Construction of a Predictive Model of Gangrenous Cholecystitis Based on Machine Learning

NCT06399081 | Completed

• 1 other identifier: KY2024-006-02
• Study Type: observational
• Target: 1,006
• Locations: 1 country
• Sites: 1

Brief Summary

Gangrenous cholecystitis is the most common complication of acute cholecystitis. There is no research using machine learning models to construct predictive diagnostic models for gangrenous cholecystitis.

Conditions

Gangrenous Cholecystitis

Outcome Measures

Primary Outcomes (2)

• pathological diagnosis of patients with cholecystectomy

  Check the patient's pathological report and whether the pathological description contains phenomena such as full layer ischemic necrosis and ulceration of the gallbladder wall. Diagnose as gangrenous cholecystitis or non-gangrenous cholecystitis.

  30 days

• The predictive performance of diagnostic prediction models

  The predictive diagnosis was obtained by the model and each predictive variable, and the metric (Accuracy, Recall, Precision, F1score) of the model was obtained by comparing with the actual pathological diagnosis.

  through study completion, an average of 4 months

Secondary Outcomes (6)

• WBC value (10*9/L)

  through study completion, an average of 4 months

• Alanine transaminase value (ALT, U/L)

  through study completion, an average of 4 months

• D-dimer value

  through study completion, an average of 4 months

• Fibrinogen value (g/L)

  through study completion, an average of 4 months

• BMI (Kg/m2)

  through study completion, an average of 4 months

Study Arms (2)

Gangrenous cholecystitis

Defined based on intraoperative findings or pathological diagnosis

Other: Observational

Non-gangrenous cholecystitis

Non-gangrenous cholecystitis, such as chronic cholecystitis, acute cholecystitis, acute attack of chronic cholecystitis

Other: Observational

Interventions

Observational OTHER

Observational

Gangrenous cholecystitis; Non-gangrenous cholecystitis

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The patients admitted to the Second Hospital of Dalian Medical University who were diagnosed with cholecystitis through ICD-9 code recognition and underwent cholecystectomy from January 2015 to May 2023

You may qualify if:

• patients diagnosed with acute cholecystitis or acute exacerbation of chronic cholecystitis in our hospital and receiving complete clinical treatment in our hospital;
• performing cholecystectomy;
• having complete and searchable clinical data, such as patient's age, surgical records, and hospitalization days.

You may not qualify if:

• previous diagnosis of chronic cholecystitis, this time for elective surgical treatment;
• previous diagnosis of acute cholecystitis, ultrasound-guided cholecystectomy after elective laparoscopic cholecystectomy;
• concomitant with other acute biliary and pancreatic system-related diseases, such as obstructive jaundice caused by choledochal stones, acute cholangitis, acute pancreatitis, etc.;
• exclude patients who combined with other surgery patients such as choledochotomy and lithotripsy, choledochoscopic exploration and lithotripsy, bile-intestinal anastomosis, appendectomy, etc;
• those with incomplete data

Sponsors & Collaborators

• Dalian Medical University: lead
• National Natural Science Foundation of China: collaborator

Study Sites (1)

The Second Hospital of Dalian Medical University

Dalian, Liaoning, 116023, China

Location

Related Publications (3)

• Wu B, Buddensick TJ, Ferdosi H, Narducci DM, Sautter A, Setiawan L, Shaukat H, Siddique M, Sulkowski GN, Kamangar F, Kowdley GC, Cunningham SC. Predicting gangrenous cholecystitis. HPB (Oxford). 2014 Sep;16(9):801-6. doi: 10.1111/hpb.12226. Epub 2014 Mar 17.

  PMID: 24635779 BACKGROUND

• Yacoub WN, Petrosyan M, Sehgal I, Ma Y, Chandrasoma P, Mason RJ. Prediction of patients with acute cholecystitis requiring emergent cholecystectomy: a simple score. Gastroenterol Res Pract. 2010;2010:901739. doi: 10.1155/2010/901739. Epub 2010 Jun 8.

  PMID: 20631896 BACKGROUND

• Borzellino G, Sauerland S, Minicozzi AM, Verlato G, Di Pietrantonj C, de Manzoni G, Cordiano C. Laparoscopic cholecystectomy for severe acute cholecystitis. A meta-analysis of results. Surg Endosc. 2008 Jan;22(1):8-15. doi: 10.1007/s00464-007-9511-6. Epub 2007 Aug 18.

  PMID: 17704863 BACKGROUND

MeSH Terms

Interventions

Watchful Waiting

Intervention Hierarchy (Ancestors)

Outcome Assessment, Health Care; Outcome and Process Assessment, Health Care; Quality of Health Care; Health Services Administration

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: resident physician

Study Record Dates

• First Submitted: April 29, 2024
• First Posted: May 3, 2024
• Study Start: December 1, 2023
• Primary Completion: March 1, 2024
• Study Completion: March 2, 2024
• Last Updated: May 3, 2024

Record last verified: 2024-05

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)