Headache Assessment of Children for Emergent Intracranial Abnormalities

儿童突发颅内异常的头痛评估

• 批准号: 10451639
• 负责人: Daniel Sing-Kwong Tsze
• 金额: $ 135.54万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 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/10451639
• 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; Lead; 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; base; 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

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.

项目摘要 美国每年有超过40万名儿童前往急诊室（ED）， 抱怨头痛。这些儿童中有一小部分（0.5-1%）会出现异常， 需要紧急识别的大脑中，如肿瘤，出血或中风。然而，一个更大的 比例在艾德接受大脑神经成像，多达三分之一的头痛儿童被诊断为头痛。 不必要地暴露在与神经成像相关的风险中。这些风险中最突出的是致命的 由于计算机断层扫描（CT）辐射而导致的恶性肿瘤。过度使用的主要原因是 艾德中的神经成像缺乏关于哪些临床特征，或“红旗”发现， 准确识别患有头痛的儿童，他们有出现大脑异常的风险。电流 危险信号的发现是从研究中发现的，这些研究的方法有限，并且/或者有少量的 患者;事实上，经常使用的红旗结果（例如头痛将患者从睡眠中唤醒）是常见的 并且不具有特异性，在多达30-40%的头痛儿童中出现某些发现。很长的- 我们研究的长期目标是广泛实施一种决策支持工具，帮助临床医生进行平衡 根据对患有以下疾病的儿童出现脑异常风险的精确估计， 头痛当前研究的目标是产生明确的证据，使临床医生能够 确定在其他健康儿童中出现紧急大脑异常的风险， 头痛我们目前研究的主要目的是推导和内部验证一个决策工具， 对儿童出现头痛的ED风险进行了分层。该模型将使用临床上合理的， 可靠的因素，以确定儿童在近零风险的紧急大脑异常与接近完美的准确性。 我们将通过开展一项前瞻性多中心研究来实现这一目标，我们将招募28，000名 2至17岁患有头痛的儿童前往儿科急诊室的18名急诊室之一就诊 应用研究网络（PECARN）。我们将前瞻性地收集一份全面的历史清单， 这些患者的体格检查结果，并使用复杂的统计建模分析， 风险分层模型。我们的目标是得到一个模型，这是高度准确的识别病人在接近零 突发性大脑异常的风险。提供一个确定儿童接近零的决策工具 基于特定头痛特征的突发性脑异常的风险和更高风险将 从根本上改善儿童急性头痛的治疗方法。这些信息将有助于优化 紧急神经影像学的使用，包括安全减少儿童不必要的神经影像学检查。