Sepsis: New Insights into Diagnosis and Treatment

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Infectious Diseases".

Deadline for manuscript submissions: 30 July 2025 | Viewed by 2292

Special Issue Editors


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Guest Editor
Anesthesia and Intensive Care, Anesthesia and Resuscitation Department, Azienda Ospedaliero Universitaria Pisana, University of Pisa, Pisa, Italy
Interests: sepsis; continuous renal replacement therapy; blood purification; ultrasound; adjuvant therapy; ARDS; nutrition; infection disease
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Guest Editor
Department Anaesthesia and Intensive Care, University of Pisa, 56126 Pisa, Italy
Interests: sepsis; ECMO; ultrasound; haemodynamic management; adjuvant therapy; ARDS

Special Issue Information

Dear Colleagues,

Sepsis represents a life-threatening condition with a huge impact on health care costs. Further, Sepsis is a “time-dependent” disease; the outcome is highly influenced by the prompt detection and efficiency of the management, even from the very “first hour”. Due to the centrality of the complex interactions between the infectious insult and the host's immune response, a deeper understanding of the mechanisms involved in the dysregulation host response is mandatory.

Interestingly, It is now clear that the individual genomic profile is partly responsible for the interindividual variability of the clinical evolution of sepsis. In light of this evidence, immunomorinitoring and immunotherapy have gained increasing recognition in recent decades. Unfortunately, until now, evidence has not supported the extensive introduction of adjuvant therapy in current clinical practice.

In this Special Issue, we invite researchers and clinicians to submit their work, including original clinical research studies, meta-analyses, and systematic reviews, that will provide additional insight on the diagnosis and treatment of septic shock.

Prof. Dr. Francesco Forfori
Dr. Etrusca Brogi
Guest Editors

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Keywords

  • sepsis and sepsis subphenotypes
  • adjuvant therapy
  • blood purification strategies
  • immunomonitoring and immunotherapy
  • the microbiome in sepsis
  • crosstalk in multi-organ failure (MOF)
  • ultrasound in sepsis (POCUS)
  • sepsis-induced coagulophaty and DIC
  • antibiotic therapy
  • multimodal approaches to surgical source control

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Published Papers (1 paper)

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Review

20 pages, 578 KiB  
Review
Artificial Intelligence in Sepsis Management: An Overview for Clinicians
by Elena Giovanna Bignami, Michele Berdini, Matteo Panizzi, Tania Domenichetti, Francesca Bezzi, Simone Allai, Tania Damiano and Valentina Bellini
J. Clin. Med. 2025, 14(1), 286; https://doi.org/10.3390/jcm14010286 - 6 Jan 2025
Viewed by 1800
Abstract
Sepsis is one of the leading causes of mortality in hospital settings, and early diagnosis is a crucial challenge to improve clinical outcomes. Artificial intelligence (AI) is emerging as a valuable resource to address this challenge, with numerous investigations exploring its application to [...] Read more.
Sepsis is one of the leading causes of mortality in hospital settings, and early diagnosis is a crucial challenge to improve clinical outcomes. Artificial intelligence (AI) is emerging as a valuable resource to address this challenge, with numerous investigations exploring its application to predict and diagnose sepsis early, as well as personalizing its treatment. Machine learning (ML) models are able to use clinical data collected from hospital Electronic Health Records or continuous monitoring to predict patients at risk of sepsis hours before the onset of symptoms. Background/Objectives: Over the past few decades, ML and other AI tools have been explored extensively in sepsis, with models developed for the early detection, diagnosis, prognosis, and even real-time management of treatment strategies. Methods: This review was conducted according to the SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research Type) framework to define the study methodology. A critical overview of each paper was conducted by three different reviewers, selecting those that provided original and comprehensive data relevant to the specific topic of the review and contributed significantly to the conceptual or practical framework discussed, without dwelling on technical aspects of the models used. Results: A total of 194 articles were found; 28 were selected. Articles were categorized and analyzed based on their focus—early prediction, diagnosis, mortality or improvement in the treatment of sepsis. The scientific literature presents mixed outcomes; while some studies demonstrate improvements in mortality rates and clinical management, others highlight challenges, such as a high incidence of false positives and the lack of external validation. This review is designed for clinicians and healthcare professionals, and aims to provide an overview of the application of AI in sepsis management, reviewing the main studies and methodologies used to assess its effectiveness, limitations, and future potential. Full article
(This article belongs to the Special Issue Sepsis: New Insights into Diagnosis and Treatment)
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