Ola, Olatunde

Abstract Aims Diagnosing myocardial infarction (MI) in patients with chronic kidney disease (CKD) is difficult as they often have increased high-sensitivity cardiac troponin T (hs-cTnT) concentrations. Methods and results Observational US cohort study of emergency department patients undergoing hs-cTnT measurement. Cases with ≥1 hs-cTnT increase > 99th percentile were adjudicated following the Fourth Universal Definition of MI. Diagnostic performance of baseline and serial 2 h hs-cTnT thresholds for ruling-in acute MI was compared between those without and with CKD (estimated glomerular filtration rate < 60 mL/min/1.73 m2). The study cohort included 1992 patients, amongst whom 501 (25%) had CKD. There were 75 (15%) and 350 (70%) patients with CKD and 80 (5%) and 351 (24%) without CKD who had acute MI and myocardial injury. In CKD patients with baseline hs-cTnT thresholds of ≥52, >100, >200, or >300 ng/L, positive predictive values (PPVs) for MI were 36% (95% CI 28–45), 53% (95% CI 39–67), 73% (95% CI 50–89), and 80% (95% CI 44–98), and in those without CKD, 61% (95% CI 47–73), 69% (95% CI 49–85), 59% (95% CI 33–82), and 54% (95% CI 25–81). In CKD patients with a 2 h hs-cTnT delta of ≥10, >20, or >30 ng/L, PPVs were 66% (95% CI 51–79), 86% (95% CI 68–96), and 88% (95% CI 68–97), and in those without CKD, 64% (95% CI 50–76), 73% (95% CI 57–86), and 75% (95% CI 58–88). Conclusion Diagnostic performance of standard baseline and serial 2 h hs-cTnT thresholds to rule-in MI is suboptimal in CKD patients. It significantly improves when using higher baseline thresholds and delta values.

Background: The 2021 ACC/AHA chest pain guidelines recommend risk scores such as HEAR (History, Electrocardiogram, Age, Risk Factors) for short term risk-stratification yet limited data exists integrating them with high-sensitivity cardiac troponin T (hs-cTnT). Methods: Retrospective, multicenter (n=2), observational, U.S. cohort study of consecutive ED patients without ST-elevation myocardial infarction (MI) who had at least one hs-cTnT (limit of quantitation, LoQ, <6 ng/L, and sex-specific 99 th percentiles of 10 ng/L for women and 15 ng/L for men) measurement on clinical indication in whom HEAR scores (0-8) were calculated. The composite major adverse cardiovascular (MACE) outcome was 30-day MI and death. Results: Among 1,979 ED patients undergoing hs-cTnT measurement, 1045 (53%) were classified as low-risk (0-3), 914 (46%) as intermediate-risk (4-6), and 20 (1%) as high-risk (7-8) based on HEAR scores. HEAR scores were not associated with an increased risk of 30-day MACE after adjusted analyses. Outcomes according to risk-strata based on HEAR scores and baseline hs-cTnT are shown in Table 1. Patients with quantifiable hs-cTnT (LoQ-99 th ) had an increased risk for 30-day MACE (3.4%) despite being estimated to be low-risk (0-3) per HEAR scores. Conversely, those with serial hs-cTnT<99 th percentile remained at low-risk (range 0% to 1.2%) for 30-day MACE across HEAR score strata. Conclusions: HEAR scores are of limited value in those with baseline hs-cTnT<LoQ or hs-cTnT>99 th percentile where hs-cTnT identifies very low and high-risk patients irrespective of HEAR scores. In those with baseline quantifiable hs-cTnT within the reference range (<99 th percentile), a higher risk (>1%) for 30-day MACE exists even in those with low HEAR scores. With serial hs-cTnT measurements, HEAR scores overestimate risk when hs-cTnT remains <99 th percentile.

Introduction: Differentiating type 2 myocardial infarction (T2MI) from myocardial injury can be difficult. The presence of objective evidence of acute myocardial ischemia may facilitate the identification of high-risk T2MI patients. Methods: Retrospective, observational cohort post-hoc analysis of adult emergency department patients undergoing hs-cTnT measurement. Patients with ≥1 hs-cTnT>99th percentile were adjudicated following the Fourth Universal Definition of MI. Patients were categorized as “subjective T2MI” when ischemic symptoms were the lone criteria supporting T2MI, or “objective T2MI” when there was ≥1 objective clinical feature (electrocardiography, imaging, angiography) of acute myocardial ischemia. The primary outcome was mortality. Results: A total of 857 patients were included, amongst which 55 (6.4%) were classified as subjective T2MI, 36 (4.2%) as objective T2MI, and 702 (82%) as myocardial injury. Among objective T2MIs, the most common criteria were ischemic electrocardiographic changes (n=29). Median (IQR) maximum hs-cTnT were 24 (18, 43) ng/L in myocardial injury, 34 (19, 80) in subjective T2MI, and 74 (35, 237) in objective T2MI. Those with objective T2MI had a higher risk of mortality during the index presentation (17% vs. 1.7%, p<0.0001; HR 11.1 95% CI 3.7-33.4) and at 2-year follow-up (47% vs. 31%, p=0.04; HR 1.92, 95% CI 1.17-3.14) than those with myocardial injury (Figure). Objective T2MI had a higher mortality than subjective T2MI at index presentation (17% vs. 2.0%, p=0.01) and at 1- (25% vs. 9.1%, p=0.04) and 3-months (31% vs. 13%, p=0.04) follow-up. There were no mortality differences between subjective T2MI and myocardial injury. Conclusions: In patients diagnosed with T2MI, those with objective evidence of myocardial ischemia have significantly worse outcomes compared to those with myocardial injury and subjective T2MI. A more rigorous definition of T2MI might be a more effective way to define this important entity.

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 &lt; 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 &lt; 0.0001; adjusted HR 1.26, 95% 0.95–1.66) and heart failure hospitalizations (26 vs. 6.1%, P &lt; 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 &lt; 99th percentile and negative AI-ECG: 116/1176 (11%; reference), hs-cTnT &lt; 99th percentile and positive AI-ECG: 28/107 (26%; adjusted HR 1.54, 95% CI 1.01–2.36), hs-cTnT &gt; 99th percentile and negative AI-ECG: 233/553 (42%; adjusted HR 2.12, 95% CI 1.66, 2.70), and hs-cTnT &gt; 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.

Abstract Aims Limited US outcome data exist among patients with myocardial injury and types 1 and 2 myocardial infarction (MI) evaluated with high-sensitivity cardiac troponin (hs-cTn). Methods and results This is an observational US cohort study of emergency department (ED) patients undergoing hs-cTnT measurement. Cases with ≥1 hs-cTnT increase &gt;99th percentile were adjudicated following the Fourth Universal Definition of MI. Post-discharge major adverse cardiovascular events (MACE) included death, MI, heart failure (HF) hospitalization, stroke or transient ischaemic attack, and new-onset atrial fibrillation or flutter during 2 years follow-up. Among 2002 patients, 857 (43%) had ≥1 hs-cTnT &gt;99th percentile. Among these, 702 (81.9%) had myocardial injury, 64 (7.5%) had type 1 MI, and 91 (10.6%) had type 2 MI. Compared with patients without myocardial injury, type 2 MI [8.4 vs. 50%; adjusted hazard ratio (HR) 2.31, 95% confidence interval (CI) 1.49–3.58] and myocardial injury (8.4 vs. 47%; adjusted HR 3.13, 95% CI 2.39–4.09) had a higher risk of MACE, in large part because of death and HF hospitalizations. Compared with patients with type 1 MI, type 2 MI (23 vs. 50%; adjusted HR 2.24; 95% CI 1.23–4.10) and myocardial injury (23 vs. 47%; adjusted HR 2.02; 95% CI 1.20–3.40) also have a higher risk of MACE. Conclusion Among unselected US ED patients undergoing hs-cTnT measurement, most increases are due to myocardial injury, and type 2 MI is more frequent than type 1 MI. Patients with myocardial injury and type 2 MI have morbid outcomes, in large part due to death and HF.

Background: There are good data to support using a single high-sensitivity cardiac troponin T (hs-cTnT) below the limit of detection of 5 ng/L to exclude acute myocardial infarction. Per the US Food and Drug Administration, hs-cTnT can only report to the limit of quantitation of 6 ng/L, a threshold for which there are limited data. Our goal was to determine whether a single hs-cTnT below the limit of quantitation of 6 ng/L is a safe strategy to identify patients at low risk for acute myocardial injury and infarction. Methods: The efficacy (proportion identified as low risk based on baseline hs-cTnT<6 ng/L) of identifying low-risk patients was examined in a multicenter (n=22 sites) US cohort study of emergency department patients undergoing at least 1 hs-cTnT (CV Data Mart Biomarker cohort). We then determined the performance of a single hs-cTnT<6 ng/L (biomarker alone) to exclude acute myocardial injury (subsequent hs-cTnT >99th percentile in those with an initial hs-cTnT<6 ng/L). The clinically intended rule-out strategy combining a nonischemic ECG with a baseline hs-cTnT<6 ng/L was subsequently tested in an adjudicated cohort in which the diagnostic performance for ruling out acute myocardial infarction and safety (myocardial infarction or death at 30 days) were evaluated. Results: A total of 85 610 patients were evaluated in the CV Data Mart Biomarker cohort, among which 24 646 (29%) had a baseline hs-cTnT<6 ng/L. Women were more likely than men to have hs-cTnT<6 ng/L (38% versus 20%, P <0.0001). Among 11 962 patients with baseline hs-cTnT<6 ng/L and serial measurements, only 1.2% developed acute myocardial injury, resulting in a negative predictive value of 98.8% (95% CI, 98.6–99.0) and sensitivity of 99.6% (95% CI, 99.5–99.6). In the adjudicated cohort, a nonischemic ECG with hs-cTnT<6 ng/L identified 33% of patients (610/1849) as low risk and resulted in a negative predictive value and sensitivity of 100% and a 30-day rate of 0.2% for myocardial infarction or death. Conclusions: A single hs-cTnT below the limit of quantitation of 6 ng/L is a safe and rapid method to identify a substantial number of patients at very low risk for acute myocardial injury and infarction.

Abstract Background Limited data exist on high-sensitivity cardiac troponin (hs-cTn) for risk-stratification in COVID-19. Methods We conducted a multicenter, retrospective, observational, US-based study of COVID-19 patients undergoing hs-cTnT. Outcomes included short-term mortality (in-hospital and 30-days post-discharge) and a composite of major adverse events, including respiratory failure requiring mechanical ventilation, cardiac arrest, and shock within the index presentation and/or mortality during the index hospitalization or within 30-days post-discharge. Results Among 367 COVID-19 patients undergoing hs-cTnT, myocardial injury was identified in 46%. They had a higher risk for mortality (20% vs 12%, P &lt; 0.0001; unadjusted HR 4.44, 95% CI 2.13–9.25, P &lt; 0.001) and major adverse events (35% vs. 11%, P &lt; 0.0001; unadjusted OR 4.29, 95% CI 2.50–7.40, P &lt; 0.0001). Myocardial injury was associated with major adverse events (adjusted OR 3.84, 95% CI 2.00–7.36, P &lt; 0.0001) but not mortality. Baseline (adjusted OR 1.003, 95% CI 1.00–1.007, P = 0.047) and maximum (adjusted OR 1.005, 95% CI 1.001–1.009, P = 0.0012) hs-cTnT were independent predictors of major adverse events. Most (95%) increases were due to myocardial injury, with 5% (n = 8) classified as type 1 or 2 myocardial infarction. A single hs-cTnT &lt;6 ng/L identified 26% of patients without mortality, with a 94.9% (95% CI 87.5–98.6) negative predictive value and 93.1% sensitivity (95% CI 83.3–98.1) for major adverse events in those presenting to the ED. Conclusions Myocardial injury is frequent and prognostic in COVID-19. While most hs-cTnT increases are modest and due to myocardial injury, they have important prognostic implications. A single hs-cTnT &lt;6 ng/L at presentation may facilitate the identification of patients with a favorable prognosis.

Abstract Background: The prevalence of electronic cigarette (e-cigarette) use and its impact on smoking cessation among cancer survivors in the United States is largely unknown. We sought to estimate the prevalence of e-cigarette use and examine its associations with cigarette smoking and smoking quit attempts among smoking-related cancer survivors in the United States. Methods: We obtained data from the 2014–2017 annual cycles of the National Health Interview Survey for participants with self-reported history of smoking-related cancer(s). We calculated the prevalence of current e-cigarette use and utilized multinomial logistic regression in examining the independent association between e-cigarette use and cigarette smoking. Appropriate survey weights were applied in estimating the prevalence rates, relative risk ratios (RRR), ORs, and confidence intervals (CI). Results: Our sample comprised 3,162 smoking-related cancer survivors. The prevalence of current e-cigarette use was 3.18% (95% CI, 2.40–3.96). Current e-cigarette users were 83 times as likely as never users to be current cigarette smokers (RRR, 82.89; 95% CI, 16.54–415.37). Among those with a history of cigarette smoking, current e-cigarette users were 90% less likely to be former smokers (OR, 0.10; 95% CI, 0.05–0.18). No association was seen between current e-cigarette use and a smoking quit attempt in the prior year. Conclusions: E-cigarette use among cigarette ever smokers was associated with a lower likelihood of being a former smoker/having quit smoking, and e-cigarette use was not associated with smoking quit attempts. Impact: Our findings do not provide evidence that e-cigarette use facilitates smoking cessation among smoking-related cancer survivors.