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1.
Tidsskr Nor Laegeforen ; 144(3)2024 Feb 27.
Article in English, Norwegian | MEDLINE | ID: mdl-38415568

ABSTRACT

Necrotising soft tissue infections can affect the skin, subcutaneous tissue, superficial fascia, deep fascia and musculature. The infections are severe, they spread quickly and can result in extensive tissue loss. Although rare, morbidity and mortality rates are high. Early clinical identification is crucial for the outcome, and rapid infection control through surgery and targeted antibiotic treatment is needed to save lives. Few prospective clinical trials have been conducted for the treatment of this type of infection. Specific challenges include rapid identification of the condition and the uncertain efficacy of the various treatment options. In this clinical review article, we describe clinical characteristics, diagnostics and treatment.


Subject(s)
Fasciitis, Necrotizing , Soft Tissue Infections , Humans , Soft Tissue Infections/diagnosis , Soft Tissue Infections/drug therapy , Fasciitis, Necrotizing/diagnosis , Fasciitis, Necrotizing/drug therapy , Prospective Studies , Debridement , Anti-Bacterial Agents/therapeutic use
2.
Biomolecules ; 13(2)2023 01 24.
Article in English | MEDLINE | ID: mdl-36830594

ABSTRACT

Sepsis is a dysregulated host response to infection that causes potentially life-threatening organ dysfunction. We investigated the serum metabolomic profile at hospital admission for patients with bacterial sepsis. The study included 60 patients; 35 patients fulfilled the most recent 2016 Sepsis-3 criteria whereas the remaining 25 patients only fulfilled the previous Sepsis-2 criteria and could therefore be classified as having systemic inflammatory response syndrome (SIRS). A total of 1011 identified metabolites were detected in our serum samples. Ninety-seven metabolites differed significantly when comparing Sepsis-3 and Sepsis-2/SIRS patients; 40 of these metabolites constituted a heterogeneous group of amino acid metabolites/peptides. When comparing patients with and without bacteremia, we identified 51 metabolites that differed significantly, including 16 lipid metabolites and 11 amino acid metabolites. Furthermore, 42 metabolites showed a highly significant association with the maximal total Sequential Organ Failure Assessment (SOFA )score during the course of the disease (i.e., Pearson's correlation test, p-value < 0.005, and correlation factor > 0.6); these top-ranked metabolites included 23 amino acid metabolites and a subset of pregnenolone/progestin metabolites. Unsupervised hierarchical clustering analyses based on all 42 top-ranked SOFA correlated metabolites or the subset of 23 top-ranked amino acid metabolites showed that most Sepsis-3 patients differed from Sepsis-2/SIRS patients in their systemic metabolic profile at the time of hospital admission. However, a minority of Sepsis-3 patients showed similarities with the Sepsis-2/SIRS metabolic profile even though several of them showed a high total SOFA score. To conclude, Sepsis-3 patients are heterogeneous with regard to their metabolic profile at the time of hospitalization.


Subject(s)
Intensive Care Units , Sepsis , Humans , Adult , Hospital Mortality , Retrospective Studies , Systemic Inflammatory Response Syndrome/diagnosis
3.
Metabolites ; 13(1)2022 Dec 29.
Article in English | MEDLINE | ID: mdl-36676977

ABSTRACT

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. In the present study, we investigated the systemic/serum lipidomic profile at the time of hospital admission for patients with bacterial sepsis. The study included 60 patients; 35 patients fulfilled the most recent 2016 Sepsis-3 criteria (referred to as Sepsis-3) whereas the remaining 25 patients had sepsis only according to the previous Sepsis-2 definition and could be classified as having Systemic Inflammatory Response Syndrome (SIRS). A total of 966 lipid metabolites were identified. Patients fulfilling the Sepsis-3 criteria differed from the Sepsis-2 patients with regard to only 15 lipid metabolites, and especially sphingolipids metabolism differed between these patient subsets. A total of only 43 metabolites differed between patients with and without bacteremia, including 12 lysophosphatidylcholines and 18 triacylglycerols (15 C18/C20 fatty acid metabolites decreased and three C14 myristate acid metabolites that were increased in bacteremia). Unsupervised hierarchical clustering analyses based on the identified sphingolipids, phosphatidylcholine and triacylglycerols showed that (i) the majority of Sepsis-3 patients differed from SIRS patients especially with regard to lysophosphatidylcholine levels; (ii) the minority of Sepsis-3 patients that clustered together with the majority of SIRS patients showed lower Sequential Organ Failure Assessment (SOFA) scores than the other Sepsis-3 patients; and (iii) the variation between the patients in the identified/altered sphingolipid and triacylglycerol metabolites further increased the heterogeneity of Sepsis-3 patients with regard to their systemic lipidomic profile at the time of diagnosis. To conclude, patients fulfilling the Sepsis-3 criteria differ with regard to their metabolic profile, and this variation depends on disease severity.

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