Biomarkers and Prediction of Tigecycline Induced Coagulation Dysfunction

Sponsor

The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School (Other)

Overall Status

Not yet recruiting

CT.gov ID

NCT05698160

Collaborator

(none)

200

Enrollment

Anticipated Duration (Months)

Study Details

Study Description

Brief Summary

This study is to screen out the biomarkers and establish the model to predict coagulation dysfunction induced tigecycline

Condition or Disease	Intervention/Treatment	Phase
Blood Coagulation Disorder

Detailed Description

The critically ill patients treated with tigecycline in in tensive care unit will be recruited and divided into tigecycline-induced coagulation dysfunction group and non-coagulation dysfunction group. The multi-omics will be used to screen out biomarkers for early prediction of coagulation dysfunction caused by tigecycline. Afterwards, machine learning methods will be adopted to establish the the early prediction model of tigecycline-induced coagulation dysfunction.

Study Design

Study Type:

Observational [Patient Registry]

Anticipated Enrollment :

200 participants

Observational Model:

Other

Time Perspective:

Prospective

Official Title:

Biomarkers and Prediction of Tigecycline Induced Coagulation Dysfunction Based on Multi-omics and Machine Learning Techbology

Anticipated Study Start Date :

Feb 1, 2023

Anticipated Primary Completion Date :

Dec 31, 2025

Anticipated Study Completion Date :

Dec 31, 2025

Arms and Interventions

Arm	Intervention/Treatment
coagulation dysfunction group The critically ill patients in intensive care unit showed coagulation dysfunction after treated with tigecycline.
non-coagulation dysfunction group The critically ill patients in intensive care unit showed normal coagulation function after treated with tigecycline.

Outcome Measures

Primary Outcome Measures

Biomarkers associated with the coagulation dysfunction induced tigecycline [January 2023-December 2025]
Multi-omics will be adopted to screen out biomarkers associated with the coagulation dysfunction induced by tigecycline.

Secondary Outcome Measures

Prediction model for coagulation dysfunction induced by tigecycline [January 2023-December 2025]
Machine learning techbology will be adopted to establish the prediction model for coagulation dysfunction induced by tigecycline

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

Inpatients receiving tigecycline treatment in the Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Intravenous tigecycline ≥ 3 days
Monitoring the plasma concentration of tigecycline