Faculty Bibliography

Readmission to the intensive care unit (ICU) during the index hospitalization is associated with poor outcomes in medical or surgical ICU survivors. Little is known about critically ill patients with acute cardiovascular conditions cared for in a cardiac intensive care unit (CICU). We sought to describe the incidence, risk factors, and outcomes of all ICU readmissions in patients who survived to CICU discharge. We retrospectively reviewed Mayo Clinic patients from 2007 to 2015 who survived the index CICU admission and identified patients with a second ICU stay during their index hospitalization; these patients were categorized as ICU transfers (patients who went directly from the CICU to another ICU) or ICU readmissions (patients initially transferred from the CICU to the ward, and then back to an ICU). Among 9,434 CICU survivors (mean age 67 years), 138 patients (1.5%) had a second ICU stay during the index hospitalization: 60 ICU transfers (0.6%) and 78 ICU readmissions (0.8%). The most common indications for ICU readmission were respiratory failure and procedure/surgery. On multivariable modeling, respiratory failure, severe acute kidney injury, and Charlson Comorbidity Index at the time of discharge from the index ICU stay were associated with ICU readmission. Death during the first ICU readmission (n = 78) occurred in 7.7% of patients. In-hospital mortality was higher for patients with a second ICU stay. In conclusion, few CICU survivors have a second ICU stay during their index hospitalization; these patients are at a higher risk of in-hospital and 1-year mortality. Respiratory failure, severe acute kidney injury, and higher co-morbidity burden identify CICU survivors at elevated risk of ICU readmission.

Despite advances in early revascularization, percutaneous hemodynamic support platforms, and systems of care, cardiogenic shock (CS) remains associated with a mortality rate higher than 50%. Several risk stratification models have been derived since the 1990 s to identify patients at high risk of adverse outcomes. Still, limited information is available on the differences between scoring systems and their relative applicability to both acute myocardial infarction and advanced decompensated heart failure CS. Thus, we reviewed the similarities, differences, and limitations of published CS risk prediction models and herein discuss their suitability to the contemporary management of CS care.

OBJECTIVES:The prediction of right heart failure (RHF) after left ventricular assist device (LVAD) implantation remains a challenge. Recently, risk scores were derived from analysis of the European Registry for Patients with Mechanical Circulatory Support (EUROMACS) data, the EUROMACS-RHF, and the modified postoperative EUROMACS-RHF. The authors assessed the performance characteristics of these 2 risk score formulations in a continuous-flow LVAD cohort at their institution. DESIGN:A retrospective, observational study. SETTING:At a tertiary-care academic medical center. PARTICIPANTS:Adult patients who underwent durable LVAD implantation between 2015 and 2018. INTERVENTIONS:None MEASUREMENTS AND MAIN RESULTS: Early post-LVAD RHF was defined as follows: (1) need for right ventricular assist device, or (2) inotropic or inhaled pulmonary vasodilator support for ≥14 postoperative days. The authors used logistic regression and examined receiver operating characteristic (ROC) curves to evaluate the ability of the 2 risk scores to distinguish between outcome groups. A total of 207 patients met the inclusion criteria. Of the patients, 16% developed RHF (33/207). The EUROMACS-RHF score was not predictive of RHF in the authors' cohort (odds ratio [OR] 1.25; 95% CI [0.99-1.60]; p = 0.06), but the postoperative EUROMACS-RHF CPB score was significantly associated (OR 1.38; 95% CI [1.03-1.89]; p = 0.03). The scores had similar ROC curves, with weak discriminatory performance: 0.601 (95% CI [0.509-0.692]) and 0.599 (95% CI [0.505-0.693]) for EUROMACS-RHF and postoperative EUROMACS-RHF, respectively. CONCLUSIONS:In the authors' single-center retrospective analysis, the EUROMACS-RHF risk score did not predict early RHF. An optimized risk score for the prediction of RHF after LVAD implantation remains an urgent unmet need.

BACKGROUND:Cardiac arrest (CA) is a common reason for admission to the cardiac intensive care unit (CICU), though the relative burden of morbidity, mortality, and resource use between admissions with in-hospital (IH) and out-of-hospital (OH) CA is unknown. We compared characteristics, care patterns, and outcomes of admissions to contemporary CICUs after IHCA or OHCA. METHODS:The Critical Care Cardiology Trials Network is a multicenter network of tertiary CICUs in the US and Canada. Participating centers contributed data from consecutive admissions during 2-month annual snapshots from 2017 to 2021. We analyzed characteristics and outcomes of admissions by IHCA vs OHCA. RESULTS:We analyzed 2,075 admissions across 29 centers (50.3% IHCA, 49.7% OHCA). Admissions with IHCA were older (median 66 vs 62 years), more commonly had coronary disease (38.3% vs 29.7%), atrial fibrillation (26.7% vs 15.6%), and heart failure (36.3% vs 22.1%), and were less commonly comatose on CICU arrival (34.2% vs 71.7%), p<0.001 for all. IHCA admissions had lower lactate (median 4.3 vs 5.9) but greater utilization of invasive hemodynamics (34.3% vs 23.6%), mechanical circulatory support (28.4% vs 16.8%), and renal replacement therapy (15.5% vs 9.4%); p<0.001 for all. Comatose IHCA patients underwent targeted temperature management less frequently than OHCA patients (63.3% vs 84.9%, p<0.001). IHCA admissions had lower unadjusted CICU (30.8% vs 39.0%, p<0.001) and in-hospital mortality (36.1% vs 44.1%, p<0.001). CONCLUSION:Despite a greater burden of comorbidities, CICU admissions after IHCA have lower lactate, greater invasive therapy utilization, and lower crude mortality than admissions after OHCA.

BACKGROUND:Targeted temperature management (TTM) has been recommended after cardiac arrest (CA), however the specific temperature targets and cooling methods (intravascular cooling (IVC) versus surface cooling (SC)) remain uncertain. METHODS:PUBMED and EMBASE were searched until October 8, 2022 for randomized clinical trials (RCTs) investigating the efficacy of TTM after CA. The randomized treatment arms were categorized into the following 6 groups: 31..C to 33..C IVC, 31..C to 33..C SC, 34..C to 36..C IVC, 34..C to 36..C SC, strict normothermia or fever prevention (Strict NT or FP), and standard of care without TTM (No-TTM). The primary outcome was neurological recovery. P-score was used to rank the treatments, where a larger value indicates better performance. RESULTS:We identified 15 RCTs, involving 5,218 patients with CA. Compared to No-TTM as the reference, the other therapeutic options significantly improved neurological outcomes (vs No-TTM; 31..C to 33.. C IVC/UNASSIGNED:RR = 0.67, 95% CI 0.54 to 0.83; 31..C to 33..C SC RR = 0.73, 95% CI 0.61 to 0.87; 34..C to 36.. C IVC/UNASSIGNED:RR = 0.66, 95% CI 0.51 to 0.86; 34..C to 36..C SC: RR = 0.73, 0.59 to 0.90; Strict NT or FP: RR = 0.75, 95% CI 0.62 to 0.90). Overall, 31-33..C IVC had the highest probability to be the best therapeutic option to improve outcomes (the ranking P-score of 0.836). As a subgroup analysis, the ranking P-score showed that IVC might be a better cooling method compared to SC (IVC vs SC P-score: 0.960 vs 0.670). CONCLUSIONS:Hypothermia (31..C to 36..C IVC and SC) and active normothermia (Strict-NT and Strict-FP) were associated with better neurological outcomes compared to No-TTM, with IVC having a greater probability of being the better cooling method than SC.

Oxygen supplementation has been a mainstay in the management of patients with acute cardiac disease. While hypoxia is known to be detrimental, the adverse effects of artificially high oxygen levels (hyperoxia) have only recently been recognized. Hyperoxia may induce harmful hemodynamic effects, including peripheral and coronary vasoconstriction, and direct cellular toxicity through the production of reactive oxygen species. In addition, emerging evidence has shown that hyperoxia is associated with adverse clinical outcomes. Thus, it is essential for the cardiac intensive care unit (CICU) clinician to understand the available evidence and titrate oxygen therapies to specific goals. This review summarizes the pathophysiology of oxygen within the cardiovascular system and the association between supplemental oxygen and hyperoxia in patients with common CICU diagnoses, including acute myocardial infarction, heart failure, shock, cardiac arrest, pulmonary hypertension, and respiratory failure. Finally, we highlight lessons learned from available trials, gaps in knowledge, and future directions.

AIMS/OBJECTIVE:The aims of the Critical Care Cardiology Trials Network (CCCTN) are to develop a registry to investigate the epidemiology of cardiac critical illness and to establish a multicenter research network to conduct randomized clinical trials (RCTs) in patients with cardiac critical illness. METHODS AND RESULTS/RESULTS:The CCCTN was founded in 2017 with 16 centers and has grown to a research network of over 40 academic and clinical centers in the United States and Canada. Each center enters data for consecutive cardiac intensive care unit (CICU) admissions for at least two months of each calendar year. More than 20 000 unique CICU admissions are now included in the CCCTN Registry. To date, scientific observations from the CCCTN Registry include description of variations in care, the epidemiology and outcomes of all CICU patients, as well as subsets of patients with specific disease states, such as shock, heart failure, renal dysfunction, and respiratory failure. The CCCTN has also characterized utilization patterns, including use of mechanical circulatory support in response to changes in the heart transplantation allocation system, and the use and impact of multidisciplinary shock teams. Over years of multicenter collaboration, the CCCTN has established a robust research network to facilitate multicenter registry-based randomized trials in patients with cardiac critical illness. CONCLUSIONS:The CCCTN is a large, prospective registry dedicated to describing processes-of-care and expanding clinical knowledge in cardiac critical illness. The CCCTN will serve as an investigational platform from which to conduct randomized controlled trials in this important patient population.

AIMS/OBJECTIVE:Contemporary cardiac intensive care unit (CICU) outcomes remain highly heterogeneous. As such, a risk-stratification tool using readily available lab data at time of CICU admission may help inform clinical decision-making. METHODS AND RESULTS/RESULTS:The primary derivation cohort included 4352 consecutive CICU admissions across 25 tertiary care CICUs included in the Critical Care Cardiology Trials Network (CCCTN) Registry. Candidate lab indicators were assessed using multivariable logistic regression. An integer risk score incorporating the top independent lab indicators associated with in-hospital mortality was developed. External validation was performed in a separate CICU cohort of 9716 patients from the Mayo Clinic (Rochester, MN, USA). On multivariable analysis, lower pH [odds ratio (OR) 1.96, 95% confidence interval (CI) 1.72-2.24], higher lactate (OR 1.40, 95% CI 1.22-1.62), lower estimated glomerular filtration rate (OR 1.26, 95% CI 1.10-1.45), and lower platelets (OR 1.18, 95% CI 1.05-1.32) were the top four independent lab indicators associated with higher in-hospital mortality. Incorporated into the CCCTN Lab-Based Risk Score, these four lab indicators identified a 20-fold gradient in mortality risk with very good discrimination (C-index 0.82, 95% CI 0.80-0.84) in the derivation cohort. Validation of the risk score in a separate cohort of 3888 patients from the Registry demonstrated good performance (C-index of 0.82; 95% CI 0.80-0.84). Performance remained consistent in the external validation cohort (C-index 0.79, 95% CI 0.77-0.80). Calibration was very good in both validation cohorts (r = 0.99). CONCLUSION/CONCLUSIONS:A simple integer risk score utilizing readily available lab indicators at time of CICU admission may accurately stratify in-hospital mortality risk.

Background Several studies have shown improved outcomes in closed compared with open medical and surgical intensive care units. However, very little is known about the ideal organizational structure in the modern cardiac intensive care unit (CICU). Methods and Results We retrospectively reviewed consecutive unique admissions (n=3996) to our tertiary care CICU from September 2013 to October 2017. The aim of our study was to assess for differences in clinical outcomes between an open compared with a closed CICU. We used multivariable logistic regression adjusting for demographics, comorbidities, and severity of illness. The primary outcome was in-hospital mortality. We identified 2226 patients in the open unit and 1770 in the closed CICU. The unadjusted in-hospital mortality in the open compared with closed unit was 9.6% and 8.9%, respectively (P=0.42). After multivariable adjustment, admission to the closed unit was associated with a lower in-hospital mortality (odds ratio [OR], 0.69; 95% CI: 0.53-0.90, P=0.007) and CICU mortality (OR, 0.70; 95% CI, 0.52-0.94, P=0.02). In subgroup analysis, admissions for cardiac arrest (OR, 0.42; 95% CI, 0.20-0.88, P=0.02) and respiratory insufficiency (OR, 0.43; 95% CI, 0.22-0.82, P=0.01) were also associated with a lower in-hospital mortality in the closed unit. We did not find a difference in CICU length of stay or total hospital charges (P>0.05). Conclusions We found an association between lower in-hospital and CICU mortality after the transition to a closed CICU. These results may help guide the ongoing redesign in other tertiary care CICUs.