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Artificial Intelligence Prediction for the Severity of Acute Pancreatitis

NCT04735055 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1334

Last updated 2021-05-05

No results posted yet for this study

Summary

The incidence of acute pancreatitis (AP) is increasing nowadays. The diagnosis of AP is defined according to Atlanta criteria with the presence of two of the following 3 findings; a) characteristic abdominal pain b) amylase and lipase values ≥3 times c) AP diagnosis in ultrasonography (USG), magnetic resonance imaging (MRI), or computerized tomography (CT) imaging. While 80% of the disease has a mild course, 20% is severe and requires intensive care treatment. Mortality varies between 10-25% in severe (severe) AP, while it is 1-3% in mild AP.

Scoring systems with clinical, laboratory, and radiological findings are used to evaluate the severity of the disease. Advanced age (\>70yo), obesity (as body mass index (BMI, as kg/m2), cigarette and alcohol usage, blood urea nitrogen (BUN) ≥20 mg/dl, increased creatinine, C reactive protein level (CRP) \>120mg/dl, decreased or increased Hct levels, ≥8 Balthazar score on abdominal CT implies serious AP. According to the revised Atlanta criteria, three types of severity are present in AP. Mild (no organ failure and no local complications), moderate (local complications such as pseudocyst, abscess, necrosis, vascular thrombosis) and/or transient systemic complications (less than 48h) and severe (long-lasting systemic complications (\>48h); organ insufficiencies such as lung, heart, gastrointestinal and renal). Although Atlanta scoring is considered very popular today, it still seems to be in need of revision due to some deficiencies in the subjects of infected necrosis, non-pancreatic infection and non-pancreatic necrosis, and the dynamic nature of organ failure. Even though the presence of 30 severity scoring systems (the most accepted one is the APACHE 2 score among them), none of them can definitely predict which patient will have very severe disease and which patient will have a mild course has not been discovered yet.

Today, artificial intelligence (machine learning) applications are used in many subjects in medicine (such as diagnosis, surgeries, drug development, personalized treatments, gene editing skills). Studies on machine learning in determining the violence in AP have started to appear in the literature. The purpose of this study is to investigate whether the artificial intelligence (AI) application has a role in determining the disease severity in AP.

Conditions

Sponsors & Collaborators

  • Medipol University

    collaborator OTHER

  • Bezmialem Vakif University

    lead OTHER

Principal Investigators

  • Gökhan Silahtaroğlu, Prof. · Medipol University

Eligibility

Min Age
18 Years
Max Age
100 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-09-03
Primary Completion
2020-09-23
Completion
2020-09-30

Countries

  • Turkey (Türkiye)

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04735055 on ClinicalTrials.gov