van Diepen, Sean

Background Acute kidney injury (AKI) is associated with high morbidity and mortality in critically ill patients. Multicenter analyses describing the epidemiology of AKI in the cardiac intensive care unit (CICU) are scarce. Here, we describe the prevalence, predictors, and outcomes associated with AKI in a contemporary multicenter CICU population. Methods The Critical Care Cardiology Trials Network (CCCTN) is a collaboration of CICUs in North America coordinated by the TIMI Study Group (Boston, MA). We evaluated patient and hospital-level outcomes as a function of creatinine-only Kidney Disease: Improving Global Outcomes (KDIGO) AKI stage within the CCCTN registry. Logistic regression was used to assess associations with in-hospital mortality. Results Among 21 603 admissions, the overall prevalence of AKI was 23.7%, which was composed of KDIGO stage 1: 12.7%, stage 2: 1.7%, and stage 3: 9.2%. A higher prevalence and severity of AKI were seen in patients with baseline kidney disease, hypertension, or diabetes and in admissions with heart failure, cardiogenic shock, and cardiac arrest ( P < .001 for all). There was a stepwise increase in hospital mortality across AKI stages (stage 1: 23%, stage 2: 39%, stage 3: 42%; P < .0001). The increased risk of death associated with progressive AKI stage persisted after multivariate adjustment (adjusted OR: stage 1: 2.1, stage 2: 3.7, stage 3: 3.4). Conclusions AKI occurs in 1 in 4 admissions to the CICU, and a higher AKI stage is incrementally associated with in-hospital mortality, highlighting a need to develop strategies to mitigate AKI and its complications.

Abstract Aims The Shock Academic Research Consortium (SHARC) recently proposed pragmatic consensus definitions to standardize classification of cardiogenic shock (CS) in registries and clinical trials. We aimed to describe contemporary CS epidemiology using the SHARC definitions in a cardiac intensive care unit (CICU) population. Methods and results The Critical Care Cardiology Trials Network (CCCTN) is a multinational research network of advanced CICUs coordinated by the TIMI Study Group (Boston, MA). Cardiogenic shock was defined as a cardiac disorder resulting in SBP &lt; 90 mmHg for ≥30 min [or the need for vasopressors, inotropes, or mechanical circulatory support (MCS) to maintain SBP ≥ 90 mmHg] with evidence of hypoperfusion. Primary aetiologic categories included acute myocardial infarction-related CS (AMI-CS), heart failure-related CS (HF-CS), and non-myocardial (secondary) CS. Post-cardiotomy CS was not included. Heart failure-related CS was further subcategorized as de novo vs. acute-on-chronic HF-CS. Patients with both cardiogenic and non-cardiogenic components of shock were classified separately as mixed CS. Of 8974 patients meeting shock criteria (2017–23), 65% had isolated CS and 17% had mixed shock. Among patients with CS (n = 5869), 27% had AMI-CS (65% STEMI), 59% HF-CS (72% acute-on-chronic, 28% de novo), and 14% secondary CS. Patients with AMI-CS and de novo HF-CS were most likely to have had concomitant cardiac arrest (P &lt; 0.001). Patients with AMI-CS and mixed CS were most likely to present in more severe shock stages (SCAI D or E; P &lt; 0.001). Temporary MCS use was highest in AMI-CS (59%). In-hospital mortality was highest in mixed CS (48%), followed by AMI-CS (41%), similar in de novo HF-CS (31%) and secondary CS (31%), and lowest in acute-on-chronic HF-CS (25%; P &lt; 0.001). Conclusion SHARC consensus definitions for CS classification can be pragmatically applied in contemporary registries and reveal discrete subpopulations of CS with distinct phenotypes and outcomes that may be relevant to clinical practice and future research.

BACKGROUND: Associations of early changes in vasoactive support with cardiogenic shock (CS) mortality remain incompletely defined. METHODS: The Critical Care Cardiology Trials Network is a multicenter registry of cardiac intensive care units. Patients admitted with CS (2018–2023) had vasoactive dosing assessed at 4 and 24 hours from cardiac intensive care unit admission and quantified by the vasoactive-inotropic score (VIS). Prognostic associations of VIS at both time points, as well as change in VIS from 4 to 24 hours, were examined. Interaction testing was performed based on mechanical circulatory support status. RESULTS: Among 3665 patients, 82% had a change in VIS <10, with 7% and 11% having a ≥10-point increase and decrease from 4 to 24 hours, respectively. The 4 and 24-hour VIS were each associated with cardiac intensive care unit mortality (13%–45% and 11%–73% for VIS <10 to ≥40, respectively; P trend <0.0001 for each). Stratifying by the 4-hour VIS, changes in VIS from 4 to 24 hours had a graded association with mortality, ranging from a 2- to >4-fold difference in mortality comparing those with a ≥10-point increase to ≥10-point decrease in VIS ( P trend <0.0001). The change in VIS alone provided good discrimination of cardiac intensive care unit mortality (C-statistic, 0.72 [95% CI, 0.70–0.75]) and improved discrimination of the 24-hour Sequential Organ Failure Assessment score (0.72 [95% CI, 0.69–0.74] to 0.76 [95% CI, 0.74–0.78]) and the clinician-assessed Society for Cardiovascular Angiography and Interventions shock stage (0.72 [95% CI, 0.70–0.74] to 0.77 [95% CI, 0.75–0.79]). Although present in both groups, the mortality risk associated with VIS was attenuated in patients managed with versus without mechanical circulatory support (odds ratio per 10-point higher 24-hour VIS, 1.36 [95% CI, 1.23–1.49] versus 1.84 [95% CI, 1.69–2.01]; P interaction <0.0001). CONCLUSIONS: Early changes in the magnitude of vasoactive support in CS are associated with a gradient of risk for mortality. These data suggest that early VIS trajectory may improve CS prognostication, with the potential to be leveraged for clinical decision-making and research applications in CS.

Background One‐time assessment of the Society for Cardiovascular Angiography and Interventions (SCAI) shock classification robustly predicts mortality in the cardiac intensive care unit (CICU). We sought to determine whether serial SCAI shock classification could improve risk stratification. Methods and Results Unique admissions to a single academic level 1 CICU from 2015 to 2018 were included in this retrospective cohort study. Electronic health record data were used to assign the SCAI shock stage during 4‐hour blocks of the first 24 hours of CICU admission. Shock was defined as hypoperfusion (SCAI shock stage C, D, or E). In‐hospital death was evaluated using logistic regression. Among 2918 unique CICU patients, 1537 (52.7%) met criteria for shock during ≥1 block, and 266 (9.1%) died in the hospital. The SCAI shock stage on admission was: A, 37.6%; B, 31.5%; C, 25.9%; D, 1.8%; and E, 3.3%. Patients who met SCAI criteria for shock on admission (first 4 hours) and those with worsening SCAI shock stage after admission were at higher risk for in‐hospital death. Each higher admission (adjusted odds ratio, 1.36 [95% CI, 1.18–1.56]; area under the receiver operating characteristic curve, 0.70), maximum (adjusted odds ratio, 1.59 [95% CI, 1.37–1.85]; area under the receiver operating characteristic curve, 0.73) and mean (adjusted odds ratio, 2.42 [95% CI, 1.99–2.95]; area under the receiver operating characteristic curve, 0.78) SCAI shock stage was incrementally associated with a higher in‐hospital mortality rate. Discrimination was highest for the mean SCAI shock stage ( P <0.05). Each additional 4‐hour block meeting SCAI criteria for shock predicted a higher mortality rate (adjusted odds ratio, 1.15 [95% CI, 1.07–1.24]). Conclusions Dynamic assessment of shock using serial SCAI shock classification assignment can improve mortality risk stratification in CICU patients by quantifying the magnitude and duration of shock.

Abstract Aims Invasive haemodynamic assessment with a pulmonary artery catheter is often used to guide the management of patients with cardiogenic shock (CS) and may provide important prognostic information. We aimed to assess prognostic associations and relationships to end-organ dysfunction of presenting haemodynamic parameters in CS. Methods and results The Critical Care Cardiology Trials Network is an investigator-initiated multicenter registry of cardiac intensive care units (CICUs) in North America coordinated by the TIMI Study Group. Patients with CS (2018–2022) who underwent invasive haemodynamic assessment within 24 h of CICU admission were included. Associations of haemodynamic parameters with in-hospital mortality were assessed using logistic regression, and associations with presenting serum lactate were assessed using least squares means regression. Sensitivity analyses were performed excluding patients on temporary mechanical circulatory support and adjusted for vasoactive-inotropic score. Among the 3603 admissions with CS, 1473 had haemodynamic data collected within 24 h of CICU admission. The median cardiac index was 1.9 (25th–75th percentile, 1.6–2.4) L/min/m2 and mean arterial pressure (MAP) was 74 (66–86) mmHg. Parameters associated with mortality included low MAP, low systolic blood pressure, low systemic vascular resistance, elevated right atrial pressure (RAP), elevated RAP/pulmonary capillary wedge pressure ratio, and low pulmonary artery pulsatility index. These associations were generally consistent when controlling for the intensity of background pharmacologic and mechanical haemodynamic support. These parameters were also associated with higher presenting serum lactate. Conclusion In a contemporary CS population, presenting haemodynamic parameters reflecting decreased systemic arterial tone and right ventricular dysfunction are associated with adverse outcomes and systemic hypoperfusion.

BACKGROUND: Cardiovascular and critical care professional societies recommend incorporating family engagement practices into routine clinical care. However, little is known about current family engagement practices in contemporary cardiac intensive care units (CICUs). METHODS: We implemented a validated 12-item family engagement practice survey among site investigators participating in the Critical Care Cardiology Trials Network, a collaborative network of CICUs in North America. The survey includes 9 items assessing specific engagement practices, 1 item about other family-centered care practices, and 2 open-ended questions on strategies and barriers concerning family engagement practice. We developed an engagement practice score by assigning 1 point for each family engagement practice partially or fully adopted at each site (max score 9). We assessed for relationships between the engagement practice score and CICU demographics. RESULTS: All sites (N=39; 100%) completed the survey. The most common family engagement practices were open visitation (95%), information and support to families (85%), structured care conferences (n=82%), and family participation in rounds (77%). The median engagement practice score was 5 (interquartile range, 4). There were no differences in engagement practice scores by geographic region or CICU type. The most commonly used strategies to promote family engagement were family presence during rounds (41%), communication (28%), and family meetings (28%). The most common barriers to family engagement were COVID-related visitation policies (38%) and resource limitations (13%). CONCLUSIONS: Family engagement practices are routinely performed in many CICUs; however, considerable variability exists. There is a need for strategies to address the variability of family engagement practices in CICUs.

Background: Mortality remains high in patients with ST-segment–elevation myocardial infarction (STEMI) complicated by cardiogenic shock (CS), and early reperfusion has been shown to improve outcomes. We analyzed the association between first medical contact (FMC)-to-percutaneous coronary angiography time with mortality and major adverse cardiovascular events among patients with STEMI with and without CS. Methods: We performed a retrospective analysis of the Vancouver Coastal Health Authority STEMI registry, including all patients with STEMI who received primary percutaneous coronary angiography between January 1, 2010, and December 31, 2020, and stratified them by presence or absence of CS at hospital arrival. The primary outcome was in-hospital mortality, the secondary outcome was in-hospital major adverse cardiovascular events, defined as a composite of the first occurrence of mortality, cardiac arrest, heart failure, intracerebral hemorrhage, cerebrovascular accident, or reinfarction. Mixed effects logistic regression with restricted cubic splines was used to estimate the relationships between FMC-to-device time and the outcomes in the CS and non-CS groups. Results: 2929 patients were included, 9.4% (n=275) had CS. Median FMC-to-device time was 113.5 (interquartile range, 93.0–145.0) and 103.0 (interquartile range, 85.0–130.0) minutes for patients with CS and without CS, respectively. More patients with CS had FMC-to-device times above guideline recommendations (76.6% versus 54.1%, P <0.001). Between 60 and 90 minutes, for each 10-minute increase in FMC-to-device time, absolute mortality for patients with CS increased by 4% to 7%, whereas for patients without CS, it increased by <0.5%. Conclusions: Among patients with STEMI undergoing primary percutaneous coronary angiography, reperfusion delays among patients with CS are associated with significantly worse outcomes. Strategies to reduce FMC-to-device times for patients with STEMI presenting with CS are required.

Background: Algorithmic application of the 2019 Society of Cardiovascular Angiography and Intervention (SCAI) shock stages effectively stratifies mortality risk for patients with cardiogenic shock. However, clinician assessment of SCAI staging may differ. Moreover, the implications of the 2022 SCAI criteria update remain incompletely defined. Methods: The Critical Care Cardiology Trials Network is a multicenter registry of cardiac intensive care units (CICUs). Between 2019 and 2021, participating centers (n=32) contributed at least a 2-month snapshot of consecutive medical CICU admissions. In-hospital mortality was assessed across 3 separate staging methods: clinician assessment, Critical Care Cardiology Trials Network algorithmic application of the 2019 SCAI criteria, and a revision of the Critical Care Cardiology Trials Network application using the 2022 SCAI criteria. Results: Of 9612 admissions, 1340 (13.9%) presented with cardiogenic shock with in-hospital mortality of 35.2%. Both clinician and algorithm-based staging using the 2019 SCAI criteria identified a stepwise gradient of mortality risk (stage C–E: 19.0% to 83.7% and 14.6% to 52.2%, respectively; P trend <0.001 for each). Clinician assignment of SCAI stages identified higher risk patients compared with algorithm-based assignment (stage D: 49.9% versus 29.3%; stage E: 83.7% versus 52.2%). Algorithmic application of the 2022 SCAI criteria, with incorporation of the vasoactive-inotropic score, more closely approximated clinician staging (mortality for stage C-E: 21.9% to 70.5%; P trend <0.001). Conclusions: Both clinician and algorithm-based application of the 2019 SCAI stages identify a stepwise gradient of mortality risk, although clinician-staging may better allocate higher risk patients into advanced SCAI stages. Updated algorithmic staging using the 2022 SCAI criteria and vasoactive-inotropic score further refines risk stratification.

Abstract Aims Shock severity predicts mortality in patients with cardiogenic shock (CS). We evaluated the association between pre-cannulation Society for Cardiovascular Angiography and Intervention (SCAI) shock classification and mortality among patients receiving venoarterial (VA) extracorporeal membrane oxygenation (ECMO) support for CS. Methods and results We included Extracorporeal Life Support Organization (ELSO) Registry patients from 2010 to 2020 who received VA ECMO for CS. SCAI shock stage was assigned based on hemodynamic support requirements prior to ECMO initiation. In-hospital mortality was analyzed using multivariable logistic regression. We included 12 106 unique VA ECMO patient runs with a median age of 57.9 (interquartile range: 46.8, 66.1) years and 31.8% were females; 3472 (28.7%) were post-cardiotomy. The distribution of SCAI shock stages at ECMO initiation was: B, 821 (6.8%); C, 7518 (62.1%); D, 2973 (24.6%); and E, 794 (6.6%). During the index hospitalization, 6681 (55.2%) patients died. In-hospital mortality increased incrementally with SCAI shock stage (adjusted OR: 1.24 per SCAI shock stage, 95% CI: 1.17–1.32, P &lt; 0.001): B, 47.5%; C, 52.8%; D, 60.8%; E, 65.1%. A higher SCAI shock stage was associated with increased in-hospital mortality in key subgroups, although the SCAI shock classification was only predictive of mortality in non-surgical (medical) CS and not in post-cardiotomy CS. Conclusion The severity of shock prior to cannulation is a strong predictor of in-hospital mortality in patients receiving VA ECMO for CS. Using the pre-cannulation SCAI shock classification as a risk stratification tool can help clinicians refine prognostication for ECMO recipients and guide future investigations to improve outcomes.