Outcomes among patients admitted for non-ST-segment myocardial infarction in the pre-pandemic and pandemic COVID-19 era: Israel Nationwide study.

BACKGROUND: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic in 2019, several countries have reported a substantial drop in the number of patients admitted with non-ST-segment myocardial infarction (NSTEMI). OBJECTIVE: We aimed to evaluate the changes in admissions, in-hospital management and outcomes of patients with NSTEMI in the COVID-19 era in a nationwide survey. METHOD: A prospective, multicenter, observational, nationwide study involving 13 medical centers across Israel aimed to evaluate consecutive patients with NSTEMI admitted to intensive cardiac care units over an 8-week period during the COVID-19 outbreak and to compare them with NSTEMI patients admitted at the same period 2 years earlier (control period). RESULTS: There were 624 (43%) NSTEMI patients, of whom 349 (56%) were hospitalized during the COVID-19 era and 275 (44%) during the control period. There were no significant differences in age, gender and other baseline characteristics between the two study periods. During the COVID-19 era, more patients arrived at the hospital via an emergency medical system compared with the control period (P = 0.05). Time from symptom onset to hospital admission was longer in the COVID-19 era as compared with the control period [11.5 h (interquartile range, IQR, 2.5-46.7) vs. 2.9 h (IQR 1.7-6.8), respectively, P < 0.001]. Nevertheless, the time from hospital admission to reperfusion was similar in both groups. The rate of coronary angiography was also similar in both groups. The in-hospital mortality rate was similar in both the COVID-19 era and the control period groups (2.3% vs. 4.7%, respectively, P = 0.149) as was the 30-day mortality rate (3.7% vs. 5.1%, respectively, P = 0.238). CONCLUSION: In contrast to previous reports, admission rates of NSTEMI were similar in this nationwide survey during the COVID-19 era. With longer time from symptoms to admission, but with the same time from hospital admission to reperfusion therapy and with similar in-hospital and 30-day mortality rates. Even in times of crisis, adherence of medical systems to clinical practice guidelines ensures the preservation of good clinical outcomes.

Comparison Between Echocardiography and Cardiac Computed Tomography in the Evaluation of Diastolic Dysfunction and Prediction of Heart Failure.

Recent data indicate that left atrial (LA) function assessment by cardiac computed tomography (CT) is closely related to diastolic dysfunction (DD). Therefore, we aimed to perform a direct comparison between CT and echocardiography for diagnosis of advanced DD and prediction of future heart failure or cardiovascular death. We identified 340 patients who had both spiral cardiac CT and a proximate echocardiogram. LA total emptying fraction (LATEF), a measure of global LA function, was automatically calculated from CT data, as a surrogate for diastolic function and was compared with echocardiographic grades of diastolic function. The area under the receiver operating characteristic curve for LATEF to differentiate between advanced DD (grades 2 and 3) and all other grades was 0.84 (0.79 to 0.88). Over a median of 4 years, 69 events (admissions for heart failure and cardiovascular deaths) occurred. By multivariate Cox analysis, LATEF <40% provided incremental prognostic information after adjustments for advanced DD by echocardiography (hazard ratio 2.15, 95% confidence interval 1.13 to 3.94). There was a significant interaction (p = 0.03) between LATEF and echocardiography-based diastolic grades. Stratified analyses within the diastolic function groups revealed that LATEF <40% was equivalent to echocardiography in predicting events in the subgroup with advanced DD by echocardiography (p = 0.20) but was associated with a significantly higher event rates in patients with normal filling pressures (p = 0.0001) or indeterminate diastolic function (p = 0.04) by echocardiography. In conclusion, LA function derived from CT can accurately detect advanced DD diagnosed by echocardiography and has additive value to echocardiography-derived DD.

Left atrial function by cardiac computed tomography is a predictor of heart failure and cardiovascular death.

OBJECTIVES: We sought to evaluate cardiac CT angiography (CCTA)-based assessment of left atrial (LA) function as a predictor of hospitalizations for heart failure (HF) and cardiovascular (CV) mortality. METHODS: LA function was evaluated using automatic derivation of LA volumes to calculate LA total emptying fraction (LATEF) in 788 consecutive patients with normal sinus rhythm who had undergone spiral CT scans. The relationship between LATEF evaluated by CCTA and the composite endpoint of admission for HF or CV mortality was analyzed using Cox models. RESULTS: During a median follow-up of 4 years, there were 100 events, 62 HF hospitalizations, and 38 cardiovascular deaths. Mean LATEF was 30.7 ± 10.7% and 40.5 ± 11.2% in patients with and without events, respectively (p < 0.0001). A high LATEF (upper tertile > 46%) was associated with a very low event rate (3.5% at 6 years [95% CI 1.7-7.1%]). The adjusted HR for HF or CV mortality was 4.37 (95% CI 1.99-9.60) in the lowest LATEF tertile, and 2.29 (95% CI 1.03-5.14) in the middle tertile, relative to the highest tertile. For the endpoint of HF alone, adjusted HR for the lowest LATEF tertile was 5.93 (95% CI 2.23-15.82) and for the middle tertile 2.89 (95% CI 1.06-7.86). The association of LATEF with outcome was similar for patients with both reduced and preserved left ventricular (LV) ejection fraction (Pinteraction = 0.724). Reduced LATEF was associated with a high event rate, even when coupled with normal LA volume. CONCLUSION: CCTA-derived LA function is a predictor of HF hospitalization or CV death, independent of clinical risk factors, LA volume, and LV systolic function. KEY POINTS: • Left atrial function can be automatically derived from cardiac CTA scans. • Cardiac CTA-derived left atrial function is a predictor of hospitalization for heart failure and cardiovascular death. • Evaluation of left atrial function could be useful in identifying patients at risk of heart failure.

Acute myocardial infarction in the Covid-19 era: Incidence, clinical characteristics and in-hospital outcomes-A multicenter registry.

BACKGROUND: We aimed to describe the characteristics and in-hospital outcomes of ST-segment elevation myocardial infarction (STEMI) patients during the Covid-19 era. METHODS: We conducted a prospective, multicenter study involving 13 intensive cardiac care units, to evaluate consecutive STEMI patients admitted throughout an 8-week period during the Covid-19 outbreak. These patients were compared with consecutive STEMI patients admitted during the corresponding period in 2018 who had been prospectively documented in the Israeli bi-annual National Acute Coronary Syndrome Survey. The primary end-point was defined as a composite of malignant arrhythmia, congestive heart failure, and/or in-hospital mortality. Secondary outcomes included individual components of primary outcome, cardiogenic shock, mechanical complications, electrical complications, re-infarction, stroke, and pericarditis. RESULTS: The study cohort comprised 1466 consecutive acute MI patients, of whom 774 (53%) were hospitalized during the Covid-19 outbreak. Overall, 841 patients were diagnosed with STEMI: 424 (50.4%) during the Covid-19 era and 417 (49.6%) during the parallel period in 2018. Although STEMI patients admitted during the Covid-19 period had fewer co-morbidities, they presented with a higher Killip class (p value = .03). The median time from symptom onset to reperfusion was extended from 180 minutes (IQR 122-292) in 2018 to 290 minutes (IQR 161-1080, p < .001) in 2020. Hospitalization during the Covid-19 era was independently associated with an increased risk of the combined endpoint in the multivariable regression model (OR 1.65, 95% CI 1.03-2.68, p value = .04). Furthermore, the rate of mechanical complications was four times higher during the Covid-19 era (95% CI 1.42-14.8, p-value = .02). However, in-hospital mortality remained unchanged (OR 1.73, 95% CI 0.81-3.78, p-value = .16). CONCLUSIONS: STEMI patients admitted during the first wave of Covid-19 outbreak, experienced longer total ischemic time, which was translated into a more severe disease status upon hospital admission, and a higher rate of in-hospital adverse events, compared with parallel period.

The impact of lockdown enforcement during the SARSCoV-2 pandemic on the timing of presentation and early outcomes of patients with ST-elevation myocardial infarction.

INTRODUCTION: Early reports described decreased admissions for acute cardiovascular events during the SarsCoV-2 pandemic. We aimed to explore whether the lockdown enforced during the SARSCoV-2 pandemic in Israel impacted the characteristics of presentation, reperfusion times, and early outcomes of ST-elevation myocardial infarction (STEMI) patients. METHODS: A multicenter prospective cohort comprising all STEMI patients treated by primary percutaneous coronary intervention admitted to four high-volume cardiac centers in Israel during lockdown (20/3/2020-30/4/2020). STEMI patients treated during the same period in 2019 served as controls. RESULTS: The study comprised 243 patients, 107 during the lockdown period of 2020 and 136 during the same period in 2019, with no difference in demographics and clinical characteristics. Patients admitted in 2020 had higher admission and peak troponin levels, had a 2.4 fold greater likelihood of Door-to-balloon times> 90 min (95%CI: 1.2-4.9, p = 0.01) and 3.3 fold greater likelihood of pain-to-balloon times> 12 hours (OR 3.3, 95%CI: 1.3-8.1, p<0.01). They experienced higher rates hemodynamic instability (25.2% vs 14.7%, p = 0.04), longer hospital stay (median, IQR [4, 3-6 Vs 5, 4-6, p = 0.03]), and fewer early (<72 hours) discharge (12.4% Vs 32.4%, p<0.001). CONCLUSIONS: The lockdown imposed during the SARSCoV-2 pandemic was associated with a significant lag in the time to reperfusion of STEMI patients. Measures to improves this metric should be implemented during future lockdowns.

Machine learning for nocturnal mass diagnosis of atrial fibrillation in a population at risk of sleep-disordered breathing.

OBJECTIVE: In this research, we introduce a new methodology for atrial fibrillation (AF) diagnosis during sleep in a large population sample at risk of sleep-disordered breathing. APPROACH: The approach leverages digital biomarkers and recent advances in machine learning (ML) for mass AF diagnosis from overnight-hours of single-channel electrocardiogram (ECG) recording. Four databases, totaling n = 3088 patients and p = 26 913 h of continuous single-channel electrocardiogram raw data were used. Three of the databases (n = 125, p = 2513) were used for training a ML model in recognizing AF events from beat-to-beat time series. Visit 1 of the sleep heart health study database (SHHS1, n = 2963, p = 24 400) was used as the test set to evaluate the feasibility of identifying prominent AF from polysomnographic recordings. By combining AF diagnosis history and a cardiologist's visual inspection of individuals suspected of having AF (n = 118), a total of 70 patients were diagnosed with prominent AF in SHHS1. MAIN RESULTS: Model prediction on SHHS1 showed an overall [Formula: see text]and [Formula: see text] in classifying individuals with or without prominent AF. [Formula: see text] was non-inferior (p = 0.03) for individuals with an apnea-hypopnea index (AHI) ≥15 versus AHI < [Formula: see text]. Over 22% of correctly identified prominent AF rhythm cases were not previously documented as AF in SHHS1. SIGNIFICANCE: Individuals with prominent AF can be automatically diagnosed from an overnight single-channel ECG recording, with an accuracy unaffected by the presence of moderate-to-severe obstructive sleep apnea. This approach enables identifying a large proportion of AF individuals that were otherwise missed by regular care.