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BACKGROUND: The increasing problem of bacterial resistance, particularly with quinolone-resistant Escherichia coli (QnR eco) poses a serious global health issue. METHODS: We collected data on QnR eco resistance rates and detection frequencies from 2014 to 2021 via the China Antimicrobial Resistance Surveillance System, complemented by meteorological and socioeconomic data from the China Statistical Yearbook and the China Meteorological Data Service Centre (CMDC). Comprehensive nonparametric testing and multivariate regression models were used in the analysis. RESULT: Our analysis revealed significant regional differences in QnR eco resistance and detection rates across China. Along the Hu Huanyong Line, resistance rates varied markedly: 49.35 in the northwest, 54.40 on the line, and 52.30 in the southeast (P = 0.001). Detection rates also showed significant geographical variation, with notable differences between regions (P < 0.001). Climate types influenced these rates, with significant variability observed across different climates (P < 0.001). Our predictive model for resistance rates, integrating climate and healthcare factors, explained 64.1% of the variance (adjusted R-squared = 0.641). For detection rates, the model accounted for 19.2% of the variance, highlighting the impact of environmental and healthcare influences. CONCLUSION: The study found higher resistance rates in warmer, monsoon climates and areas with more public health facilities, but lower rates in cooler, mountainous, or continental climates with more rainfall. This highlights the strong impact of climate on antibiotic resistance. Meanwhile, the predictive model effectively forecasts these resistance rates using China's diverse climate data. This is crucial for public health strategies and helps policymakers and healthcare practitioners tailor their approaches to antibiotic resistance based on local environmental conditions. These insights emphasize the importance of considering regional climates in managing antibiotic resistance.
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Proteínas de Escherichia coli , Quinolonas , Escherichia coli , China/epidemiología , Farmacorresistencia Bacteriana , Antibacterianos/farmacologíaRESUMEN
AIMS: Voriconazole is a broad-spectrum antifungal agent for the treatment of invasive fungal infections. There is limited information about the pharmacokinetics and appropriate dosage of voriconazole in patients with liver dysfunction. This study aimed to explore the relationship between voriconazole trough concentration (Ctrough ) and toxicity, identify the factors significantly associated with voriconazole pharmacokinetic parameters and propose an optimised voriconazole dosing regimen for patients with liver dysfunction. METHODS: The study prospectively enrolled 51 patients with 272 voriconazole concentrations. Receiver operating characteristic curves were used to explore the relationship between voriconazole Ctrough and toxicity. The pharmacokinetic data was analysed with nonlinear mixed-effects method. Dosing simulations stratified by total bilirubin (TBIL, TBIL-1: TBIL < 51 µmol/L; TBIL-2: 51 µmol/L ≤ TBIL < 171 µmol/L; TBIL-3: TBIL ≥ 171 µmol/L) were performed. RESULTS: Receiver operating characteristic curve analysis revealed that voriconazole Ctrough of ≤ 5.1 mg/L were associated with significantly lower the incidence of adverse events. A 1-compartment pharmacokinetic model with first-order absorption and elimination was used to describe the data. Population pharmacokinetic parameters of clearance, volume of distribution and oral bioavailability were 0.88 L/h, 148.8 L and 88.4%, respectively. Voriconazole clearance was significantly associated with TBIL and platelet count. The volume of distribution increased with body weight. Patients with TBIL-1 could be treated with a loading dose of 400 mg every 12 hours (q12h) for first day, followed by a maintenance dose of 100 mg q12h administered orally or intravenously. TBIL-2 and TBIL-3 patients could be treated with a loading dose of 200 mg q12h and maintenance doses of 50 mg q12h or 100 mg once daily and 50 mg once daily orally or intravenously, respectively. CONCLUSIONS: Lower doses and longer dosing intervals should be considered for patients with liver dysfunction. TBIL-based dosing regimens provide a practical strategy for achieving voriconazole therapeutic range and therefore maximizing treatment outcomes.
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Infecciones Fúngicas Invasoras , Hepatopatías , Antifúngicos/efectos adversos , Humanos , Infecciones Fúngicas Invasoras/tratamiento farmacológico , Hepatopatías/tratamiento farmacológico , Estudios Prospectivos , Voriconazol/efectos adversosRESUMEN
PURPOSE: Polymyxin B, with its unique structure and mechanism of action, has emerged as a key therapeutic agent against Gram-negative bacteria. The study aims to explore potential factors to influence its effectiveness and safety. METHODS: A model-based meta-analysis of 96 articles was conducted, focusing on factors like dosage, bacterial species, and combined antibiotic therapy. The analysis evaluated mortality rates and incidence rate of renal dysfunction, also employing parametric survival models to assess 30-d survival rates. RESULTS: In the study involving 96 articles and 9716 patients, polymyxin B's daily dose showed minimal effect on overall mortality, with high-dose group mortality at 33.57% (95% confidence intervals [CI]: 29.15-38.00) compared to the low-dose group at 35.44% (95% CI: 28.99-41.88), P = 0.64. Mortality significantly varied by bacterial species, with Pseudomonas aeruginosa infections at 58.50% (95% CI: 55.42-63.58). Monotherapy exhibited the highest mortality at 40.25% (95% CI: 34.75-45.76), P < 0.01. Renal dysfunction was more common in high-dose patients at 29.75% (95% CI: 28.52-30.98), with no significant difference across antibiotic regimens, P = 0.54. The 30-d overall survival rate for monotherapy therapy was 63.6% (95% CI: 59.3-67.5) and 70.2% (95% CI: 64.4-76.2) for association therapy with ß-lactam drugs. CONCLUSIONS: The dosage of polymyxin B does not significantly change death rates, but its effectiveness varies based on the bacterial infection. Certain bacteria like P. aeruginosa are associated with higher mortality. Combining polymyxin B with other antibiotics, especially ß-lactam drugs, improves survival rates. Side effects depend on the dose, with lower doses being safer. These findings emphasize the importance of customizing treatment to balance effectiveness and safety.
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Background: Pneumocystis jirovecii pneumonia (PJP) has been reported with ICIs but limited to case reports. The clinical features of PJP with ICIs remain mostly unknown. This study aims to investigate the association of PJP with ICIs and describe clinical features. Methods: Reports of PJP recorded in FAERS (January 2004-December 2022) were identified through the preferred term "Pneumocystis jirovecii pneumonia". Demographic and clinical features were described, and disproportionality signals were assessed through the Reporting Odds Ratio (ROR) and Information Component (IC), using traditional chemotherapy and targeted therapy as comparators, and adjusting signals by excluding contaminant immunosuppressive drugs and pre-existing diseases. A systematic literature review was conducted to describe clinical features of published PJP reports with ICIs. Bradford Hill criteria was adopted for global assessment of the evidence. Results: We identified 677 reports of PJP associated with ICIs, in which 300 (44.3%) PJP cases with fatal outcome. Nivolumab (IC025 2.05), pembrolizumab (IC025 1.88), ipilimumab (IC025 1.43), atezolizumab (IC025 0.36), durvalumab (IC025 1.65), nivolumab plus ipilimumab (IC025 1.59) have significant signals compared to other drugs in FAERS database. After excluding pre-existing diseases and immunosuppressive agents which may increase susceptibility of PJP, the signals for PJP associated with nivolumab, pembrolizumab, durvalumab, nivolumab plus ipilimumab remained robust (IC025 > 0). When compared to other anticancer regimens, although all ICIs showed a lower disproportionate signal for PJP than chemotherapy, nivolumab (IC025 0.33, p < 0.001), pembrolizumab (IC025 0.16, p < 0.001), both PD-1 inhibitors, presented a higher signal for PJP than targeted therapy. Male gender (IC025 0.26, p < 0.001) and age >65 years (IC025 0.38, p < 0.001) were predominant in PJP cases associated with across all ICIs. In literature, 15 PJP cases associated with ICIs were reported in 10 published case reports. 12 of 15 (80.0%) of cases received PD-1 inhibitors before PJP was diagnosed. Conclusion: By the combined analysis of post-marketing data from FAERS and published case reports, we identified ICIs may be associated with PJP, especially in males aged >65years. After accounting for confounders, PD-1 inhibitors emerged with a robust disproportionality signal when compared to PD-L1/CTLA-4 inhibitors as well as targeted therapy. Further research is warranted to validate our findings.
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INTRODUCTION: Meropenem is a carbapenem antibiotic, which has demonstrated excellent antimicrobial activity against gram-negative clinical isolates. It is also commonly used in critically ill patients. This study aimed to determine the pharmacokinetics/pharmacodynamics of meropenem in critically ill patients and whether prolonged injection duration is really beneficial to meropenem therapy. METHODS: We included 209 samples in 64 patients in this prospective study. PPK analysis and Monte Carlo dosing simulations were developed using Phoenix. RESULTS: A two-compartment model described the data adequately. Clearance (CL), volume (V), clearance of peripheral compartment (CL2), and volume of peripheral compartment (V2) were 6.15 l/h, 2.83 l/h, 17.40 l, and 17.48 l, respectively. Creatinine clearance and uric acid were significant covariates. Patients with creatinine clearance ≤ 60 ml/min and uric acid > 400 µmol/l could achieve the target > 90% under the minimum inhibitory concentration (MIC) of 8 mg/l, even with the administration dose of 500 mg/8 h with a 2-h infusion. Prolonging the infusion time significantly improved the therapeutic effect when MIC < 4. However, for the pharmacodynamic (PD) effects of 100% fT > MIC and 100% fT > 4 MIC, no significant statistical difference was observed in critically ill patients. CONCLUSIONS: Critically ill patients with lower creatinine clearance and higher uric acid levels tended to need a lower dosage of meropenem. Prolonged infusion time was not always beneficial for those who needed a higher therapeutic target (100% fT > MIC, 100% fT > 4 MIC) or with MIC > 4 mg/l. Increasing dose or alternative therapeutic strategies may be required for critically ill patients with drug-resistant or severe infections. The study is of great significance to guide the rational use of meropenem in critically ill patients. TRIAL REGISTRATION: The trial was registered in the China Clinical Trial (ChiCTR1900020672). Registered on 12 January 2019.
Meropenem is commonly used empirically or targeted in critically ill patients for bacterial infection. Many studies have reported that prolonged infusion time can improve the efficacy of meropenem therapy. However, we are skeptical about that. Meanwhile, prolonged injections can sometimes cause mobility problems for patients. A quantitative method is used to evaluate meropenem use. It is called the population pharmacokinetic model or pharmacodynamic study. Using this method, we found two significant influencing factors of meropenem metabolism: creatinine clearance and uric acid level. It is likely that patients with a lower level of creatinine clearance and a high uric acid level tend to require lower dosages of meropenem. As for the effect of infusion time, Monte Carlo simulation was used, which can do 3000 simulations on an individual. The result was complex. We found infusion time was beneficial only when bacteria were sensitive to meropenem. The evidence suggests that prolonged injection duration sometimes does not significantly improve the outcome of antimicrobial therapy.
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Introduction: Antibody-drug conjugates (ADCs) produce unparalleled efficacy in refractory neoplasms but can also lead to serious toxicities. Although ADC-related sepsis has been reported, the clinical features are not well characterized in real-world studies. Objective: The aim of this study was to identify the association between ADCs and sepsis using FAERS data and uncover the clinical characteristics of ADC-related sepsis. Methods: We performed disproportionality analysis using FAERS data and compared rates of sepsis in cancer patients receiving ADCs vs. other regimens. Associations between ADCs and sepsis were assessed using reporting odds ratios (RORs) and information component (IC). For each treatment group, we detected drug interaction signals, and conducted subgroup analyses (age, gender, and regimens) and sensitivity analyses. Results: A total of 24,618 cases were reported with ADCs between Q1, 2004 and Q3, 2021. Sepsis, septic shock, multiple organ dysfunction syndrome, and other sepsis-related toxicities were significantly associated with ADCs than other drugs in this database. Sepsis and multiple organ dysfunction syndrome have the highest safety concerns with ADCs compared with other anticancer monotherapies. Gemtuzumab ozogamicin and inotuzumab ozogamicin showed increased safety risks than other ADCs. For the top nine ADC-related sepsis, males showed higher sepsis safety concern than females (p <0.001); however, age did not exert influence on the risk of sepsis. We identified that 973 of 2,441 (39.9%) cases had acute myeloid leukemia (AML), and 766 of 2613 (29.3%) cases on ADCs died during therapy. Time-to-onset analysis indicated ADC-related sepsis is prone to occur within a month after administration. Co-administration of ADCs with colony-stimulating factors, proton pump inhibitors, H2-receptor antagonists, or CYP3A4/5 inhibitors showed to synergistically increase the risk of sepsis-related toxicities. Conclusion: Antibody-drug conjugates may increase the risk of sepsis in cancer patients, leading to high mortality. Further studies are warranted to characterize the underlying mechanisms and design preventive measures for ADC-related sepsis.
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Tacrolimus is an immunosuppressant with a narrow therapeutic window. Tacrolimus exposure increased significantly during voriconazole co-therapy. The magnitude of this interaction is highly variable, but it is hard to predict quantitatively. We conducted a study on 91 kidney transplantation recipients with voriconazole co-therapy. Furthermore, 1701 tacrolimus concentration data were collected. Standard concentration adjusted by tacrolimus daily dose (C/D) and weight-adjusted standard concentration (CDW) increased to 6 times higher during voriconazole co-therapy. C/D and CDW increased with voriconazole concentration. Patients with the genotype of CYP3A5 *3/*3 and CYP2C19 *2/*2 or *2/*3 were more variable at the same voriconazole concentration level. The final prediction model could explain 54.27% of the variation in C/D and 51.11% of the variation in CDW. In conclusion, voriconazole was the main factor causing C/D and CDW variation, and the effect intensity should be quantitative by its concentration. Kidney transplant recipients with CYP3A5 genotype of *3/*3 and CYP2C19 genotype of *2/*2 and *2/*3 should be given more attention during voriconazole co-therapy. The prediction model established in this study may help to reduce the occurrence of rejection.
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Voriconazole is a triazole antifungal agent commonly used for the treatment and prevention of invasive aspergillosis (IA). However, the study of voriconazole's use in children is limited. The present study was performed to explore maintenance dose to optimize voriconazole dosage in children and the factors affecting voriconazole trough concentration. This is a non-interventional retrospective clinical study conducted from 1 January 2016 to 31 December 2020. The study finally included 94 children with 145 voriconazole trough concentrations. The probability of achieving a targeted concentration of 1.0-5.5 µg/mL with empiric dosing increased from 43 (45.3%) to 78 (53.8%) after the TDM-guided adjustment. To achieve targeted concentration, the overall target maintenance dose for the age group of less than 2, 2 to 6, 6 to 12, and 12 to 18 years old was approximately 5.71, 6.67, 5.08 and 3.31 mg·kg-1/12 h, respectively (p < 0.001). Final multivariate analysis found that weight (p = 0.019), dose before sampling (p < 0.001), direct bilirubin (p < 0.001), urea nitrogen (p = 0.038) and phenotypes of CYP2C19 were influencing factors of voriconazole trough concentration. These factors can explain 36.2% of the variability in voriconazole trough concentration. Conclusion: In pediatric patients, voriconazole maintenance doses under the target concentration tend to be lower than the drug label recommended, but this still needs to be further studied. Age, body weight, dose, direct bilirubin, urea nitrogen and phenotypes of CYP2C19 were found to be influencing factors of voriconazole concentration in Chinese children. The influence of these factors should be taken into consideration during voriconazole use.
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Voriconazole is the mainstay for the treatment of invasive fungal infections in patients who underwent a kidney transplant. Variant CYP2C19 alleles, hepatic function, and concomitant medications are directly involved in the metabolism of voriconazole. However, the drug is also associated with numerous adverse events. The purpose of this study was to identify predictors of adverse events using binary logistic regression and to measure its trough concentration using multiple linear modeling. We conducted a prospective analysis of 93 kidney recipients cotreated with voriconazole and recorded 213 trough concentrations of it. Predictors of the adverse events were voriconazole trough concentration with the odds ratios (OR) of 2.614 (P = 0.016), cytochrome P450 2C19 (CYP2C19), and hemoglobin (OR 0.181, P = 0.005). The predictive power of these three factors was 91.30%. We also found that CYP2C19 phenotypes, hemoglobin, platelet count, and concomitant use of ilaprazole had quantitative relationships with voriconazole trough concentration. The fit coefficient of this regression equation was R2 = 0.336, demonstrating that the model explained 33.60% of interindividual variability in the disposition of voriconazole. In conclusion, predictors of adverse events are CYP2C19 phenotypes, hemoglobin, and voriconazole trough concentration. Determinants of the voriconazole trough concentration were CYP2C19 phenotypes, platelet count, hemoglobin, concomitant use of ilaprazole. If we consider these factors during voriconazole use, we are likely to maximize the treatment effect and minimize adverse events.