Severe Hypoglycemia: Ascertainment, Surveillance and Pharmacovigilance

严重低血糖：确定、监测和药物警戒

• 批准号: 8963214
• 负责人: Andrew John Karter
• 金额: $ 54.56万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-06 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8963214
• 关键词: 18 year old; Accident and Emergency department; Accidents; Adult; Adverse drug event; Algorithms; American; Arrhythmia; Blood Glucose; California; Cessation of life; Clinical Trials; Code; Complex; Complications of Diabetes Mellitus; Data; Dementia; Diabetes Mellitus; Drug Interactions; Elderly; Emergency Situation; Emergency department visit; Epidemic; Epidemiology; Evaluation; Event; Family member; Friends; General Population; Glucose; Glycosylated hemoglobin A; Goals; Graph; Head; Health Personnel; Hospital Records; Hospitalization; Hospitals; Hypoglycemia; ICD-9; Incidence; Insulin; International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10); Knowledge; Lead; Medical; Non-Insulin-Dependent Diabetes Mellitus; Participant; Patient Care; Patient Self-Report; Patients; Pharmaceutical Preparations; Pharmacotherapy; Plasma; Polypharmacy; Population; Provider; Public Health; Quality of life; Randomized Clinical Trials; Regimen; Reporting; Respondent; Risk; Risk Estimate; Risk Factors; Safety; Sampling; Structural Models; Subgroup; Sulfonylurea Compounds; Surveillance Methods; Surveys; System; Techniques; Ventricular Arrhythmia; abstracting; antimicrobial; base; causal model; clinical care; cohort; diabetes management; diabetes risk; experience; falls; health care delivery; high risk; improved; mortality; national surveillance; non-diabetic; novel; public health relevance; tool; treatment as usual; trend

MODIFIED PROJECT SUMMARY/ABSTRACT Most patients with type 2 diabetes are prescribed medications to lower glucose levels and reduce the risk of long-term complications. Severe hypoglycemia (SH) occurs as an unintended consequence of medications (i.e., an iatrogenic effect) and is defined as a low blood glucose level for which the patient requires assistance. SH is associated with poorer quality of life, serious falls, car accidents, ventricular arrhythmia, dementia, hospitalizations, and a several-fold increased risk of death. Despite advances in pharmacotherapy, SH leading to emergency department (ED) visits or hospitalization has emerged as one of the most prevalent complications of diabetes treatment and is a critical public health concern. One in four emergency hospitalizations for adverse drug events among older adults is due to SH. Yet, we lack sufficiently robust ascertainment tools to estimate the total incidence of SH. Despite increasing treatment complexity and prevalent polypharmacy, we also lack a reliable understanding of how SH risk changes when patients initiate combinations of glucose-lowering therapies or their interactions with non-diabetic drugs. We propose to study SH in a large (n~229,000), diverse cohort of adults with type 2 diabetes from an integrated healthcare delivery system (Kaiser Permanente Northern California or KPNC) with these 3 specific aims: In Aim 1, we will develop and validate novel algorithms for identifying SH from EMR data (ED and hospital). Using these EMR coding algorithms, we will conduct comprehensive surveillance of trends in clinically recognized SH. We will also estimate the proportion of SH not clinically recognized (based on linkage with self-reported SH from a previous survey), which will facilitate calculation of the total rates of SH. In Aim 2, we will quantify the change in risk of SH associated with initiation of medications commonly used by people with diabetes (i.e., examining the effect of diabetes medications, non-diabetes medications, or their interactions), using rigorous, causal modeling techniques (e.g., difference-in-difference analysis, marginal structural models, directed acyclic graphs). In Aim 3, we will estimate whether the change in SH risk associated with initiation of medications (from Aim 2) differs substantively across specific risk subgroups (e.g., prior SH, CKD, long duration diabetes, the elderly), and by baseline and changes in HbA1c. This study will 1) provide new SH ascertainment tools to improve surveillance nationwide and thereby enable a more comprehensive understanding of SH epidemiology; and 2) provide valid estimates of change in SH risk associated with initiation of medications commonly used by people with diabetes, thus helping providers and patients individualize diabetes management while minimizing the risk of SH.

修改后的项目摘要/摘要 大多数 2 型糖尿病患者都会服用药物来降低血糖水平并降低长期并发症的风险。严重低血糖 (SH) 是药物治疗的意外后果（即医源性效应），定义为患者需要帮助的低血糖水平。 SH 与生活质量较差、严重跌倒、车祸、室性心律失常、痴呆、住院治疗以及死亡风险增加数倍有关。尽管药物治疗取得了进步，但导致急诊室 (ED) 就诊或住院的 SH 已成为糖尿病治疗最常见的并发症之一，也是一个重要的公共卫生问题。老年人中四分之一的因药物不良事件而紧急住院的人是由 SH 引起的。然而，我们缺乏足够强大的确定工具来估计 SH 的总发病率。尽管治疗复杂性不断增加且多药治疗普遍存在，但我们对当患者开始联合降糖疗法或其与非糖尿病药物的相互作用时 SH 风险如何变化仍缺乏可靠的了解。我们建议在综合医疗保健服务系统（北加州凯撒医疗机构或 KPNC）的大型（n~229,000）、多样化的 2 型糖尿病成人队列中研究 SH，具有以下 3 个具体目标：在目标 1 中，我们将开发并验证从 EMR 数据（急诊室和医院）中识别 SH 的新算法。使用这些 EMR 编码算法，我们将对临床认可的 SH 趋势进行全面监测。我们还将估计未经临床识别的 SH 比例（基于与之前调查中自我报告的 SH 的联系），这将有助于计算 SH 的总发生率。在目标 2 中，我们将使用严格的因果建模技术（例如，双重差分分析、边际结构模型、有向无环图），量化与糖尿病患者开始常用药物（即检查糖尿病药物、非糖尿病药物或其相互作用的效果）相关的 SH 风险变化。在目标 3 中，我们将根据基线和 HbA1c 的变化来估计与开始用药相关的 SH 风险变化（与目标 2 相比）在特定风险亚组（例如既往 SH、CKD、长期糖尿病、老年人）之间是否存在实质性差异。这项研究将 1) 提供新的 SH 确定工具，以改善全国范围内的监测，从而更全面地了解 SH 流行病学； 2) 提供与糖尿病患者常用药物开始相关的 SH 风险变化的有效估计，从而帮助提供者和患者个体化糖尿病管理，同时最大限度地降低 SH 风险。