Jaffe, Allan S.

Background The association between growth differentiation factor-15 concentrations and cardiovascular disease has been well described. The study hypothesis was that growth differentiation factor-15 may help cardiac risk stratification in noncardiac surgical patients, in addition to clinical evaluation. Methods The objective of the study was to determine whether preoperative serum growth differentiation factor-15 is associated with the composite primary outcome of myocardial injury after noncardiac surgery and vascular death at 30 days and can improve cardiac risk prediction in noncardiac surgery. This is a prospective cohort study of patients 45 yr or older having major noncardiac surgery. The association between preoperative growth differentiation factor-15 and the primary outcome was determined after adjusting for the Revised Cardiac Risk Index. Preoperative N-terminal-pro hormone brain natriuretic peptide was also added to compare predictive performance with growth differentiation factor-15. Results Between October 27, 2008, and October 30, 2013, a total of 5,238 patients were included who had preoperative growth differentiation factor-15 measured (median, 1,325; interquartile range, 880 to 2,132 pg/ml). The risk of myocardial injury after noncardiac surgery and vascular death was 99 of 1,705 (5.8%) for growth differentiation factor-15 less than 1,000 pg/ml, 161 of 1,332 (12.1%) for growth differentiation factor-15 1,000 to less than 1,500 pg/ml, 302 of 1476 (20.5%) for growth differentiation factor-15 1,500 to less than 3,000 pg/ml, and 247 of 725 (34.1%) for growth differentiation factor-15 concentrations 3,000 pg/ml or greater. Compared to patients who had growth differentiation factor-15 concentrations less than 1,000 pg/ml, the corresponding adjusted hazard ratio for each growth differentiation factor-15 category was 1.93 (95% CI, 1.50 to 2.48), 3.04 (95% CI, 2.41 to 3.84), and 4.8 (95% CI, 3.76 to 6.14), respectively. The addition of growth differentiation factor-15 improved cardiac risk classification by 30.1% (301 per 1,000 patients) compared to Revised Cardiac Risk Index alone. It also provided additional risk classification beyond the combination of preoperative N-terminal-pro hormone brain natriuretic peptide and Revised Cardiac Risk Index (16.1%; 161 per 1,000 patients). Conclusions Growth differentiation factor-15 is strongly associated with 30-day risk of major cardiovascular events and significantly improved cardiac risk prediction in patients undergoing noncardiac surgery. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Abstract The International Federation of Clinical Chemistry Committee on Clinical Applications of Cardiac Biomarkers (IFCC C-CB) provides educational documents to facilitate the interpretation and use of cardiac biomarkers in clinical laboratories and practice. Our aim is to improve the understanding of certain key analytical and clinical aspects of cardiac biomarkers and how these may interplay. Measurements of cardiac troponin (cTn) have a prominent place in the clinical work-up of patients with suspected acute coronary syndrome. It is therefore important that clinical laboratories know how to recognize and assess analytical issues. Two emerging analytical issues resulting in falsely high cTn concentrations, often several fold higher than the upper reference limit (URL), are antibody-mediated assay interference due to long-lived cTn-antibody complexes, called macrotroponin, and crosslinking antibodies that are frequently referred to as heterophilic antibodies. We provide an overview of antibody-mediated cTn assay interference and provide recommendations on how to confirm the interference and interpret the results.

Cardiovascular biomarkers play a major diagnostic role for cardiologists. Different biomarkers provide different insights into a variety of cardiovascular conditions and in doing so they improve diagnosis and management. Often, these biomarkers are deployed without carefully evaluating the use of sex-specific cut off values. It is now becoming apparent that the use of such cut off values can improve prognostication and discrimination in some clinical situations. This review paper will focus on the data indicating that there is benefit to the use of sex-specific thresholds. It should be clear that these thresholds will vary depending on the analyte being measured and the specific clinical indication for which the patients are being evaluated; and sex-specific cut off values may be important in some situations but not others. Nonetheless, it is now clear that when evaluating sex-specific cut off values, one often finds benefit. We will highlight these situations using specific cardiac biomarkers as examples.

Abstract Background Myocardial injury after non-cardiac surgery (MINS), based on measurement of troponin T, is associated with perioperative major adverse cardiovascular events (MACE). We therefore determined the high-sensitivity troponin I (hsTnI) thresholds associated with 30 day MACE after non-cardiac surgery. Methods We performed a nested biobank cohort study of 4553 patients from the Vascular Events in Non-Cardiac Surgery Patients Cohort Evaluation (VISION) Study. We measured hsTnI (ADVIA Centaur® hsTnI assay) on postoperative days 1 to 3 in patients ≥45 years undergoing non-cardiac surgery. An iterative Cox proportional hazard model determined peak postoperative hsTnI thresholds independently associated with MACE (i.e., death, myocardial infarction occurring on postoperative day 4 or after, non-fatal cardiac arrest, or congestive heart failure) within 30 days after surgery. Results MACE occurred in 89/4545 (2.0%) patients. Peak hsTnI values of <75 ng/L, 75 ng/L to <1000 ng/L, and ≥1000 ng/L were associated with 1.2% (95% CI, 0.9–1.6), 7.1% (95% CI, 4.8–10.5), and 25.9% (95% CI, 16.3–38.4) MACE, respectively. Compared to peak hsTnI <75 ng/L, values 75 ng/L to <1000 ng/L and ≥1000 ng/L were associated with adjusted hazard ratios (aHR) of 4.53 (95% CI, 2.75–7.48) and 16.17 (95% CI, 8.70–30.07), respectively. MACE was observed in 9% of patients with peak hsTnI ≥75 ng/L vs 1% in patients with peak hsTnI <75 ng/L (aHR 5.76; 95% CI, 3.64–9.11). A peak hsTnI ≥75 ng/L was associated with MACE in the presence (aHR 9.35; 95% CI, 5.28–16.55) or absence (aHR 3.99; 95% CI, 2.19–7.25) of ischemic features of myocardial injury. Conclusion A peak postoperative hsTnI ≥75 ng/L was associated with >5-fold increase in the risk of 30 days MACE compared to levels <75 ng/L. This threshold could be used for MINS diagnosis when the ADVIA Centaur hsTnI assay is used. Clinicaltrials.gov Registration Number: NCT00512109.

Abstract The International Federation of Clinical Chemistry and Laboarator Medicine (IFCC) Committee on Clinical Applications of Cardiac Bio-Markers (C-CB) has provided evidence-based educational resources to aid and improve the understanding of important analytical and clinical aspects of cardiac biomarkers. The present IFCC C-CB educational report focuses on recommendations for appropriate use, analytical performance, and gaps in clinical studies related to the use of cardiac troponin (cTn) by point of care (POC) measurement, often referred to as a point of care testing (POCT). The use of high-sensitivity (hs)-cTn POC devices in accelerated diagnostic protocols used in emergency departments or outpatient clinics investigating acute coronary syndrome has the potential for improved efficacy, reduction of length of stay and reduced costs in the health care system. POCT workflow integration includes location of the instrument, assignment of collection and testing responsibility to (non-lab) staff, instrument maintenance, in-service and recurrent training, quality control, proficiency assessments, discrepant result trapping, and troubleshooting and inventory management.

Abstract Aims Our goal was to evaluate a previously validated artificial intelligence–augmented electrocardiography (AI-ECG) screening tool for left ventricular systolic dysfunction (LVSD) in patients undergoing high-sensitivity-cardiac troponin T (hs-cTnT). Methods and results Retrospective application of AI-ECG for LVSD in emergency department (ED) patients undergoing hs-cTnT. AI-ECG scores (0–1) for probability of LVSD (left ventricular ejection fraction ≤ 35%) were obtained. An AI-ECG score ≥0.256 indicates a positive screen. The primary endpoint was a composite of post-discharge major adverse cardiovascular events (MACEs) at two years follow-up. Among 1977 patients, 248 (13%) had a positive AI-ECG. When compared with patients with a negative AI-ECG, those with a positive AI-ECG had a higher risk for MACE [48 vs. 21%, P < 0.0001, adjusted hazard ratio (HR) 1.39, 95% confidence interval (CI) 1.11–1.75]. This was largely because of a higher rate of deaths (32 vs. 14%, P < 0.0001; adjusted HR 1.26, 95% 0.95–1.66) and heart failure hospitalizations (26 vs. 6.1%, P < 0.001; adjusted HR 1.75, 95% CI 1.25–2.45). Together, hs-cTnT and AI-ECG resulted in the following MACE rates and adjusted HRs: hs-cTnT < 99th percentile and negative AI-ECG: 116/1176 (11%; reference), hs-cTnT < 99th percentile and positive AI-ECG: 28/107 (26%; adjusted HR 1.54, 95% CI 1.01–2.36), hs-cTnT > 99th percentile and negative AI-ECG: 233/553 (42%; adjusted HR 2.12, 95% CI 1.66, 2.70), and hs-cTnT > 99th percentile and positive AI-ECG: 91/141 (65%; adjusted HR 2.83, 95% CI 2.06, 3.87). Conclusion Among ED patients evaluated with hs-cTnT, a positive AI-ECG for LVSD identifies patients at high risk for MACE. The conjoint use of hs-cTnT and AI-ECG facilitates risk stratification.

New more effective lipid-lowering therapies have made it important to accurately determine Low-density lipoprotein-cholesterol (LDL-C) at both high and low levels. LDL-C was measured by the β-quantification reference method (BQ) (N = 40,346) and compared to Friedewald (F-LDL-C), Martin (M-LDL-C), extended Martin (eM-LDL-C) and Sampson (S-LDL-C) equations by regression analysis, error-grid analysis, and concordance with the BQ method for classification into different LDL-C treatment intervals. For triglycerides (TG) < 175 mg/dL, the four LDL-C equations yielded similarly accurate results, but for TG between 175 and 800 mg/dL, the S-LDL-C equation when compared to the BQ method had a lower mean absolute difference (mg/dL) (MAD = 10.66) than F-LDL-C (MAD = 13.09), M-LDL-C (MAD = 13.16) or eM-LDL-C (MAD = 12.70) equations. By error-grid analysis, the S-LDL-C equation for TG > 400 mg/dL not only had the least analytical errors but also the lowest frequency of clinically relevant errors at the low (<70 mg/dL) and high (>190 mg/dL) LDL-C cut-points (S-LDL-C: 13.5%, F-LDL-C: 23.0%, M-LDL-C: 20.5%) and eM-LDL-C: 20.0%) equations. The S-LDL-C equation also had the best overall concordance to the BQ reference method for classifying patients into different LDL-C treatment intervals. The S-LDL-C equation is both more analytically accurate than alternative equations and results in less clinically relevant errors at high and low LDL-C levels.

Abstract Background Artificial intelligence-augmented electrocardiogram (AI-ECG) algorithms have been developed from the standard 12-lead ECG and validated for the recognition of left ventricular systolic dysfunction (LVSD), defined as LV ejection fraction (LVEF)≤35%. Whether AI-ECG facilitates identification of LVSD and is associated with adverse outcomes in emergency department (ED) patients undergoing high-sensitivity cardiac troponin (hs-cTnT) testing is uncertain. Purpose To investigate the diagnostic and prognostic performance of AI-ECG in ED patients undergoing hs-cTnT measurement. Methods Observational US cohort study of ED patients undergoing hs-cTnT measurement. Cases with hs-cTnT increases &gt;sex-specific 99th percentiles were adjudicated following the Fourth Universal Definition of Myocardial Infarction (MI). Post-discharge major adverse cardiac events (MACE) included death, MI, heart failure (HF) hospitalization, stroke or transient ischemic attack, and new onset atrial fibrillation/flutter during 2-years follow-up. The AI-ECG network output, which is a continuous number between 0–1, that provides a probability of LVSD, was obtained for each patient from the first ECG during the index presentation. An AI-ECG threshold of ≥0.256 indicates a positive screen that correlates with a high probability of LVSD. Results Among 1977 patients, 1729 (87%) had a negative AI-ECG screen, while 248 (13%) had a positive AI-ECG screen. Patients with a positive AI-ECG screen were older and had more comorbidities. As compared to patients with hs-cTnT≤99th percentile in whom AI-ECG was positive in 5.8%, those with hs-cTnT&gt;99th percentile had a positive AI-ECG in 22% of cases (p&lt;0.0001). Based on adjudicated diagnoses, the frequency of a positive AI-ECG was 20% in myocardial injury, 38% in type 1 MI, and 20% in type 2 MI. At 2-years follow-up, as compared to patients with a negative AI-ECG, those with a positive AI-ECG had a higher risk for MACE (48% vs. 21%, p&lt;0.0001, adjusted HR 1.39, 95% CI 1.11–1.75) (Figure 1), mainly because of more deaths (43% vs. 30%, p=0.004) and HF hospitalizations (36% vs. 13%, p&lt;0.0001). A positive AI-ECG was associated with a higher risk for MACE (60% vs. 41%, p&lt;0.0001, adjusted HR 1.30, 95% CI 1.02–1.64) in those with hs-cTnT increases &gt;99th percentile, but not in those without hs-cTnT increases. Among patients with an echocardiogram during index presentation or within 30-days (n=452), the diagnostic accuracy of AI-ECG for LVEF ≤35% was 81.4% (95% CI 77.5, 84.9) with a negative predictive value of 96.5% (95% CI 94.0, 98.2). A normal LVEF (&gt;50%) was observed in 87% of those with a negative AI ECG, whereas in those with a positive AI-ECG LVEF was reduced (&lt;50%) in 60%. Conclusions Among ED patients evaluated with hs-cTnT, a positive AI-ECG screen for LVSD identifies patients at high risk of MACE. These findings are largely because of more deaths and HF hospitalizations in those with hs-cTnT increases &gt;sex-specific 99th percentiles. Funding Acknowledgement Type of funding sources: None.