Mehta, Ramila A.

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.

Significance Statement Antibiotics modify human microbiomes and may contribute to kidney stone risk. In a population-based case-control study using 1247 chart-validated first-time symptomatic kidney stone formers and 4024 age- and sex-matched controls, the risk of kidney stones was transiently higher during the first year after antibiotic use. However, this risk was no longer evident after adjustment for comorbidities and excluding participants with prior urinary symptoms. Findings were consistent across antibiotic classes and the number of antibiotic courses received. This suggests that antibiotics are not important risk factors of kidney stones. Rather, kidney stones when they initially cause urinary symptoms are under-recognized, resulting in antibiotic use before a formal diagnosis of kidney stones ( i.e. , reverse causality). Background Antibiotics modify gastrointestinal and urinary microbiomes, which may contribute to kidney stone formation. This study examined whether an increased risk of a first-time symptomatic kidney stone episode follows antibiotic use. Methods A population-based case-control study surveyed 1247 chart-validated first-time symptomatic kidney stone formers with a documented obstructing or passed stone (cases) in Olmsted County, Minnesota, from 2008 to 2013 and 4024 age- and sex-matched controls. All prescriptions for outpatient oral antibiotic use within 5 years before the onset of symptomatic stone for the cases and their matched controls were identified. Conditional logistic regression estimated the odds ratio (OR) of a first-time symptomatic kidney stone across time after antibiotic use. Analyses were also performed after excluding cases and controls with prior urinary tract infection or hematuria because urinary symptoms resulting in antibiotic prescription could have been warranted because of undiagnosed kidney stones. Results The risk of a symptomatic kidney stone was only increased during the 1-year period after antibiotic use (unadjusted OR, 1.31; P = 0.001), and this risk was attenuated after adjustment for comorbidities (OR, 1.16; P = 0.08). After excluding cases and controls with prior urinary symptoms, there was no increased risk of a symptomatic kidney stone during the 1-year period after antibiotic use (unadjusted OR, 1.04; P = 0.70). Findings were consistent across antibiotic classes and the number of antibiotic courses received. Conclusions The increased risk of a first-time symptomatic kidney stone with antibiotic use seems largely due to both comorbidities and prescription of antibiotics for urinary symptoms. Under-recognition of kidney stones that initially cause urinary symptoms resulting in antibiotic use may explain much of the perceived stone risk with antibiotics ( i.e. , reverse causality).

Objectives This study aimed to evaluate the prevalence of obstetric and gynecologic (Ob/Gyn) hospitalists and determine if an association exists between the presence of Ob/Gyn hospitalists and severe maternal morbidity (SMM). Methods This observational study included data from hospitals listed in the USA TODAY’s 2019 article titled, “Deadly deliveries: Childbirth complication rates at maternity hospitals.” Telephone and email surveys of staff in these hospitals identified the presence or absence of continuous providers in the hospital 24 hours, 7 days a week (24/7 coverage) and the types of providers who are employed, then compared these responses with the SMM cited by USA TODAY. Results Eight hundred ten hospitals were contacted, with participation from 614 labor and delivery units for a response rate of 75.8%. Fifty-seven percent of units were staffed with 24/7 coverage, with 46% of hospitals’ coverage primarily provided by an Ob/Gyn hospitalist and 54% primarily by a nonhospitalist OB/Gyn provider. The SMM and presence of 24/7 coverage increased with the level of neonatal care and delivery volume. Of hospitals with 24/7 coverage, those that primarily used Ob/Gyn hospitalists had a lower SMM for all mothers (1.7 versus 2.0, P = 0.014) and for low-income mothers (1.9 versus 2.30, P = 0.007) than those who primarily used nonhospitalist OB/Gyn providers. Conclusions Severe maternal morbidity increases with delivery volume, level of neonatal care, and 24/7 coverage. Of hospitals with 24/7 coverage, units that staff with Ob/Gyn hospitalists have lower levels of SMM than those that use nonhospitalist Ob/Gyn providers.

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 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.

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.