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Machine learnINg for the rElapse Risk eValuation in Acute Biliary Pancreatitis.

NCT06124989 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 430

Last updated 2023-11-09

No results posted yet for this study

Summary

The MINERVA (Machine learnINg for the rElapse Risk eValuation in Acute biliary pancreatitis) project stems from the need in the clinical practice of taking an operational decision in patients that are admitted to the hospital with a diagnosis of acute biliary pancreatitis. In particular, the MINERVA prospective cohort study aims to develop a predictive score that allows to assess the risk of hospital readmission for patients diagnosed with mild biliary acute pancreatitis using Machine Learning and artificial intelligence.

The objectives of the MINERVA study are to:

1. Propose a novel methodology for the assessment of the risk of relapse in patients with mild biliary acute pancreatitis who did not undergo early cholecystectomy (within 3 to 7 days from hospital admission);
2. Propose a Machine Learning predictive model using a Deep Learning architecture applied to easily collectable data;
3. Validate the MINERVA score on an extensive, multicentric, prospective cohort;
4. Allow national and international clinicians, medical staff, researchers and the general audience to freely and easily access the MINERVA score computation and use it in their daily clinical practice.

The MINERVA score model will be developed on a retrospective cohort of patients (MANCTRA-1, already registered in ClinicalTrials.gov) and will be validated on a novel prospective multicentric cohort. After validation, the MINERVA score will be free and easy to compute instantly for all medical staff; it will be accessible at any time on the MINERVA website and web app, and will provide an immediate and reliable result that can be a clear indication for the best treatment pathway for the clinician and for the patient.

Conditions

  • Acute Pancreatitis
  • Pancreatitis Due to Gallstones
  • Pancreatitis Biliary
  • Pancreatitis Relapsing

Interventions

DIAGNOSTIC_TEST

MINERVA Machine Learning model

The MINERVA score for the prediction of the risk of relapse of acute pancreatitis in patients who did not undergo early cholecystectomy after the first episode of acute biliary pancreatitis will be grounded upon a Machine Learning model that takes into account patients' demographic, clinical, and laboratory variables that can be easily collected and recorded at index patient admission.

Sponsors & Collaborators

  • Università di Napoli Federico II

    collaborator UNKNOWN

  • Università della Campania Luigi Vanvitelli

    collaborator UNKNOWN

  • University of Cagliari

    lead OTHER

Principal Investigators

  • Mauro Podda, MD · University of Cagliari, Department of Surgical Science

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-01-01
Primary Completion
2024-12-31
Completion
2025-12-31

Countries

  • Italy

Study Locations

More Related Trials

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 NCT06124989 on ClinicalTrials.gov