Missouri Baptist Medical Center

Introduction: Cardiogenic shock (CS) remains a critical form of circulatory failure with high mortality. Early identification and risk stratification are essential. The Society for Cardiovascular Angiography and Interventions (SCAI) classification provides a set of clinical definitions for different stages of CS (A through E). While it guides clinical thinking, it does not offer a specific, quantifiable scoring system for assigning a patient to a stage. Based on this framework, we developed a novel Cardiogenic Shock Staging and Triage Assessment Tool (CS-STAT) to address this challenge. The CS-STAT is a scoring system that uses objective clinical, hemodynamic, and laboratory data to produce a numerical score. This study’s purpose was to validate that the CS-STAT specific scoring method and is predictive of patient outcomes. We hypothesize that the CS-STAT score is a predictor of mortality. Methods: A retrospective cohort study was conducted at a single community hospital on 61 patients with CS (ICD-10 code R57.0) between January-March 2025. We examined patients’ demographic and clinic data, including APACHE II and CardShock scores. Statistical analyses included Chi-Square, Pearson correlations, and both linear and logistic regression models. Results: Chi-Square analysis showed a significant relationship between the SCAI stage derived from CS-STAT and patient mortality (p =.032). Mortality rates increased progressively from 45.0% in SCAI Stage C to 65.4% in Stage D, and 66.7% in Stage E. Pearson’s correlations revealed significant associations between the CS-STAT score and both the APACHE II score (p =.000, r =.492) and CardShock score (p =.001, r =.420). Logistic regression confirmed the CS-STAT’s strong predictive capability, accurately classifying 83.6% of cases (sensitivity 83.3%, specificity 83.9%), and was a significant predictor of mortality (p =.028, odds ratio 1.437). Other significant predictors included age (p =.006) and cardiac surgery status (p =.021). Conclusions: The CS-STAT demonstrates its potential for risk stratification and mortality prediction. This study’s findings, along with the observed strong, dose-dependent relationship between increasing SCAI stage and mortality, provide a robust scientific basis for a prospective validation of the CS-STAT in a real-time clinical setting.

Introduction: With nearly 20% of intensive care unit (ICU) patients facing end-of-life, timely palliative care (PC) is critical. Traditional electronic medical record (EMR)-based referrals often lead to delayed, disjointed care due to insufficient interdisciplinary collaboration, which can be confusing for patients and families. Our aim was to enhance early identification of ICU patients needing PC, fostering interdisciplinary collaboration—especially nursing involvement—to achieve earlier referrals and improved patient outcomes. Methods: We utilized an artificial intelligence (AI)-enhanced predictive algorithm to create a collaborative system for early ICU patient assessment. Conducted in a 30-bed ICU at a Midwest community hospital (Nov 2024 - Feb 2025), this AI-enhanced algorithm leveraged EMR and claims data to predict mortality and identify PC candidates daily. The process involved: 1) Educating nurses on PC definition and skills; 2) A dedicated palliative care nurse practitioner (NP) generating daily algorithm reports; 3) A structured workflow where the acute care NP, staff nurses, and interdisciplinary team discussed eligible patients, leading to physician approvals, often via secure messaging. The acute care NP then placed consensus-driven referrals. Results: The project resulted in 162 PC referrals and a notable increase in physician-approved consultations, as observed by ICU and PC NPs. Of these, 117 patients transitioned from active to do-not-resuscitate code status. Eligible patients identified by the algorithm and interdisciplinary team received PC consultations within 1-2 days. Key discharge diagnoses included sepsis, cardiovascular, and respiratory conditions, reflecting severe illness. Approximately 41% of patients were discharged to hospice, and a 16% death rate (predominantly sepsis) highlighted the prevalence of life-limiting conditions and the focus on improving timely end-of-life care delivery. Conclusions: By integrating AI-enhanced insights with a robust interdisciplinary approach, we improved patient identification and facilitated physician consultations. This model highlights the transformative potential of technology and collaboration in palliative care. Future research will quantify long-term benefits on patient and family well-being.

Right ventricular dysfunction (RVD) with severe tricuspid regurgitation is a major prognostic factor in cardiopulmonary disease, yet the effects of improving tricuspid regurgitation remains unknown. In this study, we evaluated the effects of a novel percutaneous tricuspid valve replacement device (or TVR, Evoque®) on RVD utilizing the right ventricular index of myocardial performance (RIMP, or Tei index). The RIMP encompasses both systolic and diastolic components of right ventricular function. We prospectively analyzed our first 10 patients with severe tricuspid regurgitation undergoing percutaneous TVR. RIMP was measured via echocardiography both before and after percutaneous TVR and compared to normal controls. Patients with RVD had significantly elevated RIMP values (mean 0.55 -/+ 0.08) compared to controls (mean 0.32 -/+ 0.05, p < 0.001). Following percutaneous TVR using the Evoque device, there was a significant reduction in RIMP (mean 0.41 -/+ 0.06, P<0.01), demonstrating an improved global RV function. These findings are correlated with improved invasive hemodynamics and measurements of quality of life. Conclusions: Improving severe tricuspid regurgitation with percutaneous TVR in patients with RVD results in an improvement in global right ventricular function as assessed by the RIMP. This study further highlights RIMP as a reliable marker of RV dysfunction and demonstrates it's responsiveness to interventions that alleviate volume overload from severe TR. Further studies assessing the effect of the improved hemodynamics from percutaneous TVR on patient outcome are ongoing.

BackgroundLung cancer remains the leading cause of cancer-related mortality in the United States, yet disparities in lung cancer screening (LCS) outcomes exist and remain understudied, particularly in the Midwestern region. Our objective was to investigate disparities in lung radiology outcomes and follow-up care based on patient, provider, and place-based characteristics (i.e., area deprivation index; ADI).MethodsThis cross-sectional study used data from the LCS program at Siteman Cancer Center (SCC) in St. Louis, Missouri, from January to December 2023. SCC’s catchment area includes 82 counties in Missouri and Illinois; approximately 15% of the population reside in a rural zip code, and 29% reside in medically underserved areas 80% are White. The study included 1,946 individuals aged 50–80, meeting LCS eligibility criteria based on smoking history and age. Lung radiology findings were assessed as primary outcomes, and timely follow-up adherence (i.e., return for follow-up visit) was analyzed among patients with high-risk findings (Lung-RADS 3 [”Probably Benign”] and 4 [”Suspicious”]) from January to June 2023, requiring follow-up by December 2023. Multivariable logistic regression was conducted, adjusting for patient and provider characteristics and ADI.ResultsOf the 1,946 individuals who accessed LCS, 57% were Black, 41% White, 1% Asian, and 1% of another race; 54% were male and 46% female. Lung findings were classified as “probably benign/suspicious” (high risk) for 14%. Annual visits were associated with higher likelihood of high-risk scores compared to baseline visits (AOR = 2.10 (1.40–3.15); p < 0.001). Racial differences were noted in the association between provider type and lung outcomes. Among White individuals only, specialist compared to primary care provider referral was associated with increased odds of being high risk (AOR = 1.58 (1.00–2.50); p = 0.048). Sex, insurance, smoking status, park-years and ADI were not associated with lung radiology outcomes. Timely adherence to return follow-up visit among high-risk patients was suboptimal, with only 20.0% returning within 3–6 months for their repeat LCS. Individuals residing in moderate ADI (distress) areas were less likely to have timely follow-up (for high-risk findings) compared to those in high distress (AOR = 0.393, 95% CI = 0.155–1.001, p = 0.050). There were no differences by sex, insurance, smoking status, and pack-years for being classified as high risk.ConclusionsSCC’s LCS program successfully captured Black populations and individuals from highly distressed areas, in a predominantly White catchment area. There were no observable race disparities in timely follow-up of high-risk findings, reflecting progress toward equity in access and outcomes. Place-based disparities in follow-up were observed that warrant further characterization and risk assessment to improve follow-up of patients undergoing LCS.

Urinanalysis, considered the “liquid biopsy” of the kidney, is rapidly becoming a lost art among nephrologists. A well-performed urinanalysis provides information on the presence of kidney disease, identifies the affected compartment, and helps monitor disease activity. The three main components of urine analysis are gross examination, dipstick tests, and urine sediment examination under microscopy. The urine sediments should be analyzed under a bright-field, dark-field, phase-contrast, and polarization microscope for better visualization and categorization of cells, casts, and crystals. The Sternheimer-Malbin (SM) stain can enhance urine sediments under a microscope. The urine sediment, like in a kidney biopsy, should be systematically analyzed for evidence of glomerular (dysmorphic RBCs, acanthocytes, RBC casts, lipid casts) and tubulointerstitial (RTE cell casts, Granular casts, Leucocyte casts, broad waxy casts) injury. For crystal identification in sediments, knowledge of urinary pH, morphology, and birefringence features under polarized light is essential.

BackgroundMetastatic breast cancer (MBC) remains incurable despite significant treatment advances. Coordinating care for patients with MBC can be challenging given the various treatment options, available clinical trials, and frequent need for ancillary services. To optimize MBC care, we designed a project for adapting and developing an academic and community practice collaborative care model for MBC care (Project ADAPT), based on the Ending Metastatic Breast Cancer for Everyone (EMBRACE) program developed at Dana Farber Cancer Institute.ObjectiveWe aim to describe the implementation science–based study design and innovative components of Project ADAPT.MethodsProject ADAPT uses the Dynamic Adaptation Process informed by the Exploration, Preparation, Implementation, Sustainment framework. Washington University School of Medicine (WUSM) partnered with 3 community hospitals in the St. Louis region covering rural and urban settings. The exploration and preparation phases provide patient and provider feedback on current referral practices to finalize the approach for the implementation phase. At the implementation phase, we will enroll patients with MBC at these 3 community sites to evaluate potential collaborative care at WUSM and assess the impact of this collaborative care model on referral satisfaction and acceptability for patients with MBC and their providers. Patients may then return to their community site for care or continue to receive part of their care at WUSM. We are incorporating virtual and digital health strategies to improve MBC care coordination in order to minimize patient burden.ResultsThe exploration phase is ongoing. As of August 2021, we have recruited 21 patient and provider participants to complete surveys of the current collaborative care process at WUSM. Using a 2-tailed paired t test, 44 patients (including 10 patients from the exploration phase) and 32 oncologists are required to detect an effect size of 0.5 with 80% power at a level of significance of .05. Throughout this phase and in preparation for the implementation phase, we have iteratively updated and refined our surveys for the implementation phase based on testing of our data collection instruments. Our partner sites are in various stages of the single institutional review board (IRB) approval process. We have ongoing engagement with all partner sites, which has helped solidify our participant recruitment strategies and design patient-friendly recruitment materials. In addition, we have included a patient advocate on the research team. Members of the research team have launched a single IRB Support Network at WUSM to create a repository of the single IRB procedures in order to streamline the partner site onboarding process and facilitate enhanced collaboration across institutions.ConclusionsWith this robust model, we expect that patients with MBC will receive optimal care regardless of geographical location and the model will improve patient and provider experiences when navigating the health system.International Registered Report Identifier (IRRID)DERR1-10.2196/35736

Laboratory evidence supporting diagnosis of the prevalent condition of mast cell activation syndrome (MCAS) currently includes elevated levels in blood or urine of mediators relatively specific to mast cells (MCs) and/or increased numbers of MCs in luminal gastrointestinal (GI) tract tissues. However, identification of elevated mediators is technically challenging and expensive, and controversy persists regarding the normal ranges of numbers/counts of MCs in various GI tract segments, let alone challenges in determining how many of the visualized MCs are activated. To aid diagnosis of MCAS, we developed a potential new approach for the pathologist to identify the extent of GI tract MC activation easily and inexpensively. Visualization of MCs in gastrointestinal biopsies from 251 patients vs. 95 controls using antibodies against CD117 and tryptase; MC counting per mm2; calculation of the difference between the CD117-positive MCs (identifying all MCs) vs. tryptase-positive MCs (identifying non-activated tryptase-containing MCs), which we define as the tryptase depletion index (TDI). Mean total MC counts did not differ significantly between patients and controls, but mean TDIs differed significantly. Non-overlapping confidence intervals at the 99.9% level identified cut-offs of TDIs between patients vs. controls of 26, 45 and 32 MCs/mm2 in gastric antrum, duodenum, and colon, respectively. The TDI may discriminate between MCAS patients vs. controls. If this preliminary work can be independently confirmed, the TDI may become a useful additional minor diagnostic criterion for MCAS.