.

AIMS: Anaemia is common in patients with acute myocardial infarction (MI). We investigated the association of high-sensitivity cardiac troponin (hs-cTn) and haemoglobin (Hb) and the influence of anaemia on the performance of diagnostic protocols for suspected MI. METHODS AND RESULTS: Patients with suspected MI were consecutively enrolled at a tertiary centre. Final diagnoses were independently adjudicated by two cardiologists. Performance measures of hs-cTn-based algorithms were compared for anaemic and non-anaemic patients (Hb <12 g/dL in women and <13 g/dL in men). The influence of anaemia on survival (median follow-up 1.7 years) was investigated using multivariable cox-regression analysis and the association of Hb and hs-cTn by multivariable linear regression analysis. Overall, 2223 patients were included, of whom 415 (18.7%) had anaemia. In anaemic patients, the incidence of MI was similar; however, chronic myocardial injury was significantly more prevalent (20.1% vs. 48.2%). The negative predictive value to rule-out MI was similar for both algorithms and all assays in patients with anaemia, although the positive predictive value to rule-in MI was partly reduced for the 0/3-h algorithm. Fewer anaemic patients were triaged after 1 h. Anaemia was an independent predictor of death. Adjusted for patient characteristics, Hb was significantly associated with hs-cTn. By providing a point-based tool, the Hb-associated hs-cTn concentration and thus chronic myocardial injury may be predicted. CONCLUSION: Anaemia partly affects the rule-in, but not the rule-out of MI in hs-cTn-based diagnostic protocols. Hs-cTn concentrations and thus chronic myocardial injury may be predicted by clinical variables and Hb. TRIAL REGISTRATION: clinicaltrials.gov (NCT02355457 and NCT03227159).

Diagnostic Validation of a High-Sensitivity Cardiac Troponin I Assay.

BACKGROUND: Emergency departments worldwide are increasingly adopting rapid diagnosis of patients with suspected myocardial infarction (MI) based on high-sensitivity troponin. We set out to assess the diagnostic accuracy of a high-sensitivity cardiac troponin I (hs-cTnI) assay in a prospective study. METHODS: In a cohort study including 1800 patients presenting with suspected acute MI, we developed and temporally validated a 0/1 h diagnostic algorithm using the Siemens Atellica IM hs-cTnI assay. The algorithm was established in the first 928 patients and validated in the following 872 patients. RESULTS: The derived algorithm consisted of a baseline rule-out of non-ST-segment elevation MI using a cutoff <3 ng/L in patients with symptom onset ≥3 h or an admission troponin I level <6 ng/L with a Δ change of <3 ng/L from 0 h to 1 h. For rule-in, an admission troponin I level ≥120 ng/L or an increase within the first hour ≥12 ng/L was required. Application of the algorithm to the validation cohort showed a negative predictive value of 99.8% (95% CI, 98.7%-100.0%), sensitivity of 99.1% (95% CI, 95.1%-100.0%), and 48.3% of patients ruled out, whereas 15.1% were ruled in with a positive predictive value of 68.0% (95% CI, 59.1%-75.9%) and specificity of 94.4% (95% CI, 92.5%-96.0%). The diagnostic performance was comparable to guideline-recommended application of an established hs-cTnI assay in a rapid 0/1 h strategy. CONCLUSIONS: The Siemens hs-cTnI assay is well suited for application in rapid diagnostic stratification of patients with suspected MI. STUDY REGISTRATION: www.clinicaltrials.gov (NCT02355457).

Prognostic Implications of a Second Peak of High-Sensitivity Troponin T After Myocardial Infarction.

BACKGROUND: After an acute myocardial infarction (MI), repeated measurement of cardiac biomarkers is commonly performed, although not recommended in current guidelines. There is only limited data on the kinetics of troponin in this phase. For high-sensitivity cardiac troponin T (hs-cTnT), but not high-sensitivity cardiac troponin I (hs-cTnI), late increases in terms of a second peak have been described. Their impact on the prognosis of patients with MI remains unclear. METHODS: We included 2,305 patients presenting to the emergency department with symptoms suggestive of MI. Five hundred and seven were diagnosed with MI. Hs-cTnT, creatine kinase (CK) and the MB fraction of CK (CK-MB) were measured at admission, after 1 and 3 h and thereafter as indicated by the treating physician. A mixed-model approach was applied for modeling the biomarker kinetics. All patients were followed up to assess a composite endpoint of mortality, recurrent MI, revascularization and rehospitalization and to investigate the effect of a second hs-cTnT peak on prognosis. RESULTS: Out of 507 patients with MI, 192 had a sufficient amount of hs-cTnT measurements after the index MI. In 111 (57.8%) patients a second hs-cTnT peak was found after 4.48 days. For CK and CK-MB a second peak could not be identified. Regarding the composite endpoint there was no significant difference between patients with and without a second hs-cTnT peak. CONCLUSION: In our analyses, a second peak of hs-cTnT after an acute MI was common, but not associated with poorer outcome. Thus, the clinical value of hs-cTnT for monitoring myocardial ischemia might be limited in this phase and other biomarkers might be more suitable.Trial Registration: www.ClinicalTrials.gov, identifier: NCT02355457, Date of registration: February 4, 2015.

Predictive Value of Serial ECGs in Patients with Suspected Myocardial Infarction.

The electrocardiogram (ECG) is an important diagnostic tool for patients with suspected acute myocardial infarction (AMI). Current guidelines recommend serial ECGs in case of persisting symptoms. We aimed to analyze the predictive value of ischemic ECG-signs in patients with suspected AMI. Patients presenting to the emergency department with suspected AMI were included. All patients with ST-elevation AMI were excluded from analyses. Patients received 12-lead-ECG and high-sensitive Troponin T (hs-TnT)-measurement at admission and after 3 h. Four groups were defined: no ischemic signs in either ECG; new ischemic signs in the second ECG; resolved ischemic signs in the second ECG; and persistent ischemic signs in both ECGs. Patients were followed for 2 years to assess the composite endpoint of all-cause-mortality, AMI, and coronary revascularization. Using a 30-day landmark analysis, a Cox regression with ischemic signs as the variable of interest, adjusted by cardiovascular risk factors, was calculated. Of 1675 patients, 1321 showed no ischemic signs, in 25 new-, in 92 resolved- and in 237 patients, persistent ischemic signs were documented. Patients with persistent ischemic signs had significantly worse outcomes, compared to those without. Compared to no ischemic signs, adjusted hazard ratios for the combined endpoint were 0.81 (95% CI 0.20, 3.31; p-value = 0.77) for new-, 0.59 (95% CI 0.26, 1.34; p-value = 0.21) for resolved-, and 1.47 (95% CI 1.102, 2.13; p-value = 0.041) for persistent ischemic signs. In patients with suspected AMI, persistent ischemic ECG-signs are predictive of a higher rate of all-cause-mortality, AMI, and revascularization.

Application of a machine learning-driven, multibiomarker panel for prediction of incident cardiovascular events in patients with suspected myocardial infarction.

Background: In patients with suspected myocardial infarction (MI), we sought to validate a machine learning-driven, multibiomarker panel for prediction of incident major adverse cardiovascular events (MACE). Methodology & results: A previously described prognostic panel for MACE consisting of four biomarkers was measured in 748 patients with suspected MI. The investigated end point was incident MACE within 1 year. The prognostic value of a continuous score and an optimal cut-off was investigated. The area under the curve was 0.86 for the overall model. Using the optimal cut-off resulted in a negative predictive value of 99.4% for incident MACE. Patients with an elevated prognostic score were at high risk for MACE. Conclusion: Among patients with suspected MI, we validated a multibiomarker panel for predicting 1-year MACE. Clinical Trial Registration: NCT02355457 (ClinicalTrials.gov).

Clinical application of the 4th Universal Definition of Myocardial Infarction.

AIMS: The recently released 4th version of the Universal Definition of Myocardial Infarction (UDMI) introduces an increased emphasis on the entities of acute and chronic myocardial injury. We applied the 4th UDMI retrospectively in patients presenting to the emergency department with symptoms potentially indicating myocardial infarction (MI) to investigate its effect on diagnosis and prognosis. METHODS AND RESULTS: We included 2302 patients presenting to the emergency department with symptoms suggestive of MI. The final diagnosis was adjudicated sequentially according to the 3rd and 4th UDMI. Reclassification after readjudication was assessed. Established diagnostic algorithms for patients with suspected MI were applied to compare diagnostic accuracy. All patients were followed to assess mortality, recurrent MI, revascularization, and rehospitalization to investigate the effect of the 4th UDMI on prognosis. After readjudication, 697 patients were reclassified. Most of these patients were reclassified as having acute (n = 78) and chronic myocardial injury (n = 585). Four hundred and thirty-four (18.9%) patients were diagnosed with MI, compared with 501 (21.8%) MIs when adjudication was based on the 3rd UDMI. In the non-MI population, patients with myocardial injury (n = 663) were older, more often female and had worse renal function compared with patients without myocardial injury (n = 1205). Application of diagnostic algorithms for patients with suspected MI revealed a high accuracy after readjudication. Reclassified patients had a substantially higher rate of cardiovascular events compared with not-reclassified patients, particularly patients reclassified to the category of myocardial injury. CONCLUSION: By accentuating the categories of acute and chronic myocardial injury the 4th UDMI succeeds to identify patients with higher risk for cardiovascular events and poorer outcome and thus seems to improve risk assessment in patients with suspected MI. Application of established diagnostic algorithms remains safe when using the 4th UDMI.