Severe Hypoglycemia: Ascertainment, Surveillance and Pharmacovigilance

严重低血糖：确定、监测和药物警戒

基本信息

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
项目类别：
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

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

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项目摘要

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.

修改的项目摘要/摘要大多数2型糖尿病患者是处方药物可降低葡萄糖水平并降低长期并发症的风险。严重的低血糖（SH）是药物的意外结果（即医源性作用），并将其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，汽车事故，心室心律不齐，痴呆，住院治疗以及死亡风险增加相关。尽管药物治疗取得了进步，但导致出现科（ED）就诊或住院治疗的SH还是成为糖尿病治疗中最普遍的并发症之一，这是一个严重的公共卫生问题。老年人不良药物事件的四分之一紧急住院是由SH造成的。但是，我们缺乏足够强大的确定性工具来估计SH的总发生率。尽管治疗的复杂性增加和普遍的多药性，但当患者启动降糖疗法的组合或其与非糖尿病药物的相互作用时，我们也缺乏对SH风险如何变化的可靠理解。我们建议在大型（N〜229,000）中研究SH，其中包括综合医疗保健输送系统（Kaiser Permanente North California或KPNC）的2型糖尿病的成年人队列，具有这3个具体目标：在AIM 1中，我们将开发和验证从EMR数据中识别SH的新算法（ED和医院）。使用这些EMR编码算法，我们将对临床认可的SH进行全面监视趋势。我们还将估计未临床认可的SH的比例（基于与先前调查的自我报告的SH的联系），这将有助于计算SH的总率。在AIM 2中，我们将量化与糖尿病患者普遍使用的药物相关的SH风险变化（即检查糖尿病药物，非糖尿病药物或其相互作用的影响），使用严格的，因果关系建模技术（例如，差异，差异分析分析，大小写的结构模型）。在AIM 3中，我们将估计与药物启动相关的SH风险的变化（来自AIM 2）是否在特定的风险亚组（例如先前的SH，CKD，长期持续时间糖尿病，较长的糖尿病）以及基线和基线和HBA1C的变化方面存在实质性不同。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视，从而对SH流行病学有更全面的了解； 2）提供与糖尿病患者常用药物相关的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，同时最大程度地减少SH的风险。