Construction of a Predictive Model of Gangrenous Cholecystitis Based on Machine Learning
A Real-world Study of Predictive Models of Gangrenous Cholecystitis Based on Machine Learning
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.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
-
-
Liaoning
-
Dalian, Liaoning, China, 116023
- The Second Hospital of Dalian Medical University
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- 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.
Exclusion Criteria:
- 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
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Gangrenous cholecystitis
Defined based on intraoperative findings or pathological diagnosis
|
Observational
|
|
Non-gangrenous cholecystitis
Non-gangrenous cholecystitis, such as chronic cholecystitis, acute cholecystitis, acute attack of chronic cholecystitis
|
Observational
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
pathological diagnosis of patients with cholecystectomy
Time Frame: 30 days
|
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
Time Frame: through study completion, an average of 4 months
|
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 Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
WBC value (10*9/L)
Time Frame: through study completion, an average of 4 months
|
Correlation between WBC and patients with gangrenous cholecystitis and non-gangrenous cholecystitis
|
through study completion, an average of 4 months
|
|
Alanine transaminase value (ALT, U/L)
Time Frame: through study completion, an average of 4 months
|
Correlation between liver function and patients with gangrenous cholecystitis and non-gangrenous cholecystitis
|
through study completion, an average of 4 months
|
|
D-dimer value
Time Frame: through study completion, an average of 4 months
|
Correlation between coagulopathy and patients with gangrenous cholecystitis and non-gangrenous cholecystitis
|
through study completion, an average of 4 months
|
|
Fibrinogen value (g/L)
Time Frame: through study completion, an average of 4 months
|
Correlation between coagulopathy and patients with gangrenous cholecystitis and non-gangrenous cholecystitis
|
through study completion, an average of 4 months
|
|
BMI (Kg/m2)
Time Frame: through study completion, an average of 4 months
|
Correlation between obesity level and patients with gangrenous cholecystitis and non-gangrenous cholecystitis
|
through study completion, an average of 4 months
|
|
Gallbladder wallness (cm)
Time Frame: through study completion, an average of 4 months
|
Correlation between Gallbladder wallness and patients with gangrenous cholecystitis and non-gangrenous cholecystitis
|
through study completion, an average of 4 months
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Publications and helpful links
General Publications
- 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.
- 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.
- 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.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Estimated)
First Posted
Study Record Updates
Last Update Posted (Estimated)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- KY2024-006-02
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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