Objective To systematically explore the characteristics of risk signals of ravulizumab in real-world settings by stratifying adverse events according to severity, establish a differentiated risk map, and provide evidence for stratified clinical safety management.

Methods Data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) covering the first quarter of 2004 to the fourth quarter of 2025 were extracted. Reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) were adopted for signal analysis. Reports were divided into severe and non-severe subgroups for stratified analysis based on clinical outcomes.

Results A total of 10,500 ravulizumab -associated adverse event reports were included, among which 176 positive signals were detected, covering 27 system organ classes (SOCs). Subgroup analysis showed that, in the non-serious adverse event subgroup, the signal strength was highest for treatment response shortening, diplopia and ptosis; in the serious adverse event subgroup, the strongest signals were for myasthenia gravis and haemolytic anaemia.

Conclusion This study constructed a bidirectional severity-stratified risk map for ravulizumab. The clustering pattern of neurological manifestations and diminished therapeutic response in non-severe reports differs distinctly from the distribution of myasthenia gravis and hemolytic events in severe reports, offering distinct perspectives for clinicians to identify potential risks. This stratified strategy facilitates targeted risk surveillance and individualized medication administration in clinical practice.

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