Biomarkers and Prediction of Tigecycline Induced Coagulation Dysfunction

The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School200 enrolled

Overview

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

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 Type

OBSERVATIONAL

Enrollment

200

Conditions

Blood Coagulation Disorder

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

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 Exclusion Criteria: * Missing clinical data

Outcomes

Primary Outcomes

Biomarkers associated with the coagulation dysfunction induced tigecycline

Multi-omics will be adopted to screen out biomarkers associated with the coagulation dysfunction induced by tigecycline.

Time frame: January 2023-December 2025

Secondary Outcomes

Prediction model for coagulation dysfunction induced by tigecycline

Machine learning techbology will be adopted to establish the prediction model for coagulation dysfunction induced by tigecycline

Time frame: January 2023-December 2025

Data from ClinicalTrials.gov

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