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Related Concept Videos

Appendicitis-II: Diagnostic Studies and Management01:29

Appendicitis-II: Diagnostic Studies and Management

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Diagnosing and managing appendicitis requires a structured and comprehensive approach that spans from initial assessment to postoperative care. Here is an overview of the process:
Diagnosing Appendicitis
It requires a multifaceted approach, starting with a detailed physical examination to pinpoint the location and nature of the pain and identify any associated symptoms. Laboratory tests play a crucial role. A complete Blood Count (CBC) typically reveals leukocytosis (an increased number of...
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Appendicitis-I: Introduction01:22

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The appendix, a small, narrow, blind tube extending from the inferior part of the cecum, is widely regarded as a vestigial organ, having lost much of its original function through evolution. Despite its diminished role, the appendix can become inflamed, a condition known as appendicitis.
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Related Experiment Video

Updated: Dec 9, 2025

Murine Appendectomy Model of Chronic Colitis Associated Colorectal Cancer by Precise Localization of Caecal Patch
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Differentiation between complicated and uncomplicated appendicitis: diagnostic model development and validation

Hae Young Kim1, Ji Hoon Park2, Sung Soo Lee1

  • 1Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea.

Abdominal Radiology (New York)
|September 11, 2020
PubMed
Summary
This summary is machine-generated.

A new diagnostic model accurately identifies uncomplicated appendicitis using CT scans and neutrophil counts. This tool helps select patients for non-operative management, reducing unnecessary surgeries for appendicitis.

Keywords:
AppendicitisConservative treatmentSensitivity and specificityTomography, X-ray computed

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Area of Science:

  • Radiology
  • Surgical Pathology
  • Medical Diagnostics

Background:

  • Non-operative management is increasingly feasible for uncomplicated appendicitis.
  • Accurate differentiation between complicated and uncomplicated appendicitis is crucial for treatment decisions.
  • Existing diagnostic methods require improvement for precise classification.

Purpose of the Study:

  • To develop and validate a diagnostic model for differentiating complicated from uncomplicated appendicitis.
  • To identify patients suitable for non-operative management with a low risk of treatment failure.

Main Methods:

  • Retrospective study of 1153 patients with appendicitis diagnosed via CT.
  • Development and validation of a multivariable logistic regression model incorporating five CT features and segmented neutrophil percentage.
  • Assessment of model performance using calibration plots, area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Main Results:

  • The model included CT findings (wall enhancement defect, abscess, fat stranding, diameter, extraluminal air) and neutrophil percentage.
  • In the validation dataset, the model achieved an AUC of 0.81 (95% CI 0.77-0.85) with a calibration slope of 1.03.
  • Sensitivity was 93.4%, specificity 28.1%, PPV 40.8%, and NPV 88.9%, with a target of 95% sensitivity.

Conclusions:

  • The developed diagnostic model demonstrates good performance in differentiating appendicitis types.
  • It may help identify patients with uncomplicated appendicitis who can safely undergo non-operative management.
  • The model has the potential to reduce unnecessary surgical interventions.