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

## TL;DR

This study uses US FAERS data to identify drugs and drug combinations linked to shock, highlighting cardiovascular and anti-infective agents as high-risk.

## Contribution

The study introduces a multi-method pharmacovigilance approach to systematically analyze drug-induced shock using FAERS data.

## Key findings

- Cardiovascular drugs, anti-infectives, and nervous system agents were most associated with shock.
- High-risk drug combinations like anastrozole + levofloxacin showed strong signals.
- The four-method signal detection achieved 94% positive predictive value.

## Abstract

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.