OBJECTIVE:To develop and validate a rapid, evidence-based benefit-risk assessment index for off-label drug use in pediatrics, thereby promoting standardized clinical decision-making. METHODS:Under the auspices of the Guangdong Pharmaceutical Association, a multidisciplinary expert panel from pediatrics, pharmacy, methodology, and ethics was convened. Systematic literature searches informed a preliminary index framework. Three Delphi rounds refined indicators. Weights were assigned using the analytic hierarchy process. Expert-based validation involved 20 hematology-oncology experts assessing 10 cases; intraclass correlation coefficient (ICC) and Spearman's correlations evaluated reliability and validity. RESULTS:The index consists of 2 primary dimensions (benefits: 56 points; risks: 44 points), 10 third-level, and 40 fourth-level indicators, with five prerequisites (e.g., no alternatives, informed consent). The ICC was 0.77 (good reliability); Spearman's correlations were rs = 0.97 (benefits) and rs = 0.68 (risks) (both p < 0.05), indicating strong alignment with expert consensus. Junior experts showed lower correlations (benefits rs = 0.89; risks rs = 0.56) than seniors (benefits rs = 0.97; risks rs = 0.78), highlighting the system's role in standardizing assessments. CONCLUSION:This quantitative index provides an evidence-based tool for pediatric off-label drug decisions, supporting clinicians, policymakers, and standardization efforts.

Linezolid (LZD) is used to treat infectious diseases caused by Gram-positive bacteria, but thrombocytopenia is one of the main adverse reactions to LZD administration. Early prediction of linezolid-induced thrombocytopenia (LI-TP) is of great importance to improve the clinical outcomes and prognoses. The aim of this study was to develop and validate a prediction model for LI-TP. A retrospective cohort of hospitalized adults receiving LZD therapy (January 2014–June 2022) was analyzed. Independent risk factors for LI-TP were identified via logistic regression in the training set (n = 757). A nomogram model for LI-TP were developed based on independent risk factors, and verified in validation set (n = 123). The incidence of LI-TP was 13.5

Objective:Linezolid (LZD), a commonly used antimicrobial agent in clinical practice, has not undergone adequate pharmacokinetic (PK) assessment in pediatric populations with renal impairment (RI). Physiologically based pharmacokinetic (PBPK) modeling provides unique benefits for investigating drug pharmacokinetics in specific patient groups. This study aimed to employ the PBPK model to refine and optimize the therapeutic dosing protocol of LZD for RI pediatric patients. Methods:The model was developed and validated for both healthy adults and RI adults, which was subsequently adapted for pediatric applications. Upon verification of the pediatric Based on clinical PK data and real-world study findings, the PBPK model demonstrated precise prediction of LZD exposure in pediatric populations with varying degrees of RI, encompassing weight- and age-associated PK variations. Results:The PBPK modeling simulations exhibited robust agreement with observational data for LZD across both oral and intravenous delivery routes under diverse dosing protocols, as evidenced by the fold error (FE) always between 0.5 and 2 times, geometric mean fold error (GMFE) was less than 2.0 and mean absolute prediction error (MAPE) was within 100%. Pediatric populations with severe or end-stage RI exhibited 1.21-fold and 1.28-fold elevations in plasma concentration-time curve (AUC) values, respectively, relative to healthy pediatric counterparts when administered equivalent 10 mg/kg LZD doses. Pharmacodynamic analysis confirmed that the proposed dosing regimens-8 mg/kg every 8 hours for children with severe or end-stage RI -were effective in achieving the target AUC0-24/MIC ratio of ≥80 at a susceptible inhibitory concentration of ≤ 2 mg/L. Conclusion:Our model provides a predictive instrument to enhance precision in determining therapeutic LZD dosage regimens for pediatric populations through systematic integration of developmental PK parameters.

Background:The package insert is a key reference and legal basis for clinical medication. However, in the field of rare diseases, advances in diagnosis and treatment often outpace updates to drug labels, resulting in widespread off-label drug use-a practice that is particularly common and often unavoidable in pediatric populations. Inappropriate off-label use, however, carries significant clinical and safety risks. Methods:Under the guidance of the Rare Disease Expert Committee of the Guangdong Pharmaceutical Association, a multidisciplinary panel of experts from clinical medicine, pharmacy, and related specialties developed the "Expert consensus on the off-label use of drugs for pediatric rare diseases in China (2025 edition)". The consensus integrates available evidence, clinical experience, evidence quality, and medication safety profiles, and was finalized after several rounds of rigorous iterative review. Results:The consensus presents 73 recommendations on off-label drug use across 21 rare diseases, organized in a tabular format for clarity and ease of reference. Conclusions:This consensus aims to standardize the management of off-label drug use in pediatric rare diseases. It supports medical institutions in developing off-label drug formularies, promotes rational drug use, and helps address the diagnostic and therapeutic needs of pediatric rare disease patients. Furthermore, it contributes to the establishment of a structured evaluation and management framework for off-label drug use in this clinical context.

BackgroundTorsades de pointes (TdP) is a rare yet potentially fatal cardiac arrhythmia that is often drug-induced. Drug-drug interactions (DDIs) are a major risk factor for TdP development, but the specific drug combinations that increase this risk have not been extensively studied. ObjectiveThis study aims to identify clinically significant, high-priority DDIs to provide a foundation to minimize the risk of TdP and effectively manage DDI risks in the future. MethodsWe used the following 4 frequency statistical models to detect DDI signals using the Food and Drug Administration Adverse Event Reporting System (FAERS) database: Ω shrinkage measure, combination risk ratio, chi-square statistic, and additive model. The adverse event of interest was TdP, and the drugs targeted were all registered and classified as “suspect,” “interacting,” or “concomitant drugs” in FAERS. The DDI signals were identified and evaluated using the Lexicomp and Drugs.com databases, supplemented with real-world data from the literature. ResultsAs of September 2023, this study included 4313 TdP cases, with 721 drugs and 4230 drug combinations that were reported for at least 3 cases. The Ω shrinkage measure model demonstrated the most conservative signal detection, whereas the chi-square statistic model exhibited the closest similarity in signal detection tendency to the Ω shrinkage measure model. The κ value was 0.972 (95% CI 0.942-1.002), and the Ppositive and Pnegative values were 0.987 and 0.985, respectively. We detected 2158 combinations using the 4 frequency statistical models, of which 241 combinations were indexed by Drugs.com or Lexicomp and 105 were indexed by both. The most commonly interacting drugs were amiodarone, citalopram, quetiapine, ondansetron, ciprofloxacin, methadone, escitalopram, sotalol, and voriconazole. The most common combinations were citalopram and quetiapine, amiodarone and ciprofloxacin, amiodarone and escitalopram, amiodarone and fluoxetine, ciprofloxacin and sotalol, and amiodarone and citalopram. Although 38 DDIs were indexed by Drugs.com and Lexicomp, they were not detected by any of the 4 models. ConclusionsClinical evidence on DDIs is limited, and not all combinations of heart rate–corrected QT interval (QTc)–prolonging drugs result in TdP, even when involving high-risk drugs or those with known risk of TdP. This study provides a comprehensive real-world overview of drug-induced TdP, delimiting both clinically significant DDIs and negative DDIs, providing valuable insights into the safety profiles of various drugs, and informing the optimization of clinical practice.

Torsades de Pointes (TdP) is a rare yet potentially fatal cardiac arrhythmia, and that is often drug-induced. Drug-drug interactions (DDIs) is a major risk factor for TdP development, while the specific drug combinations that increase this risk have not been extensively studied. The primary objective of this study was to identify clinically significant DDIs to minimize the risk of TdP, without unnecessary treatment discontinuations or alterations. Four frequency statistical models: the Ω shrinkage measure, combination risk ratio, chi-square statistics, and additive models were employed to detect DDIs signals using the FDA Adverse Event Reporting System (FAERS) database. The adverse event of interest was TdP, and the drugs targeted were all registered and classified as "suspect", "interacting", or "concomitant drugs" in FAERS. The DDIs signals were identified and evaluated using the Lexicomp® and Drugs.com® databases, supplemented with real-world data from literature evidence. Of the 4,313 TdP cases, 721 drugs and 4,230 drug combinations reported in at least 3 cases. The Ω shrinkage measure model demonstrated the most conservative in signal detection, whereas the chi-square statistic model exhibited the closest similarity in signal detection tendency to the Ω shrinkage measure model. 2,158 combinations were detected by the four frequency statistical models, of which 241 combinations were indexed by Drugs.com® or Lexicomp®, and 105 were indexed by both. The most commonly interacting drugs were amiodarone, citalopram, quetiapine, ondansetron, ciprofloxacin, methadone, escitalopram, sotalol, voriconazole, etc. The most common combinations were citalopram & quetiapine, amiodarone & ciprofloxacin, amiodarone & escitalopram, amiodarone & fluoxetine, ciprofloxacin & sotalol, amiodarone & citalopram. While 38 DDIs indexed by Drugs.com® and Lexicomp®, but not detected by any of the four models. Clinical evidence on DDIs is limited, and not all combinations of QTc-prolonging drugs result in TdP, even when involving high-risk drugs or those with known risk of TdP. This study provides a comprehensive real-world overview of drug-induced TdP, delineateing both clinically significant DDIs and negative DDIs, providing valuable insights into the safety profiles of various drugs and informing the optimization of clinical practice.

The pre BCR complex plays a crucial role in B cell production, and its successful expression marks the B cell differentiation from the pro-B to pre-B. The CD79a and CD79b mutations, encoding Igα and Igβ respectively, have been identified as the cause of autosomal recessive agammaglobulinemia (ARA). Here, we present a case of a patient with a homozygous CD79a mutation, exhibiting recurrent respiratory infections, diarrhea, growth and development delay, unique facial abnormalities and microcephaly, as well as neurological symptoms including tethered spinal cord, sacral canal cyst, and chronic enteroviral E18 meningitis. Complete blockade of the early B cell development in the bone marrow of the patient results in the absence of peripheral circulating mature B cells. Whole exome sequencing revealed a Loss of Heterozygosity (LOH) of approximately 19.20Mb containing CD79a on chromosome 19 in the patient. This is the first case of a homozygous CD79a mutation caused by segmental uniparental diploid (UPD). Another key outcome of this study is the effective management of long-term chronic enteroviral meningitis using a combination of intravenous immunoglobulin (IVIG) and fluoxetine. This approach offers compelling evidence of fluoxetine's utility in treating enteroviral meningitis, particularly in immunocompromised patients.

For more than two decades, regulatory agencies throughout the world released guidelines, rules and laws to stimulate and assist in paediatric drug development. In 2014, the National Health and Family Planning Commission (now known as the National Health Commission, NHC) and five other departments in China jointly issued 'Several Opinions on Safeguarding Medication for Children', after which several policies and regulations were issued to implement the priority review and approval of paediatric medicinal products and support the development of new drugs, including new dosage forms and strengths, for children. A total of 172 special medicinal products for children were approved from 2018 to 2022. Since 2016, the NHC, together with relevant administrative departments, has formulated and issued four paediatric drug lists containing 129 medicinal products to encourage research and development. At present, approximately 25 of these drugs (at exactly the same dosage forms and strengths as on the lists) have been approved for marketing, including antitumour drugs and immunomodulators, nervous system drugs, drugs for mental disorders and drugs for rare diseases. In this review, we analysed the regulations issued for promoting paediatric drug development in China, including the priority review and approval system, technical guidelines, data protection and financial support policies and general profiles of paediatric drug approval, clinical trials and the addition of information for children in the labels of marketed medicinal products. Finally, we discussed the challenges and possible strategies in the research and development of paediatric drugs in China.

BackgroundVoriconazole (VRZ) is involved in a variety of drug‒drug interactions (DDIs), but few studies have reported adverse events (AEs) associated with the DDIs of VRZ. The primary goal of this study was to analyse the potential risk factors for AEs caused by DDIs between VRZ and other drugs via the OpenVigil FDA platform and to provide a reference for preventing VRZ DDIs and monitoring clinically related adverse drug events.MethodsA retrospective pharmacovigilance study was conducted to investigate the AEs related to DDIs between VRZ and four categories of drugs: proton pump inhibitors (PPIs), non-steroidal anti-inflammatory drugs (NSAIDs), immunosuppressants, and other antibacterial drugs. AE information for the target drugs from the first quarter of 2004 to the third quarter of 2022 was downloaded from the OpenVigil FDA data platform. Four frequency statistical models—the reporting ratio method, Ω shrinkage measure model, combination risk ratio model, and the chi-square statistics model—were used to analyse the AEs related to DDIs and evaluate the correlation and influence of sex and age between the drug(s) and the target AEs detected.ResultsA total of 38 drugs were included, with 262 AEs detected by at least one of the four models and 48 AEs detected by all four models. Some 77 detected AEs were significantly positively correlated with DDIs and were related to higher reporting rates of AEs than when used alone. Graft-versus-host disease was the AE that had the strongest correlation with the drug interaction between VRZ and immunosuppressants (tacrolimus, mycophenolate mofetil, cyclophosphamide, and cyclosporine), and multiple organ dysfunction syndrome was correlated with VRZ in combination with other antibacterial drugs (linezolid, meropenem, cefepime, and vancomycin). Significant sex and age differences in the target AEs were detected for five and nine target drugs, respectively. For VRZ in combination with linezolid, aggravated conditions and respiratory failure should be given more attention in male patients, and mycophenolate mofetil and respiratory failure in female patients. When conditions are aggravated, febrile neutropenia and septic shock should be of particular concern in patients over 18 years of age who use VRZ in combination with ceftazidime, ciprofloxacin, or cytarabine. In patients aged under 18, septic shock should be considered when VRZ is used in combination with meropenem and dexamethasone.ConclusionAEs related to DDIs should receive more attention when VRZ is used in combination with PPIs (renal impairment), NSAIDs (constipation and renal failure), immunosuppressants (graft versus host disease, septic shock) and other antibacterial drugs (multiple organ dysfunction syndrome, febrile neutropenia, and respiratory failure). Considering the influence of sex and age differences in VRZ DDIs, these factors need to be considered when assessing the risk of AEs in patients receiving VRZ and other drugs.

Background: The equivalence of generic drugs to their brand-name counterparts is a controversial issue. Current literature indicates disparities between the generic nebivolol (GN) and the brand nebivolol (BN).Aim: The study is designed to investigate the safety difference between GN and BN and provide reference information for clinical practice.Methods: We reviewed adverse event (AE) reports that recorded nebivolol as the primary suspect drug in the FDA Adverse Event Reporting System (FAERS) database from 2004 to 2022, conducted a disproportional analysis to detect signals for the GN and BN respectively, and compared the AE heterogeneity between them using the Breslow-Day test.Results: A total of 2613 AE reports of nebivolol were recorded in the FAERS database from 2004 to 2022, of which 2,200 were classified as BN, 346 as GN, and 67 unclassifiable AE reports were excluded. The signals of 37 AEs distributed in cardiac, gastrointestinal, psychiatric, and nervous systems were detected in disproportional analysis. 33 out of 37 AEs were positive signals, with 21 not previously listed on the drug label, indicating an unrecognized risk with nebivolol. In the heterogeneity analysis of AE signals between GN and BN, the GN generally showed a higher AE signal value than BN, especially 15 AEs distributed in the cardiac, neurological, and psychiatric systems that showed statistically significantly higher risk by taking GN.Conclusion: Our study shows some previously overlooked adverse effects of nebivolol. It suggests that the risk of GN’s adverse effects may be higher than those in BN, which deserves further attention and investigation by healthcare professionals, regulators, and others.

AbstractDetailed data on safety associated with drug–drug interactions (DDIs) between Linezolid (LZD) and other antibiotics are limited. The aim of this study was to investigate the safety signals related to these DDIs and to provide a reference for clinically related adverse drug event monitoring. Adverse event (AE) information from 1 January 2004 to 16 June 2022 of the target antibiotics including LZD using alone or in combination with LZD was extracted from the OpenVigil FDA data platform for safety signal analysis. The combined risk ratio model, reporting ratio method, Ω shrinkage measure model, and chi‐square statistics model were used to analyze the safety signals related to DDIs. Meanwhile, we evaluated the correlation and the influence of sex and age between the drug(s) and the target AE detected. There were 18991 AEs related to LZD. There were 2293, 1726, 4449, 821, 2431, 1053, and 463 AE reports when LZD was combined with amikacin, voriconazole, meropenem, clarithromycin, levofloxacin, piperacillin‐tazobactam, and azithromycin, respectively. Except for azithromycin, there were positive safety signals related to DDIs between LZD and these antibiotics. These DDIs might influence the incidence of 13, 16, 7, 7, 6, and 15 types of AEs, respectively, and is associated with higher reporting rates of AEs compared with use alone. Moreover, sex and age might influence the occurrence of AEs. We found that the combinations of LZD and other antibiotics are related to multiple AEs, such as hepatotoxicity, drug resistance and electrocardiogram QT prolonged, but further research is still required to investigate their underlying mechanisms. This study can provide a new reference for the safety monitoring of LZD combined with other antibiotics in clinical practice.

Abstract Background Randomized controlled trials (RCTs) are usually the basis of evidence-based medicine, but whether the results of RCTs can be correctly translated into clinical practice depends on the quality of the literature reported. In this study, we evaluated the general characteristics and quality of paediatric RCTs published in China to provide evidence for the reporting of paediatric RCTs and their application in clinical practice. Methods We conducted a cross-sectional observational study of paediatric RCTs published in paediatric journals in China between January 1, 1999, and December 30, 2022. All RCTs that included children (younger than 18 years old) were retrieved, and the general characteristics of the RCTs were extracted and analysed. The quality of the RCTs was assessed by the Cochrane quality assessment protocol. Results After screening 20 available paediatric journals, 3545 RCTs were included for analysis. The average annual growth rate of the number of published paediatric RCTs from 1999 to 2022 was 7.8% (P = 0.005, R2 = 0.311). Most of the studies were carried out in East China [1148 (32.4%]; the centres of the RCTs were mainly single-centre [3453 (97.4%], and the interventions were mainly medication [2442 (68.9%)]. Comparing RCTs published in 2017–2022 with RCTs published in 1999–2004, the quality of RCTs significantly improved in terms of random sequence generation, allocation concealment, blinding participants and personnel, incomplete outcome data and selective outcome reporting. RCTs published in multiple centres from the Chinese Science Citation Database were identified, and the approval of the ethics committee was of better quality for all the analysed risk of bias items. Conclusion The number and quality of paediatric RCTs reported in China have improved in recent years, but the overall quality was relatively low. Special attention should be given to allocation concealment and blinding outcome assessment, and dropouts, adverse effects and sample size calculations should be reported. Promoting government policies, strengthening the standardization of journal publishing and advancing the registration of clinical trials are feasible measures.

目的 挖掘和分析阿片类药物不良事件(ADE)性别差异的信号,为临床实施个体化用药提供参考.方法 调取美国食品药品管理局不良事件报告系统(FAERS)数据库2004年1月1日—2020年9月30日接收的吗啡和芬太尼ADE报告,采用报告比值比(ROR)数据挖掘方法进行信号挖掘,重点分析阿片类药物性别差异的信号强度.结果 纳入分析的吗啡ADE报告女性和男性分别为7968,7570份;芬太尼女性和男性报告为37505,26866份.经ROR挖掘,男性更易出现药物依赖性、戒断综合征、呼吸抑制、药物过量及滥用等,而女性更易出现药物不耐受、恶心、呕吐、抑郁、皮疹、瘙痒、关节痛等.结论 阿片类药物不良事件信号存在性别差异,临床实践中应充分利用以探索机会性治疗可能.

Anti-seizure medications (ASMs) are the main therapy for epilepsy.There are many kinds of ASMs with complex mechanism of action, so it is difficult for pharmacists to examine prescriptions.This paper put forward some suggestions on the indications, dosage forms/routes of administration, appropriateness of usage and dosage, combined medication and drug interaction, long-term prescription review, individual differences in pathophysiology of children, and drug selection when complicated with common epilepsy, for the reference of doctors and pharmacists.

BACKGROUND:High-dose methotrexate (HD-MTX) is a potent chemotherapeutic agent used to treat pediatric acute lymphoblastic leukemia (ALL). HD-MTX is known for cause delayed elimination and drug-related adverse events. Therefore, close monitoring of delayed MTX elimination in ALL patients is essential.OBJECTIVE:This study aimed to identify the risk factors associated with delayed MTX elimination and to develop a predictive tool for its occurrence.METHODS:Patients who received MTX chemotherapy during hospitalization were selected for inclusion in our study. Univariate and least absolute shrinkage and selection operator (LASSO) methods were used to screen for relevant features. Then four machine learning (ML) algorithms were used to construct prediction model in different sampling method. Furthermore, the performance of the model was evaluated using several indicators. Finally, the optimal model was deployed on a web page to create a visual prediction tool.RESULTS:The study included 329 patients with delayed MTX elimination and 1400 patients without delayed MTX elimination who met the inclusion criteria. Univariate and LASSO regression analysis identified eleven predictors, including age, weight, creatinine, uric acid, total bilirubin, albumin, white blood cell count, hemoglobin, prothrombin time, immunological classification, and co-medication with omeprazole. The XGBoost algorithm with SMOTE exhibited AUROC of 0.897, AUPR of 0.729, sensitivity of 0.808, specificity of 0.847, outperforming the other models. And had AUROC of 0.788 in external validation.CONCLUSION:The XGBoost algorithm provides superior performance in predicting the delayed elimination of MTX. We have created a prediction tool to assist medical professionals in predicting MTX metabolic delay.

H 1-antihistamines are widely used in the treatment of various allergic diseases, but there are still many challenges in the safe and rational use of H 1-antihistamines in pediatrics, and there is a lack of guidance on the prescription review of H 1-antihistamines for children.In this paper, suggestions are put forward from the indications, dosage, route of administration, pathophysiological characteristics of children with individual difference and drug interactions, so as to provide reference for clinicians and pharmacists.

目的:挖掘和评价奥司他韦上市后的安全信号,为临床合理用药提供依据.方法:检索美国食品药品监督管理局不良事件报告系统(FAERS)数据库中 2004 年 1 月至 2022 年 9 月收录的以奥司他韦为首要怀疑对象的药品不良事件(ADE)报告,采用报告比值比法(ROR)和贝叶斯置信区间递进神经网络法(BCPNN)检测ADE信号,重点分析胃肠系统、神经系统、精神病类、肝胆系统等 11 个系统器官分类(SOC)所涉及的安全信号.结果:收集到以奥司他韦为首要怀疑药物的ADE报告 794 份(794 例患者),其中女性患者所占比例(394 例,占 49.62%)高于男性患者(297 例,占 37.41%);年龄<18 岁的患者居多(489 例,占61.59%);严重不良事件(SAE)共 232 例(占 29.22%).检出的ADE信号共涉及 21 个SOC.对重点SOC进行分析发现,神经系统相关ADE中,信号主要集中在惊厥发作(ROR=2.77,IC=1.43)、意识丧失(ROR=2.01,IC=0.99)、言语障碍(ROR=2.67,IC= 1.37);精神系统主要表现为异常行为(ROR=30.34,IC=4.74)、幻觉(ROR=20.69,IC=4.22)、失眠(ROR=2.08,IC=1.03)等;奥司他韦侵犯胃肠道主要表现为上腹痛(ROR=2.05,IC=1.01)、呕吐(ROR=6.19,IC=2.48)、出血性小肠结肠炎(ROR=46.35,IC=4.28)等.其他系统高风险信号主要为爆发性肝炎(ROR=10.88,IC=2.70)、急性心力衰竭(ROR=5.89,IC=2.17)、心肌炎(ROR=4.49,IC=1.93)、弥散性血管内凝血(ROR=2.60,IC=1.25)、史-约综合征(ROR=3.44,IC=1.70)、中毒性表皮坏死松解症(ROR=2.06,IC=0.94)等.结论:在患者使用奥司他韦的过程中,除密切关注惊厥发作、异常行为、幻觉、失眠、呕吐、上腹痛等常见ADE外,还应关注爆发性肝炎、急性心力衰竭、弥散性血管内凝血等SAE.

Objectives: There have been limited studies concerning the safety and efficacy of linezolid (LZD) in children. This study aimed to evaluate the association between LZD exposure and clinical safety and efficacy in Chinese pediatric patients.Methods: This retrospective cross-sectional study included patients ≤18 years of age who received ≥3 days of LZD treatment between 31 January 2015, and 31 December 2020. Demographic characteristics, medication information, laboratory test information, and bacterial culture results were collected from the Hospital Information System (HIS). Exposure was defined as AUC24 and calculated by the non-linear mixed-effects modeling program (NONMEM), version 7.2, based on two validated population pharmacokinetic models. Binary logistic regression analyses were performed to analyze the associations between AUC24 and laboratory adverse events, and receiver operating characteristic curves were used to calculate the cut-off values. Efficacy was evaluated by bacterial clearance.Results: A total of 413 paediatric patients were included, with an LZD median (interquartile range) dose, duration, clearance and AUC24 of 30.0 (28.1-31.6) mg/kg/day, 8 (4‒15) days,1.31 (1.29-1.32) L/h and 81.1 (60.6-108.7) mg/L·h, respectively. Adverse events associated with TBil, AST, ALT, PLT, hemoglobin, WBC, and neutrophil count increased during and after LZD treatment when compared with before medication (p < 0.05), and the most common adverse events were thrombocytopaenia (71/399, 17.8%) and low hemoglobin (61/401, 15.2%) during the LZD treatment. Patients with AUC24 higher than 120.69 mg/L h might be associated with low hemoglobin 1–7 days after the end of the LZD treatment, and those with an AUC24 higher than 92.88 mg/L∙h might be associated with thrombocytopaenia 8–15 days after the end of the LZD treatment. A total of 136 patients underwent bacterial culture both before and after LZD treatment, and the infection was cleared in 92.6% (126/136) of the patients, of whom 69.8% (88/126) had AUC24/MIC values greater than 80.Conclusion: Hematological indicators should be carefully monitored during LZD treatment, especially thrombocytopaenia and low hemoglobin, and a continuous period of monitoring after LZD withdrawal is also necessary. Since the AUC24 cut-off values for laboratory adverse events were relatively low, a trade-off is necessary between the level of drug exposure required for treatment and safety, and the exposure target (AUC24/MIC) in pediatric patients should be further studied, especially for patients with complications and concomitant medications.

目的 对氨氯地平和乐卡地平药物不良事件(ADE)进行信号检测并评价.方法 检索美国FDA不良事件报告系统(FAERS)数据库2004年1月1日至2021年9月30日收录的"氨氯地平"和"乐卡地平"所有ADE报告,采用报告比值比法和贝叶斯可信区间递进神经网络法检测ADE信号,筛选出重点系统内的中强信号及强信号进行分析.结果 从FAERS数据库中提取得到以氨氯地平、乐卡地平为怀疑药物的ADE报告各249657、10558份,检出氨氯地平、乐卡地平安全信号分别为62、58个.两药同时检出外周水肿、低血压、直立性低血压、低血容量性休克等中强信号,以上均为两药常见的不良反应.较为特殊的ADE如下:呼吸系统、胸及纵隔疾病系统中,氨氯地平检出非心源性肺水肿强信号,乐卡地平检出静息时呼吸困难强信号;胃肠系统中,氨氯地平检出齿龈肥大强信号;皮肤及皮下组织类疾病系统中,两药均检出"血管炎相关"的中强信号,氨氯地平检出线状IgA病中强信号,乐卡地平检出大疱性皮炎中强信号;肾脏及泌尿系统疾病系统中,两药均检出急性肾损伤安全信号(氨氯地平检出中强信号,乐卡地平检出强信号);精神病类系统中,氨氯地平检出自杀既遂中强信号.低血压和急性肾损伤在两药报告数中均排在前2位.信息成分(IC)时间扫描图谱结果显示,2004-2021年,氨氯地平的非心源性肺水肿、自杀既遂信号IC值分别从0.76、-0.49增至4.48、1.95,置信区间分别从(-0.44,1.97)、(-1.01,0.03)缩窄至(4.24,4.72)、(1.90,2.01),提示信号稳定.结论 临床使用氨氯地平和乐卡地平时,应警惕外周水肿、低血压、心律失常、肺水肿、牙龈增生、皮肤相关ADE、急性肾损伤及抑郁、自杀等风险.

目的 挖掘并评价β受体阻滞剂药物相关急性肾衰竭(ARF)信号.方法 采用报告比值比(ROR)法和贝叶斯置信区间递进神经网络(BCPNN)法,并从标准国际医学用语词典(MedDRA)分析查询(SMQ)术语集、首选术语(PT)级术语2个维度对美国FDA不良事件报告系统(FAERS)中4种β受体阻滞剂(美托洛尔、比索洛尔、阿替洛尔、奈必洛尔)药物相关ARF进行信号检测与分析,当2种方法同时检出阳性信号时,提示检出可疑信号.结果 以SMQ术语集"acute renal failure"狭义范围检索到4种β受体阻滞剂致ARF报告共14328份,其中男性(6964份)多于女性(6206份),患者年龄主要集中在中老年(≥45岁),严重不良事件占77.23％.基于SMQ术语集的信号检索结果显示,美托洛尔、比索洛尔、阿替洛尔、奈必洛尔使用ROR法检出的ROR值及95％置信区间分别为:2.58(2.51,2.65)、5.30(5.14,5.47)、2.80(2.69,2.91)、3.28(3.04,3.53);BCPNN法检出的信号成分(IC)及IC下限分别为:1.29(1.25)、2.26(2.22)、1.42(1.36)、1.64(1.53),提示这4种β受体阻滞剂药物相关ARF均检出可疑信号.基于PT级术语的信号检测结果显示,ROR法检出37个阳性信号,BCPNN法检出38个阳性信号,2种方法同时检出36个可疑信号.具体到各药物,美托洛尔均检出12个可疑信号,比索洛尔和阿替洛尔均检出9个可疑信号,奈必洛尔均检出6个可疑信号,且4种药物检出的信号数量和类型都存在一定差异.结论 4种β受体阻滞剂均可能存在ARF发生风险.与美托洛尔、阿替洛尔相比,比索洛尔、奈必洛尔与ARF的统计学相关性较强,提示医务人员在临床使用过程中应注意观察该类药物可能的肾脏相关药物不良反应.