Predicting biomass gasification products for bubbling fluidised beds using high order polynomial regression with regularisation: a simple but highly effective strategy.

In recent years, there has been remarkable progress in the field of medical technology, particularly in the domain of rehabilitation. Among the many innovative solutions that have emerged, continuous passive machines (CPMs) have gained significant attention and appreciation for their effectiveness in aiding the recovery process for various musculoskeletal injuries and conditions. This approach delves into the fascinating world of CPMs specifically designed for ankle, knee, and hip rehabilitation, highlighting their benefits, functionality, and potential applications. Continuous passive machines are mechanical devices used to facilitate passive movement of joints. These machines play a pivotal role in rehabilitating individuals who have suffered from a range of orthopedic injuries, including ankle sprains, knee ligament tears, hip replacements, and other musculoskeletal conditions. By employing a continuous, controlled range of motion, CPMs promote joint mobility, reduce stiffness, enhance circulation, and facilitate the healing process. For patients recovering from ankle, knee, or hip injuries, APMM offer several advantages over traditional rehabilitation methods. Firstly, these machines allow for precise control and customization of the range of motion, speed, and intensity of movement. This adaptability ensures that the treatment aligns with the specific needs and limitations of each patient, promoting safety and comfort during rehabilitation.

BackgroundThe aim was to compare the hemodynamic and metabolic effectiveness of manual chest compressions and a mechanical chest compression device during in-hospital cardiac arrest by monitoring carotid Doppler flow and end-tidal carbon dioxide (ETCO₂) and arterial lactate levels.MethodsIn this single-center, prospective, observational cohort study, 54 adult patients with nontraumatic cardiac arrest in the emergency department were enrolled between December 2023 and February 2024. Chest compressions were delivered manually for the first three 2-minute cycles and mechanically for the subsequent two cycles. The peak-systolic velocity (PSV) and end-diastolic velocity (EDV) of the common carotid artery and the ETCO₂ and lactate levels were recorded at cycles 1, 3 and 5. The primary and secondary outcomes were the return of spontaneous circulation (ROSC) and 24-h survival, respectively. The predictive performance of physiological markers was assessed with receiver operating characteristic (ROC) analysis.ResultsROSC was achieved in 41/54 patients (75.9%), and 22/41 patients (53.7%) were alive at 24 h. The ultrasound acquisition time decreased from 39.9 ± 7.2 s in the first (manual) cycle to 25.7 ± 5.5 s in the fifth (mechanical) cycle (p < 0.01). Compared with manual cardiopulmonary resuscitation (CPR), mechanical compression was associated with greater increases in PSV (Δ₃–₅ = 9.0 ± 3.3 cm s⁻¹ vs. Δ₁–₃ = 2.7 ± 2.9 cm s⁻¹; p < 0.01) and EDV, a greater increase in ETCO₂ (3.5 ± 1.7 mm Hg vs. 1.3 ± 1.6 mm Hg; p < 0.01) and a more pronounced decrease in lactate levels (-0.30 ± 0.34 mmol L⁻¹ vs. -0.10 ± 0.19 mmol L⁻¹; p < 0.01). An ETCO₂ value ≥ 35 mm Hg predicted ROSC with 75.6% sensitivity and 53.9% specificity (AUC = 0.70), whereas a lactate level ≤ 5.3 mmol L⁻¹ predicted ROSC with 76.9% sensitivity and 82.9% specificity (AUC = 0.81). Carotid Doppler velocities showed limited discrimination for ROSC (AUC ≈ 0.56–0.58) and should not be used alone for prognostication.ConclusionCompared with the preceding manual cycles, the mechanical cycles were associated with higher carotid flow velocities and more favorable ETCO₂–lactate trajectories; however, given the fixed sequence and co-interventions, causality cannot be inferred.

Anomaly recognition method of high- and low-frequency sensing data for complex machining environment of machine tools

This article focuses on the application of digital management of agricultural machinery in agricultural production, analyzes the management upgrading value brought by the Internet of Things, big data and other technologies, and deeply explores the problems of inconsistent policy standards, high technology landing cost, weak infrastructure, and prominent data security risks faced in practice. Through targeted suggestions such as improving the policy system, increasing financial technical support, strengthening infrastructure, and building a data security protection system, it provides reference for breaking through the bottleneck of digital management and promotion of agricultural machinery and helping agricultural mechanization move towards a new stage of digital intelligence.

BackgroundThe prognosis of aortic stenosis (AS) with cardiogenic shock remains poor, and optimal initial treatment remains unclear. Emergent balloon aortic valvuloplasty (BAV) is a treatment option for salvage and recent studies have reported that early release of valve obstruction by emergent BAV could improve prognosis. This study aimed to assess the efficacy and safety of emergent BAV for severe AS with cardiogenic shock.MethodsAmong 8,230 patients hospitalized for heart failure, 7924 patients with heart failure unrelated to severe AS were excluded. Among the remaining 306 patients, 256 patients who developed cardiogenic shock due to other causes except severe AS were further excluded. Finally, a total of 41 patients with severe AS in cardiogenic shock were enrolled and divided into the emergent (underwent BAV within 6 h of admission, n = 9) and non-emergent (underwent BAV more than 6 h after admission, n = 16) groups, after excluding 16 patients who did not undergo BAV. The primary endpoints were the 30-day mortality rate and procedural complications. The secondary endpoints were days to withdrawal from the mechanical support device, days to initial rehabilitation, and clinical frailty scale (CFS) score at discharge.ResultsIn the emergent group, the time from admission to BAV was 3.0 ± 1.4 h, whereas BAV was performed 4.5 days (median) after admission in the non-emergent group. The 30-day mortality rate was not significantly different between the emergent and non-emergent groups (0% vs. 25%, p = 0.260); furthermore, there was no statistically significant difference regarding the incidence of procedural complications (0% in the emergent vs. 12.5% in the non-emergent group, p = 0.520). The days to withdrawal from mechanical support device and to start rehabilitation were earlier in emergent group (2.9 ± 1.2 days vs. 7.8 ± 4.6 days; p = 0.008, 4.2 ± 1.9 days vs. 10.8 ± 6.5 days; p = 0.004). The CFS score at discharge in the emergent group was maintained compared to before admission (from 3.8 ± 1.0 to 3.9 ± 1.1; p = 0.347), whereas worsened in the non-emergent group (from 3.8 ± 0.9 to 4.6 ± 1.2; p = 0.032).ConclusionsEmergent BAV for cardiogenic shock is feasible, and earlier BAV may support faster recovery and help prevent deterioration of frailty.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12872-025-05310-6.

Formate, valued at $700M globally, serves as a critical feedstock in de-icing, corrosion removal, and as a preservative in animal feed. Electrochemical CO2 conversion to formate delivers three quantifiable advantages over conventional production methods: (1) operation at ambient temperature and pressure, reducing capital equipment costs by 30-40%, (2) potential for direct utilization of intermittent renewable electricity, achieving a 60% lower carbon footprint than the petrochemical process, and (3) compatibility with downstream bioprocessing to high-value compounds like methanol and acetate, increasing potential market value by 2-3 times.1 This approach enables industrial decarbonization while creating new revenue streams from captured CO2. Various systems have demonstrated the ability to electrochemically reduce CO2 into formate with high selectivity,2 and recent advancements have enabled industrial-scale electrolysis. However, challenges such as energy efficiency, long-term stability, and cost-effectiveness persist, requiring further improvements in flow electrolyzers. Herein, we address one of the main failure mechanisms for CO2 electrolysis: flooding. Flooding is caused by inevitable salt formation, which leads to a gradual transition of gas diffusion electrodes from hydrophobic to hydrophilic properties, blocking CO2 diffusion channels and reducing CO2 availability. Additionally, in long-term testing, catalyst degradation further hinders performance due to catalyst dissolution and redeposition, nanoparticle agglomeration and sintering, carbonate formation blocking active sites, and membrane poisoning by electrolyte impurities. These issues collectively compromise Faradaic efficiency at low overpotentials, highlighting the need for further advancements in durability and stability.In this study, a zero-gap membrane electrode assembly architecture equipped with a conventional cation exchange membrane and commercial catalyst was used for the direct electrochemical synthesis of formate from CO2. Through careful optimization of the ink and deposition process, selection of improved carbon electrode substrates for better water management, and the use of a cost-effective and more efficient anode material in a lab-scale flow electrolyzer, an industrial-scale electrolyzer containing five cells with a total electrode area of 2500 cm2 were stacked to produce formate continuously. Our system demonstrated unprecedented stability, achieving over 1000 hours of continuous operation through strategic anolyte concentration management, impurity removal protocols, and systematic maintenance. This breakthrough performance yielded 600 L of 0.71 M formate solution, effectively fixing 14.33 kg of CO₂ as value-added product. These results validate the industrial viability of our electrochemical CO₂ conversion technology, overcoming critical barriers in scalability, energy efficiency, and long-term durability that have historically limited commercial deployment for carbon capture and utilization. Reference S. Guo, T. Asset, and P. Atanassov, ACS Catal, 11, 5172–5188 (2021) https://doi.org/10.1021/acscatal.0c04862.S. Guo et al., Appl Catal B, 316, 121659 (2022) https://www.sciencedirect.com/science/article/pii/S0926337322006002.

This study aims to develop and validate a machine learning-based mortality risk prediction model for V-A ECMO patients to improve the precision of clinical decision-making. This multicenter retrospective cohort study included 280 patients receiving V-A ECMO from the Second Affiliated Hospital of Guangxi Medical University, Yulin First People’s Hospital, and the MIMIC-IV database. The data from the Second Affiliated Hospital of Guangxi Medical University and the MIMIC-IV database were merged and randomly divided in a 7:3 ratio into a training set and an internal validation set, respectively. The dataset from Yulin First People’s Hospital was reserved as an external validation cohort. The primary study outcome was defined as in-hospital mortality.Feature selection was conducted using Lasso regression, followed by the development of six machine learning models: Logistic Regression, Random Forest (RF), Deep Neural Network (DNN), Support Vector Machine (SVM), LightGBM, and CatBoost. Model performance was assessed using the Area Under the Curve (AUC), accuracy, sensitivity, specificity, and F1 score. Model validation was performed through calibration and decision curve analysis. Feature importance was evaluated using SHAP, and subgroup analysis was conducted to assess the model’s applicability across different clinical scenarios. In internal validation, the Logistic Regression model performed the best, with an AUC of 0.86 (95% CI: 0.77–0.93), accuracy of 0.76, sensitivity of 0.73, specificity of 0.79, and an F1 score of 0.73. It outperformed other models (RF: AUC = 0.79, DNN: AUC = 0.78, SVM: AUC = 0.76, LightGBM: AUC = 0.71, CatBoost: AUC = 0.77). External validation yielded consistent results, with the Logistic Regression model’s AUC at 0.75 (95% CI: 0.56–0.92), accuracy of 0.69, sensitivity of 0.64, specificity of 0.73, and an F1 score of 0.66. Calibration curve analysis revealed that the Logistic Regression model had the lowest Brier score (0.1496), indicating the most reliable predicted probabilities. Decision curve analysis demonstrated that the model provided the highest net benefit across most decision thresholds. SHAP analysis identified lactate, age, and albumin as key predictors of mortality, with lactate and age positively correlated, and albumin negatively correlated. Subgroup analysis revealed better performance in the cardiac arrest group (AUC = 0.81), non-sepsis group (AUC = 0.75), and non-diabetes group (AUC = 0.78). The Logistic Regression-based mortality risk prediction model for V-A ECMO patients demonstrated comparable or even favorable performance to more complex machine learning models, with the advantage of higher interpretability.By explicitly incorporating lactate, age, and albumin as the principal predictors, this model facilitates precise risk stratification and provides practical support for clinical decision-making in ECMO management.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-25423-4.

ABSTRACT OBJECTIVES Los Angeles County initiated an extracorporeal cardiopulmonary resuscitation (eCPR) program to transport patients with refractory shockable out-of-hospital cardiac arrest (OHCA) to dedicated eCPR-capable centers (ECCs). The impact of an eCPR program on patients with OHCA who do not receive eCPR has not been described. METHODS We measured the association between EMS unit participation in the program and survival-to-hospital discharge for patients with OHCA who did not receive eCPR, treated between July 2019 and September 2023. Six of the 29 EMS agencies participated in the program, which included eCPR protocol development, hands-on scenario-based training on the eCPR protocol and application of the mechanical compression device (MCD) on a manikin, and provision of MCDs. Because the deployment model for one agency differed from others (MCDs on supervisor units, no paramedic hands-on training), we prespecified a subgroup analysis excluding that agency. RESULTS We analyzed 30,855 patients with EMS-treated OHCA: 7% had a shockable rhythm, 32% were treated by a pilot unit pre-implementation, 24% by a pilot unit post-implementation, and 44% were treated by a unit that never participated in the eCPR pilot. Treatment by a pilot unit post-implementation was not associated with a significant difference in the odds of survival-to-discharge compared to pre-implementation (1.14 95%CI 0.99-1.34) in the primary analysis but was associated with it in the subgroup analysis (1.61 95%CI 1.37-1.95). Similar results were found for neurologic outcome at discharge. CONCLUSIONS Implementation of an eCPR program is not associated with worse outcomes for patients with OHCA who did not receive eCPR and may be associated with benefit depending on implementation.

Background/Objectives: Cochlear implantation is the most widely used treatment option for patients with severe to profound hearing loss. Despite being a relatively standardized surgical procedure, cochlear implant (CI) outcomes vary considerably among patients. Several studies have attempted to develop predictive models for CI outcomes but achieving accurate and generalizable predictions remains challenging. The present study aimed to evaluate whether simple and complex statistical and machine learning models could outperform the Null model based on various pre-CI implantation variables. Methods: We conducted a retrospective analysis of 236 ears with postlingual profound sensorineural hearing loss (SNHL) and measurable residual hearing (WRSmax > 0%) at the time of implantation. The median postoperative word recognition score with CI (WRS65(CI)) was 75% [Q1: 55%, Q3: 80%]. The dataset was divided using a 70:15:15 split into training (n = 165), validation (n = 35) and test (n = 36) cohorts. We evaluated multiple modeling approaches: different Generalized Linear Model (GLM) approaches, Elastic Net, XGBoost, Random Forest, ensemble methods, and a Null model baseline. Results: All models demonstrated similar predictive performance, with root mean squared errors ranging from 26.28 percentage points (pp) to 30.74 and mean absolute errors ranging from 20.62 pp to 23.75 pp. Coefficients of determination (R2) ranged from −0.468 to −0.073. Bland–Altman analyses revealed wide limits of agreement and consistent negative bias, while Passing–Bablok regression indicated calibration errors. Nonetheless, all models incorporating predictors significantly outperformed the Null model. Conclusions: Increasing model complexity yielded only marginal improvements in predictive accuracy compared with simpler statistical models. Pre-implantation clinical variables showed limited evidence of predictive validity for CI outcomes, although further research is needed.

ABSTRACT This paper makes an empirical and methodological contribution to estimating the impact of failed support services, such as electricity, on agricultural value chains. Our research offers estimates of the effects of loadshedding (scheduled power outages) on three distinct agricultural value chains, along with strategies used to manage these disruptions. To compare the effects of loadshedding with a baseline of uninterrupted electricity supply, we utilise semi-structured interviews, a multi-market Partial Equilibrium (PE) model integrated with a farm-level financial simulation model (FinSim). This forward-looking, scenario-based approach overcomes a key limitation in existing studies, which typically assess either market outcomes or farm-level impacts in isolation. The modelling simulates how current loadshedding conditions could influence future production, profitability, and value chain performance under alternative assumptions. Our analysis highlights four key considerations. First, the reliance of value chains on Eskom for electricity affects operational continuity. Second, additional costs are internalised or passed on to upstream and downstream operators, putting pressure on firm and chain profitability. Some costs are also inadequately transferred to already vulnerable consumers. Third, production cycles lead to short-term disruptions and longer-term structural adjustments. Reduced demand for inputs or products within the chain can also result in underutilised facilities, increasing overhead costs and causing further disruptions. Lastly, adopting alternative energy sources at an extra cost negatively affects profitability, impacting capital access, equipment availability, affordability, and operational layout. Implementing mitigation strategies, such as investments in renewable energy infrastructure and incentives for energy efficiency, can help ensure a reliable power supply for agricultural activities.

The mobility of physically disabled people has become an important social concern in today's society. A wheelchair is used for the mobility of disabled people. Some wheelchairs are operated manually, while others are operated by a joystick. In recent years, the use of renewable energy in various sectors has gained popularity. The solar-assisted wheelchair is an innovative mechanical device that offers self-mobility with the help of a Bluetooth control app. It allows users to control the wheelchair using an Android app, eliminating the need for a joystick and addressing related issues, while utilizing renewable energy sources. The wheelchair is powered by a solar panel that charges the battery through an electrochemical process, which provides power to the motors that rotate the wheels. As a result, the user's effort to operate and control the wheelchair’s wheels and joysticks is reduced. Different buttons in Android apps allow the wheelchair to go left, right, forward, and backward. If no button is pressed, the wheelchair remains stationary due to the motor’s high torque. Additionally, there is a manual brake system available for use when needed. The wheelchair also features a charging regulator and a cord for charging mobile devices. This solar-assisted wheelchair has been successfully developed and tested. The average speed of this vehicle is 2.47 km/hr on concrete roads, 2.84 km/hr on asphalt roads, 1.96 km/hr on brick roads, and 2.54 km/hr on floors. This wheelchair is especially beneficial for people with disabilities in rural areas, and it is an affordable, user-friendly, self-driven solution. It provides greater independence and is cost-effective, making it a viable option for low-income countries like Bangladesh.

Abstract Surgeons often hesitate to utilize absorbable sutures in adults due to concerns about suture line breakage, which can lead to aneurysmal formation. The annealing process was employed to improve the physical properties of PGA/TMC copolymer sutures, enhancing their mechanical properties for safer use in adult vascular surgery. The trade name of the PGA/TMC copolymer suture is Maxon. In vitro degradation studies were conducted to assess the impact of the annealing process on the mechanical properties and degradation rate of both untreated and annealed samples at 100 °C, 120 °C, and 140 °C for 2 h. A Mach–Zehnder interferometer, coupled with a mechanical device, was used to determine optomechanical properties and 3D refractive index profiles for the Maxon samples. X-ray diffraction, Fourier-transform infrared spectroscopy, and optical microscopy were employed to measure structural variations in the samples due to annealing and in vitro degradation. The results showed that the annealed sample at 100 °C retained 69 % of its original mechanical strength after 32 days of degradation, compared to 51 % for the untreated sample, demonstrating a 35 % improvement in degradation resistance. This indicates that the annealed sample exhibited improved mechanical stability and degradation resistance, making it more suitable for vascular surgical applications.

Autism is a genetically and clinically very heterogeneous group of disorders. Gene co-expression network analysis can help unravel its complex genetic architecture through the identification of communities of genes that are dysregulated. Using a publicly available brain microarray dataset (experiment GSE28475), we performed a gene co-expression analysis based on Leiden community detection to identify stable communities of genes and used them within a robust machine learning framework with feature selection. We reached an accuracy as high as in discriminating between autism and control subjects and validated our results on an independent microarray experiment obtaining an accuracy of . Furthermore, we found two communities of 43 and 44 genes that were enriched for genetically associated variants and reached an accuracy of and on the independent set, respectively.An eXplainable Artificial Intelligence analysis on these two causal communities confirmed the pivotal role of autism specific variants thus independently validating our analysis. Further analysis on the restricted number of genes in the identified communities may reveal essential mechanisms responsible for autism spectrum disorder.

Background: Studies have revealed Gender-based differences in the management and outcomes of myocardial infarction (MI), with women often facing a poorer prognosis compared to men. Our study aims to analyze the gender based disparities in the clinical outcomes and the overall utilization of mechanical circulatory support (MCS) devices among patients with myocardial infarction (MI). Methods: A retrospective analysis was carried out using data from the National Inpatient Sample, focusing on patients admitted with acute myocardial infarction complicated by cardiogenic shock (AMI-CS) between 2016 and 2022. The study examined the use of mechanical circulatory support (MCS) devices, which included intra-aortic balloon pumps (IABP), percutaneous left ventricular assist devices (pLVAD), and extracorporeal membrane oxygenation (ECMO). It also assessed in-hospital mortality rates, stratified by Gender, among patients with myocardial infarction. Results: Among 2,604,638 patients hospitalized with myocardial infarction, significant disparities were observed between men and women in both clinical presentation and management. Women were more likely to present with NSTEMI and had a higher prevalence of premature coronary artery disease (34.8% vs. 20.8%, p &lt;0.001). In contrast, men were more likely to present with STEMI (27.1% vs. 19.7%, p &lt;0.001). Despite the higher prevalence of NSTEMI in women, they underwent fewer invasive procedures compared to men, including coronary angiography (68.5% vs. 76.4%, p &lt;0.001), percutaneous coronary intervention (44.6% vs. 56.6%, p &lt;0.001), and coronary artery bypass grafting (6.5% vs. 11.0%, p &lt;0.001). The overall use of mechanical circulatory support devices in men vs women (6.1% vs 4.2%, p &lt;0.001), with intra-aortic balloon pumps (IABP)(4.4% vs 3.1%, p &lt;0.001), extracorporeal membrane oxygenation ECMO (0.3% vs 0.2%, p &lt; 0.001), and percutaneous left ventricular assist devices (pLVAD)(1.8% vs 1.2%, p &lt;0.001), use lower in women. Notably, in-hospital mortality was significantly higher among women compared to men (5.5% vs. 4.7%, p &lt;0.001). Conclusion: There are significant gender based disparities in the management and outcomes of myocardial infarction. Women are less likely to receive invasive procedures and advanced device support, even though they experience higher in-hospital mortality rates. These findings highlight the urgent need for more equitable care strategies to address these inequities and to improve outcomes.

Introduction: Impella CP (Abiomed, Danvers, MA) microaxial flow pumps are commonly used in acute myocardial infarction (AMI) and heart failure (HF) cardiogenic shock (CS). Contemporary data from large, unselected populations are needed to understand differences between these groups. Hypothesis: Differences in patient and hospitalization characteristics such as device exposure and shock complications may contribute to differences in outcomes between those with AMI-CS compared to HF-CS. Methods: The Cardiogenic Shock Working Group (CSWG) registry enrolls patients with CS at 36 international sites. We analyzed patients with CS and Impella CP enrolled from 2019-2024, categorized by CS etiology and mechanical support device exposure. Baseline characteristics, complications, and outcomes were compared. Outcomes included survival to discharge, native heart survival, and heart replacement therapy. Multivariable analysis was performed to identify predictors of mortality and complications. Results: 1486 patients with CS (34.9% HF-CS, 57.9% AMI-CS) and Impella CP were analyzed. Patients with HF-CS were younger (60 vs 64 years), more often had chronic kidney disease (26.4% vs 13.6), less commonly had cardiac arrest (13.3% vs 27.6%), and less commonly had CSWG-SCAI stage E CS (45.7% vs 57.2%) than those with AMI-CS (p&lt;0.001 for all). Impella CP alone was used in 38.3%. Multi-device strategies (sequential or concurrent) included CP+IABP in 9.8%, CP+Impella 5.0/5.5 in 8.3%, CP+ECMO in 23.1%, and CP+≥2 other devices in 20.4%. Impella CP alone was the most common device strategy in both HF-CS (37.9%) and AMI-CS (38.9%) followed by CP+ECMO (26.4% and 20.8%). Acute kidney injury and renal replacement therapy were more common in HF-CS than AMI-CS (66.5% vs 59.7%, p=0.03 for AKI; 40.5% vs 32.7%, p=0.002 for RRT). Acute limb ischemia was less common in HF-CS than in AMI-CS (11.0% vs 14.4%; p=0.05), with no difference in bleeding (36.8% vs 41.7%; p=0.08). Survival to discharge was 53.4% and was higher in HF-CS than AMI-CS (59.7% vs 49.8%; p&lt;0.001). Patients supported by Impella CP+≥2 other devices had the lowest survival (43.8%). Multivariable modeling revealed several factors that were significantly associated with mortality, limb ischemia, and bleeding ( Figure ). Conclusion: Differences in baseline characteristics, shock severity, mechanical device exposure, and hospital complications between patients with HF-CS and AMI-CS supported by Impella CP may influence outcomes.

Background: The use of temporary mechanical circulatory support (tMCS) devices in cardiogenic shock has sharply risen; however, there are limited data depicting the current rates of device related complications and associated downstream clinical ramifications. Methods: The Critical Care Cardiology Trials Network is an international multicenter research network of advanced cardiac intensive care units (CICUs). Between 2017-2024 participating CICUs captured all consecutive admissions with cardiogenic shock during annual minimum 2-month collection periods. This analysis focused on cases managed with non-ECMO tMCS. We conducted Wilcoxon rank-sum tests for continuous variables, chi-squared test for categorical variables, and a multi-variable linear mixed-effect regression model. Results: Among 2,015 admissions with cardiogenic shock and tMCS, 103 (5.1%) developed an MCS-related complication with substantial variation across device types (2.8% to 10.9%, Fig A ). Limb ischemia (28.9%) and access site bleeding (22.9%) were the most common tMCS-related complications. Admissions with a tMCS related complication were slightly younger (61 v. 63 years) and more likely female (34% v. 27%). Cases with tMCS-related complications had higher shock severity reflected by more SCAI D shock (43.7% versus 35.1%) and number of vasoactive medications (3 v. 2). Admissions with an MCS complication had higher rates of mechanical ventilation (68.9% v. 59.1%) and renal replacement therapy (33.0% v. 17.6%) with longer ICU length of stay (9.2 v. 6.6 days). In-hospital mortality was higher among cases with complications (46.6% v. 31.6%; Fig B ); complications were associated with a higher mortality even after adjustment (OR 1.63; 95% CI: 1.00 – 2.67; p = 0.05). Conclusions: The rates of MCS related complications vary notably by access site and specific modality; complications were associated with longer ICU stays and high mortality rates.

Background: Glucagon-like peptide 1 (GLP-1) receptor agonists have demonstrated cardiovascular benefits in diabetic patients. However, their role in patients with dilated cardiomyopathy (DCM) without diabetes remains unclear. Methods: We conducted a real-world, retrospective cohort study using the TriNetX Global Collaborative Network. Adults aged 18 or older with a diagnosis of DCM (ICD-10 I42.0) and no diagnosis of diabetes (ICD-10 E10–E13) were identified. Patients were stratified based on GLP-1 receptor agonist use (liraglutide, semaglutide, dulaglutide, lixisenatide, tirzepatide, pramlintide). Propensity score matching (1:1) was performed to balance demographics, comorbidities, and cardiovascular medications, yielding 2,871 patients per group. Outcomes were assessed from 1 day to 365 days after the index event. The primary outcome was all-cause mortality; secondary outcomes included hospitalization, myocardial infarction (MI), and heart failure exacerbation (HF-exa). Median follow-up time was approximately 11 months in both groups. Results: GLP-1 receptor agonist use was associated with significantly lower risks of all-cause mortality (1.3% vs 4.1%; risk ratio [RR] 0.316; 95% CI 0.219–0.456; p&lt;0.001), hospitalization (17.5% vs 32.0%; RR 0.547; p&lt;0.001), MI (2.5% vs 6.5%; RR 0.392; p&lt;0.001), and HF-exa (0.8% vs 3.7%; RR 0.220; p&lt;0.001). Kaplan-Meier analysis confirmed higher 1-year survival probabilities and lower event rates in the GLP-1 group across all endpoints. No significant differences were observed in use of mechanical circulatory support devices (LVAD or Impella). Conclusion: In this real-world, propensity-matched study of non-diabetic patients with DCM, GLP-1 receptor agonists were associated with substantial reductions in 1-year mortality, hospitalization, MI, and HF exacerbation. Although a 3-year follow-up window was available, median follow-up (~11 months) supported 1 year as the most reliable endpoint. Limitations include lack of LVEF or biomarker data, unmeasured confounding, and inability to confirm long-term medication adherence or persistence. Additionally, GLP-1 use may reflect closer outpatient monitoring or healthier behaviors not captured in the dataset. These findings warrant prospective trials to evaluate GLP-1 receptor agonists as cardioprotective therapies in heart failure beyond glycemic control.

Introduction: Temporary mechanical circulatory support (tMCS) devices are often used in patients with cardiogenic shock (CS). Whether tMCS device-related adverse events (DRAEs) affect patient outcomes is unclear. Aim: To assess whether DRAEs are associated with worse in-hospital outcomes in patients with CS. Methods: A retrospective chart review was conducted to identify patients with CS requiring tMCS at the Medical University of South Carolina from 8/2021 to 8/2023. Patients were stratified by presence/absence of a DRAE (occurring while on tMCS support or ≤48 hrs of tMCS removal). DRAE definitions were based on published guidelines and included bacteremia, bleeding, neurologic event, vascular injury, heparin induced thrombocytopenia and hemolysis. Outcomes included in-hospital death and “unfavorable outcome” (death prior to heart transplant, durable LVAD, or discharge). Multivariable logistic regression was performed to account for differences in baseline characteristics. Results: Among 268 patients included, 112 (41.8%) had a DRAE and 156 (58.2%) did not. The median (25 th , 75 th ) age was 60 (44, 67) years, 36.6% were Black, and 28.4% were female (p=NS between groups). Historical atrial fibrillation (AF) and HFrEF were more common in those with a DRAE than those without (34.0% vs 22.3%, p=0.04 for AF; 73.7% vs 54.5%, p&lt;0.01 for HFrEF). Those with a DRAE had more advanced CS (stage D/E 72.3% vs 50.0%, p&lt;0.01), more commonly had cardiac arrest prior to tMCS (23.2% v 9.6%, p&lt;0.01), and more commonly were on ECMO (33.9% v 5.1%, p&lt;0.01). The median hospital length of stay was 30 (18, 46) days, with no significant difference between groups. In the DRAE group, a total of 161 unique DRAEs occurred, with 48 patients experiencing &gt;1 DRAE. The most common AE was bleeding, followed by hemolysis, and bacteremia ( Figure ). In-hospital death was more common in the DRAE group (32.1% vs 12.2%; unadjusted OR [95% CI] 3.42 [1.83-6.37]; p&lt;0.01). Unfavorable outcome was also more common in the DRAE group (28.6% vs 10.9%, unadjusted OR 3.27 [1.71-6.26]; p&lt;0.01) ( Figure ). These findings were consistent after adjustment for age, sex, history of HFrEF, history of AF, and ECMO exposure. Conclusion: The presence of a DRAE in patients with CS and tMCS is associated with a significantly higher in-hospital mortality and unfavorable outcome.

Introduction: Gastrointestinal bleeding (GIB) is a common, potentially modifiable, complication in patients receiving mechanical circulatory support (MCS) but head-to-head data for single and multi-device MCS strategies remains sparse. Research Question: To compare the incidence of GIB, transfusion burden, and in-hospital mortality across single- and multi-device MCS strategies using the MIMIC-IV critical care database. Methods: This retrospective study analyzed ICU encounters (2009-2022) of adults at Beth Israel Deaconess Medical Center with documented Extracorporeal Membranous Oxygen (ECMO), Impella, or Intra-aortic Balloon Pump (IABP) use. Data was obtained using the MIMIC-IV database with 85,000 ICU encounters. Exposures were categorized as single-device (ECMO, Impella, IABP) or multi-device combinations. The primary endpoint was any GIB (ICD-9/10 diagnoses). Secondary endpoints were packed red-blood-cell (pRBC) transfusion, hemorrhagic anemia, and in-hospital mortality. Categorical variables were compared using Fisher’s exact test; relative risks (RR) with 95% confidence intervals (CI) were calculated in comparison to IABP. Further analyses were stratified by support duration (&lt;7 vs. ≥7 days). Results: A total of 1,404 MCS encounters were analyzed. Among 1,280 single-device ICU admissions (IABP=1,006, Impella=141, ECMO=133) GIB occurred in 5.1%, 5.0%, and 11%, respectively. ECMO had 2.2x higher risk vs. IABP (p&lt;.01) and 2.3x vs. Impella (p=0.07). When limited to patients supported for &lt;7 days, the risk of GIB on ECMO vs. IABP narrowed to 1.8 (95% CI 0.85-3.9), but the risk of need for pRBC transfusion or hemorrhagic anemia remained 2.4 (95% CI 2.0-2.9) and 1.6 (95% CI 1.2-2.0) times higher, respectively. pRBC units per transfused patient was likewise greatest at both durations with ECMO (6.9, 20.4) vs. Impella (2.9, 4.4) and IABP (2.5, 5.5). Multi-device cases showed higher crude bleeding (19–25%) but small sample size and heterogeneous timing or sequencing limit inference. In-hospital mortality likely reflected underlying severity of illness, with single-device ECMO and Impella both exceeding 50% vs.18% for IABP. Conclusions: Gastrointestinal bleeding and transfusion burden vary significantly by MCS strategy and duration, with ECMO carrying the greatest risk. Bleeding risk should factor into MCS selection. Prospective studies are needed to evaluate individualized bleeding mitigation protocols.