An approach to model Right Iliac Fossa pain using pain-only-parameters for screening acute appendicitis

Subhagata Chattopadhyay, Fethi Rabhi, U Rajendra Acharya, Rohan Joshi, Rudhram Gajendran

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)


Acute appendicitis (AA) is one of the commonest of multiple possible pathologies at the backdrop of Right Iliac Fossa (RIF) pain. AA is the most common acute surgical condition of the abdomen. Even though AA is a recognized disease entity since decades, its diagnosis still lacks clinical confidence and mandates laboratory tests. Given the issue, this paper proposes a mathematical model using Pain-Only-Parameters (POP) obtained from available literature to screen AA. Weights have been assigned for each POP to create a training data matrix (N = 51) and used to calculate the cumulative effect or weighted sum, which is termed as the Pain Confidence Score (PCS). Based on PCS, a group of real-world patients (N = 40; AA and NA = 20 each) are classified as cases of AA or non-appendicitis (NA) with satisfactory results (sensitivity 85%, specificity 75%, precision 77%, and accuracy 80%). Most rural health centers (RHC) in developing nations lack specialist services and related infrastructure. Hence, such a tool could be useful in RHC to assist general physicians in screening AA and their timely referral to higher centers.

Original languageEnglish
Pages (from-to)1491-502
Number of pages12
JournalJournal of Medical Systems
Issue number3
Publication statusPublished - Jun 2012
Externally publishedYes


  • Abdominal Pain
  • Acute Disease
  • Algorithms
  • Appendicitis
  • Humans
  • Mass Screening
  • Models, Theoretical
  • Predictive Value of Tests


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