Comparing Acute Kidney Injury Reports Among Antibiotics: A Pharmacovigilance Study of the FDA Adverse Event Reporting System (FAERS)

Drug Safety ◽  
2019 ◽  
Vol 43 (1) ◽  
pp. 17-22 ◽  
Author(s):  
Taylor M. Patek ◽  
Chengwen Teng ◽  
Kaitlin E. Kennedy ◽  
Carlos A. Alvarez ◽  
Christopher R. Frei
Keyword(s):  
Acute Kidney Injury ◽  
Adverse Event ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Kidney Injury ◽  
Adverse Event Reporting ◽  
Event Reporting

scholarly journals 1977. Comparing Acute Kidney Injury Risk among Antibiotic Classes: A Study of the FDA Adverse Event Reporting System (FAERS)

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S662-S662
Author(s):  
Taylor M Patek ◽  
Chengwen Teng ◽  
Kaitlin E Kennedy ◽  
Christopher R Frei
Keyword(s):  
Acute Kidney Injury ◽  
Adverse Event ◽  
Injury Risk ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Kidney Injury ◽  
Adverse Event Reporting ◽  
Drug Event ◽  
Event Reporting ◽  
Increased Risk

Abstract Background A recent article published in 2018 studied the FDA Adverse Event Reporting System (FAERS) and listed the most common medications associated with acute kidney injury (AKI) based on number of AKI reports. In regards to antibiotics, the study only ranked vancomycin, fluoroquinolones, penicillin combinations, and trimethoprim–sulfamethoxazole as having a significant association with AKI. The objective of this study was to evaluate those and additional antibiotic classes using FAERS, and to compare their risk associated with this adverse drug event. Methods FAERS reports from January 1, 2015 to December 31, 2017 were included in the study. The Medical Dictionary for Regulatory Activities (MedDRA) was used to identify AKI cases. Reporting Odds Ratios (RORs) and corresponding 95% confidence intervals (95% CI) for the association between antibiotics and AKI were calculated. An association was considered statistically significant when the lower limit of the 95% CI was greater than 1.0. Results A total of 2,042,801 reports (including 20,138 acute kidney injury reports) were considered, after inclusion criteria were applied. Colistin had the greatest proportion of AKI reports, representing 25% of all colistin reports. Acute kidney injury RORs (95% CI) for antibiotics were (in descending order): colistin 33.10 (21.24–51.56), aminoglycosides 17.41 (14.49–20.90), vancomycin 15.28 (13.82–16.90), trimethoprim-sulfamethoxazole 13.72 (11.94–15.76), penicillin combinations 7.95 (7.09–8.91), clindamycin 6.46 (5.18–8.04), cephalosporins 6.07 (5.23–7.05), daptomycin 6.07 (4.61–7.99), macrolides 3.60 (3.04–4.26), linezolid 3.48 (2.54–4.77), carbapenems 3.31 (2.58–4.25), metronidazole 2.55 (1.94–3.36), tetracyclines 1.73 (1.26–2.36), and fluoroquinolones 1.71 (1.49–1.97). Conclusion This study found 17 classes of antibiotics and combinations that were significantly associated with AKI compared with four antibiotics that were mentioned in a recently published article looking at drug-associated AKI. While this study confirmed previous literature of certain antibiotics associated with increased risk of AKI, it also compared antibiotics within classes and provided additional insight regarding which antibiotics had the highest associated risk of an AKI. Disclosures All authors: No reported disclosures.

scholarly journals Proton pump inhibitors associated acute kidney injury and chronic kidney disease: data mining of US FDA adverse event reporting system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bin Wu ◽  
Dan Li ◽  
Ting Xu ◽  
Min Luo ◽  
Zhiyao He ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Acute Kidney Injury ◽  
Adverse Event ◽  
Kidney Disease ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Kidney Injury ◽  
Adverse Event Reporting ◽  
Event Reporting ◽  
Us Fda

AbstractProton pump inhibitors (PPIs) were widely used. Observational studies suggested increasing risk of kidney injury in patients with PPIs treatment. We gathered six PPI regimens and adverse reports of acute kidney injury (AKI) and chronic kidney disease (CKD) based on US FDA Adverse Event Reporting System (FAERS) database from 2004 to 2019. We employed reporting odds ratio (ROR) to detect signals. Finally, we identified 3187 PPIs-associated AKI cases and 3457 PPIs-associated CKD cases. We detected significant signals between PPIs and AKI as well as CKD. The signal strength was stronger for CKD (ROR = 8.80, 95% CI 8.49–9.13) than AKI (ROR = 3.95, 95% CI 3.81–4.10), while dexlansoprazole performed stronger association for CKD (ROR = 34.94, 95% CI 30.89–39.53) and AKI (ROR = 8.18, 95% CI 7.04–9.51) than the other five PPIs. The median time from PPIs use to event occurrence was 23 days for AKI and 177 days for CKD. PPIs-associated AKI resulted larger proportion of death, life-threatening, hospitalization and disability events than PPIs-associated CKD. By mining the FAERS big data, we provided more information between PPIs use and the AKI and CKD events. PPIs rational use should be repeatedly stressed.

scholarly journals Correction to: Comparing Acute Kidney Injury Reports Among Antibiotics: A Pharmacovigilance Study of the FDA Adverse Event Reporting System (FAERS)

Drug Safety ◽  
2020 ◽  
Vol 43 (8) ◽  
pp. 825-825
Author(s):  
Taylor M. Patek ◽  
Chengwen Teng ◽  
Kaitlin E. Kennedy ◽  
Carlos A. Alvarez ◽  
Christopher R. Frei
Keyword(s):  
Acute Kidney Injury ◽  
Adverse Event ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Kidney Injury ◽  
Adverse Event Reporting ◽  
Event Reporting

scholarly journals Systematic analysis of safety profile for darunavir and its boosted agents using data mining in the FDA Adverse Event Reporting System database

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaojiang Tian ◽  
Yao Yao ◽  
Guanglin He ◽  
Yuntao Jia ◽  
Kejing Wang ◽  
...  
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Reporting System ◽  
Proportional Reporting Ratio ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Systematic Analysis ◽  
Event Reporting ◽  
Exfoliative Dermatitis

AbstractThis current investigation was aimed to generate signals for adverse events (AEs) of darunavir-containing agents by data mining using the US Food and Drug Administration Adverse Event Reporting System (FAERS). All AE reports for darunavir, darunavir/ritonavir, or darunavir/cobicistat between July 2006 and December 2019 were identified. The reporting Odds Ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) were used to detect the risk signals. A suspicious signal was generated only if the results of the three algorithms were all positive. A total of 10,756 reports were identified commonly observed in hepatobiliary, endocrine, cardiovascular, musculoskeletal, gastrointestinal, metabolic, and nutrition system. 40 suspicious signals were generated, and therein 20 signals were not included in the label. Severe high signals (i.e. progressive extraocular muscle paralysis, acute pancreatitis, exfoliative dermatitis, acquired lipodystrophy and mitochondrial toxicity) were identified. In pregnant women, umbilical cord abnormality, fetal growth restriction, low birth weight, stillbirth, premature rupture of membranes, premature birth and spontaneous abortion showed positive signals. Darunavir and its boosted agents induced AEs in various organs/tissues, and were shown to be possibly associated with multiple adverse pregnant conditions. This study highlighted some novel and severe AEs of darunavir which need to be monitored prospectively.

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