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Acute Pyelonephritis II: Diagnostic Studies and Management01:28

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Introduction:For diagnosing acute pyelonephritis, a comprehensive patient history is collected to identify symptoms such as dysuria, frequent or urgent urination, flank pain, or costovertebral angle (CVA) tenderness that may suggest a kidney infection.Physical ExaminationDuring the physical examination, CVA tenderness is assessed. This involves gentle percussion over the costovertebral angle, where tenderness often indicates a kidney infection.Diagnostic TestsUrinalysis: Used to identify white...

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Related Experiment Video

Updated: Jun 5, 2026

Intraductal Injection of LPS as a Mouse Model of Mastitis: Signaling Visualized via an NF-κB Reporter Transgenic
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Pittsburgh Classification and Treatment Algorithm for Idiopathic Granulomatous Mastitis: A Multicenter Cohort Study.

Atilla Soran1,2, Merve Tokoçin2,3, Hüseyin Özgür Aytaç2,4

  • 1Breast Surgery Unit, Department of Surgery, Magee-Womens Hospital Pittsburgh, Pennsylvania, USA.

European Journal of Breast Health
|March 24, 2026
PubMed
Summary
This summary is machine-generated.

A new Pittsburgh classification and treatment algorithm for idiopathic granulomatous mastitis (IGM) significantly improved treatment outcomes. Adhering to this algorithm led to higher complete response rates in IGM patients.

Keywords:
Idiopathicalgorithmclassificationgranulomatousmastitis

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Area of Science:

  • Breast pathology
  • Inflammatory breast disease
  • Medical imaging

Background:

  • Idiopathic granulomatous mastitis (IGM) is a rare inflammatory breast condition with no standardized treatment and unpredictable outcomes.
  • Clinical and ultrasound findings are crucial for diagnosing and staging IGM.
  • Existing treatment strategies for IGM lack standardization, leading to variable patient responses.

Purpose of the Study:

  • To develop and evaluate the effectiveness of the Pittsburgh Classification and a corresponding treatment algorithm for idiopathic granulomatous mastitis (IGM).
  • To stratify IGM severity using clinical and ultrasound findings.
  • To improve treatment outcomes for patients with IGM.

Main Methods:

  • Retrospective multicenter study of biopsy-proven IGM patients (2020-2025).
  • Development of the Pittsburgh clinical (Type 1-5) and ultrasound (Type A-D) classifications for IGM severity.
  • Assessment of treatment responses (CR, nCR, NR) based on the Pittsburgh treatment algorithm.

Main Results:

  • Algorithm-concordant treatment was administered to 86.4% of patients, achieving high complete response (CR) rates (68.7%).
  • Patients receiving algorithm-discordant treatment had significantly lower CR rates (21.1%) compared to those with CR (65.4%) (p<0.001).
  • Multifocal disease and specific clinical types (e.g., Type 4) correlated with poorer outcomes (NR/nCR), while Type 1 IGM showed better response rates.

Conclusions:

  • Concordance with the Pittsburgh IGM treatment algorithm significantly enhances complete response rates.
  • IGM severity, multifocal disease, and clinical type are important prognostic factors.
  • Further prospective global research is recommended to validate these findings.