Performance of the EDACS-ADP incorporating high-sensitivity troponin assay:Do components of major adverse cardiac events matter?

BACKGROUND:The accelerated diagnostic protocol(ADP)using the Emergency Department Assessment of Chest pain Score(EDACS-ADP),a tool to identify patients at low risk of a major adverse cardiac event(MACE)among patients presenting with chest pain to the emergency department,was developed using a contemporary troponin assay.This study was performed to validate and compare the performance of the EDACS-ADP incorporating high-sensitivity cardiac troponin I between patients who had a 30-day MACE with and without unstable angina(MACE I and II,respectively).METHODS:A single-center prospective observational study of adult patients presenting with chest pain suggestive of acute coronary syndrome was performed.The performance of EDACS-ADP in predicting MACE was assessed by calculating the sensitivity and negative predictive value.RESULTS:Of the 1,304 patients prospectively enrolled,399(30.6%;95%confidence interval[95%CI]:27.7%–33.8%)were considered low-risk using the EDACS-ADP.Among them,the rates of MACE I and II were 1.3%(5/399)and 1.0%(4/399),respectively.The EDACS-ADP showed sensitivities and negative predictive values of 98.8%(95%CI:97.2%–99.6%)and 98.7%(95%CI:97.0%–99.5%)for MACE I and 98.7%(95%CI:96.8%–99.7%)and 99.0%(95%CI:97.4%–99.6%)for MACE II,respectively.CONCLUSION:EDACS-ADP could help identify patients as safe for early discharge.However,when unstable angina was added to the outcome,the 30-day MACE rate among the designated lowrisk patients remained above the level acceptable for early discharge without further evaluation.

Impact of body mass index on adverse kidney events in diabetes mellitus patients: A systematic-review and meta-analysis

BACKGROUND The incidence of chronic kidney disease among patients with diabetes mellitus(DM)remains a global concern.Long-term obesity is known to possibly influence the development of type 2 diabetes mellitus.However,no previous meta-analysis has assessed the effects of body mass index(BMI)on adverse kidney events in patients with DM.AIM To determine the impact of BMI on adverse kidney events in patients with DM.METHODS A systematic literature search was performed on the PubMed,ISI Web of Science,Scopus,Ovid,Google Scholar,EMBASE,and BMJ databases.We included trials with the following characteristics:(1)Type of study:Prospective,retrospective,randomized,and non-randomized in design;(2)participants:Restricted to patients with DM aged≥18 years;(3)intervention:No intervention;and(4)kidney adverse events:Onset of diabetic kidney disease[estimated glomerular filtration rate(eGFR)of<60 mL/min/1.73 m2 and/or microalbuminuria value of≥30 mg/g Cr],serum creatinine increase of more than double the baseline or end-stage renal disease(eGFR<15 mL/min/1.73 m2 or dialysis),or death.RESULTS Overall,11 studies involving 801 patients with DM were included.High BMI(≥25 kg/m2)was significantly associated with higher blood pressure(BP)[systolic BP by 0.20,95%confidence interval(CI):0.15–0.25,P<0.00001;diastolic BP by 0.21 mmHg,95%CI:0.04–0.37,P=0.010],serum albumin,triglycerides[standard mean difference(SMD)=0.35,95%CI:0.29–0.41,P<0.00001],low-density lipoprotein(SMD=0.12,95%CI:0.04–0.20,P=0.030),and lower high-density lipoprotein(SMD=–0.36,95%CI:–0.51 to–0.21,P<0.00001)in patients with DM compared with those with low BMIs(<25 kg/m2).Our analysis showed that high BMI was associated with a higher risk ratio of adverse kidney events than low BMI(RR:1.22,95%CI:1.01–1.43,P=0.036).CONCLUSION The present analysis suggested that high BMI was a risk factor for adverse kidney events in patients with DM.

Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio:Markers predicting immune-checkpoint inhibitor efficacy and immune-related adverse events

We conducted a comprehensive review of existing prediction models pertaining to the efficacy of immune-checkpoint inhibitor(ICI)and the occurrence of immune-related adverse events(irAEs).The predictive potential of neutrophil-to-lymphocyte ratio(NLR)and platelet-to-lymphocyte ratio(PLR)in determining ICI effectiveness has been extensively investigated,while limited research has been conducted on predicting irAEs.Furthermore,the combined model incor-porating NLR and PLR,either with each other or in conjunction with additional markers such as carcinoembryonic antigen,exhibits superior predictive capabilities compared to individual markers alone.NLR and PLR are promising markers for clinical applications.Forthcoming models ought to incorporate established efficacious models and newly identified ones,thereby constituting a multifactor composite model.Furthermore,efforts should be made to explore effective clinical application approaches that enhance the predictive accuracy and efficiency.

Prediabetes: An overlooked risk factor for major adverse cardiac and cerebrovascular events in atrial fibrillation patients

BACKGROUND Prediabetes is a well-established risk factor for major adverse cardiac and cerebrovascular events(MACCE).However,the relationship between prediabetes and MACCE in atrial fibrillation(AF)patients has not been extensively studied.Therefore,this study aimed to establish a link between prediabetes and MACCE in AF patients.AIM To investigate a link between prediabetes and MACCE in AF patients.METHODS We used the National Inpatient Sample(2019)and relevant ICD-10 CM codes to identify hospitalizations with AF and categorized them into groups with and without prediabetes,excluding diabetics.The primary outcome was MACCE(all-cause inpatient mortality,cardiac arrest including ventricular fibrillation,and stroke)in AF-related hospitalizations.RESULTS Of the 2965875 AF-related hospitalizations for MACCE,47505(1.6%)were among patients with prediabetes.The prediabetes cohort was relatively younger(median 75 vs 78 years),and often consisted of males(56.3%vs 51.4%),blacks(9.8%vs 7.9%),Hispanics(7.3%vs 4.3%),and Asians(4.7%vs 1.6%)than the non-prediabetic cohort(P<0.001).The prediabetes group had significantly higher rates of hypertension,hyperlipidemia,smoking,obesity,drug abuse,prior myocardial infarction,peripheral vascular disease,and hyperthyroidism(all P<0.05).The prediabetes cohort was often discharged routinely(51.1%vs 41.1%),but more frequently required home health care(23.6%vs 21.0%)and had higher costs.After adjusting for baseline characteristics or comorbidities,the prediabetes cohort with AF admissions showed a higher rate and significantly higher odds of MACCE compared to the non-prediabetic cohort[18.6%vs 14.7%,odds ratio(OR)1.34,95%confidence interval 1.26-1.42,P<0.001].On subgroup analyses,males had a stronger association(aOR 1.43)compared to females(aOR 1.22),whereas on the race-wise comparison,Hispanics(aOR 1.43)and Asians(aOR 1.36)had a stronger association with MACCE with prediabetes vs whites(aOR 1.33)and blacks(aOR 1.21).CONCLUSION This population-based study found a significant association between prediabetes and MACCE in AF patients.Therefore,there is a need for further research to actively screen and manage prediabetes in AF to prevent MACCE.

Predicting major adverse cardiovascular events after orthotopic liver transplantation using a supervised machine learning model:A cohort study

BACKGROUND Liver transplant(LT)patients have become older and sicker.The rate of post-LT major adverse cardiovascular events(MACE)has increased,and this in turn raises 30-d post-LT mortality.Noninvasive cardiac stress testing loses accuracy when applied to pre-LT cirrhotic patients.AIM To assess the feasibility and accuracy of a machine learning model used to predict post-LT MACE in a regional cohort.METHODS This retrospective cohort study involved 575 LT patients from a Southern Brazilian academic center.We developed a predictive model for post-LT MACE(defined as a composite outcome of stroke,new-onset heart failure,severe arrhythmia,and myocardial infarction)using the extreme gradient boosting(XGBoost)machine learning model.We addressed missing data(below 20%)for relevant variables using the k-nearest neighbor imputation method,calculating the mean from the ten nearest neighbors for each case.The modeling dataset included 83 features,encompassing patient and laboratory data,cirrhosis complications,and pre-LT cardiac assessments.Model performance was assessed using the area under the receiver operating characteristic curve(AUROC).We also employed Shapley additive explanations(SHAP)to interpret feature impacts.The dataset was split into training(75%)and testing(25%)sets.Calibration was evaluated using the Brier score.We followed Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines for reporting.Scikit-learn and SHAP in Python 3 were used for all analyses.The supplementary material includes code for model development and a user-friendly online MACE prediction calculator.RESULTS Of the 537 included patients,23(4.46%)developed in-hospital MACE,with a mean age at transplantation of 52.9 years.The majority,66.1%,were male.The XGBoost model achieved an impressive AUROC of 0.89 during the training stage.This model exhibited accuracy,precision,recall,and F1-score values of 0.84,0.85,0.80,and 0.79,respectively.Calibration,as assessed by the Brier score,indicated excellent model calibration with a score of 0.07.Furthermore,SHAP values highlighted the significance of certain variables in predicting postoperative MACE,with negative noninvasive cardiac stress testing,use of nonselective beta-blockers,direct bilirubin levels,blood type O,and dynamic alterations on myocardial perfusion scintigraphy being the most influential factors at the cohort-wide level.These results highlight the predictive capability of our XGBoost model in assessing the risk of post-LT MACE,making it a valuable tool for clinical practice.CONCLUSION Our study successfully assessed the feasibility and accuracy of the XGBoost machine learning model in predicting post-LT MACE,using both cardiovascular and hepatic variables.The model demonstrated impressive performance,aligning with literature findings,and exhibited excellent calibration.Notably,our cautious approach to prevent overfitting and data leakage suggests the stability of results when applied to prospective data,reinforcing the model’s value as a reliable tool for predicting post-LT MACE in clinical practice.

Adverse Events following AstraZeneca COVID-19 Vaccination: A Case Study in Abidjan, Côte d’Ivoire

Introduction: Pharmaceutical companies have boosted vaccine production following the global COVID-19 pandemic. In Côte d’Ivoire, the first vaccination campaign with the AstraZeneca vaccine began on March 1, 2021, as part of the Covax program. Despite the positive benefit/risk balance, the adverse effects of vaccination should not be minimized. Objective: To identify adverse events of AstraZeneca’s COVID-19 vaccination for better management. Materials and Methods: This is a case of a 57-year-old obese (BMI = 39 kg/m2) female health care worker who experienced adverse events in March 2021 after the second dose of AstraZeneca vaccine administered 4 weeks apart. These were subject to mandatory case reporting. Results: Major post-vaccination events occurred in a noisy systemic picture with parameters showing significant disturbances. Biological surveillance remains costly and makes the accountability of the vaccine complex. Conclusion: Vaccination remains the ultimate weapon in the fight against endemic diseases but should not overshadow the reporting of adverse events.

基于FAERS数据库的白消安不良事件信号挖掘与分析

目的 利用美国食品药品管理局不良事件报告系统(FAERS)数据库对白消安的药品不良事件(ADE)进行研究,挖掘潜在的ADE信号,为临床安全用药提供参考。方法 检索FAERS数据库中2004年第1季度至2023年第1季度的数据,通过数据清洗、目标药物名称标准化,获得以白消安为首要怀疑药物的ADE记录。采用报告比值比法、比例报告比值法和综合标准法挖掘白消安ADE信号,并利用信息成分法进行信号强弱判断。以《国际医学用语词典》对ADE进行系统器官分类(SOC),并按照ADE发生频次和信号强度分别排序。结果 共获得20 326份以白消安为首要怀疑药物的ADE报告,涉及患者5 615例,男性患者比例高于女性(40.71%vs.30.74%);年龄小于18岁占31.56%;上报人群主要为医师(33.71%)、其他健康专业人员(24.35%)以及药师(23.86%);上报国家主要为美国(29.69%)、日本(15.78%)、法国(11.79%)。共挖掘出白消安相关ADE信号556个,其中117个ADE信号未被药品说明书收载。556个ADE信号中,发生频次前五位ADE分别为产品用于未经批准的适应证、肝小静脉闭塞症、黏膜炎症、巨细胞病毒感染和移植物抗宿主病;信号强度排名前五位ADE分别为肝小静脉闭塞症、急性移植物抗宿主病、静脉闭塞性疾病、移植物抗宿主病以及慢性移植物抗宿主病。挖掘的ADE信号共累及23个SOC,数量排名前三的SOC分别为感染及侵染类疾病,各类检查,良性、恶性及性质不明的肿瘤(包括囊状和息肉状)。结论 白消安临床应用中,应警惕肝小静脉闭塞症、感染、移植物抗宿主病、神经相关毒性和血栓性微血管病等易造成严重后果的ADE,临床药师协助医师做好ADE的预防方案,提高白消安的使用安全性。

基于FAERS的儿童奥司他韦不良事件信号挖掘与分析

目的 为临床安全使用奥司他韦提供参考。方法 检索美国食品和药物管理局不良事件报告系统(FAERS)数据库中2004年第1季度至2023年第1季度以奥司他韦为首要怀疑药物、发生于0~17岁患儿的药品不良事件(ADE)报告,采用报告比值比(ROR)法、比例报告比值比(PRR)法进行信号挖掘,采用《国际医学用语词典》中的首选语(PT)及系统器官分类(SOC)进行编码和归类。结果 共挖掘到奥司他韦相关ADE报告3 100份,检测到阳性信号76个,主要集中在精神病类(34个)、各类神经系统疾病(13个)、胃肠系统疾病(7个)、全身性疾病及给药部位各种反应(6个)、免疫系统疾病(3个)等12个SOC。发生频次排前20位的ADE有幻觉(455次)、异常行为(428次)、呕吐(410次)、谵妄(120次)、意识模糊状态(111次)等,信号强度排前20位的ADE仍以精神病类、各类神经系统疾病、胃肠系统疾病为主。发生频次和信号强度均排前20位的ADE有尖叫、恐惧、睡惊症,药品说明书中均未提及。结论 患儿临床应用奥司他韦时,应关注精神疾病、神经系统和胃肠道系统,以及皮肤和眼部的ADE。

关注免疫检查点抑制剂发生irAE后免疫治疗再挑战

免疫检查点抑制剂(immune-checkpoint inhibitors,ICIs)是近年来肿瘤学领域最重要的突破之一,为不同类型的实体瘤治疗提供了新的范式。ICIs通过阻断免疫内在下调因子,如细胞毒性T淋巴细胞抗原4(CTLA-4)和程序性细胞死亡1(PD-1)或其配体程序性细胞死亡配体1(PD-L1),增加抗肿瘤免疫力[1]。然而,由于免疫应答增强和免疫系统失衡,患者可能会发生免疫相关不良事件(immune-related adverse events,irAE)。

基于FAERS数据库的达罗他胺不良反应信号挖掘与分析

目的:挖掘达罗他胺相关的不良反应风险信号,为临床安全用药提供参考。方法:利用报告比值比法(ROR)对美国FDA不良反应报告系统(FAERS)中2019年第三季度至2022年第四季度以达罗他胺为首要怀疑药物的不良反应进行挖掘,检测阈值为报告数≥3且ROR的95%置信区间下限>1的不良反应。结果及结论:共筛选出以达罗他胺为首要怀疑药物的不良反应报告1376份,去除非药品不良反应后为1013份,涉及患者589例,检测出风险信号40个,涉及16个系统器官,主要集中在全身性疾病及给药部位各种反应、胃肠系统疾病、皮肤及皮下组织类疾病、各类检查及各类神经系统疾病。达罗他胺的不良反应最常出现在服药的第1个月。挖掘出药品说明书未提及的信号21个,具体包括横纹肌溶解、谵妄、男性乳腺发育、周围神经病变和水肿等。

基于FAERS数据库的奥马珠单抗不良事件信号挖掘

目的运用数据挖掘的方法检测奥马珠单抗上市后的不良反应信号,为临床安全合理用药提供参考。方法本研究采用报告比值比法(ROR)和贝叶斯判别可信区间递进神经网络法(BCPNN)对美国FDA不良事件报告系统(FAERS)中2004年第1季度至2023年第2季度的奥马珠单抗相关不良事件(ADE)报告进行数据挖掘和信号检测。结果通过数据挖掘和信号检测,涉及奥马珠单抗的ADE报告中提取了186,353份报告,涉及45,383例患者。在这些报告中,女性(65.31%)比例远高于男性(24.97%)。主要报告国家为美国(64.93%)和加拿大(11.96%)。报告者中以消费者(41.35%)和医师(36.97%)为主要群体。研究发现了621个ADE阳性信号,涉及25个系统器官分类(SOC),主要包括呼吸系统、胸部和纵隔疾病(21.29%)以及感染和侵染类疾病(10.91%)。其中,183个信号被评定为高风险信号,其中包括57个新的高风险信号,如血压升高、易醒型失眠和心律失常等。这些发现有助于更全面地了解奥马珠单抗的安全性和潜在风险。结论在奥马珠单抗的临床应用过程中,除了要注意药品说明中提到的已知不良反应外,还需特别警惕潜在的不良药物事件,如血压升高、心率升高、中间易醒型失眠、体位性心动过速综合征等。

基于FAERS的哌拉西林他唑巴坦不良事件信号挖掘与分析

目的挖掘哌拉西林他唑巴坦(TZP)的药品不良事件(ADE)信号,促进临床合理、安全用药。方法采用比例失衡法对美国食品药品管理局不良事件报告系统(FAERS)自建库至2024年3月所有TZP ADE报告进行信号挖掘,分析报告病例的基本情况及不良反应相关信息。结果共提取得到主要怀疑药物涉及ADE报告数为20620513条,TZP为主要怀疑药物涉及ADE报告数为6489条。共挖掘ADE信号543个,涉及25个器官/系统分类(SOC),二次筛选最终检测出ADE信号数43个,其中新的ADE信号17个,ADE信号涉及SOC分类的数量排名前5为分别是皮肤及皮下组织类疾病、全身性疾病及给药部位各种反应、各类检查、感染及侵染类疾病、血液及淋巴系统疾病;ADE信号数排名前5位的首选术语分别为皮疹、发热、急性肾损伤、瘙痒、血小板减少症。青霉素类药物在血液及淋巴系统疾病存在多种不良反应信号,TZP导致血小板减少病例数最多,苯唑西林导致粒细胞缺乏关联强度比例报告比值比最高;TZP导致白细胞减少疗程中位数为11.00 d,累积剂量中位数为148.50 g;该药导致粒细胞缺乏疗程中位数为14.00 d,累积剂量中位数为216.00 g;该药导致血小板减少症疗程中位数为7.00d,累积剂量中位数为87.00 g。结论用药期间需密切关注皮肤及皮下组织类疾病相关不良反应,可能较胃肠道系统疾病更多;临床大剂量或长疗程应用TZP时可导致多个系统发生不良反应,尤其需密切关注血液及淋巴系统疾病相关不良反应,避免发生严重不良反应。

基于FAERS数据库的米诺环素不良事件信号挖掘研究

目的挖掘米诺环素的药品不良事件(ADE)信号,为临床安全用药提供参考。方法联合报告比值比法、比例报告比值法、综合标准法和贝叶斯置信度递进神经网络法,对美国食品药品管理局不良事件报告系统(FAERS)数据库中2004年一季度至2023年四季度上报的米诺环素ADE报告进行数据挖掘,全面分析ADE信号分布、信号强度、性别及年龄差异、死亡病例情况,并基于标准国际医学用语词典(MedDRA)分析查询(SMQ)检索超敏性ADE并进行深入分析。结果共筛选出米诺环素ADE16871例次,阳性ADE信号364个,涉及27个系统/器官分类(SOC),主要为全身性疾病及给药部位各种反应、皮肤及皮下组织类疾病、各类神经系统疾病等,ADE例数排序前列的强信号分别为药物反应伴嗜酸粒细胞增多和全身性症状(DRESS)、结节性多动脉炎和特发性颅内压增高。与其他药物相比,米诺环素致特发性颅内压增高患者中女性构成比较高(P<0.05)。挖掘到8岁以下儿童ADE 29例次,涉及10个SOC。全部ADE中死亡206例,涉及相关ADE 1046例次。超敏性ADE 1565例次,超敏性SMQ层级下获得首选语信号88个,其中DRESS、荨麻疹、抗中性粒细胞胞浆抗体阳性血管炎和面部水肿上报例次高且信号较强。结论米诺环素临床使用中需警惕超敏性及自身免疫性疾病导致严重ADE的风险,女性患者尤其需关注头痛、视力下降等特发性颅内压增高的相关症状,必要时可行眼科监测。应加强米诺环素在8岁以下儿童中的用药监护及ADE收集。

基于FAERS数据库的PD-1/PD-L1抑制剂免疫相关不良事件信号分析

目的基于美国FAERS数据库挖掘帕博利珠单抗、纳武利尤单抗、阿替利珠单抗、度伐利尤单抗的免疫相关不良事件(irAE)信号,为降低临床用药风险和药品上市后安全性监测提供导向和参考。方法提取美国FAERS数据库2012年第四季度至2022年第一季度的不良事件报告,采用报告比值比法、MHRA综合标准法、贝叶斯置信递进神经网络法(BCPNN)展开信号检测,应用标准MedDRA分析查询(Standardized MedDRA Queries,SMQ)在特定“免疫介导/自身免疫性疾病”中广义检索irAEs信号,分析四种PD-1/PD-L1抑制剂导致irAEs的共有特征。结果统计分析结果显示,纳武利尤单抗不良事件报告数最多且逐年增幅最大,不良事件患者中男性群体和老年群体占比较高,且主要临床结局为其他严重的重要医疗事件、住院和死亡。信号检测结果显示,四种PD-1/PD-L1抑制剂共检出23个irAEs信号,包括脑炎、重症肌无力、甲状腺疾病、类天疱疮、结肠炎、肌炎、肝炎、暴发性1型糖尿病等,累及11个系统器官分类(SOC);其中年龄差异性信号较多,主要表现为免疫性血小板减少症、肌炎、心肌炎在老年群体中高发。结论PD-1/PD-L1抑制剂irAEs信号累及SOC范围较广泛,建议临床用药前详细询问患者既往病史,尤其需要关注老年群体的用药风险,加强免疫相关不良事件的早期管理和迅速评估;注重中国用药群体免疫相关不良事件数据的收集和分析,挖掘其不良反应特征,不断完善药品说明书,促进我国临床安全、合理使用PD-1/PD-L1抑制剂。

基于FAERS数据库的替莫唑胺不良事件信号挖掘与分析

目的 挖掘真实世界中替莫唑胺相关的药物不良事件(ADE)信号,为替莫唑胺的临床安全用药提供参考依据。方法 运用美国食品药品管理局不良事件报告系统(FAERS),收集2004年1月1日至2022年12月31日FAERS数据库中替莫唑胺的ADE报告数据,通过报告比值法和贝叶斯可信区间递进神经网络法进行信号挖掘,分析其ADE发生情况。结果 数据库中,以替莫唑胺作为首要怀疑药物的ADE报告共24 725份,共识别出300个ADE信号,共涉及23个系统器官分类,排名前5位的依次是血液及淋巴系统疾病、全身性疾病及给药部位各种反应、各类检查、各类神经系统疾病,以及各类损伤、中毒及操作并发症等;报告数较多的ADE信号有血小板减少症、血小板计数降低、中性粒细胞减少症、全血细胞减少症、惊厥发作和发热性中性粒细胞减少症等。挖掘到42个新的疑似不良反应,这些在说明书中未有记录,如假单胞菌皮肤感染、疱疹性脑膜脑炎、舌下神经性瘫痪、汗孔角化病等。结论 替莫唑胺在真实世界中发生的常见不良反应与说明书大体一致,但也有一些新的疑似不良反应被发现,临床使用时应特别关注这些新的不良反应,并建议对患者的不良反应进行监测,及时采取相应措施。

基于FAERS数据库的替扎尼定不良事件信号挖掘研究

目的 基于美国食品药品管理局不良事件报告系统(FAERS)数据库对替扎尼定不良事件(ADE)进行信号挖掘,探索ADE的发生特点,为临床安全应用替扎尼定提供参考。方法 运用报告比值比法和综合标准法分析FAERS数据库2004年第1季度至2022年第2季度的替扎尼定ADE报告数据。利用《国际医学用语词典》对ADE信号挖掘结果进行汉化及系统归类。结果 获得替扎尼定ADE报告数7 135份,涉及患者1 732例,涉及ADE共1 304种。基于2种ADE信号挖掘方法,在首选语(PT)层级共获得177个信号。药品说明书中未记载的PT信号有32个,包括钾消耗性肾病、心脏呼吸骤停、胎儿生长受限等。1 732例患者中,发生ADE的女性例数是男性的2.37倍(1 057例vs. 446例),年龄在40~64岁的人群占比较大(36.03%),报告人员以消费者占比最大(32.79%),累及的系统/器官主要有各类神经系统疾病、精神病类等。替扎尼定相关ADE的中位发病时间为75 d(四分位间距:28~223 d),但需警惕开始用药1年后仍有ADE发生的可能(13.38%)。结论 临床应用替扎尼定时应充分关注其钾消耗性肾病、自杀既遂等ADE的发生及女性、40~64岁等重点人群。

Knowledge,perceptions,and practice towards adverse events following immunization surveillance among vaccination workers in Zhejiang province,China

Objective:To access the level of knowledge,perceptions,and practice towards adverse events following immunization(AEFI)surveillance among vaccination workers in Zhejiang province,China.Methods:This was a cross-sectional survey involving 768 vaccination workers.Data were collected using self-administered questionnaires and analyzed by using SAS 9.3 software.Knowledge,perceptions,and practice on AEFI surveillance were summarized using frequency tables.The mean±SD value was used as the cut-off for defining good(values≥mean)and poor(values<mean)knowledge,perceptions or practice.Binary logistic regression analysis was used to determine sociodemographic variables associated with knowledge,perceptions,and practice towards AEFI.Results:The proportions of good knowledge,perceptions and practice on AEFI surveillance were 78.13%,57.81%and 66.15%,respectively.Having a higher education background,longer years of experience,previous training on AEFI and≥30 years of age were factors associated with good knowledge,perceptions and practice on AEFI surveillance among vaccination workers.Conclusions:Over half of the respondents had good knowledge,perceptions and practice on AEFI surveillance work.Interventions on improving the vaccination workers’knowledge,perceptions and practice on AEFI surveillance should be considered in order to develop a more effective surveillance system.

儿童应用左氧氟沙星不良反应信号挖掘与分析:基于FAERS数据库的真实世界研究

目的利用FAERS数据库检索儿童使用左氧氟沙星不良事件报告情况,并进行数据挖掘和分析,为临床安全用药提供参考。方法通过OpenVigil 2.1平台检索2004年1月1日至2023年6月30日儿童使用左氧氟沙星不良事件报告数据,基于报告比值比法(ROR),对相关数据进行分析。结果共检索到儿童应用左氧氟沙星不良事件报告484例,发现94个阳性风险信号。主要累及的系统器官为各种肌肉骨骼及结缔组织、胃肠系统、全身性及给药部位,前5位阳性信号为地霉菌感染(ROR=822.87)、肌腱疼痛(ROR=563.71)、溃疡分枝杆菌感染(ROR=352.65)、肌腱断裂(ROR=341.91)、免疫重建炎性综合征相关结核病(ROR=310.84)。说明书中未提及的阳性信号排名前5分别为:溃疡分枝杆菌感染(ROR=352.65)、免疫重建炎性综合征相关结核病(ROR=310.84)、中枢神经系统结核瘤(ROR=102.85)、线状IgA病(ROR=82.68)、颅内压力增高(ROR=32.46)。结论左氧氟沙星用于儿童除已知的不良事件外,颅内压升高、结核相关疾病等不良反应风险信号强度较高,建议谨慎选择并加强相关安全性监测。

基于FAERS数据库的秋水仙碱相关神经毒性风险分析

目的 评价秋水仙碱相关神经系统不良事件(nAEs)的风险及特征,为临床用药安全提供参考。方法 基于美国食品药品监督管理局(FDA)不良事件报告系统(FAERS),检索2004年1月1日至2022年12月31日的秋水仙碱相关nAEs报告,采用比例失衡法和贝叶斯分析法对nAEs及缺血性、出血性中枢神经系统血管疾病不良事件进行信号挖掘,并分析事件发生时间及患者结局。结果 共提取秋水仙碱相关nAEs 906例,报告例数排名前3位的不良事件分别是头痛(ROR_(025)=1.09,IC_(025)=0.30)、感觉减退(ROR_(025)=1.79,IC_(025)=1.09)、意识丧失(ROR_(025)=1.62,IC_(025)=0.99),在缺血性和出血性中枢神经血管疾病中均不存在信号。秋水仙碱相关nAEs发生时间中位数为30 d,7.42%的患者死亡。结论 秋水仙碱在缺血性和出血性中枢神经血管疾病中未检测到信号,但临床应警惕一些其他罕见神经毒性不良事件,加强监测。

基于FAERS数据库的维泊妥珠单抗不良反应信号挖掘

目的:评价和分析维泊妥珠单抗上市后的药物不良反应(adverse drug reaction,ADR)信号,为临床安全性管理提供参考。方法:通过开放性OpenVigil数据平台,收集2019年6月10日(美国FDA批准上市时间)至2023年3月31日美国FDA不良事件报告系统(FAERS)数据库中维泊妥珠单抗的ADR报告。采用比例失衡法中的报告比值比(ROR)和比例报告比(PRR)进行信号挖掘。为提高阈值,得到信号较强、较常出现的ADR,将信号进行二次筛选。结果:共检索到维泊妥珠单抗相关ADR报告2408份,经过二次筛选得到83个ADR信号。其中,脊柱磁共振成像异常、骨吸收增加、骨质溶解、天门冬氨酸氨基转移酶降低、丙氨酸氨基转移酶降低、低纤维蛋白原血症、肺栓塞等26个ADR信号在药品说明书中未提及。信号数或累积例数较多的系统器官分类包含感染及侵染类疾病(24个信号、632例),各类检查(17个信号、675例),血液及淋巴系统疾病(11个信号、734例),各类神经系统疾病(7个信号、153例),免疫系统疾病(3个信号、95例),全身性疾病及给药部位各种反应(2个信号、145例),代谢及营养类疾病(2个信号、87例)等。结论:除说明书提示的常见ADR外,本研究发现了维泊妥珠单抗新的ADR风险信号。建议临床在关注感染、骨髓抑制、周围神经病、输液相关反应、肝功能异常等已知常见ADR的同时,予以脊柱磁共振成像异常、骨吸收增加等新的风险信号更多关注。