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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 Background: Chronic inflammation is implicated in ovarian carcinogenesis, but how different inflammation-related exposures individually or jointly affect histotype-specific associations remains unclear. Materials and Methods: We pooled data from 16 case-control studies in the Ovarian Cancer Association Consortium to evaluate associations of eight inflammation-related factors (anti-inflammatory: aspirin use, tubal ligation (TL); pro-inflammatory: endometriosis, obesity, lifetime ovulatory cycles (LOC), smoking, pelvic inflammatory disease (PID), polycystic ovary syndrome (PCOS)) with epithelial ovarian cancer (OvC) by histologic subtype. We examined individual associations and clustering of risk factors across histotypes and computed population attributable risk (PAR) for each factor. We assessed additive and multiplicative interactions for exposure combinations. Results: Associations with OvC risk differed by histotype (e.g., high-grade serous: aspirin: OR=0.90; 95%CI 0.82, 0.99; TL: OR=0.80; 95%CI 0.73, 0.88; overall serous: endometriosis: OR=1.17; 95%CI 1.03, 1.31; high LOC: OR=1.42; 95%CI 1.28, 1.58; obesity (low-grade serous): OR=1.50; 95%CI 1.14, 1.98). Clustering analyses showed highly correlated risk profiles in endometrioid and clear cell (r=0.91). High-grade serous and mucinous profiles were moderately correlated with endometrioid and clear cell (r=0.60) tumors. The profile for low-grade serous (r=0.36) tumors was distinct from other histotypes. PAR estimates suggested modifying aspirin use, TL, and LOCs could substantially reduce burdens of endometrioid, clear cell and mucinous tumors. Out of 28 exposure combinations tested in overall OvC and 189 by histotype, we observed 12 interactions. Not using aspirin regularly showed positive additive interactions with obesity and high LOCs, particularly in endometrioid tumors (obesity relative excess risk due to interaction (RERI)=0.74, 95%CI 0.31, 1.18; Pint=0.001 for; LOCs RERI=0.80, 95%CI 0.03, 1.56; Pint=0.04). Not using aspirin regularly also showed a positive additive interaction with endometriosis in clear cell tumors (RERI=1.77, 95%CI 0.03, 3.52; Pint=0.05). Lack of TL showed positive interactions with obesity in endometrioid (RERI=0.86, 95%CI 0.17, 1.53; Pint=0.01) and mucinous (RERI=1.10, 95%CI 0.23, 1.97; Pint=0.01) tumors, while negative additive interactions were observed for smoking and endometriosis in endometrioid tumors (RERI=-1.12, 95%CI -2.19, -0.05; Pint=0.04). A multiplicative interaction was observed between obesity and endometriosis in mucinous tumors (Pint=0.01). Conclusion: The findings suggest ovarian tumorigenesis is strongly shaped by pro- and anti-inflammatory pathways that act largely independently. Further examining these pathways may clarify the origins of histotype heterogeneity and guide prevention strategies. Citation Format: Maxwell Akonde, Britton Trabert, SHELLEY TWOROGER, Allan Jensen, Kathryn L. Terry, Joshua Sampson, Hoda Anton-Culver, David Bowtell, Elisa V. Bandera, Angela Brooks-Wilson, Andrew Berchuck, Daniel William Cramer, Linda S. Cook, Julie M. Cunningham, Jennifer A. Doherty, Ellen L. Goode, Marc T. Goodman, Holly Ruth Harris, Susanne K. Kjaer, Nhu Le, Alice Wen-Ron Lee, Francesmary Modugno, Kirsten B. Moysich, Celeste Pearce, Malcolm C. Pike, Harvey A. Risch, Mary A. Rossing, Joellen M. Schildkrau, Daniel O. Stram, Rebecca Sutphen, David Van Den Berg, Penelope M. Webb, Anna Wu, Argyrios Ziogas, Nicolas A. Wentzensen. Inflammation-related exposures and histotype- specific ovarian cancer risk in the Ovarian Cancer Association Consortium (OCAC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6261.

Introduction: Among patients with cardiogenic shock (CS), high right atrial pressure (RAP) and low mean arterial pressure (MAP) are associated with in-hospital mortality. Pressure-adjusted heart rate (PAHR), defined as heart rate * RAP-to-MAP ratio (HR * [RAP/MAP]), integrates these parameters and has been used to identify cardiovascular dysfunction in critical illness. Higher PAHR values associate with higher surgical ICU mortality, but the prognostic significance of PAHR has not been assessed in cardiac intensive care unit (CICU) patients with CS. Hypothesis: We hypothesized that higher PAHR values are associated with higher risk of in-hospital mortality in patients with CS. Methods: The Critical Care Cardiology Trials Network (CCCTN) is a multinational registry of CICUs coordinated by the TIMI Study Group. Among CS admissions (2018-2023) undergoing invasive hemodynamic assessment within 24h of CICU admission, we calculated PAHR (in bpm) and assessed its relationship with in-hospital mortality. Patients on temporary mechanical circulatory support were excluded. Odds ratios were adjusted for age, sex, vasoactive-inotropic score (VIS), SCAI stage, and preceding cardiac arrest. Subgroup analyses stratifying by CS subtype were performed. Results: Among the 1411 CS admissions in the analysis cohort (mean age 61 years, 31% women), 18% had AMI-CS, 75% had HF-CS, and 7% had secondary CS. At the time of assessment (median 1.4h after CICU admission), 75% were on vasoactive support (median VIS 3.8). Median HR was 92 (Q1-Q3 77-109) bpm, RAP 15 (Q1-Q3 10-19) mmHg, MAP 75 (Q1-Q3 67-87) mmHg, and PAHR 17 (Q1-Q3 11-24) bpm. A stepwise gradient of higher in-hospital mortality with increasing PAHR values (p-trend <0.001; Fig ) was observed. In adjusted models, a higher PAHR was associated with higher in-hospital mortality (aOR per 10-bpm, 1.35 [95% CI, 1.15-1.58]), and had stronger prognostic associations with mortality than its individual hemodynamic components (Fig) . Conclusion: Higher PAHR is strongly associated with in-hospital mortality in CS patients. PAHR, a simple parameter which is readily calculable without needing a pulmonary artery catheter, may aid in identifying CS patients at higher risk of death.

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.

Cardiogenic shock continues to carry a high mortality rate despite contemporary care, with no breakthrough therapies shown to improve survival over the past few decades. It is a time‐sensitive condition that commonly results in cardiovascular complications and multisystem organ failure, necessitating multidisciplinary expertise. Managing patients with cardiogenic shock remains challenging even in well‐resourced settings, and an important subgroup of patients may require cardiac replacement therapy. As a result, the idea of leveraging the collective cognitive and procedural proficiencies of multiple providers in a collaborative, team‐based approach to care (the “shock team”) has been advocated by professional societies and implemented at select high‐volume clinical centers. A slowly maturing evidence base has suggested that cardiogenic shock teams may improve patient outcomes. Although several registries exist that are beginning to inform care, particularly around therapeutic strategies of pharmacologic and mechanical circulatory support, none of these are currently focused on the shock team approach, multispecialty partnership, education, or process improvement. We propose the creation of a Cardiogenic Shock Team Collaborative—akin to the successful Pulmonary Embolism Response Team Consortium—with a goal to promote sharing of care protocols, education of stakeholders, and discovery of how process and performance may influence patient outcomes, quality, resource consumption, and costs of care.

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: 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.