Mining and analysis of drug-induced shock adverse reactions: A comprehensive pharmacovigilance study based on the US...

Shock is a life-threatening clinical condition characterized by high morbidity and mortality. Drug-induced shock represents a complex subset of adverse drug reactions that has not been systematically investigated on a large scale. Comprehensive pharmacovigilance analyses are needed to identify high-risk drugs and drug combinations.

We conducted a retrospective pharmacovigilance analysis using the FDA Adverse Event Reporting System (FAERS) covering the period from 2004Q1 to 2024Q2. Shock-related events were extracted using standardized MedDRA preferred terms. Data deduplication followed FDA guidelines, and four complementary signal detection methods-reporting odds ratio (ROR), proportional reporting ratio (PRR), information component (IC), and empirical Bayes geometric mean (EBGM)-were applied. Drug classification was performed using the Anatomical Therapeutic Chemical (ATC) system, and drug-drug interaction analysis was carried out with the Ω shrinkage method.

The initial dataset contained 3,611,216 duplicate records, and after deduplication, 17,947,720 demographic records were retained. From these, 8,511,840 records reported by healthcare professionals were included, yielding 277,956 shock-related adverse event reports involving 244,030 patients. Among these patients, 46.38% were female, 43.09% were male, and 10.53% had unspecified gender, while the main age groups were 45-64 years (27.35%) and ≥65 years (27.82%). Geographically, the United States accounted for 26.09% of reports, followed by France (8.20%), Japan (4.76%), and the United Kingdom (4.16%), with 99.26% of cases classified as serious events. Signal detection analysis showed that among 847 drugs, 158 (18.7%) were positive in three methods and 79 (9.3%) were positive in all four methods. Metformin was associated with 2,604,602 reports and amlodipine with 2,783,836 reports, both strongly linked to shock. ATC classification revealed cardiovascular drugs accounted for 32% of signals, anti-infectives for 28%, and nervous system drugs for 23%. High-risk drug combinations included anastrozole + levofloxacin (Ω = 4.23), duloxetine + ondansetron (Ω = 4.29), amphotericin B + fluoxetine (Ω = 4.30), quetiapine + sertindole (Ω = 4.25), and risperidone + sulfamethoxazole/trimethoprim (Ω = 4.16). Performance evaluation showed the combined four-method approach achieved a positive predictive value of 94% and a negative predictive value of 89%.

This study demonstrates strong associations between specific drug classes and shock, with cardiovascular, anti-infective, and nervous system agents identified as the most critical categories. The application of advanced multi-method signal detection enhances the accuracy of pharmacovigilance, reveals novel associations, and provides important evidence for clinical monitoring and risk management.