Machine learning predicts emergency physician specialties from treatment strategies for patients suspected of myocardial infarction.

BACKGROUND: Our investigation aimed to determine how the diverse backgrounds and medical specialties of emergency physicians (Eps) influence the accuracy of diagnoses and the subsequent treatment pathways for patients presenting preclinically with MI symptoms. By scrutinizing the relationships between EPs' specialties and their approaches to patient care, we aimed to unveil potential variances in diagnostic accuracy and treatment choices. METHODS: In this retrospective, monocenter cohort study, we leveraged machine learning techniques to analyze a comprehensive dataset of 2328 patients with suspected MI, encompassing preclinical diagnoses, electrocardiogram (ECG) interpretations, and subsequent treatment strategies by attending EPs. RESULTS: We demonstrated that diagnosis and treatment patterns of different specialties were distinct enough, that machine learning (ML) was able to differentiate between specialties (maximum area under the receiver operating characteristic = 0.80 for general medicine and 0.80 for surgery). In our study, internist demonstrated the highest accuracy for preclinical identification of STEMI (0.96) whereas surgeons showed the highest accuracy for identifying NSTEMI. Our findings highlight significant correlations between EP specialties and the accuracy of both preclinical diagnoses and subsequent treatment pathways for patients with suspected MI. CONCLUSIONS: Our results offer valuable insights into how the diverse backgrounds and specialties of EPs can influence the optimization of patient care in emergency settings. Understanding these patterns can help in the development of tailored training programs and protocols to enhance diagnostic accuracy and treatment efficacy in emergency cardiac care, ultimately optimizing patient treatment and improving outcomes.

Preclinical identification of acute coronary syndrome without high sensitivity troponin assays using machine learning algorithms.

Preclinical management of patients with acute chest pain and their identification as candidates for urgent coronary revascularization without the use of high sensitivity troponin essays remains a critical challenge in emergency medicine. We enrolled 2760 patients (average age 70 years, 58.6% male) with chest pain and suspected ACS, who were admitted to the Emergency Department of the University Hospital Tübingen, Germany, between August 2016 and October 2020. Using 26 features, eight Machine learning models (non-deep learning models) were trained with data from the preclinical rescue protocol and compared to the "TropOut" score (a modified version of the "preHEART" score which consists of history, ECG, age and cardiac risk but without troponin analysis) to predict major adverse cardiac event (MACE) and acute coronary artery occlusion (ACAO). In our study population MACE occurred in 823 (29.8%) patients and ACAO occurred in 480 patients (17.4%). Interestingly, we found that all machine learning models outperformed the "TropOut" score. The VC and the LR models showed the highest area under the receiver operating characteristic (AUROC) for predicting MACE (AUROC = 0.78) and the VC showed the highest AUROC for predicting ACAO (AUROC = 0.81). A SHapley Additive exPlanations (SHAP) analyses based on the XGB model showed that presence of ST-elevations in the electrocardiogram (ECG) were the most important features to predict both endpoints.

cGMP modulates hemin-mediated platelet death.

BACKGROUND AND AIMS: Hemolysis is a known risk factor for thrombosis resulting in critical limb ischemia and microcirculatory disturbance and organ failure. Intravasal hemolysis may lead to life-threatening complications due to uncontrolled thrombo-inflammation. Until now, conventional antithrombotic therapies failed to control development and progression of these thrombotic events. Thus, the pathophysiology of these thrombotic events needs to be investigated to unravel underlying pathways and thereby identify targets for novel treatment strategies. METHODS: Here we used classical experimental set-ups as well as high-end flow cytometry, metabolomics and lipidomic analysis to in-depth analyze the effects of hemin on platelet physiology and morphology. RESULTS: Hemin does strongly and swiftly induce platelet activation and this process is modulated by the sGC-cGMP-cGKI signaling axis. cGMP modulation also reduced the pro-aggregatory potential of plasma derived from patients with hemolysis. Furthermore, hemin-induced platelet death evokes distinct platelet subpopulations. Typical cell death markers, such as ROS, were induced by hemin-stimulation and the platelet lipidome was specifically altered by high hemin concentration. Specifically, arachidonic acid derivates, such as PGE2, TXB2 or 12-HHT, were significantly increased. Balancing the cGMP levels by modulation of the sGC-cGMP-cGKI axis diminished the ferroptotic effect of hemin. CONCLUSION: We found that cGMP modulates hemin-induced platelet activation and thrombus formation in vitro and cGMP effects hemin-mediated platelet death and changes in the platelet lipidome. Thus, it is tempting to speculate that modulating platelet cGMP levels may be a novel strategy to control thrombosis and critical limb ischemia in patients with hemolytic crisis.

Cyclophilin A is a ligand for RAGE in thrombo-inflammation.

AIMS: Cyclophilin A (CyPA) induces leucocyte recruitment and platelet activation upon release into the extracellular space. Extracellular CyPA therefore plays a critical role in immuno-inflammatory responses in tissue injury and thrombosis upon platelet activation. To date, CD147 (EMMPRIN) has been described as the primary receptor mediating extracellular effects of CyPA in platelets and leucocytes. The receptor for advanced glycation end products (RAGE) shares inflammatory and prothrombotic properties and has also been found to have similar ligands as CD147. In this study, we investigated the role of RAGE as a previously unknown interaction partner for CyPA. METHODS AND RESULTS: Confocal imaging, proximity ligation, co-immunoprecipitation, and atomic force microscopy were performed and demonstrated an interaction of CyPA with RAGE on the cell surface. Static and dynamic cell adhesion and chemotaxis assays towards extracellular CyPA using human leucocytes and leucocytes from RAGE-deficient Ager-/- mice were conducted. Inhibition of RAGE abrogated CyPA-induced effects on leucocyte adhesion and chemotaxis in vitro. Accordingly, Ager-/- mice showed reduced leucocyte recruitment and endothelial adhesion towards CyPA in vivo. In wild-type mice, we observed a downregulation of RAGE on leucocytes when endogenous extracellular CyPA was reduced. We furthermore evaluated the role of RAGE for platelet activation and thrombus formation upon CyPA stimulation. CyPA-induced activation of platelets was found to be dependent on RAGE, as inhibition of RAGE, as well as platelets from Ager-/- mice showed a diminished activation and thrombus formation upon CyPA stimulation. CyPA-induced signalling through RAGE was found to involve central signalling pathways including the adaptor protein MyD88, intracellular Ca2+ signalling, and NF-κB activation. CONCLUSION: We propose RAGE as a hitherto unknown receptor for CyPA mediating leucocyte as well as platelet activation. The CyPA-RAGE interaction thus represents a novel mechanism in thrombo-inflammation.

Critical shifts in lipid metabolism promote megakaryocyte differentiation and proplatelet formation.

During megakaryopoiesis, megakaryocytes (MK) undergo cellular morphological changes with strong modification of membrane composition and lipid signaling. Here we adopt a lipid-centric multiomics approach to create a quantitative map of the MK lipidome during maturation and proplatelet formation. Data reveal that MK differentiation is driven by an increased fatty acyl import and de novo lipid synthesis, resulting in an anionic membrane phenotype. Pharmacological perturbation of fatty acid import and phospholipid synthesis blocked membrane remodeling and directly reduced MK polyploidization and proplatelet formation resulting in thrombocytopenia. The anionic lipid shift during megakaryopoiesis was paralleled by lipid-dependent relocalization of the scaffold protein CKIP-1 and recruitment of the kinase CK2α to the plasma membrane, which seems to be essential for sufficient platelet biogenesis. Overall, this study provides a framework to understand how the MK lipidome is altered during maturation and the impact of MK membrane lipid remodeling on MK kinase signaling involved in thrombopoiesis.

Translating genomic tools to Raman spectroscopy analysis enables high-dimensional tissue characterization on molecular resolution.

Spatial transcriptomics of histological sections have revolutionized research in life sciences and enabled unprecedented insights into genetic processes involved in tissue reorganization. However, in contrast to genomic analysis, the actual biomolecular composition of the sample has fallen behind, leaving a gap of potentially highly valuable information. Raman microspectroscopy provides untargeted spatiomolecular information at high resolution, capable of filling this gap. In this study we demonstrate spatially resolved Raman "spectromics" to reveal homogeneity, heterogeneity and dynamics of cell matrix on molecular levels by repurposing state-of-the-art bioinformatic analysis tools commonly used for transcriptomic analyses. By exploring sections of murine myocardial infarction and cardiac hypertrophy, we identify myocardial subclusters when spatially approaching the pathology, and define the surrounding metabolic and cellular (immune-) landscape. Our innovative, label-free, non-invasive "spectromics" approach could therefore open perspectives for a profound characterization of histological samples, while additionally allowing the combination with consecutive downstream analyses of the very same specimen.

Development of an Anticipatory Triage-Ranking Algorithm Using Dynamic Simulation of the Expected Time Course of Patients With Trauma: Modeling and Simulation Study.

BACKGROUND: In cases of terrorism, disasters, or mass casualty incidents, far-reaching life-and-death decisions about prioritizing patients are currently made using triage algorithms that focus solely on the patient's current health status rather than their prognosis, thus leaving a fatal gap of patients who are under- or overtriaged. OBJECTIVE: The aim of this proof-of-concept study is to demonstrate a novel approach for triage that no longer classifies patients into triage categories but ranks their urgency according to the anticipated survival time without intervention. Using this approach, we aim to improve the prioritization of casualties by respecting individual injury patterns and vital signs, survival likelihoods, and the availability of rescue resources. METHODS: We designed a mathematical model that allows dynamic simulation of the time course of a patient's vital parameters, depending on individual baseline vital signs and injury severity. The 2 variables were integrated using the well-established Revised Trauma Score (RTS) and the New Injury Severity Score (NISS). An artificial patient database of unique patients with trauma (N=82,277) was then generated and used for analysis of the time course modeling and triage classification. Comparative performance analysis of different triage algorithms was performed. In addition, we applied a sophisticated, state-of-the-art clustering method using the Gower distance to visualize patient cohorts at risk for mistriage. RESULTS: The proposed triage algorithm realistically modeled the time course of a patient's life, depending on injury severity and current vital parameters. Different casualties were ranked by their anticipated time course, reflecting their priority for treatment. Regarding the identification of patients at risk for mistriage, the model outperformed the Simple Triage And Rapid Treatment's triage algorithm but also exclusive stratification by the RTS or the NISS. Multidimensional analysis separated patients with similar patterns of injuries and vital parameters into clusters with different triage classifications. In this large-scale analysis, our algorithm confirmed the previously mentioned conclusions during simulation and descriptive analysis and underlined the significance of this novel approach to triage. CONCLUSIONS: The findings of this study suggest the feasibility and relevance of our model, which is unique in terms of its ranking system, prognosis outline, and time course anticipation. The proposed triage-ranking algorithm could offer an innovative triage method with a wide range of applications in prehospital, disaster, and emergency medicine, as well as simulation and research.

The Subtilisin-Like Protease Furin Regulates Hemin-Dependent Ectodomain Shedding of Glycoprotein VI.

INTRODUCTION: Hemolysis results in release of free hemoglobin and hemin liberation from erythrocytes. Hemin has been described to induce platelet activation and to trigger thrombosis. METHODS: We evaluated the effect of hemin on platelet function and surface expression of the platelet collagen receptor glycoprotein VI (GPVI). Isolated platelets were stimulated with increasing concentrations of hemin. RESULTS: We found that hemin strongly enhanced platelet activation, aggregation, and aggregate formation on immobilized collagen under flow. In contrast, we found that surface expression of GPVI was significantly reduced upon hemin stimulation with high hemin concentrations indicating that hemin-induced loss of surface GPVI does not hinder platelet aggregation. Loss of hemin-induced surface expression of GPVI was caused by shedding of the ectodomain of GPVI as verified by immunoblotting and is independent of the GPVI or CLEC-2 mediated ITAM (immunoreceptor-tyrosine-based-activation-motif) signaling pathway as inhibitor studies revealed. Hemin-induced GPVI shedding was independent of metalloproteinases such as ADAM10 or ADAM17, which were previously described to regulate GPVI degradation. Similarly, concentration-dependent shedding of CD62P was also induced by hemin. Unexpectedly, we found that the subtilisin-like proprotein convertase furin controls hemin-dependent GPVI shedding as shown by inhibitor studies using the specific furin inhibitors SSM3 and Hexa-D-arginine. In the presence of SSM3 and Hexa-D-arginine, hemin-associated GPVI degradation was substantially reduced. Further, SSM3 inhibited hemin-induced but not CRP-XL-induced platelet aggregation and thrombus formation, indicating that furin controls specifically hemin-associated platelet functions. CONCLUSION: In summary, we describe a novel mechanism of hemin-dependent GPVI shedding and platelet function mediated by furin.

ACKR3 regulates platelet activation and ischemia-reperfusion tissue injury.

Platelet activation plays a critical role in thrombosis. Inhibition of platelet activation is a cornerstone in treatment of acute organ ischemia. Platelet ACKR3 surface expression is independently associated with all-cause mortality in CAD patients. In a novel genetic mouse strain, we show that megakaryocyte/platelet-specific deletion of ACKR3 results in enhanced platelet activation and thrombosis in vitro and in vivo. Further, we performed ischemia/reperfusion experiments (transient LAD-ligation and tMCAO) in mice to assess the impact of genetic ACKR3 deficiency in platelets on tissue injury in ischemic myocardium and brain. Loss of platelet ACKR3 enhances tissue injury in ischemic myocardium and brain and aggravates tissue inflammation. Activation of platelet-ACKR3 via specific ACKR3 agonists inhibits platelet activation and thrombus formation and attenuates tissue injury in ischemic myocardium and brain. Here we demonstrate that ACKR3 is a critical regulator of platelet activation, thrombus formation and organ injury following ischemia/reperfusion.

Platelet surface expression of cyclophilin A is associated with increased mortality in patients with symptomatic coronary artery disease.

BACKGROUND: Cyclophilin A (CyPA) is an important intracellular molecule mediating essential cellular functions such as signaling and protein folding. Enhanced CyPA platelet surface expression is associated with hypertension and hypercholesterolemia in patients with stable coronary artery disease (CAD). In patients with acute myocardial infarction CyPA platelet surface expression is significantly decreased. The aim of this study was to investigate possible associations of CyPA platelet surface expression and a clinically relevant CyPA single-nucleotide polymorphism (CyPA PPIA rs6850) with prognosis in patients with symptomatic cardiovascular disease. MATERIALS AND METHODS: Blood was obtained from 335 consecutive patients with symptomatic CAD. All patients were followed up for 1080 days for endpoints all-cause death, myocardial infarction (MI), ischemic stroke, and bleeding. The primary combined endpoint was defined as a composite of all-cause death and/or MI and/or ischemic stroke. Cyclophilin A platelet surface expression levels less than or equal to the median were significantly associated with a worse prognosis (combined endpoint and all-cause death) when compared to CyPA greater than the median. Genotyping for CyPA PPIA rs6850 was performed in 752 patients with symptomatic CAD. Homozygous carriers of the minor allele showed a significantly worse cumulative event-free survival for both combined endpoint and MI when compared to carriers of the major allele. CONCLUSION: The CyPA platelet surface expression is associated with mortality whereas CyPA PPIA rs6850 is associated with recurrent MI in patients with symptomatic CAD. Cyclophilin A might offer a new biomarker for risk stratification and tailoring therapies in patients with cardiovascular disease.