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Healthcare
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New Tools and Technologies in Emergency Medicine and Critical Care
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New Tools and Technologies in Emergency Medicine and Critical Care

A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Clinical Care".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 978

Special Issue Editor

Dr. Daniele Orso

E-Mail Website
Guest Editor
Department of Emergency, “Santa Maria della Misericordia” University Hospital of Udine, Azienda Sanitaria Universitaria Friuli Centrale, 33100 Udine, Italy
Interests: sepsis; ultrasound; emergency medicine; intensive care medicine; hemodynamics; systematic reviews

Special Issue Information

Dear Colleagues,

Emergency medicine and emergency critical care represent a dynamic synergy in modern healthcare, where rapid diagnosis and decisive intervention meet to manage critically ill patients. In the fast-paced environment of the emergency department, clinicians employ state-of-the-art techniques to stabilize patients, seamlessly integrating advanced critical care methods when necessary. This interconnected approach not only ensures timely interventions during the initial resuscitation phase but also paves the way for a smooth transition into ongoing intensive care. The evolution of these fields has led to the development of specialized protocols and multidisciplinary strategies that significantly improve patient outcomes in high-stake, time-sensitive situations.

Recent breakthroughs in technology are revolutionizing emergency medicine and critical care, enabling faster, more accurate diagnoses and tailored interventions. Point-of-care ultrasound and portable imaging devices now offer immediate insights at a patient's bedside, while telemedicine solutions expand expert consultation to remote and resource-limited settings. Additionally, artificial intelligence and machine learning algorithms are being integrated to predict patient deterioration and guide critical decision-making, optimizing treatment protocols in real time. Wearable sensors and advanced monitoring systems provide ongoing, real-time data that help clinical teams respond proactively. Collectively, these innovations not only streamline workflow and improve patient outcomes but also pave the way for a more adaptable, technology-driven model in emergency and critical care settings.

As the Editor of this Special Issue, I am excited to invite new scientific contributions on the evolving frontiers of emergency medicine and critical care. We are particularly interested in manuscripts that explore innovative technologies and novel tools in these fields. Whether your research focuses on breakthrough point-of-care devices, wearable monitoring systems, or the integration of artificial intelligence for real-time clinical decision-making, we welcome studies that challenge traditional models and offer fresh, evidence-based insights into patient management in critical and time-sensitive settings. We look forward to receiving your contributions and to fostering a dynamic exchange of ideas that will help shape the future of emergency and critical care practices.

Dr. Daniele Orso
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • emergency medicine
  • emergency critical care
  • new medical technologies
  • telemedicine
  • artificial intelligence

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Published Papers (2 papers)

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Research

12 pages, 1380 KB  
Article
Unsupervised Clustering of 41,728 Emergency Department Visits: Insights into Patient Profiles and KTAS Reliability
by Jongsun Kim, EunChul Jang, SoonChan Kwon and MyoungJe Song
Healthcare 2025, 13(23), 3073; https://doi.org/10.3390/healthcare13233073 - 26 Nov 2025
Viewed by 249
Abstract
Introduction: In the emergency room, it is essential to quickly and accurately classify the patients’ various severities. However, existing five-stage classification systems, such as the Korean Emergency Patient Classification Tool (KTAS), do not sufficiently reflect the physiological and clinical heterogeneity of all patients, [...] Read more.
Introduction: In the emergency room, it is essential to quickly and accurately classify the patients’ various severities. However, existing five-stage classification systems, such as the Korean Emergency Patient Classification Tool (KTAS), do not sufficiently reflect the physiological and clinical heterogeneity of all patients, so there is a possibility of under-classification in some age groups or specific symptom groups. Methods: A retrospective cross-sectional study was conducted using KTAS and the physiological and clinical data of 41,728 patients who visited the emergency room of a university hospital in Incheon in 2022. K-prototypes unsupervised cluster analysis incorporating demographic, physiological, and clinical variables was applied, and the number of clusters was determined as the optimal value through the Silhouette, Dunn, and Davies–Bouldin indicators. Dimension reduction was performed by UMAP, and differences between clusters were compared by t-test, Mann–Whitney U, and chi-square test. Results: Two different clusters were identified. Cluster 0 was a stable patient group with a mean age of 58 years and an average arterial pressure of 104 mmHg. On the other hand, Cluster 1 was a young but physiologically unstable patient group with an average age of 46 years and an average arterial pressure of 90 mmHg. There were significant differences in age, MAP, heart rate, respiratory rate, body temperature, and pain scores between clusters (p < 0.001), and a moderate association was observed between KTAS classification and clusters (Cramer’s V = 0.208). Discussion: This study suggested the possibility of early identification of high-risk groups in the emergency room and efficient resource allocation by identifying potential patient heterogeneity that KTAS cannot detect through unsupervised learning. This approach can be used as a basis for precision triage and patient-centered emergency medical policy establishment by supplementing rather than replacing the existing classification system. Full article
(This article belongs to the Special Issue New Tools and Technologies in Emergency Medicine and Critical Care)
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17 pages, 1178 KB  
Article
Hemodynamic Heterogeneity in Community-Acquired Sepsis at Intermediate Care Admission: A Prospective Pilot Study Using Impedance Cardiography
by Gianni Turcato, Arian Zaboli, Lucia Filippi, Fabrizio Lucente, Michael Maggi, Alessandro Cipriano, Massimo Marchetti, Daniela Milazzo, Christian J. Wiedermann and Lorenzo Ghiadoni
Healthcare 2025, 13(21), 2686; https://doi.org/10.3390/healthcare13212686 - 23 Oct 2025
Viewed by 426
Abstract
Background: Sepsis is a heterogeneous syndrome in which patients with similar clinical presentations at admission may exhibit markedly different treatment responses and outcomes, suggesting that comparable macroscopic features can conceal profoundly distinct perfusion and hemodynamic states. Aim: This study aimed to [...] Read more.
Background: Sepsis is a heterogeneous syndrome in which patients with similar clinical presentations at admission may exhibit markedly different treatment responses and outcomes, suggesting that comparable macroscopic features can conceal profoundly distinct perfusion and hemodynamic states. Aim: This study aimed to characterize the hemodynamic profile of patients with community-acquired sepsis, assess its correlation with macro-hemodynamic indices, compare fluid responders with non-responders, and explore the prognostic value of early identification of a feature consistent with distributive shock. Methods: A prospective observational pilot study was conducted in the Intermediate Medical Care Unit (IMCU) of Ospedale Alto Vicentino (Santorso, Italy), September 2024–May 2025. 115 consecutive adults with community-acquired sepsis underwent NICaS® bioimpedance assessment at IMCU admission. Sepsis was diagnosed at IMCU admission as suspected/confirmed infection plus an acute increase in total Sequential Organ Failure Assessment (SOFA) ≥ 2 points. Hemodynamic indices were analyzed in relation to the Sequential Organ Failure Assessment (SOFA) score and mean arterial pressure (MAP), fluid responsiveness, and 30-day mortality. Results: Hemodynamics were heterogeneous across patients and within SOFA strata. SOFA showed no correlation with SV, SI, CO, or CI; weak inverse associations for TPR (r = −0.198, p = 0.034) and TPRI (r = −0.241, p = 0.009) were observed. MAP did not correlate with SV, SI, CO, or CI, but correlated positively with TPR (r = 0.461) and TPRI (r = 0.547) and with CPI (ρ = 0.550), all p < 0.001. A distributive profile was present in 21.7% (25/115), increasing with higher SOFA (p = 0.033); only 20% of those with this profile had MAP < 65 mmHg at admission. Fluid non-responders (27.8%) had lower resistance and higher CI (4.1 vs. 3.4 L/min/m2; p = 0.015). The distributive profile was not associated with 30-day mortality (log-rank p = 0.808). Conclusions: In IMCU patients with community-acquired sepsis, macro-indices (SOFA, MAP) correlate poorly with the underlying hemodynamic state. Early noninvasive profiling reveals within-SOFA circulatory heterogeneity and may support operational, individualized resuscitation strategies; these pilot findings are hypothesis-generating and warrant prospective interventional testing. Full article
(This article belongs to the Special Issue New Tools and Technologies in Emergency Medicine and Critical Care)
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