Trial reportThe Journal of clinical investigation2021
Discriminatory plasma biomarkers predict specific clinical phenotypes of necrotizing soft-tissue infections.
Trial report in The Journal of clinical investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01790698 (Improving Outcome of Necrotizing Fasciitis), which is not on this map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Improving Outcome of Necrotizing Fasciitis: Elucidation of Complex Host and Pathogen Signatures That Dictate Severity of Tissue Infection
Who cites it
13 citing papers in PubMed, 19 citations in OpenAlex.
- Article
- DAMPs, PAMPs, and Alarmins: From Mechanism to Therapy.MedComm · 2026Review
- Identification of immunostimulatory antigens in Group AProceedings of the National Academy of Sciences of the United States of America · 2026Article
- A validated model for early prediction of group A streptococcal aetiology in necrotising soft tissue infections using minimal patient data.BMC medicine · 2026Article
- Diagnostic strategies in necrotizing soft tissue infections: from clinical scores to multi-omics and machine learning.Burns & trauma · 2026Review
- Host-response trajectories in necrotizing fasciitis: host-pathogen interactions, immune evasion, and immunoparalysis.Frontiers in cellular and infection microbiology · 2026Review
- Early identification and diagnosis of fournier gangrene: a machine learning approach integrating serological characterization.BMC infectious diseases · 2025Article
- Complicated and deep bacterial skin and soft tissue infections.Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG · 2025Review
- The intricate pathogenicity of Group AVirulence · 2024Review
- Reduced interleukin-18 secretion by human monocytic cells in response to infections with hyper-virulent Streptococcus pyogenes.Journal of biomedical science · 2024Article
- Neutrophil-derived reactive agents induce a transient SpeB negative phenotype in Streptococcus pyogenes.Journal of biomedical science · 2023Article
- Clinical Characteristics and Histopathology in Suspected Necrotizing Soft Tissue Infections.Open forum infectious diseases · 2022Article
- Analysis of host-pathogen gene association networks reveals patient-specific response to streptococcal and polymicrobial necrotising soft tissue infections.BMC medicine · 2022Article
Corrections and comments
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Authors and funding
17 authors at 7 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUNDNecrotizing soft-tissue infections (NSTIs) are rapidly progressing infections frequently complicated by septic shock and associated with high mortality. Early diagnosis is critical for patient outcome, but challenging due to vague initial symptoms. Here, we identified predictive biomarkers for NSTI clinical phenotypes and outcomes using a prospective multicenter NSTI patient cohort.METHODSLuminex multiplex assays were used to assess 36 soluble factors in plasma from NSTI patients with positive microbiological cultures (n = 251 and n = 60 in the discovery and validation cohorts, respectively). Control groups for comparative analyses included surgical controls (n = 20), non-NSTI controls (i.e., suspected NSTI with no necrosis detected upon exploratory surgery, n = 20), and sepsis patients (n = 24).RESULTSThrombomodulin was identified as a unique biomarker for detection of NSTI (AUC, 0.95). A distinct profile discriminating mono- (type II) versus polymicrobial (type I) NSTI types was identified based on differential expression of IL-2, IL-10, IL-22, CXCL10, Fas-ligand, and MMP9 (AUC >0.7). While each NSTI type displayed a distinct array of biomarkers predicting septic shock, granulocyte CSF (G-CSF), S100A8, and IL-6 were shared by both types (AUC >0.78). Finally, differential connectivity analysis revealed distinctive networks associated with specific clinical phenotypes.CONCLUSIONSThis study identifies predictive biomarkers for NSTI clinical phenotypes of potential value for diagnostic, prognostic, and therapeutic approaches in NSTIs.TRIAL REGISTRATIONClinicalTrials.gov NCT01790698.FUNDINGCenter for Innovative Medicine (CIMED); Region Stockholm; Swedish Research Council; European Union; Vinnova; Innovation Fund Denmark; Research Council of Norway; Netherlands Organisation for Health Research and Development; DLR Federal Ministry of Education and Research; and Swedish Children's Cancer Foundation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.