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Related Concept Videos

Phases of Wound Repair01:28

Phases of Wound Repair

Following injury, the integrity of the injured tissues must be reestablished. For example, in skin tissue, wound repair involves coordination among resident skin cells, blood mononuclear cells, extracellular matrix, growth factors, and cytokines to complete the healing cascade.
Formation of Blood Clot
In case of deep injuries, trauma to blood vessels results in blood loss. In the meantime, phospholipids released from the ruptured endothelial cellular membrane are converted into arachidonic...
Peripheral Artery Disease III: Interprofessional Care01:27

Peripheral Artery Disease III: Interprofessional Care

Peripheral Artery Disease (PAD) is characterized by narrowed arteries that diminish blood flow to the extremities. Effective management of PAD requires an interprofessional approach involving various healthcare professionals. The critical aspects of interprofessional care for PAD patients focus on risk factor modification, drug therapy, exercise therapy, nutrition therapy, critical limb ischemia care, and interventional radiology and surgical procedures.The primary treatment goal for PAD...
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Peripheral Artery Disease IV: Nursing Management

The nursing management of a patient with peripheral artery disease (PAD) begins with a thorough assessment of the patient’s health history and clinical manifestations.AssessmentHealth History: Evaluate the patient’s history of hypertension, hyperlipidemia, family history of cardiovascular issues, and lifestyle factors such as dietary patterns, smoking, and physical activity.Physical Examination:Assess the affected extremity for decreased or absent peripheral pulses, temperature changes,...

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Related Experiment Video

Updated: Jun 11, 2026

Assessment of Acute Wound Healing using the Dorsal Subcutaneous Polyvinyl Alcohol Sponge Implantation and Excisional Tail Skin Wound Models.
09:06

Assessment of Acute Wound Healing using the Dorsal Subcutaneous Polyvinyl Alcohol Sponge Implantation and Excisional Tail Skin Wound Models.

Published on: March 25, 2020

Validation of a Clinical Decision-Support Algorithm for Chronic Wound Classification and Treatment: An Expert

Raquel Marques1,2, Carla Pais-Vieira1,2, Marcos Lopes3

  • 1Faculdade de Ciências da Saúde e Enfermagem, Centre for Interdisciplinary Research in Health, Universidade Católica Portuguesa, Porto, Portugal.

International Wound Journal
|June 9, 2026
PubMed
Summary

A new algorithm for chronic wound classification showed substantial agreement (κ=0.70) with expert consensus, achieving 86.2% accuracy. This decision-support tool demonstrates promise for improving diagnostic standardization in wound care.

Keywords:
clinical decision support systemconsensusdiagnosisobserver variationwounds and injuries

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Related Experiment Videos

Last Updated: Jun 11, 2026

Assessment of Acute Wound Healing using the Dorsal Subcutaneous Polyvinyl Alcohol Sponge Implantation and Excisional Tail Skin Wound Models.
09:06

Assessment of Acute Wound Healing using the Dorsal Subcutaneous Polyvinyl Alcohol Sponge Implantation and Excisional Tail Skin Wound Models.

Published on: March 25, 2020

Human Ex vivo Wound Model and Whole-Mount Staining Approach to Accurately Evaluate Skin Repair
07:32

Human Ex vivo Wound Model and Whole-Mount Staining Approach to Accurately Evaluate Skin Repair

Published on: February 17, 2021

Area of Science:

  • Medical Informatics
  • Wound Care Management
  • Clinical Decision Support Systems

Background:

  • Accurate chronic wound classification is crucial for effective patient management.
  • Current diagnostic practices exhibit variability, highlighting the need for standardized tools.
  • Rule-based decision-support systems offer potential for improving diagnostic consistency.

Purpose of the Study:

  • To evaluate the agreement between a rule-based algorithm and expert consensus for chronic wound classification.
  • To assess the diagnostic accuracy of the algorithm compared to expert judgment.
  • To explore expert agreement with algorithm-generated therapeutic recommendations.

Main Methods:

  • A rule-based algorithm classified 30 standardized chronic wound cases.
  • Thirty wound-care experts formed panels to classify case subsets, establishing a consensus reference standard (≥3/5 agreement).
  • Algorithm-consensus agreement was measured using Cohen's κ; expert reliability was assessed using Krippendorff's α and Fleiss' κ.

Main Results:

  • Expert agreement was low to moderate (Krippendorff's α=0.26-0.60), varying by wound type.
  • The algorithm achieved substantial agreement with expert consensus (κ=0.70) and 86.2% accuracy.
  • Experts endorsed 85.2% of the algorithm's therapeutic recommendations, with higher agreement for specific wound types.

Conclusions:

  • The rule-based algorithm demonstrates promising performance in classifying chronic wounds under controlled conditions.
  • The findings support further prospective validation of this decision-support tool in real-world settings.
  • The algorithm has the potential to enhance standardization and accuracy in chronic wound diagnosis and management.