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Esophageal Perforation-I: Introduction

Esophageal Perforation-I: Introduction

Esophageal perforation is a severe medical condition characterized by a breach in the integrity of the esophageal wall. This breach can occur due to various factors such as trauma, medical procedures, or underlying diseases. When the esophageal wall is compromised, it allows food, fluids, and digestive juices into the chest cavity or adjacent structures, leading to potential complications and health risks.
The location of esophageal perforation can vary, occurring anywhere along the esophagus....

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Esophageal perforations manifest in various clinical forms, influenced by factors such as the perforation's cause and location (cervical, intrathoracic, or intra-abdominal), the extent of contamination, and potential injury to adjacent mediastinal structures. The timing between the perforation occurrence and treatment initiation also affects the clinical presentation.
Clinical Manifestations:

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Detection Algorithms for Gastrointestinal Perforation Cases in the Medical Information Database Network (MID-NET^®) in

Masatoshi Tanigawa¹, Mei Kohama², Kaori Hirata²

¹Clinical Research Support Center, Kagawa University Hospital, 1750-1 Ikenobe, Miki-Cho, Kita-Gun, Kagawa, 761-0793, Japan. tanigawa.masatoshi.k6@kagawa-u.ac.jp.

Therapeutic Innovation & Regulatory Science

|April 21, 2024

Summary

This study developed algorithms to identify gastrointestinal perforations (GIP) in Japan's Medical Information Database Network (MID-NET®). The best algorithm balanced accuracy and sensitivity for improved pharmacovigilance.

Keywords:

Gastrointestinal perforation ICD-10 Identification algorithm Medical information database Pharmacovigilance Positive predictive value

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Area of Science:

Pharmacovigilance
Health Informatics
Medical Data Analysis

Background:

The Medical Information Database Network (MID-NET®) is a crucial pharmacovigilance resource in Japan.
No established algorithm currently exists for identifying gastrointestinal perforation (GIP) within MID-NET®.

Purpose of the Study:

To develop and evaluate algorithms for identifying GIP in MID-NET®.
To assess the trade-offs between positive predictive value (PPV) and relative sensitivity (rSn) of different identification algorithms.

Main Methods:

Evaluated 12 algorithms combining ICD-10 codes with GIP therapeutic procedures.
Utilized inpatient data from three institutions, including ICD-10 codes, CT scan information, antimicrobial prescriptions, and operation codes.
Determined PPVs and evaluated rSn at a specific institution.

Main Results:

Observed a trade-off between PPV and rSn across algorithms.
Algorithms combining ICD-10 codes with diagnostic and procedure codes improved PPVs.
An algorithm combining ICD-10 codes, CT scan, antimicrobial information, and 80 operation codes achieved an optimal balance (PPV: 61.6%, rSn: 92.4%).
Significant PPV differences were noted among institutions.

Conclusions:

Developed effective GIP identification algorithms for MID-NET®.
Highlighted the inherent trade-offs between algorithm accuracy and sensitivity.
The study provides a balanced algorithm to enhance pharmacovigilance and future adverse event detection research.