To Örebro University

oru.seÖrebro University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Profiling the dysregulated immune response in sepsis: overcoming challenges to achieve the goal of precision medicine
Örebro University, School of Medical Sciences. Department of Infectious Diseases, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.ORCID iD: 0000-0003-3921-4244
Department of Intensive Care Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, Netherlands.
Department of Applied Biomedical Science, Faculty of Health Sciences, Mater Dei hospital, University of Malta, Msida, Malta; Centre for Molecular Medicine and Biobanking, University of Malta, Msida, Malta.
Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany.
Show others and affiliations
2024 (English)In: The Lancet Respiratory Medicine, ISSN 2213-2600, E-ISSN 2213-2619, Vol. 12, no 4, p. 305-322Article, review/survey (Refereed) Published
Abstract [en]

Sepsis is characterised by a dysregulated host immune response to infection. Despite recognition of its significance, immune status monitoring is not implemented in clinical practice due in part to the current absence of direct therapeutic implications. Technological advances in immunological profiling could enhance our understanding of immune dysregulation and facilitate integration into clinical practice. In this Review, we provide an overview of the current state of immune profiling in sepsis, including its use, current challenges, and opportunities for progress. We highlight the important role of immunological biomarkers in facilitating predictive enrichment in current and future treatment scenarios. We propose that multiple immune and non-immune-related parameters, including clinical and microbiological data, be integrated into diagnostic and predictive combitypes, with the aid of machine learning and artificial intelligence techniques. These combitypes could form the basis of workable algorithms to guide clinical decisions that make precision medicine in sepsis a reality and improve patient outcomes.

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 12, no 4, p. 305-322
National Category
Immunology
Research subject
Infectious Diseases; Anaesthesiology
Identifiers
URN: urn:nbn:se:oru:diva-110591DOI: 10.1016/S2213-2600(23)00330-2ISI: 001218413100001PubMedID: 38142698Scopus ID: 2-s2.0-85180280729OAI: oai:DiVA.org:oru-110591DiVA, id: diva2:1824787
Available from: 2024-01-08 Created: 2024-01-08 Last updated: 2024-05-29Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Cajander, Sara

Search in DiVA

By author/editor
Cajander, Sara
By organisation
School of Medical Sciences
In the same journal
The Lancet Respiratory Medicine
Immunology

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 63 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf