Severe Hypoglycemia: Ascertainment, Surveillance and Pharmacovigilance

严重低血糖：确定、监测和药物警戒

• 批准号: 9121555
• 负责人: Andrew John Karter
• 金额: $ 55.66万
• 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/9121555
• 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; novel therapeutics; personalized management; 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.

修改后的项目总结/摘要 大多数2型糖尿病患者的处方药物，以降低血糖水平，降低长期并发症的风险。严重低血糖（SH）是药物治疗的非预期后果（即，医源性效应），并被定义为患者需要帮助的低血糖水平。SH与较差的生活质量、严重福尔斯、车祸、室性心律失常、痴呆、住院和死亡风险增加数倍相关。尽管药物治疗取得了进展，但导致急诊（艾德）就诊或住院的SH已成为糖尿病治疗最常见的并发症之一，是一个严重的公共卫生问题。四分之一的老年人因药物不良事件紧急住院治疗是由于SH。然而，我们缺乏足够强大的确认工具来估计SH的总发病率。尽管治疗的复杂性增加和普遍的多药治疗，我们也缺乏一个可靠的了解如何SH风险变化时，患者开始联合降糖治疗或其与非糖尿病药物的相互作用。我们建议在一个大型（n~ 229，000）的综合医疗保健提供系统（Kaiser Permanente北方加州或KPNC）的2型糖尿病成人多样化队列中研究SH，具体目标有以下3个：在目标1中，我们将开发和验证用于从EMR数据（艾德和医院）中识别SH的新算法。使用这些EMR编码算法，我们将对临床识别的SH趋势进行全面监测。我们还将估计临床未识别的SH比例（基于与既往调查中自我报告的SH的联系），这将有助于计算SH的总发生率。在目标2中，我们将量化与糖尿病患者常用药物（即，检查糖尿病药物、非糖尿病药物或它们的相互作用的效果），使用严格的因果建模技术（例如，差异中差异分析、边际结构模型、有向无环图）。在目标3中，我们将估计与开始药物治疗相关的SH风险变化（来自目标2）是否在特定风险亚组中存在实质性差异（例如，既往SH、CKD、长期糖尿病、老年人），以及基线和HbA 1c变化。本研究将1）提供新的SH确定工具，以改善全国范围内的监测，从而能够更全面地了解SH流行病学;和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性化糖尿病管理，同时最大限度地降低SH风险。