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The current study extensively assessed CAZ\/AVI\u2010related adverse events (AEs) in the real world through data mining of the FDA Adverse Event Reporting System (FAERS) database to better understand toxicities. The signals of CAZ\/AVI\u2010related AEs were quantified using disproportionality analyses, including the reporting odds ratio, the proportional reporting ratio, the Bayesian confidence propagation neural network, and the multi\u2010item gamma Poisson shrinker algorithms. Out of 10,114,815 records retrieved from the FAERS database, 628 cases were identified, where CAZ\/AVI was implicated as the primary suspect drug. A total of 61 preferred terms with significant disproportionality that simultaneously met the criteria of all four algorithms were retained. Several unexpected safety signals may also occur, including melena, hypernatremia, depressed level of consciousness, brain edema, petechiae, delirium, and shock hemorrhagic. 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