Prehospital Diagnosis Research Articles

Impact of Gender and Marital Status on Door-to-Treatment (DTT) Time and Acute Stroke Outcome.

Delays in acute stroke treatment lead to poor outcomes. Women can present with atypical stroke symptoms, are older at the time of stroke, and tend to be living alone, causing delays in pre-hospital diagnosis and seeking care. It is unclear if gender disparities in ED arrival and stroke assessment are compounded by gender differences after ED arrival. Therefore, we sought to identify if gender and marital status were associated with faster door-to-treatment (DTT) time. Our single-center stroke database was queried for adults presenting to ED with acute stroke between January 1, 2018 and January 30, 2023 treated with IV thrombolytics (IVT)+/- endovascular thrombectomy (EVT) and a known DTT time. The primary outcome was DTT (door-to-needle+door-to-puncture) time. Data collected includes the National Institutes of Health Stroke Scale (NIHSS) at presentation and discharge, gender, marital status, age, and intervention (IVT alone or IVT+/- EVT). Among 674 patients identified, 35 patients were excluded due to missing data. Of 639 patients (median age 66y), 25%/18% of patients were married men/women, respectively, and 22%/35% were single men/women. Median DTN time, DTP time, and discharge NIHSS score were 36, 79, and 4mins, respectively. On multivariable analysis, neither DTT time nor NIHSS score at discharge improved among married men relative to any other combination of gender and marital status. Gender differences in the knowledge of stroke warning signs and gender disparities in ED assessment did not translate into faster DTT time. More work is needed to find ways to accelerate stroke care after ED arrival.

Timely empirical antibiotic therapy against sepsis in a rural Norwegian ambulance service: a prospective cohort study

BackgroundEarly diagnosis and antibiotic therapy in patients with sepsis reduce morbidity and mortality, thus pre-hospital management is likely to affect patient outcomes. Pre-hospital administration may increase the risk of unnecessary use of broad-spectrum antibiotics, but identification of an infectious focus enables more targeted antibiotic therapy. The aim of this study was to investigate how paramedics, with or without the assistance of general practitioners, can administer empiric intravenous antibiotic treatment against sepsis in a timely manner.MethodsCohort study of patients with suspected sepsis that received pre-hospital intravenous antibiotics and were transported to hospital. The setting was mainly rural with long average distance to hospital. Patients received targeted antibiotic treatment after an assessment based on clinical work-up supported by scoring systems. Patients were prospectively included from May 2018 to August 2022. Results are presented as median or absolute values, and chi-square tests were used to compare categorical data.ResultsWe included 328 patients. Median age was 76 years (IQR 64, 83) and 48.5% of patients were female. 30-days all-cause mortality was 10.4%. In cases where a suspected infectious focus was determined, the hospital discharge papers confirmed the pre-hospital diagnosis focus in 195 cases (79.3%). The presence of a general practitioner during the pre-hospital assessment increased the rate of correctly identified infectious focus from 72.6% to 86.1% (p = 0.009). Concordance between pre-hospital identification of a tentative focus and discharge diagnosis was highest for lower respiratory tract (p = 0.02) and urinary tract infections (p = 0.03). Antibiotic treatment was initiated 44 min (median) after arrival of ambulance, and median transportation time to hospital was 69 min. Antibiotic therapy was started 76 min (median) before arrival at hospital.ConclusionsPre-hospital identification of infectious focus in suspected sepsis was feasible, and collaboration with primary care physicians increased level of diagnostic accuracy. This allowed initiation of intravenous focus-directed antibiotics more than one hour before arrival in hospital in a rural setting. The effect of pre-hospital therapy on timing was much stronger than in previous studies from more urban areas.

Real-Time precision prehospital stroke diagnosis in weightlifting athletes using cutting-edge non-invasive sensors

This research paper presents an investigation into the efficacy of a novel diagnostic technology designed for the real-time monitoring of weightlifting athletes, focusing on precision, time efficiency, and user convenience compared to traditional diagnostic systems. The study introduces an advanced non-invasive sensor system, integrated into a cohesive Internet of Medical Things (IoMT) framework, which facilitates the immediate and accurate assessment of athletes' health parameters. To empirically test the benefits of this new technology, a pedagogical experiment was conducted involving two distinct groups: an experimental group that utilized the proposed technology for medical checkups, and a control group that continued with traditional diagnostic methods. Each group consisted of 30 athletes, and the outcomes were measured across three dimensions: the precision of diagnostic results, the time expended for medical checkups, and the user-reported convenience of the equipment. The findings indicate that the proposed technology not only significantly enhances the precision of health diagnostics but also reduces the time required for medical examinations, thereby increasing overall efficiency. Additionally, the higher convenience scores reported by the experimental group suggest improved user satisfaction and usability. These results demonstrate the potential of the proposed diagnostic system to transform athlete health monitoring by providing more accurate, efficient, and user-friendly medical assessments, suggesting a significant step forward in the application of advanced technologies in sports medicine.

A newly developed, easy-to-use prehospital drug-derived score compared with three conventional scores: A prospective multicenter study.

The use of medications by emergency medical services (EMS) is increasing. Conventional scores are time-consuming and therefore difficult to use in an emergency setting. For early decision-making, an easy-to-use score based on the medications administered by the EMS may have prognostic value. The primary objective of this study was to develop the prehospital drug-derived score (PDDS) for 2-day mortality. A prospective, multicenter, ambulance-based cohort study was conducted in adults with undifferentiated acute diseases treated by EMS and transferred to the emergency department. Demographic data, prehospital diagnosis data, prehospital medication and variables for the calculation of the National Early Warning Score 2 (NEWS2), Rapid Emergency Medicine Score (REMS), and Rapid Acute Physiology Score (RAPS) were collected. The PDDS was developed and validated, establishing three levels of risk of 2-day mortality. The predictive capability of each score was determined by the area under the curve of the receiver operating characteristic curve (AUROC) and compared using the Delong's test (p-value). A total of 6401 patients were included. The PDDS included age and the use of norepinephrine, analgesics, neuromuscular blocking agents, diuretics, antihypertensive agents, tranexamic acid, and bicarbonate. The AUROC of PDDS was .86 (95% CI: .816-.903) versus NEWS2 .866 (95% CI: .822-.911), p = .828; versus REMS .885 (95% CI: .845-.924), p = .311; versus RAPS .886 (95% CI: .846-.926), p = .335, respectively. The newly developed easy-to-use prehospital drug-derived PDDS score has an excellent predictive value of early mortality. The PDDS score was comparable to the conventional risk scores and therefore might serve as an alternative score in the prehospital emergency setting.

Professor Klaus Fassbender: The Father of Mobile Stroke Units.

Professor Klaus Fassbender is a distinguished neurologist from Germany, widely recognized for his groundbreaking contributions to the fields of neurology and neurodegenerative disease. His work has been pivotal in advancing our understanding of the pathophysiological mechanisms underlying neurodegenerative disorders, including Alzheimer's and Parkinson's disease, as well as in refining therapeutic strategies for their treatment. His studies in cerebrovascular disease have elucidated the complex molecular and cellular processes involved in ischemic and hemorrhagic stroke, leading to the development of novel therapeutic interventions, often bridging the gap between laboratory discoveries and their application in clinical settings. Professor Klaus Fassbender is "the father" of the mobile stroke unit (MSU). With the "time is brain" concept in mind, he proposed and developed the MSU concept for the first time, allowing prehospital stroke imaging, diagnosis, and treatment directly at the site of emergency.This concept reduced times between symptoms onset and treatment, resulting in an increased proportion of patients receiving treatment within "the golden hour" and leading to the improvement of functional outcomes at 90 days. Professor Fassbender's work has been instrumental in shaping contemporary approaches to diagnosing and managing stroke and neurodegenerative disease, making him a leading figure in modern neurology.

Optimizing Prehospital Stroke Diagnosis: Integrating Machine Learning with the FAST Scoring System

Strokes are a leading cause of disability and death worldwide, and timely diagnosis is critical for effective treatment. Prehospital stroke diagnosis by emergency medical services (EMS) is essential for ensuring prompt care. The FAST (Face, Arms, Speech, and Time) scoring system is a common tool used to identify stroke symptoms quickly. However, the traditional FAST system has limitations, including reliance on subjective assessments and potential misdiagnoses due to symptom variability. This study aims to optimize the FAST scoring system and compare its performance with various machine learning models to enhance stroke prediction accuracy. A dataset from an ambulance service, including prehospital data such as age, sex, and FAST test results, was used. Data preprocessing involved handling missing values, encoding categorical variables, and applying the Synthetic Minority Over-sampling Technique (SMOTE) to balance the dataset. A grid search was conducted to test different weighting schemes for the FAST system. Machine learning models, including Logistic Regression, Random Forest, Support Vector Machine (SVM), XGBoost, and Decision Tree, were trained and evaluated using cross-validation on the training set and tested on a separate test set. The traditional FAST system showed an accuracy of 62.95%. Optimizing the FAST system through grid search marginally increased accuracy to 64.36%. However, machine learning models, particularly Random Forest, significantly outperformed the FAST system, achieving a test set accuracy of 88.54%. XGBoost also demonstrated strong performance with an accuracy of 77.07%, while Logistic Regression, SVM, and Decision Tree showed lower accuracies. These findings suggest that integrating machine learning models into EMS protocols could substantially improve the accuracy of prehospital stroke diagnosis, leading to quicker and more accurate identification and treatment of stroke patients. Although the optimized FAST system offers slight improvements, machine learning models present a promising avenue for enhancing stroke prediction and improving patient outcomes in emergency settings while acknowledging practicality issues.

Challenges in Prehospital Diagnosis of Acute Stroke in Women: A Case-Based Reflection.

Challenges in Prehospital Diagnosis of Acute Stroke in Women: A Case-Based Reflection.

POST-TRAUMATIC HEMORRHAGE IN A PREGNANT WOMAN IN THE PRACTICE OF PRIMARY EMERGENCY MEDICAL TEAMS

Pregnancy is a unique period in a woman's life. It involves physiological changes, as well as mental and emotional ones for the mother-to-be. Pregnant women are at a higher risk of death from trauma compared to the rest of the female population. Medical activities aimed at treating pregnant trauma patients are issues that pose serious challenges for members of emergency medical teams. They require interdisciplinary medical knowledge, that of anatomy, physiology, trauma, but also obstetric and possibly neonatal care. In the pre-hospital setting, diagnosis and assistance is severely limited, so it is crucial that the pregnant woman be brought as quickly as possible to a hospital with appropriate diagnostic and specialty facilities. The aim of this study was to discuss the problem of uncontrolled internal hemorrhage in a pregnant woman, its consequences and the pre-hospital management of primary emergency medical teams. The research method was a review of the literature and recommendations of specialists of international organizations established to develop guidelines for emergency medicine. Based on the analysis, the following conclusions were drawn: 1. A traumatized pregnant woman should be given priority and special treatment in prehospital care due to measures that affect at least two lives - that of the mother and that of the child/children. 2. Due to the changes taking place in the body of the mother-to-be, injuries in pregnant women occur more frequently than in women who are not pregnant. 3. In pregnant women, the forces acting during the trauma, lead to different injuries than in non-pregnant women. 4. The effects of injuries sustained during pregnancy depend on the mechanism of injury, the severity of the injury and the stage of pregnancy. 5. Hypovolemia associated with decompensation of traumatic shock in a pregnant woman indicates an inauspicious prognosis for the health and life of the mother and baby. 6. Medical emergency procedures in pregnant trauma patients are similar to those used for other patients, but require some modifications related to the anatomical and physiological changes that occur during pregnancy. 7. Examining a pregnant patient may be difficult due to the anatomical and physiological changes occurring during this period. Increased heart rate and decreased blood pressure should not be considered a consequence of pregnancy if other causes are not ruled out. 8. It seems reasonable to introduce TXA acid into the regimens of basic emergency teams for victims with symptoms of hemorrhagic shock.

Artificial intelligence to enhance prehospital stroke diagnosis and triage: a perspective.

As health systems organize to deliver the highest quality stroke care to their patients, there is increasing emphasis being placed on prehospital stroke recognition, accurate diagnosis, and efficient triage to improve outcomes after stroke. Emergency medical services (EMS) personnel currently rely heavily on dispatch accuracy, stroke screening tools, bypass protocols and prehospital notification to care for patients with suspected stroke, but novel tools including mobile stroke units and telemedicine-enabled ambulances are already changing the landscape of prehospital stroke care. Herein, the authors provide our perspective on the current state of prehospital stroke diagnosis and triage including several of these emerging trends. Then, we provide commentary to highlight potential artificial intelligence (AI) applications to improve stroke detection, improve accurate and timely dispatch, enhance EMS training and performance, and develop novel stroke diagnostic tools for prehospital use.

Prehospital diagnosis of ischemic stroke (literature review)

Ischemic stroke is a major medical and social problem, as it is characterized by high rates of morbidity, disability and mortality. Non-invasive diagnostic methods, such as magnetic resonance and computed tomography, make it possible to visualize this pathology and, based on the results obtained, formulate a diagnosis in order to prescribe appropriate therapy for effective treatment and improve the prognosis of the disease. In recent years, the concept of prehospital diagnosis of ischemic stroke has been introduced, including mobile ultrasound machines for ultrasound examination of cerebral perfusion, as well as mobile stroke units (MSU). It was found that treatment in the MSU, including prehospital imaging, resulted in significantly better clinical outcomes, both because of early initiation of systemic thrombolysis in the golden hour and because of improved triage of patients for subsequent endovascular thrombectomy. Further financial and economic evaluation of mobile stroke units is needed, including the analysis of the cost-effectiveness of the investment project and the possibilities of introducing this innovative approach to stroke diagnosis and treatment in Russia.

GFAP point-of-care measurement for prehospital diagnosis of intracranial hemorrhage in acute coma

BackgroundPrehospital triage and treatment of patients with acute coma is challenging for rescue services, as the underlying pathological conditions are highly heterogenous. Recently, glial fibrillary acidic protein (GFAP) has been identified as a biomarker of intracranial hemorrhage. The aim of this prospective study was to test whether prehospital GFAP measurements on a point-of-care device have the potential to rapidly differentiate intracranial hemorrhage from other causes of acute coma.MethodsThis study was conducted at the RKH Klinikum Ludwigsburg, a tertiary care hospital in the northern vicinity of Stuttgart, Germany. Patients who were admitted to the emergency department with the prehospital diagnosis of acute coma (Glasgow Coma Scale scores between 3 and 8) were enrolled prospectively. Blood samples were collected in the prehospital phase. Plasma GFAP measurements were performed on the i-STAT Alinity® (Abbott) device (duration of analysis 15 min) shortly after hospital admission.Results143 patients were enrolled (mean age 65 ± 20 years, 42.7% female). GFAP plasma concentrations were strongly elevated in patients with intracranial hemorrhage (n = 51) compared to all other coma etiologies (3352 pg/mL [IQR 613–10001] vs. 43 pg/mL [IQR 29–91.25], p < 0.001). When using an optimal cut-off value of 101 pg/mL, sensitivity for identifying intracranial hemorrhage was 94.1% (specificity 78.9%, positive predictive value 71.6%, negative predictive value 95.9%). In-hospital mortality risk was associated with prehospital GFAP values.ConclusionIncreased GFAP plasma concentrations in patients with acute coma identify intracranial hemorrhage with high diagnostic accuracy. Prehospital GFAP measurements on a point-of-care platform allow rapid stratification according to the underlying cause of coma by rescue services. This could have major impact on triage and management of these critically ill patients.Graphical

Accuracy between prehospital and hospital diagnosis in helicopter emergency medical services and its consequences for trauma care

PurposeFor optimal prehospital trauma care, it is essential to adequately recognize potential life-threatening injuries in order to correctly triage patients and to initiate life-saving measures. The aim of the present study was to determine the accuracy of prehospital diagnoses suspected by helicopter emergency medical services (HEMS).MethodsThis retrospective multicenter study included patients from the Swiss Trauma Registry with ISS ≥ 16 or AIS head ≥ 3 transported by Switzerland’s largest HEMS and subsequently admitted to one of twelve Swiss trauma centers from 01/2020 to 12/2020. The primary outcome was the comparison of injuries suspected prehospital with the final diagnoses obtained at the hospital using the abbreviated injury scale (AIS) per body region. As secondary outcomes, prehospital interventions were compared to corresponding relevant diagnoses.ResultsRelevant head trauma was the most commonly injured body region and was identified in 96.3% (95% CI: 92.1%; 98.6%) of the cases prehospital. Relevant injuries to the chest, abdomen, and pelvis were also common but less often identified prehospital [62.7% (95% CI: 54.2%; 70.6%), 45.5% (95% CI: 30.4%; 61.2%), and 61.5% (95% CI: 44.6%; 76.6%)]. Overall, 7 of 95 (7.4%) patients with pneumothorax received a chest decompression and in 22 of 39 (56.4%) patients with an instable pelvic fracture a pelvic binder was applied prehospital.ConclusionApproximately half of severe chest, abdominal, and pelvic diagnoses made in hospital went undetected in the challenging prehospital environment. This underlines the difficult circumstances faced by the rescue teams. Potentially life-saving interventions such as prehospital chest decompression and increased use of a pelvic binder were identified as potential improvements to prehospital care.

Unlocking Diagnostic Precision: FATE Protocol Integration with BLUE and eFAST Protocols for Enhanced Pre-Hospital Differential Diagnosis of Pleural Effusion Manifested as Dyspnea in Adults-A Pilot Study.

Background: Dyspnea commonly stems from combined myocardial and pulmonary dysfunction, posing challenges for accurate pre-hospital diagnosis. Limited diagnostic capabilities hinder the differentiation of cardiac and pulmonary issues. This study assesses the efficacy of combined cardiac and pulmonary ultrasound using the BLUE, eFAST, and FATE protocols. Methods: Participants were consecutively enrolled from dyspnea-related emergency calls in Warsaw, Poland, from 4 April 2022, to 15 June 2023. Patients with pleural effusion were identified through pre-hospital and in-hospital radiological assessments. Pre-hospital thoracic ultrasonography followed the BLUE, eFAST, and FATE protocols, alongside comprehensive clinical assessments. The pre-hospital diagnoses were juxtaposed with the with hospital discharge diagnoses. Results: Sixteen patients (8 men, 8 women; median age: 76 years) were enrolled. Inter-rater agreement for the BLUE protocol was substantial (κ = 0.78), as was agreement for eFAST (κ = 0.75), with almost perfect agreement for combined protocol assessment (κ = 0.83). Left ventricle hypokinesis, identified via the FATE protocol, significantly correlated with hospital-diagnosed decompensated heart failure as the primary cause of dyspnea. Sensitivity and specificity were 1.0 (95%CI: 0.62-1.0) and 0.6 (95%CI: 0.15-0.95), respectively. Positive predictive value was 0.85 (95%CI: 0.55-0.98), and diagnostic accuracy was 0.86 (95%CI: 0.62-0.98). Conclusions: Integrating the FATE protocol into BLUE and eFAST enhances pre-hospital differential diagnosis accuracy of pleural effusion in adults. This synergistic approach streamlines diagnostic processes and facilitates informed clinical decision-making. Larger-scale validation studies are needed for broader applicability.

Optimization of sensitivity and specificity of a biomarker-based blood test (LVOCheck-Opti): A protocol for a multicenter prospective observational study of patients suspected of having a stroke.

Acute ischemic stroke (AIS) is a time-critical medical emergency. For patients with large-vessel occlusions (LVO), mechanical thrombectomy (MT) is the gold-standard treatment. Mobile Stroke Units (MSUs) provide on-site diagnostic capabilities via computed tomography (CT) and have been shown to improve functional outcomes in stroke patients, but are cost-efficient only in urban areas. Blood biomarkers have recently emerged as possible alternative to cerebral imaging for LVO diagnosis. Prehospital LVO diagnosis offers the potential to transport patients directly to centers that have MT treatment available. In this study, we assess the accuracy of combining two biomarkers, HFABP and NT-proBNP, with clinical indicators to detect LVO using ultra-early prehospital blood samples. The study was registered in the German Clinical Trials Register (DRKS-ID: DRKS00030399). We plan a multicenter prospective observational study with 800 patients with suspected stroke enrolled within 24 h of symptom onset. Study participants will be recruited at three sites (MSUs) in Berlin, Germany. Blood-samples will be taken pre-hospitally at the scene and tested for HFABP and NT-proBNP levels. Additional clinical data and information on final diagnosis will be collected and documented in an electronic case report form (eCRF). Sensitivity and specificity of the combination will be calculated through iterative permutation-response calculations. This study aims to evaluate the diagnostic capabilities of a combination of the biomarkers HFABP and NT-proBNP in LVO prediction. In contrast to most other biomarker studies to date, by employing MSUs as study centers, ultra-early levels of biomarkers can be analyzed. Point-of-care LVO detection in suspected stroke could lead to faster treatment in both urban and rural settings and thus improve functional outcomes on a broader scale. Deutsches Register klinischer Studien https://drks.de/search/de/trial/DRKS00030399, DRKS00030399.

Abstract TMP95: Context Matters: Geographic Decision-Making Could Improve Prehospital Stroke Triage

Introduction: Emergency medical services (EMS) play a key role in stroke outcomes, as triage decisions made under diagnostic uncertainty impact availability of time sensitive treatments. Quantifying both time varying effects and uncertainty allows for optimized algorithms to improve destination decisions for stroke patients. We developed a Bayesian model of neurological outcomes and an algorithm for hospital triage based on clinical trials data. Methods: We used data from Virtual International Stroke Trials Archive (VISTA), RACECAT, and FAST-MAG. To model prehospital diagnosis, we included patients with any stroke-like illness (ischemic/hemorrhagic stroke, and mimics). Primary outcome was 90-day modified Rankin scale (mRS). Due to variability in reported measures from each trial, model-based Bayesian imputation was used. Our model accepts time-from symptoms, location, and capability of all local hospitals as inputs. Results: We included 9048 participants with 8600 (95%) ischemic strokes, 1801 (20%) had large vessel occlusion, and 4064 (45%) had a 90-day mRS of 0-2 (good neurologic outcome). We evaluated the impact of our algorithm using 1,320 stroke events from RACECAT. The estimated median absolute difference in chance of good mRS score between bypass and non local hospital bypass was 2.3% (ranging from 0 to 7.4%) among 1,320 stroke events in the RACECAT data set; covariate-adjusted patient scenarios predicted a preference for local hospital bypass of -2.9% to 7.4%. Destination maps for Catalonia show important patterns of bypass optimality. Conclusion: We found that no uniform destination selection approach is likely to be optimal under all circumstances. This finding is important, because it suggests that a personalized approach considering diagnostic uncertainty, patient characteristics, and geospatial factors could outperform simpler approaches. Predicted time-to-treatment targets may be insufficient for appropriate system optimization.

Abstract 57: Rapid Prehospital Diagnosis of Intracerebral Hemorrhage by Measuring GFAP on a Point-of-Care Platform

Background: The rapid differentiation between intracerebral hemorrhage (ICH) and ischemic stroke (IS) in patients with symptoms of acute stroke is decisive for triage and initiation of targeted therapies. Glial fibrillary acidic protein (GFAP) is a highly promising blood biomarker indicating acute ICH. In this study we investigated the potential of a new GFAP plasma test on a point-of-care (POC) platform for rapidly distinguishing ICH from IS in the prehospital phase. Methods: Patients with symptoms of acute stroke admitted within 6 hours of symptom onset were enrolled. Blood samples were collected already in the prehospital phase in most patients. Plasma GFAP measurements were performed on the i-STAT Alinity® (Abbott) device (duration of analysis 15 min). The primary endpoint was the final diagnosis at hospital discharge categorized as ICH, IS or stroke mimics. Results: 155 patients were enrolled (mean age 75±13, 49% females; final diagnosis 33 ICH, 115 IS, 7 stroke mimics). Prehospital GFAP serum concentrations were strongly elevated in ICH patients compared to IS patients (mean 2283±3821 pg/mL, median 144 [IQR 52.5-2562] vs. mean 45±25 pg/mL, median 29 [IQR 29-53]; p&lt;0.001). In patients with a moderate to severe neurological deficit (NIHSS &gt; 7), GFAP values below 30 pg/mL were associated with a negative predictive value of 100% (i.e. ruling out ICH). The probability of ICH increased in parallel with higher GFAP levels. GFAP concentrations above 120 pg/mL indicated ICH with a positive predictive value of 94%. Conclusion: Rapid prehospital GFAP measurements on a point-of-care platform allow a reliable differentiation between patients with IS and ICH. This opens the potential for optimized triage and for the administration of antidots in severely affected patients with suspected anticoagulation-associated ICH.

Prehospital diagnosis and treatment of acute stroke

ZusammenfassungSchlaganfälle gehören zu den häufigsten Erkrankungen in Deutschland und machen einen großen Anteil der Rettungsdiensteinsätze aus. Aufgrund der hochgradig zeitkritischen Erkrankung sind eine zeiteffektive prähospitale Erkennung des Schlaganfalls, die Therapie akuter ABC-Probleme (ABC „airway, breathing, circulation“/Atemweg, Atmung, Kreislauf) und die schnelle Klinikzuweisung sehr wichtig. Eine kausale Therapie wird prähospital nicht begonnen. Durch die Einführung der endovaskulären Therapie, die nach neuester Studienlage für geeignete Patienten in einem Zeitfenster bis zu 24 h infrage kommt, ist die Klinikzuweisung komplexer geworden. Zur präzisen Zuteilung der Patienten sind eine genaue Voranmeldung, die idealerweise die Abschätzung der Schlaganfallschwere beinhaltet, und eine gute Koordination von Leitstelle, Rettungspersonal und Klinikärzten notwendig. Zukünftige Optimierungsmöglichkeiten der prähospitalen Schlaganfallversorgung bestehen in der Etablierung klarer Zuweisungskonzepte und neurologischer Telenotärzte.

Timeliness and accuracy of the 7-Item Japan Urgent Stroke Triage (JUST-7) score, a prehospital stroke triage tool, assessed by emergency medical services.

The prompt initiation of stroke treatment significantly influences patient outcomes, highlighting the crucial role of prehospital triage. This study aimed to assess the implementation of the 7-Item Japan Urgent Stroke Triage (JUST-7) score by emergency medical services (EMS) in our region and its effect on emergency transportation for suspected stroke patients. Data were collected from patients suspected of having an acute stroke with a Cincinnati Prehospital Stroke Scale (CPSS) score of 1 or more who were transferred by ambulance within 24 h of symptom onset. Two prehospital stroke scales were employed during different periods: period 1 with CPSS alone (January to December 2020) and period 2 with both CPSS and JUST-7 (January 2021 to March 2023). On-scene time data were obtained from the EMS crews, and data regarding the final diagnosis of patients and their outcomes were obtained from the respective hospitals to which the patients were transferred. These data were compared between periods 1 and 2 and between the CPSS and JUST-7. The results revealed that additional evaluation with JUST-7 did not affect ambulance transport time. The CPSS+JUST-7 approach demonstrated higher specificity in identifying stroke and major artery occlusion than with the CPSS alone; however, an appropriate cut-off value needs to be considered. The JUST-7 achieved a diagnostic concordance rate of 35.9% for the most likely stroke type and 64.0% for the first two most likely types. This research emphasizes the potential of JUST-7 as a valuable addition to prehospital stroke diagnosis protocols. Its flexibility in adapting cut-off values based on regional factors and available medical resources optimizes its utility in diverse healthcare settings. The JUST-7 score is a promising tool for improving patient outcomes through prompt and accurate prehospital assessments.

Smartphone AI vs. Medical Experts: A Comparative Study in Prehospital STEMI Diagnosis.

Prehospital telecardiology facilitates early ST-elevation myocardial infarction (STEMI) detection, yet its widespread implementation remains challenging. Extracting digital STEMI biomarkers from printed electrocardiograms (ECGs) using phone cameras could offer an affordable and scalable solution. This study assessed the feasibility of this approach with real-world prehospital ECGs. Patients suspected of having STEMI by emergency medical technicians (EMTs) were identified from a policy research dataset. A deep learning-based ECG analyzer (QCG™ analyzer) extracted a STEMI biomarker (qSTEMI) from prehospital ECGs. The biomarker was compared to a group of human experts, including five emergency medical service directors (board-certified emergency physicians) and three interventional cardiologists based on their consensus score (number of participants answering "yes" for STEMI). Non-inferiority of the biomarker was tested using a 0.100 margin of difference in sensitivity and specificity. Among 53 analyzed patients (24 STEMI, 45.3%), the area under the receiver operating characteristic curve of qSTEMI and consensus score were 0.815 (0.691-0.938) and 0.736 (0.594-0.879), respectively (p=0.081). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of qSTEMI were 0.750 (0.583-0.917), 0.862 (0.690-0.966), 0.826 (0.679-0.955), and 0.813 (0.714-0.929), respectively. For the consensus score, sensitivity, specificity, PPV, and NPV were 0.708 (0.500-0.875), 0.793 (0.655-0.966), 0.750 (0.600-0.941), and 0.760 (0.655-0.880), respectively. The 95% confidence interval of sensitivity and specificity differences between qSTEMI and consensus score were 0.042 (-0.099-0.182) and 0.103 (-0.043-0.250), respectively, confirming qSTEMI's non-inferiority. The digital STEMI biomarker, derived from printed prehospital ECGs, demonstrated non-inferiority to expert consensus, indicating a promising approach for enhancing prehospital telecardiology.

SmartEUS: An Integrated Dynamic Platform For The Innovation Of Healthcare Emergency-Urgency Services

The SmartEUS project aims to design, develop, and test a highly innovative model for the provision of Emergency Urgency Services (EUS) based on the concept of clinical pathway (i.e., the entire emergency care chain). The project is innovative both from an organizational and technological point of view. It is based on an e-Health approach, capable of exploiting new digital technologies in a coordinated way to support the evolution of emergency health systems towards dynamic and safer processes. The paper presents the SmartEUS platform which can integrate the information from all the key players in medical emergency response (emergency operation center, emergency medical service, hospital emergency department) improving their coordination. The most relevant innovations of the proposed solution are data integration and interoperability, advanced communication and collaboration, knowledge-based resource allocation, telemedicine integration to support decision making in dispatching and resource assignment. In fact, a Decision Support System is integrated into SmartEUS cloud platform to suggest to the emergency operation center which emergency medical service and hospital emergency department. In fact, information on the patient status can include results from ambulance’s on board telediagnosis equipment, alerting the hospital emergency department even before the arrive of the patient, thus guaranteeing the appropriateness of care according to patient needs (e.g., patient pre-triage index, potential pre-hospital diagnosis) and reducing emergency department overcrowding and resources saturation.