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To study the risk factors associated with multidrug-resistant bacteria (MDRB) infection in diabetic foot (DF) wounds and to develop a nomogram model to predict the risk of MDRB infection in patients with DF. A total of 157 patients with DF between January 2013 and December 2023 were included in this study. A retrospective analysis was conducted to examine the characteristics of MDRB infections. Univariate and multivariate logistic regression analyses were performed to identify risk factors associated with MDRB infection. Based on these risk factors, a predictive model was built using R software and a nomogram was constructed. Multivariate logistic regression analysis revealed that the wound area, previous hospitalization, prior use of antibacterial agents, lower extremity ischaemia grade, and hypoproteinaemia were independent risk factors for MDRB infection in DF wounds (p < 0.05). Construction of the nomogram model for MDRB infection in DF wounds: A nomogram model was developed using five identified risk factors—wound area, previous hospitalization, previous use of antibacterial drugs, lower extremity ischaemia grade and hypoproteinaemia—as predictors. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.863. The model has a good ability to predict MDRB infections in DF wounds. Wound area, previous hospitalization, previous use of antibacterial drugs, lower extremity ischaemia grade and hypoproteinaemia were identified as independent risk factors for MDRB infections in DF wounds. The nomogram model constructed on the basis of these five factors demonstrated good predictive performance for MDRB infection.
by Yu Cui, Yuxuan Gao, Na Meng, Xiaojuan Li, Na Zhao, Lili Yu
Atezolizumab is a widely used immune checkpoint inhibitor (ICI) for cancer treatment, and postmarketing testing is important. This study aims to provide a reference for the safe and rational use of drugs in clinical practice by mining and analyzing the adverse event (AE) signals of atezolizumab on the basis of the FDA Adverse Event Reporting System (FAERS). This research extracted AE reports from the second quarter (Q2) of 2016 to Q2 of 2024 from the FAERS. AEs were standardized and classified on the basis of the System Organ Class (SOC) and Preferred Term (PT) from the Medical Dictionary for Regulatory Activities (MedDRA) version 23.0. This study utilized disproportionality analysis (DPA) for signal mining and analysis, including the reporting odds ratio (ROR) method, the Medicines and Healthcare Products Regulatory Agency (MHRA) method, and the Bayesian confidence propagation neural network (BCPNN) method. We obtained a total of 3,124 AE signals and identified 640 PTs and 21 SOCs for atezolizumab. The highest signal intensity was systemic immune activation (n = 15, ROR = 449.20, PRR = 449.07, IC = 8.06), and the most frequently reported AEs were death, pyrexia, infectious pneumonia, anaemia, and febrile neutropenia. The top 100 PTs in terms of signal intensity involved a total of 16 SOCs, including those associated with endocrine disorders; respiratory, thoracic and mediastinal disorders; and renal and urinary disorders. This study revealed that AEs in the endocrine, respiratory and urinary systems need to be monitored in clinical practice.by Yuxuan Gao, Shiyao Jiang, Yu Cui, Yumeng Wang, Lili Yu
With the extensive clinical application of immune checkpoint inhibitors (ICIs), immune-related adverse events (irAEs) associated with these agents have increasingly garnered significant attention. Unlike other irAEs, endocrine irAEs are mostly irreversible, with variable and nonspecific symptoms, which poses challenges for clinicians in diagnosis. As a result, this study leveraged the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) and the Japanese Adverse Drug Event Report (JADER) pharmacovigilance databases to conduct an in-depth investigation into adverse events induced by PD-1/PD-L1 inhibitors, with a focus on irAEs induced by PD-1/PD-L1 inhibitors. This study pioneers the systematic cross-database validation of endocrine irAEs induced by PD-1/PD-L1 inhibitors. The integration of data from the JADER offers unique safety insights for Asian populations, bolsters global pharmacovigilance efforts, and uncovers regional variations in irAEs reporting. Notably, this study revealed a higher prevalence of endocrine irAEs among men aged over 50 years receiving PD-1/PD-L1 inhibitors. Both PD-1 and PD-L1 inhibitors are strongly associated with thyroid dysfunction, adrenal insufficiency, and pituitary inflammation. Additionally, it identifies several previously undocumented endocrine irAEs. This result unearthed safety signals hitherto unreported in drug inserts, underscoring the imperative for updating the safety labeling of PD-1/PD-L1 inhibitors with respect to endocrine irAEs. The emergence of off-label uses further underscores the need for additional clinical trials to assess their efficacy and safety.
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