A Joint Model Based on Deep Learning to Predict Multidrug-resistant Klebsiella Pneumoniae Liver Abscess

ConditionLiver Abscess
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorShengjing Hospital

About this trial

The goal of this observational study is to train a deep learning-based model to predict multidrug-resistant Klebsiella pneumoniae liver abscess and evaluate it on a multi-center database.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Patients diagnosed as pyogenic liver abscess and was proved by surgery or interventional process.

Patients had accepted abdominal enhance CT scans before surgery or interventional process.

Disqualifiers

Patients diagnosed with other types of liver abscess such as amoeba.

Trial population

Pyogenic liver abscess patients in 14years of a multicenter project.

Trial design

Design model

Case-control

Time perspective

Retrospective

Treatments tested in this trial

Not listed

Trial groups

550 Participants
are grouped into 2 trial groups
Group A: Patients with ESBL(-) liver abscess
Group B: Patients with ESBL(+) liver abscess

Trial outcomes

Primary outcomes

1

Result of bacteria culture

The result of bacteria culture of abscess decides which group the patients belong. This result was obtained from bacteria culture tests which were done by department of laboratory medicine.

Time frame
The first time before surgery or interventional process, usually within 1 week, up to 4 weeks.
2

Result of drug resistant test

Our destination is to find out the potential differences between Esbl(+) \& Esbl(-) liver abscess.

Time frame
The first time before surgery or interventional process, usually within 1 week, up to 4 weeks.

Secondary outcomes

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Shengjing Hospital

Lead sponsor

The First Affiliated Hospital of China University of Science and Technology (Anhui Provincial)

Collaborator

Guilin Medical University, China

Collaborator

Hebei General Hospital

Collaborator

Xijing Hospital

Collaborator

Hebei Medical University Third Hospital

Collaborator

The First Affiliated Hospital of Dalian Medical University

Collaborator

The People's Hospital of Liaoning Province

Collaborator

Fourth People's Hospital of Shenyang

Collaborator

Sir Run Run Shaw Hospital

Collaborator