临床药师在莫西沙星致QT间期延长不良事件中的实践

1例59岁女性患者,入院诊断考虑肺部感染,给予莫西沙星联合头孢曲松抗感染治疗,当日心电图检查发现患者QT间期出现延长,考虑莫西沙星所致。临床药师查阅相关文献,明确了QT间期延长的标准,并根据药物致QT间期延长的高危因素评分表,对患者进行评估后,与医生充分沟通,提出停用莫西沙星的建议,医生予以采纳。停用莫西沙星第2天,复查心电图提示患者QTc值恢复正常,治疗19 d后患者病情好转出院。     

莫西沙星致QT间期延长和室性心律失常的分析

目的回顾性分析静脉滴注莫西沙星引发药物不良反应1例,为临床用药的安全性提供参考。方法通过分析静脉输注莫西沙星诱发QT间期延长伴室性心律失常的具体病例,评估不良反应发生的可能因素及用药安全性。结果此次药物不良反应很可能与莫西沙星有关,该患者的危险因素较多,临床用药时应加强用药安全的监督。结论临床使用莫西沙星时,医务人员应关注莫西沙星的安全性问题,在合理用药的基础上密切监测药物的不良反应,加强用药监督,提高用药安全性。     

盐酸莫西沙星注射液与注射用盐酸胺碘酮联用致QT间期延长

1例75岁男性因心脏瓣膜病合并心力衰竭及肺部感染给予盐酸莫西沙星注射液(莫西沙星)400mg静脉滴注、1次/d。第2天心电图示心率校正后QT间期(QTc)从治疗前的455ms延长至490ms。第3天凌晨因心房颤动给予注射用盐酸胺碘酮(胺碘酮)150mg缓慢静脉注射,中午给予胺碘酮300mg以30mg/h持续泵入。第4天下午再次给予胺碘酮300 mg,以30 mg/h速度持续泵入。泵入约20 min患者QTc延长至607ms。第5天未再使用胺碘酮,但患者QTc继续延长,最高达到674ms。第6天停用莫西沙星后其QTc逐渐恢复至正常范围内。考虑患者QT间期延长与莫西沙星和胺碘酮有关。     

那格列奈不能降低IGT患者糖尿病或心血管事件的发生率

西罗多辛（silodosin）,一种选择性d1A肾上腺素受体拮抗剂,为了确定其治疗以及跨治疗的剂量对于QT间期的影响,此项随机双盲安慰剂（阴性对照）及莫西沙星（阳性对照,已知可以延长QT间期）试验对此进行了研究。     

药物心脏安全性评估与全面QT/QTc研究

许多非抗心律失常药物可以导致心电图QT间期延长,甚至引发尖端扭转型室性心动过速.因此在新药上市前,进行的心脏安全性评估,应该包括药物对QT间期影响的特点.全面QT/QTC研究旨在通过测量QT间期,明确药物是否具有延长QT间期的作用,判断其引发恶性心律失常的风险,并为决定药物是否进入下一步研发提供数据支持.     

氟喹诺酮类药物对健康志愿者QT间期的影响

研究已证实与左氧氟沙星和环丙沙星相比 ,莫西沙星对QT间期的影响更大。在这项研究中 ,4 8名健康志愿者 ,单剂量交叉服用莫西沙星 80 0mg ,左氧氟沙星 1 0 0 0mg、环丙沙星 1 5 0 0mg和安慰剂 ,每一治疗期间隔 7d。服药 0～ 2 4h与安慰剂比较 ,QT和QTc间期的增加莫西沙星大于左氧氟沙星或环丙沙星。与服用安慰剂相比 ,QTc(Bazett)间期的平均变化明显增加。已报道服用莫西沙星、左氧氟沙星、环丙沙星、安慰剂健康志愿者中 ,QTc变化大于 30毫秒的分别占72 %～ 81 %、33%～ 38%、34%～ 4 0 %和 1 7%～ 2 6 %。QTc(Bazett)变化大于 6 0毫…     

药物导致的获得性长QT综合征诊断与治疗

药物导致的获得性长QT综合征是由药物引起的可逆性的QT间期延长的综合征,其主要机制是药物通过对IKr的阻断作用,导致动作电位3期快速复极延迟,表现为QT间期延长。在临床上,许多结构上无关的药物,包括抗精神病药物均可以导致QT间期的延长。药物导致的获得性长QT综合征容易导致尖端扭转性室性心动过速（TdP）,临床上可以通过Tp-e和Tp-e/QT比值、巨大T-U波、QRS缓慢上升支和QT间期短期变异可以预测TdP的风险。治疗获得性长QT综合征,最根本的是识别和停用导致QT间期延长的药物并积极的纠正代谢异常,如低钾血症或低镁血症。大多数TdP的发作是短暂的,并可自行终止。然而,长时间发作会导致血流动力学紊乱,需要立即进行电复律。     

1439例药源性心律失常自发报告分析

摘要：目的:了解药源性心律失常的发生规律及特点,为临床安全用药提供参考。方法:采用回顾性研究方法,提取我中心药品不良反应数据库中2008～2019年药源性心律失常的自发报告,剔除信息不全和无效报告后对报告一般情况、患者基本信息、药物类别、给药途径、心律失常类型、ADR治疗和转归等情况进行统计分析。利用Logistic回归分析方法筛选相关风险因素。结果:1 439例药源性心律失常报告中,患者平均年龄为（55.17±21.20）岁,以45～64岁占比最高（35.72%）;共涉及19类、387种药物,排名前5位的药物是右美托咪定（24.15%）、莫西沙星（16.18%）、重组人白介素-11（11.11%）、沙丁胺醇（10.39%）、胺碘酮（7.73%）;心律失常类型多样,以心动过速（56.46%）和心动过缓（19.63%）为主。与非QT/QTc间期延长组相比,年龄>65岁（P=0.007）及患有心脑血管疾病（P=0.016）是QT/QTc间期延长患者的独立危险因素;治疗药物以抗心律失常药和抗过敏药为主。结论:莫西沙星和胺碘酮可导致多种类型的心律失常,重组人白介素-11以诱发心房颤动为主,右美托咪定主要为心动过缓,临床应加强用药监护;老年人和原患心脑血管疾病是药物导致QT/QTc间期延长的高风险因素,临床应予以重点关注;有必要开展重点品种主动监测研究,为临床提供用药参考。     

与氟喹诺酮疗法相关的心律失常

氟喹诺酮类抗生素是一类广泛应用于临床的广谱、高效、低毒性的抗菌化疗药物,普遍具有良好的耐受性.与其他药物一样,这类药物也存在多种不良反应,本文仅对氟喹诺酮疗法所致QT间期(QTc)延长问题进行了综述.相关的临床研究结果和病例报告显示,莫西沙星在所有临床用喹诺酮类药物中引起QTc延长的风险最大,那些具有扭转型室性心动过速(Tdp)潜在危险因素的患者应慎用之.虽然吉米沙星、左氧氟沙星和氧氟沙星引起QTc延长的风险比莫西沙星低,但对具有QTc延长危险因素的患者也应慎用.在临床上广泛使用的氟喹诺酮类抗生素中,环丙沙星引起QTc延长以及诱发Tdp的风险最小.总体而言,氟喹诺酮类诱发Tdp的风险相对较小,临床医师可通过避免开具可引发QTc延长的氟喹诺酮类多药联用处方(尤其是对高危患者)使这种风险降至最低.     

全面QT研究的临床试验设计

药物导致的心电图QT/QTc间期延长,虽然发生率不高,但潜在危险性大,严重的可诱发室性心律失常甚至猝死。2005年5月,人用药品注册技术要求国际协调会正式颁布了《非抗心律失常药物潜在导致QT/QTc间期延长和心律失常的临床评价指南》(E14)。本文根据该指南及从大量已完成的研究中总结的经验讨论全面QT研究的临床试验设计要点,以期对今后中国的相关研究提供有益的指导。     

Early QT assessment – how can our confidence in the data be improved?

Exposure–response (ER) analysis has emerged as an important tool to interpret QT data from thorough QT (TQT) studies and allows the prediction of effects in the targeted patient population. Recently, ER analysis has also been applied to data from early clinical pharmacology studies, such as single and multiple ascending dose studies, in which high plasma concentrations are often achieved. In line with this, there is an on-going discussion between sponsors, academicians and regulators on whether ‘early QT assessment’ can provide sufficiently high confidence in assessment of QT prolongation to replace the TQT study. In this article, we discuss how QT assessment can be applied to early clinical studies (‘early QT assessment’) and what we believe is needed to achieve the same high confidence in the data as we currently obtain from data from the TQT study. The power to exclude a QT_c effect exceeding 10 ms in small sample sizes using ER analysis will be discussed and compared with time-matched analysis, as described in the ICH E14 guidance. Two examples of early QT assessment are shared; one negative and one positive, and the challenge in terms of demonstrating assay sensitivity in the absence of a pharmacological positive control will be discussed. Finally, we describe a recent research proposal, which may generate data to support the replacement of the TQT study with data from QT assessment in early phase 1 studies.     

Update on the evaluation of a new drug for effects on cardiac repolarization in humans: issues in early drug development

Following reports of death from cardiac arrhythmias with drugs like terfenadine and cisapride, the International Conference for Harmonization formulated a guidance (E14) document. This specifies that all new drugs must undergo a ‘thorough QT/QTc’ (TQT) study to detect drug-induced QT prolongation, a surrogate marker of ventricular tachycardia, especially torsades de pointes (TdPs). With better understanding of data from several completed TQT studies, regulatory requirements have undergone some changes since the E14 guidance was implemented in October 2005. This article reviews the implications of the E14 guidance and the changes in its interpretation including choice of baseline QT, demonstration of assay sensitivity, statistical analysis of the effect of new drug and positive control, and PK-PD modelling. Some issues like use of automated QT measurements remain unresolved. Pharmaceutical companies too are modifying Phase 1 studies to detect QTc liability early in order to save time and resources. After the E14 guidance, development of several drugs that prolong QTc by >5 ms is being abandoned by sponsors. However, all drugs that prolong the QT interval do not increase risk of TdP. Researchers in regulatory agencies, academia and industry are working to find better biomarkers of drug-induced TdP which could prevent many useful drugs from being prematurely abandoned. Drug-induced TdP is a rare occurrence. With fewer drugs that prolong QT interval reaching the licensing stage, knowing which of these drugs are torsadogenic is proving to be elusive. Thus, paradoxically, the effectiveness of the E14 guidance itself has made prospective validation of new biomarkers difficult.This article is part of a themed section on QT safety. To view this issue visit http://www3.interscience.wiley.com/journal/121548564/issueyear?year=2010     

How to measure electrocardiographic QT interval in the anaesthetized rabbit

Many drugs prolong QT or QU intervals [QT(U)] in the electrocardiogram (ECG), and this may be associated with the generation of drug-induced torsades de pointes. Therefore, it is essential to assess the ability of the newly developed drugs to prolong QT(U) interval. For this purpose, both in vivo and in vitro rabbit models are frequently used. However, it is very difficult to locate the end of the QT(U) interval in most rabbit ECGs when repolarisation is delayed, as the shape of the T and U waves may be deformed. In addition, as the heart rate of the rabbit is very high, the T (or U) wave may overlap the P wave or even the QRS complex of the following sinoatrial beat. In these circumstances, application of the “extrapolation method” makes it possible to determine the length of the QT(U) interval. This article describes the extrapolation method, shows ECG examples of typical T and U waves in the anaesthetized rabbit, and makes an attempt to provide a useful guide for researchers to measure reliably and reproducibly the duration of the QT(U) interval in rabbit studies.     

Performance characteristics for some typical QT study designs under the ICH E-14 guidance

The International Conference on Harmonization (ICH) guidance for clinical evaluation of QT prolongation (E14) affected drug development by advocating that a thorough QT study (TQT) be conducted during development to assess the QT prolongation liability of a compound. The ICH E14 Statistics Group shortly thereafter recommended that a noninferiority intersection-union test (IUT) be used to exclude a clinically worrisome QT prolongation. Recent analyses have indicated that the IUT might be overly conservative with respect to excluding QT prolongation. This report assesses the IUT false positive rate for 4 recently conducted TQT trials using simple simulation experiments. Positive TQT study rates ranged from negligible to nearly 60% depending on study design, sample size, and patient status, despite no drug effect. Addition of clinically nonmeaningful QT prolongations (up to 5 milliseconds) increased the positive study rate to 80% for 1 particular study design. Ultimately, these results reveal significant limitations of the IUT with respect to excluding an effect and study interpretation for certain trial designs.     

Assessing QT/QTc interval prolongation with concentration-QT modeling for Phase I studies: impact of computational platforms,model structures and confidence interval calculation methods

Modeling the relationship between drug concentrations and heart rate corrected QT interval (QTc) change from baseline (C-?QTc), based on Phase I single ascending dose (SAD) or multiple ascending dose (MAD) studies, has been proposed as an alternative to thorough QT studies (TQT), in assessing drug-induced QT prolongation risk. The present analysis used clinical SAD, MAD and TQT study data of an experimental compound, AZD5672, to evaluate the performance of: (i) three computational platforms (linear mixed-effects modeling implemented via PROC MIXED in SAS, as well as in R using LME4 package and linear quantile mixed models (LQMM) implemented via LQMM package; (ii) different model structures with and without treatment- or time-specific intercepts; and (iii) three methods for calculating the confidence interval (CI) of QTc prolongation (analytical and bootstrap methods with fixed or varied geometric mean concentrations). We show that treatment- and time-specific intercepts may need to be included into C-?QTc modeling through PROC MIXED or LME4, regardless of their statistical significance. With the intersection union test (IUT) in the TQT study as a reference for comparison, inclusion of these intercepts increased the feasibility for C-?QTc modelling of SAD or MAD to reach the same conclusion as the IUT analysis based on TQT study. Compared to PROC MIXED or LME4, the LQMM method is less dependent on inclusion of treatment- or time-specific intercepts, and the bootstrap CI calculation methods provided higher likelihood for C-?QTc modeling of SAD and MAD studies to reach the same conclusion as the IUT based on the TQT study.     

ICH E14 Q & A (R1) document: perspectives on the updated recommendations on thorough QT studies

The International Conference on Harmonization (ICH) guidance ICH E14 provides recommendations, focusing on a clinical ‘thorough QT/QT_c (TQT) study’, to evaluate the QT liability of a drug during its development. An Implementation Working Group (IWG) was also established to assist the sponsors with any uncertainties and clarify any ambiguities. In April 2012, the IWG updated its June 2008 version of the Questions and Answers document to address additional issues. These include the gender of the study population, a reasonable approach to evaluating QT_c changes in late stage clinical development and the recommended approach to correcting the measured QT interval. This commentary provides our observations and, when appropriate, recommendations, on these issues. We review briefly evidence that suggests that (i) the greater QT effect observed in females is not entirely related to differences in drug exposure and (ii) the Fridericia correction of measured QT interval is adequate for a majority of TQT studies. Until further evidence suggests otherwise, we recommend balanced gender representation in TQT studies, unless warranted otherwise, and for positive studies, subgroup analysis of key data by common demographic variables including the gender and ethnicity. We provide a general scheme for ECG monitoring in late phase clinical trials and consider that while intensive monitoring and centralized reading of ECGs in late phase clinical trials is the norm when a TQT study is positive, there are other circumstances that also call for high quality ECG reading. Therefore, locally read ECGs should only be acceptable as long as accurate high quality ECG data can be guaranteed.     

Effect of Baseline Measurement on the Change from Baseline in QTc Intervals

Phase I thorough QT (TQT) studies are routinely conducted by pharmaceutical companies for all new compounds to satisfy the requirements of International Conference on Harmonisation (ICH) E14 guidance on the evaluation of QTc prolongation. The primary endpoint is the change from baseline in QT interval corrected for heart rate (QTc), and the hypothesis of interest is the noninferiority of drug to placebo. Sometimes, due to the properties of the compound, it becomes necessary to use parallel group designs for TQT studies. In such situations, the effect of the baseline on the change from baseline in QTc becomes an important issue because differing baseline between the drug and placebo groups may not allow for proper estimation of the drug's effect. In this work, we evaluate the effect of baseline on the change from baseline using the placebo data from several TQT studies. Resampling techniques are used to evaluate the impact of differing baselines across groups.     

Effect of baseline measurement on the change from baseline in QTc intervals

Phase I thorough QT (TQT) studies are routinely conducted by pharmaceutical companies for all new compounds to satisfy the requirements of International Conference on Harmonisation (ICH) E14 guidance on the evaluation of QTc prolongation. The primary endpoint is the change from baseline in QT interval corrected for heart rate (QTc), and the hypothesis of interest is the noninferiority of drug to placebo. Sometimes, due to the properties of the compound, it becomes necessary to use parallel group designs for TQT studies. In such situations, the effect of the baseline on the change from baseline in QTc becomes an important issue because differing baseline between the drug and placebo groups may not allow for proper estimation of the drug's effect. In this work, we evaluate the effect of baseline on the change from baseline using the placebo data from several TQT studies. Resampling techniques are used to evaluate the impact of differing baselines across groups.