Headache Assessment of Children for Emergent Intracranial Abnormalities

儿童突发颅内异常的头痛评估

基本信息

批准号：
10650325
负责人：
Daniel Sing-Kwong Tsze
金额：
$ 133.64万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10650325
关键词：
17 year old Academy Accident and Emergency department Acute Adverse event Age American Applied Research Brain Brain Neoplasms Characteristics Child Clinical Communities Craniocerebral Trauma Diagnosis Diagnostic Emergency Care Emergency Department Physician Emergency Medicine Enrollment Exposure to Goals Headache Hemorrhage Intervention Intracranial Hemorrhages Knowledge Magnetic Resonance Imaging Malignant Neoplasms Methodology Methods Migraine Minor Modeling Morbidity - disease rate Multicenter Trials Neurology Patients Pediatric Neurology Physical Examination Physicians Prevalence Prospective Studies Radiation Radiation Dose Unit Recommendation Recording of previous events Research Respiratory Tract Infections Risk Risk Estimate Risk Factors Role Sample Size Scanning Secondary to Sedation procedure Signs and Symptoms Sleep Societies Statistical Models Stroke Testing Uncertainty X-Ray Computed Tomography brain abnormalities cancer risk clinical decision support computerized decision making algorithm design high risk improved lifetime risk neuroimaging pediatric emergency pediatrician prevent prospective radiation risk research study risk stratification support tools tool tumor

项目摘要

Project Summary More than 400,000 children present annually to emergency departments (EDs) in the U.S. with chief complaints of headaches. A small but meaningful proportion (0.5-1%) of these children will have abnormalities in the brain requiring emergent identification, such as tumors, bleeding, or strokes. However, a much larger proportion undergo neuroimaging of the brain in the ED, with up to one-third of children with headaches being unnecessarily exposed to the risks associated with neuroimaging. The most prominent of these risks is a lethal malignancy due to radiation from computed tomography (CT) scanning. The primary reason for the overuse of neuroimaging in the ED is the lack of clarity regarding which clinical characteristics, or “red flag” findings, accurately identify children with headaches who are at risk of having emergent brain abnormalities. Current red flag findings were discovered from studies that were limited in their methods and/or had small numbers of patients; in fact, frequently used red flag findings (e.g. headache waking the patient from sleep) are common and non-specific, with certain findings occurring in as many as 30-40% of children with headaches. The long- term goal of our research is to widely implement a decision support tool that will help clinicians make balanced and informed decisions based on precise estimates of the risk of emergent brain abnormalities in children with headaches. The goal of the current study is to generate the definitive evidence that will allow clinicians to identify the risks of emergent brain abnormalities in otherwise healthy children presenting to EDs with headaches. The primary aim of our current study is to derive and internally validate a decision tool that stratifies the risk for children presenting to EDs with headaches. This model will use clinically sensible and reliable factors to identify children at near-zero risk of emergent brain abnormalities with near perfect accuracy. We will accomplish this aim by conducting a prospective multicenter research study in which we enroll 28,000 children 2 to 17-years-old with headaches presenting to one of 18 EDs in the Pediatric Emergency Care Applied Research Network (PECARN). We will prospectively collect a comprehensive list of history and physical examination findings for these patients and use sophisticated statistical modeling analyses to derive a model to stratify risk. We aim to derive a model which is highly accurate for identifying patients at near-zero risk of emergent brain abnormalities. The availability of a decision tool which identifies children with near-zero risk and higher risk of emergent brain abnormalities based on specific headache characteristics will fundamentally improve how children with acute headaches are managed. This information will help optimize the use of emergent neuroimaging, including the safe reduction of unnecessary neuroimaging in children.

项目概要在美国，每年有超过 400,000 名儿童到急诊室 (ED) 就诊，并由主任负责这些儿童中一小部分（0.5-1%）会出现头痛的症状。然而，需要紧急识别的大脑中，例如肿瘤、出血或中风。比例在急诊室接受脑部神经影像检查，多达三分之一的头痛儿童接受了脑部神经影像检查。不必要地暴露于与神经影像学相关的风险中，最突出的是致命的。计算机断层扫描 (CT) 扫描辐射导致的恶性肿瘤是过度使用的主要原因。急诊科的神经影像学缺乏明确哪些临床特征或“危险信号”发现，准确识别患有头痛的儿童是否有出现紧急大脑异常的风险。危险信号发现是从方法有限和/或样本数量较少的研究中发现的。患者；事实上，经常出现的危险信号（例如头痛将患者从睡梦中惊醒）很常见且非特异性，某些发现出现在多达 30-40% 的头痛儿童中。我们研究的长期目标是广泛实施决策支持工具，帮助参议员做出平衡的决策并根据对儿童突发大脑异常风险的精确估计做出明智的决定当前研究的目标是产生明确的证据，让人们能够识别其他健康儿童出现脑部异常的风险，这些儿童在急诊科就诊时患有以下疾病我们当前研究的主要目的是推导并内部验证一个决策工具该模型将使用临床上合理且可靠的方法对因头痛而就诊的儿童的风险进行分层。可靠的因素可以以近乎完美的准确度识别儿童出现大脑异常的几乎为零的风险。我们将通过开展一项前瞻性多中心研究来实现这一目标，其中我们招募了 28,000 名患有头痛的 2 至 17 岁儿童前往儿科急诊中心 18 间急诊室之一就诊应用研究网络（PECARN）。我们将前瞻性地收集历史和信息的综合列表。这些患者的体检结果，并使用复杂的统计模型分析得出我们的目标是导出一个高度准确的模型来识别接近于零的患者。紧急大脑异常风险的决策工具可识别儿童的风险接近于零。基于特定头痛特征的紧急大脑异常的风险和更高风险将该信息将有助于从根本上改善急性头痛儿童的治疗方式。使用紧急神经影像学，包括安全减少儿童不必要的神经影像学检查。