Promising Biomarkers for Chronic Wound Healing: A Pilot Cohort Study on Wound Cytokines and a Novel Biofilm Detection Kit for Predicting 90‐Day Outcomes.
Early identification of chronic wounds is essential for clinical decision‐making in wound care. Biofilm infection is a well‐known risk factor for delayed healing, while cytokines in the wound microenvironment play critical regulatory roles throughout the healing cascade. This single‐centre prospecti...
| Publicado en: | Wound Repair & Regeneration Vol. 33; no. 5; pp. 1 - 16 |
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| Autores principales: | , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Sep/Oct2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188875057&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188875057 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10671927 DPV jtl: Wound Repair & Regeneration issn: 10671927 maglogo: Y pubinfo: dt: Sep/Oct2025 vid: 33 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 188875057 188875057 188875057 10.1111/wrr.70100 188875057 ppf: 1 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Promising Biomarkers for Chronic Wound Healing: A Pilot Cohort Study on Wound Cytokines and a Novel Biofilm Detection Kit for Predicting 90‐Day Outcomes. aug: au: Wu, Yu‐Feng Sheu, Shu‐Yun Cheng, Nai‐Chen Cheng, Chao‐Min affil: Division of Plastic Surgery, Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan sug: subj: Wounds, Chronic Therapy Wound Healing Cytokines Analysis Biological Markers Analysis Point-of-Care Testing Wound Care Biofilms Prediction Models Wounds, Chronic Prognosis Treatment Outcomes Human Taiwan Funding Source Pilot Studies Prospective Studies Predictive Value of Tests Descriptive Statistics Sensitivity and Specificity C-Reactive Protein Blood Inflammation Mediators Blood Chemokines Blood ROC Curve Diabetes Mellitus Peripheral Vascular Diseases Biological Markers Blood Cytokines Blood Colorimetry Tertiary Health Care Taiwan Enzyme-Linked Immunosorbent Assay Immunoassay Staining and Labeling Wounds, Chronic Microbiology Unpaired T-Tests Pearson's Correlation Coefficient Chi Square Test Fisher's Exact Test Mann-Whitney U Test Kruskal-Wallis Test Post Hoc Analysis McNemar's Test Logistic Regression Data Analysis Software Adult Middle Age Aged Aged, 80 and Over Male Female Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: Early identification of chronic wounds is essential for clinical decision‐making in wound care. Biofilm infection is a well‐known risk factor for delayed healing, while cytokines in the wound microenvironment play critical regulatory roles throughout the healing cascade. This single‐centre prospective cohort study enrolled 66 patients with chronic wounds between 2020 and 2023 to evaluate cytokine biomarkers and biofilm detection tools for predicting wound outcomes. Clinical signs of biofilm (CSB) alone demonstrated limited predictive value, with accuracies of 66.7% for 30‐day and 45.5% for 90‐day healing. In contrast, the Wound Biofilm Detection Kit (WBDK) showed superior performance, achieving predictive accuracies of 92.4% and 60.6% for 30‐ and 90‐day outcomes, respectively, outperforming both CSB and MolecuLight i:X. Cytokine analysis identified serum CRP, wound CRP and wound MCP‐1 as significant predictors, with ROC analysis demonstrating good discriminative ability for wound CRP (AUC = 0.863) and wound MCP‐1 (AUC = 0.830). A simplified Lasso regression model incorporating diabetes mellitus, peripheral arterial disease, wound location and WBDK grade achieved an AUC of 0.77 and an accuracy of 76% for 90‐day outcomes. External validation was performed in 17 additional patients yielding a predictive accuracy of 76.5%, supporting the robustness of the model. These findings highlight the limited reliability of clinical signs alone and emphasise the value of objective biofilm detection and cytokine profiling in wound prognosis. Our high‐accuracy prediction model, based on readily accessible clinical variables and WBDK results, may facilitate precision wound care and improve real‐time management. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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