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Angina II: Classification01:27

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Angina, also known as angina pectoris, is a chest pain resulting from diminished blood flow to the heart muscle and is often a symptom of coronary artery disease. Angina presents several variants with distinctive attributes, etiologies, and therapeutic approaches. The main types of angina include stable, unstable, variant (Prinzmetal's), microvascular, intractable, and silent ischemia.Stable angina is caused by atherosclerosis, which leads to the formation of plaques that narrow the coronary...
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Development and validation of the International Classification for Orofacial Pain Algorithm.

Hamid Shakeri1, Charlotte Vueghs1, Rafael Benoliel2

  • 1Department of Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium.

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|August 19, 2025
PubMed
Summary
This summary is machine-generated.

The International Classification of Orofacial Pain Algorithm (ICOP-AL) simplifies diagnosing orofacial pain conditions. This flowchart tool shows reliable agreement with expert diagnoses, improving clinical practice.

Keywords:
AlgorithmDevelopmentInternational Classification of Orofacial PainValidation

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Area of Science:

  • Dentistry
  • Neurology
  • Pain Medicine

Background:

  • Orofacial pain (OFP) presents complex diagnostic challenges.
  • The 2020 International Classification of Orofacial Pain (ICOP) framework is extensive, posing usability issues in clinical settings.
  • Standardizing OFP diagnosis is crucial for effective patient management.

Purpose of the Study:

  • To develop and validate the International Classification of Orofacial Pain Algorithm (ICOP-AL), a flowchart tool to simplify ICOP implementation.
  • To enhance diagnostic precision and clinical applicability of OFP classification.
  • To assess the reliability and standardization potential of the ICOP-AL.

Main Methods:

  • Developed a flowchart-based algorithm (ICOP-AL) integrating ICOP criteria with established diagnostic standards.
  • Validated the ICOP-AL using 100 anonymized patient cases.
  • Evaluated ICOP-AL performance against expert clinician diagnoses and nonexpert evaluators.

Main Results:

  • The ICOP-AL demonstrated substantial agreement with expert diagnoses (Cohen's Kappa κ = 0.688, P < 0.001).
  • The algorithm outperformed nonexpert evaluators in diagnostic accuracy.
  • Results indicate potential for standardizing OFP diagnostic outcomes.

Conclusions:

  • The ICOP-AL offers a structured and accessible approach to OFP diagnosis, facilitating ICOP integration into clinical practice.
  • The tool shows promise for improving diagnostic reliability and efficiency in managing orofacial pain.
  • Further validation is needed for detailed diagnoses and broader clinical adoption.