An Approach to Model Right Iliac Fossa Pain Using Pain-Only-Parameters for Screening Acute Appendicitis

  • Authors:

  • Subhagata Chattopadhyay;Fethi Rabhi;U. Rajendra Acharya;Rohan Joshi;Rudhram Gajendran

  • Affiliations:

  • School of Computer Studies, National Institute of Science and Technology, Berhampur, India 761008;School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia 2052;Department of Electronic and Communication Engineering, Ngee Ann Polytechnic, Clementi, Singapore 599489;Department of Biomedical Engineering, Manipal Institute of Technology, Manipal University, Manipal, India 576104;Department of Biomedical Engineering, Manipal Institute of Technology, Manipal University, Manipal, India 576104

  • Venue:
  • Journal of Medical Systems
  • Year:
  • 2012

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Abstract

Acute appendicitis (AA) is one of the commonest of multiple possible pathologies at the backdrop of Right Iliac Fossa (RIF) pain. RIFis 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驴=驴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驴=驴40; AA and NA驴=驴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.