Jentzer, Jacob C

Abstract Background Effusive-constrictive pericarditis (ECP) is a condition where acute pericarditis causes a pericardial effusion and stiffening of the pericardium, which can result in haemodynamic instability due to compression of right-sided cardiac chambers. Here, we present a patient with cardiac tamponade followed by ECP complicating treatment of acute myocardial infarction/cardiogenic shock supported with a percutaneous left ventricular assist device (PVAD). Case summary A 65-year-old male presented with an anterior ST-elevation myocardial infarction and cardiogenic shock. The left anterior descending artery was stented, and a PVAD was placed. The patient was haemodynamically unstable, and the PVAD had frequent suction alarms at higher flow rates. Pulsus paradoxus was noted on the arterial line tracing. Echocardiography showed a large pericardial effusion, which was drained with improvement in cardiac output. However, the patient soon worsened again with continued PVAD suction alarms, and this time echocardiography demonstrated constrictive physiology. The patient was treated with anti-inflammatory medications with improvement in haemodynamics. The PVAD was able to be weaned, and the patient was discharged in stable condition. Discussion Effusive-constrictive pericarditis is a syndrome exhibiting the physiology of both cardiac tamponade and constrictive pericarditis. Effusive-constrictive pericarditis should be considered in patients whose haemodynamics do not improve after pericardiocentesis. This patient had a PVAD placed, which relies on left ventricular preload to increase cardiac output. The numerous suction alarms encountered during this patient’s intensive care unit course were likely due to ECP decreasing preload.

Acute right ventricular failure (ARVF) is commonly seen in the intensive care unit and constitutes a significant clinical challenge, with associated high in-hospital mortality. Recently, the treatment of ARVF has significantly changed, with the progressive implementation of mechanical circulatory support devices that now represent important tools for clinicians in treating this condition. However, despite recent advancements, the optimal approach for ARVF remains elusive, and precise treatment algorithms and comprehensive management protocols are still lacking. In the present review, we explore the pathophysiology of ARVF, highlighting the different mechanisms that may lead to this clinical entity and emphasizing the left and right heart’s complex interplay. We analyze the different therapeutic options that are now available for short- and long-term management of ARVF, with a particular focus on the advantages and disadvantages of the mechanical circulatory support devices actually used. Furthermore, we propose future directions in the field and a possible flowchart for the treatment of this condition.

Abstract Aims Left ventricular (LV) ventricular-arterial coupling (VAC) refers to the ratio of afterload (effective arterial elastance) to contractility (end-systolic elastance) as an integrated marker of cardiac performance. We sought to determine whether the echocardiographic VAC ratio, defined using the ratio of LV end-systolic volume (LVESV) to stroke volume (SV), predicted mortality in the cardiac intensive care unit (CICU). Methods and results Mayo Clinic CICU patients from 2007 and 2018 were included. Ventricular-arterial coupling ratio was calculated as the Teichholz LVESV divided by the SV calculated from LV outflow tract Doppler. The primary outcome was in-hospital mortality and the secondary outcome was all-cause 1-year mortality. A total of 4685 patients were included with a median age of 69 (58, 79) years (37.2% females), with acute coronary syndrome in 54.9% and heart failure in 49.0%. A higher VAC ratio was associated with greater severity of illness, worse echocardiographic findings, and more use of critical care therapies. A total of 329 (7%) patients died during hospitalization. Patients with a higher VAC ratio had higher in-hospital mortality overall and in each admission diagnosis subgroup. After multivariable adjustment, patients with a VAC ratio >2 were at higher risk of in-hospital mortality (adjusted odds ratio 1.63, 95% confidence interval 1.17–2.28, P = 0.010). One-year mortality was higher for patients with a higher VAC ratio, especially VAC >2. Conclusion Ventricular-arterial uncoupling was associated with worse outcomes in an unselected CICU cohort. The echocardiographic VAC ratio is a simple non-invasive bedside measure that can be used for risk prediction in the CICU.

Objectives There is substantial practice variation in the management strategies for atrial fibrillation (AF) with rapid ventricular rate (RVR) and hemodynamic instability in critically ill patients. This study aimed to evaluate the use and effectiveness of direct current cardioversion (DCCV) for unstable AF RVR in the intensive care unit (ICU). Design Multicenter retrospective cohort study. Setting Non-cardiac/cardiovascular surgery ICUs of the Mayo Clinic Hospitals in Minnesota, Wisconsin, Florida, and Arizona. Patients Adult patients who developed paroxysmal AF RVR with hemodynamic instability (heart rate ≥ 130 beats per minute and a documented SBP ≤ 90 mmHg or the need for vasopressors) during ICU stay. Interventions Emergency DCCV. Measurements and Main Results Primary outcomes were in-hospital mortality, hospital-, ICU-, and organ support-free days. Secondary outcomes were return to sinus rhythm rate before and after discharge. Among 691 patients eligible for inclusion, 47 (6.8%) received emergent DCCV in the ICU. The frequency of DCCV was higher for patients located in surgical ICUs (14.5% vs 6.1%, P = .04). Patients were 1:2 propensity-score matched. The comparative analyses were conducted on 141 patients. Those who underwent DCCV were more likely to restore sinus rhythm (odds ratio [95% confidence interval], 5.2 [1.30 20.8]). However, DCCV was not associated with increased odds of having sinus rhythm at discharge, lower mortality, or higher number of ICU-, or hospital-free days. The number of organ support-free days was significantly lower in the DCCV group (estimate ± standard error, −5.0 ± 2.0, P = .012). Conclusions Emergency DCCV is rarely used to treat unstable AF in non-cardiac ICUs. Despite increased likelihood of immediate sinus rhythm restoration, DCCV was not associated with improvement in patient-centered outcomes. Prospective studies are warranted to evaluate harms and benefits of DCCV in non-cardiac critically ill patients with unstable AF where the driver of hemodynamic instability is often an underlying condition rather than arrhythmia per se.

Background Left ventricular diastolic dysfunction (LVDD) predicts mortality in patients in cardiac intensive care units. An artificial intelligence enhanced ECG (AIECG) algorithm can predict LVDD and mortality in general populations but has not been examined in cardiac intensive care units. Methods This historical cohort study included consecutive adults admitted to Mayo Clinic cardiac intensive care unit from 2007 to 2018 with an admission AIECG. The AIECG assigned the LVDD grade (0–3). Medial mitral E/e' ratio >15 on transthoracic echocardiogram (TTE) defined elevated filling pressures. In‐hospital and 1‐year mortality was evaluated, before and after multivariable adjustment. Results We included 11 868 patients (median age 69.5 years, 37.7% female); 48% had heart failure and 44% had acute coronary syndromes. AIECG LVDD grade was 0 (normal), 33%; 1, 7%; 2, 39%; and 3, 21%. In‐hospital and 1‐year mortality increased in each higher AIECG LVDD grade. After adjustment, each higher AIECG LVDD grade was associated with higher in‐hospital (adjusted odds ratio [OR], 1.22 [95% CI, 1.13–1.32]) and 1‐year mortality (adjusted hazard ratio [HR], 1.23 [95% CI, 1.19–1.29]); this persisted after adjustment for TTE measurements. Patients with grade 2 or 3 LVDD by AIECG and medial mitral E/e' ratio >15 by TTE had the highest in‐hospital (adjusted OR, 2.54 [95% CI, 1.69–3.88]) and 1‐year (adjusted HR, 2.03 [95% CI, 1.65–2.48]) mortality, whereas patients meeting either of these criteria had similar, elevated mortality. Conclusions The AIECG LVDD grade was strongly associated with in‐hospital and 1‐year mortality in patients in cardiac intensive care units, even after adjusting for clinical variables and TTE measurements. Patients with concordant AIECG and TTE for elevated filling pressures were at highest risk.

BACKGROUND: Percutaneous microaxial ventricular assist devices (pVADs) have the potential to reduce mortality of patients with cardiogenic shock (CS). However, the association between the distribution of pVAD-performing centers and outcomes of CS has not been explored. METHODS: This observational study included Medicare fee-for-service beneficiaries aged 65 to 99 years treated with pVAD for CS from 2016 to 2020. It examined the associations between patient outcomes and 2 exposure variables: hospitals’ procedure volumes of pVAD and patient-hospital distances (in quintiles [Qn]). We developed Cox proportional hazards regression for 180-day mortality and heart failure readmission rates, and multivariable logistic regression for in-hospital outcomes, adjusting for patient demographics, comorbidities, concomitant treatments, and hospital characteristics, including CS volume, teaching status, and the ability to perform extracorporeal membrane oxygenation. RESULTS: A total of 6637 patients with CS underwent pVAD at 1041 hospitals, with the annualized hospital volume ranging widely from 0.3 to 55.6 cases/year. Patients treated at higher-volume centers experienced lower 180-day mortality compared with those treated at lower-volume centers (Qn1=reference; Qn2: adjusted hazard ratio [aHR], 0.88 [95% CI, 0.79–0.97]; Qn3: aHR, 0.88 [95% CI, 0.79–0.98]; Qn4: aHR, 0.88 [95% CI, 0.78–0.99]; Qn5: aHR, 0.84 [95% CI, 0.74–0.95]; P for trend, 0.026), while we found no evidence that patient-hospital distances were associated with mortality (Qn1=reference; Qn2: aHR, 0.99 [95% CI, 0.89–1.09]; Qn3: aHR, 0.94 [95% CI, 0.85–1.04]; Qn4: aHR, 1.01 [95% CI, 0.92–1.11]; Qn5: aHR, 0.91 [95% CI, 0.82–1.01]; P for trend, 0.160). We found no evidence that the hospital volume and patient-hospital distances were associated with in-hospital bleeding, intracranial hemorrhage, or renal replacement therapy initiation. CONCLUSIONS: Hospital volume was more strongly associated with mortality than patient-hospital distances, suggesting that rational distribution of pVAD-performing centers while ensuring adequate procedure volumes may optimize patient mortality.

Key Points Measuring blood potassium has always required access to blood. The surface electrocardiogram, analyzed using an artificial intelligence algorithm, can detect hyperkalemia bloodlessly. The artificial intelligence-analyzed electrocardiogram exhibited a high negative predictive value but substantially lower positive predictive value. Background Artificial intelligence (AI) electrocardiogram (ECG) analysis can enable detection of hyperkalemia. In this validation, we assessed the algorithm's performance in two high acuity settings. Methods An emergency department (ED) cohort (February to August 2021) and a mixed intensive care unit (ICU) cohort (August 2017 to February 2018) were identified and analyzed separately. For each group, pairs of laboratory-collected potassium and 12 lead ECGs obtained within 4 hours of each other were identified. The previously developed AI ECG algorithm was subsequently applied to leads 1 and 2 of the 12 lead ECGs to screen for hyperkalemia (potassium >6.0 mEq/L). Results The ED cohort ( N =40,128) had a mean age of 60 years, 48% were male, and 1% ( N =351) had hyperkalemia. The area under the curve (AUC) of the AI-enhanced ECG (AI-ECG) to detect hyperkalemia was 0.88, with sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and positive likelihood ratio (LR+) of 80%, 80%, 3%, 99.8%, and 4.0, respectively, in the ED cohort. Low-eGFR (<30 ml/min) subanalysis yielded AUC, sensitivity, specificity, PPV, NPV, and LR+ of 0.83, 86%, 60%, 15%, 98%, and 2.2, respectively, in the ED cohort. The ICU cohort ( N =2636) had a mean age of 65 years, 60% were male, and 3% ( N =87) had hyperkalemia. The AUC for the AI-ECG was 0.88 and yielded sensitivity, specificity, PPV, NPV, and LR+ of 82%, 82%, 14%, 99%, and 4.6, respectively in the ICU cohort. Low-eGFR subanalysis yielded AUC, sensitivity, specificity, PPV, NPV, and LR+ of 0.85, 88%, 67%, 29%, 97%, and 2.7, respectively in the ICU cohort. Conclusions The AI-ECG algorithm demonstrated a high NPV, suggesting that it is useful for ruling out hyperkalemia, but a low PPV, suggesting that it is insufficient for treating hyperkalemia.