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This study is to screen out the biomarkers and establish the model to predict coagulation dysfunction induced tigecycline
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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.
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200 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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