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Related Experiment Video

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Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
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Novel scoring system and algorithm for classifying chronic rhinosinusitis: the JESREC Study.

T Tokunaga1, M Sakashita1, T Haruna2

  • 1Department of Otorhinolaryngology Head & Neck Surgery, University of Fukui, Fukui, Japan.

Allergy
|May 7, 2015
PubMed
Summary
This summary is machine-generated.

A new scoring system helps diagnose refractory eosinophilic chronic rhinosinusitis (ECRS) before surgery. This system identifies patients at higher risk for recurrence, aiding clinical decisions for chronic rhinosinusitis management.

Keywords:
chronic rhinosinusitis severityclinical diagnostic criterionendoscopic sinus surgeryeosinophilic infiltrationrefractory chronic rhinosinusitis

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Area of Science:

  • Otolaryngology
  • Immunology
  • Respiratory Medicine

Background:

  • Chronic rhinosinusitis (CRS) presents as CRSwNP and CRSsNP, with CRSwNP showing higher eosinophilic infiltration and Th2 cytokines.
  • Mucosal eosinophilia in CRS correlates with severe symptoms and frequent recurrences, necessitating further investigation into clinical variability.
  • Objective criteria are needed for diagnosing refractory CRS, particularly eosinophilic CRS (ECRS).

Purpose of the Study:

  • To establish objective clinical criteria for diagnosing refractory CRS.
  • To develop a diagnostic algorithm for ECRS based on clinical and computed tomography (CT) findings.
  • To correlate the proposed classification with patient prognosis and recurrence risk.

Main Methods:

  • A retrospective study of 1716 patients with CRS undergoing endoscopic sinus surgery (ESS) across 15 institutions.
  • Utilized Cox proportional hazard models to estimate recurrence risk and logistic regression with ROC curves to develop diagnostic criteria for ECRS.
  • The Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis (JESREC) scoring system was developed using data on disease laterality, polyps, blood eosinophilia, and CT findings.

Main Results:

  • The JESREC scoring system for ECRS diagnosis incorporates unilateral/bilateral disease, nasal polyps, blood eosinophilia (>5%), and ethmoid sinus CT findings.
  • A cutoff score of 11 yielded 83% sensitivity and 66% specificity for ECRS diagnosis.
  • Factors significantly associated with recurrence included blood eosinophilia, ethmoid sinus disease on CT, asthma, and intolerance to aspirin/NSAIDs.

Conclusions:

  • A novel algorithm effectively subdivides CRSwNP into non-ECRS, mild, moderate, and severe ECRS categories.
  • This classification demonstrates a significant correlation with patient prognosis.
  • The algorithm offers valuable pre-operative insights into CRS refractoriness, potentially guiding treatment decisions before ESS or biopsy.