Veno-Arterial Extracorporeal Membrane Oxygenation in Patients with Fulminant Myocarditis: A Review of Contemporary Literature.

Fulminant myocarditis is characterized by life threatening heart failure presenting as cardiogenic shock requiring inotropic or mechanical circulatory support to maintain tissue perfusion. There are limited data on the role of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) in the management of fulminant myocarditis. This review seeks to evaluate the management of fulminant myocarditis with a special emphasis on the role and outcomes with VA-ECMO use.

Profile trends of non-COVID patients admitted to the cardiac intensive care unit during the 2020 COVID pandemic.

BACKGROUND: During the COVID-19 outbreak, numerous reports indicated a higher mortality rate among cardiovascular patients. We investigated how this trend applied to patients admitted to the cardiac intensive care unit (CICU). METHODS: We retrospectively compared CICU patients admitted during the initial peak of the COVID outbreak between February and May 2020 (Covid Era, CE group) to a control group in pre-pandemic time in 2019. We interviewed patients to determine the symptom onset time and the time interval between symptomology and hospital arrival. RESULTS: The data of 292 patients were used in the analysis (119 patients in the CE group and 173 in the control group). CE patients had a higher incidence of ischemic heart disease (IHD) (p<.03), heart failure (p<.04), and psychiatric disorders (p<.001). During COVID time, more patients were hospitalized with myocarditis (OR: 26.45), arrhythmias (OR: 2.88), and new heart failure (HF) (p<.001) and less with STEMI (OR: 0.39; 95% CI: 0.24-0.63). Fewer PCIs were performed in the CE group (p<.001), with an overall lower success rate (p<.05) than reported in the control group. Patients in the CE group reported a longer period between symptom onset to hospital arrival (p<.001, χ2 = 12.42). The six-month survival rate was significantly lower in CE patients (χ2 = 7.01, P = 0.008). CONCLUSIONS: Among CICU patients admitted to our center during the initial period of the COVID pandemic, STEMI events were less frequent while cases of newly diagnosed HF sharply increased. Patients waited longer after symptom onset before seeking medical care during the pandemic. The delay may have resulted in clinical deterioration that could explain the high mortality rate and the new HF admission rate.

Cardiac Intensive Care Unit Admissions during COVID-19 Pandemic-A Single Center Experience.

AIM: The impact of coronavirus disease 2019 (COVID-19) lockdown on cardiac emergency admissions to hospitals has been reported previously. We aimed to study the emergency room (ER) admissions to cardiac intensive care unit (CICU) at a tertiary care center during that period and compare this with admissions during the same time frame in the previous years. MATERIALS AND METHODS: This is a retrospective observational study of patients admitted to the CICU during the pandemic period from March 22 to August 1 (inclusive) of 2020 and compared this with CICU admissions in the same time frame in the previous 2 years (2018 and 2019). RESULTS: During the study period in 2020, a total of 216 patients (age 59 ± 14 years) were admitted via ER, which is a 33% and 30% decline in admissions compared to 2019 (n = 322, age 63 ± 12 years) and 2018 (n = 307, age 62 ± 13), respectively. The decline in admissions with the primary diagnosis of acute coronary syndrome (ACS), acute decompensated heart failure, arrhythmia, and other diagnoses during the study period in 2020 were 27%, 38%, 62%, and 59%, respectively, while there was a 50% increase in acute pulmonary embolism admission compared to the mean admission in 2018 and 2019. Weekly admission rates gradually increased from less than 10 per week in the first 3 weeks to >15 by eighth week of the study period in 2020, while the trend was same throughout the study period in the previous 2 years. The CICU mortality rate in 2020 study period was 4.6% compared to 3.9% in 2018 (p = 0.83) and 5.6% in 2019 (p = 0.70). The in-hospital mortality of these patients was also similar in all 3 years (6.5%, 7.8%, and 7.9% in 2018, 2019, and 2020, respectively; p = 0.61). CONCLUSION: Our study showed that CICU admissions during COVID-19 lockdown had declined compared to the previous years in a large tertiary center in India. Government and health organizations should educate the public early on during the pandemic about the consequences of ignoring other acute medical problems such as ACS, provide various measures for them to reach hospital early, and give reassurance with the best practices adopted in hospitals to avoid contracting the virus from the hospital environment. HOW TO CITE THIS ARTICLE: Yalamanchi R, Dasari BC, Narra L, Oomman A, Kumar P, Nayak R, et al. Cardiac Intensive Care Unit Admissions during COVID-19 Pandemic-A Single Center Experience. Indian J Crit Care Med 2020;24(11):1103-1105.

Left ventricular systolic dysfunction identification using artificial intelligence-augmented electrocardiogram in cardiac intensive care unit patients.

BACKGROUND: An artificial intelligence-augmented electrocardiogram (AI-ECG) can identify left ventricular systolic dysfunction (LVSD). We examined the accuracy of AI ECG for identification of LVSD (defined as LVEF ≤40% by transthoracic echocardiogram [TTE]) in cardiac intensive care unit (CICU) patients. METHOD: We included unique Mayo Clinic CICU patients admitted from 2007 to 2018 who underwent AI-ECG and TTE within 7 days, at least one of which was during hospitalization. Discrimination of the AI-ECG for LVSD was determined using receiver-operator characteristic curve (AUC) values. RESULTS: We included 5680 patients with a mean age of 68 ± 15 years (37% females). Acute coronary syndrome (ACS) was present in 55%. LVSD was present in 34% of patients (mean LVEF 48 ± 16%). The AI-ECG had an AUC of 0.83 (95% confidence interval 0.82-0.84) for discrimination of LVSD. Using the optimal cut-off, the AI-ECG had 73%, specificity 78%, negative predictive value 85% and overall accuracy 76% for LVSD. AUC values were higher for patients aged <70 years (0.85 versus 0.80), males (0.84 versus 0.79), patients without ACS (0.86 versus 0.80), and patients who did not undergo revascularization (0.84 versus 0.80). CONCLUSIONS: The AI-ECG algorithm had very good discrimination for LVSD in this critically-ill CICU cohort with a high prevalence of LVSD. Performance was better in younger male patients and those without ACS, highlighting those CICU patients in whom screening for LVSD using AI ECG may be more effective. The AI-ECG might potentially be useful for identification of LVSD in resource-limited settings when TTE is unavailable.