Antibiotic Use and Adverse Events

抗生素的使用和不良事件

• 批准号: 7388883
• 负责人: Sharon B Meropol
• 金额: $ 7.49万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-02-05 至 2010-02-04
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7388883
• 关键词: Acute; Acute respiratory infection; Address; Adverse event; Ambulatory Care; Antibiotic Therapy; Antibiotics; Antimicrobial Resistance; Attention; Attitude; Award; Belief; Benefits and Risks; Caring; Class; Clinical; Clinical Trials; Cohort Studies; Computerized Medical Record; Condition; Control Groups; Data; Databases; Development; Ensure; Event; Exposure to; Fluoroquinolones; Frequencies; Future; General Practices; Guidelines; Individual; Integration Host Factors; Intervention; Learning; Macrolides; Marketing; Medical; Methodology; Methods; Natural experiment; Numbers; Office Visits; Outcome; Outpatients; Patient Preferences; Patients; Pharmaceutical Preparations; Physicians; Population; Population Attributable Risks; Prospective Studies; Provider; Public Health; Randomized Clinical Trials; Range; Rate; Research; Research Personnel; Respiratory Tract Infections; Risk; Risk Factors; Serious Adverse Event; Severe Adverse Event; Training; Visit; base; beta-Lactams; drug efficacy; improved; success

DESCRIPTION (provided by applicant): Estimates of antibiotic exposure in the U.S. population range from once every 3 years to almost twice yearly; almost half of U.S. outpatient antibiotic use is unnecessary. Antibiotic overuse has individual and societal consequences, including adverse drug events (ADEs) and escalating antimicrobial resistance. Efforts to limit overuse at the patient-provider encounter level have had limited success. Even relatively small individual ADE risks from antibiotic use could result in large population attributable risks. Few studies on antibiotic ADEs have included a control group of patients without antibiotic exposure. While randomized clinical trials are ideal for ensuring comparability between exposed and unexposed groups, they are not always feasible. Observational data could offer an efficient way to study individual consequences of antibiotic use, but studies need to address confounding issues, especially confounding by indication. Enhanced adjustment methods to ensure comparability between treatment and control groups would thus help us make optimal use of observational data. This retrospective cohort study uses observational data from the UK's General Practice Research Database to study ADEs consequent to antibiotic use. This study takes advantage of the fact that antibiotic treatment for acute respiratory infections (ARIs) is variable, reflecting clinician beliefs, patient preferences and underlying clinical and nonclinical factors. The primary aim is to compare the risk of a severe adverse event between patients prescribed antibiotics, conditional on an office visit for an ARI vs. the risk for patients with ARI office visits not exposed to antibiotics. The hypothesis is that antibiotic use is associated with an increased risk of adverse events; any increased risk can be attributable to ADEs. Secondary aims are to compare the risk of a severe adverse event between patients with ARIs exposed to different classes of antibiotic drugs, and to compare the risk of a less-severe adverse event between patients with ARIs exposed to antibiotics vs. the risk for unexposed patients. We will explore methods to control for confounding by patient clinical factors such as comorbid conditions and visit frequency. This study will support the applicant's development into a productive independent investigator. This study is relevant to public health as it proposes to assess the individual risk of antibiotic-related ADEs and refine methodologies to address confounding issues inherent with using observational data. Results would help plan a prospective study using electronic medical record data to more effectively incorporate individual risks and benefits into antibiotic prescribing decisions, minimize adverse outcomes of antibiotic prescribing, and decrease unnecessary antibiotic use.

描述（由申请人提供）：美国人群中抗生素暴露的估计范围为每3年一次至几乎每年两次;几乎一半的美国门诊抗生素使用是不必要的。抗生素的过度使用会对个人和社会产生影响，包括药物不良事件（ADE）和抗生素耐药性的不断升级。在患者-提供者接触层面限制过度使用的努力取得了有限的成功。即使抗生素使用的个体ADE风险相对较小，也可能导致较大的人群归因风险。很少有关于抗生素ADE的研究包括没有抗生素暴露的对照组患者。虽然随机临床试验是确保暴露组和未暴露组之间可比性的理想方法，但它们并不总是可行的。观察性数据可以提供一种有效的方法来研究抗生素使用的个体后果，但研究需要解决混淆问题，特别是适应症的混淆。因此，加强调整方法以确保治疗组和对照组之间的可比性将有助于我们最佳利用观察数据。这项回顾性队列研究使用英国全科医学研究数据库的观察数据来研究抗生素使用后的ADE。本研究利用了急性呼吸道感染（阿里斯）的抗生素治疗是可变的，反映了临床医生的信念，患者的偏好和潜在的临床和非临床因素。主要目的是比较抗生素处方患者之间重度不良事件的风险，条件是ARI门诊访视与未暴露于抗生素的ARI门诊访视患者的风险。假设抗生素的使用与不良事件的风险增加有关;任何增加的风险都可以归因于ADE。次要目的是比较暴露于不同类别抗生素药物的阿里斯患者发生重度不良事件的风险，并比较暴露于抗生素的阿里斯患者与未暴露患者发生不太严重不良事件的风险。我们将探索控制患者临床因素（如合并症和访视频率）混杂因素的方法。这项研究将支持申请人发展成为一名富有成效的独立研究者。这项研究与公共卫生相关，因为它建议评估与药物相关的ADE的个体风险，并改进方法，以解决使用观察数据固有的混淆问题。结果将有助于计划使用电子病历数据的前瞻性研究，以更有效地将个体风险和益处纳入抗生素处方决策，最大限度地减少抗生素处方的不良后果，并减少不必要的抗生素使用。