Development of a Pediatric Acute Asthma Prediction Rule for severity and outcome

描述(申请人提供)：我们建议开发符合临床和生物统计学标准的多变量哮喘预测规则(APR)，用于临床预测规则的制定。APR将包括在提交给急诊护理机构时获得的体检结果、生命体征和客观生理变量，以及这些数据在最初6小时护理中的趋势。这些数据是由医疗团队的多个成员收集的，但很少以连贯和系统的方式使用，以最佳地推进患者护理。APR将使用那些经过统计证明的数据元素来预测住院护理的需求。此外，我们将进一步开发和验证一个数学模型，使用脉搏血氧仪的生理波形数据作为APR的候选预测变量。将这些数据整合到APR中可能会增强将要开发的APR的预测效度和可靠性。主要目的：确定与住院护理需求相关的哮喘加重患者的独立危险因素。我们假设选择的预测变量可以用于APR，它将以足够的敏感度和特异度来预测住院治疗的需求，从而客观地为临床决策提供信息。为了验证这一假设，我们将对7-17岁的儿童进行前瞻性研究，这些儿童在儿科急诊科就诊时哮喘加重。体检结果、生命体征和在就诊和前6小时护理期间获得的客观生理变量将被用作候选预测变量，以预测如果参与者入院住院超过1天的住院时间，或者如果患者出院在48小时内复发。这些数据将用于根据既定的临床和生物统计标准制定APR。第二个目的：进一步开发和验证一种实时、连续的哮喘严重程度测量方法，使用量化的血氧计体积脉搏图波形数据，可以同时使用和测试作为APR的候选预测变量。我们假设，建立的血氧计心动图评估脉冲异常(PEP)的数学模型将为纳入APR提供独立、实时、连续和有效的气道阻塞严重程度的估计。为了验证这一假设，PEP将与肺活量测定和特定呼吸道阻力的标准标准进行统计比较。(摘要结束)

DESCRIPTION (provided by applicant): We propose to develop a multivariable Asthma Prediction Rule (APR) conforming to clinical and biostatistical standards for clinical prediction rule development. The APR will include physical findings, vital signs, and objective physiologic variables obtained at presentation to an acute care facility, and trends of this data over the first 6 hours of care. This data is gathered by multiple members of a medical team, but is infrequently utilized in a coherent and systematic manner to optimally advance patient care. The APR will use those elements of data that are statistically demonstrated to predict the need for in-hospital care. In addition, we will further develop and validate a mathematic model using physiologic waveform data from the pulse oximeter as a candidate predictor variable for the APR. The novel integration of this data into the APR might enhance the predictive validity and reliability of the APR to be developed. Primary Aim: To determine independent risk factors in persons with asthma exacerbations that are associated with the need for in-hospital care. We hypothesize that select predictor variables can be utilized in an APR that will in turn predict need for in-hospital care with sufficient sensitivity and specificity to objectively inform clinical decisions. To test this hypothesis we will conduct a prospective study of children ages 7-17 years who present to a Pediatric Emergency Department with asthma exacerbations.Physical examination findings, vital signs, and objective physiologic variables obtained at presentation and during the first 6 hours of care will be used as candidate predictor variables to predict either hospital length of stay greater than 1 day if the participant is admitted to hospital, or relapse within 48 hours if discharged to home. This data will be utilized for the development of an APR in accordance with established clinical and biostatistical standards. Secondary Aim: To further develop and validate a real-time, continuous asthma severity measure using quantified oximeter plethysmograph waveform data that can be used and tested simultaneously as a candidate predictor variable for the APR. We hypothesize that an established mathematic model for oximeter Plethysmograph Estimated Pulsus paradoxus (PEP) will provide an effort-independent, real-time, continuous and valid estimate of the severity of airway obstruction for incorporation in the APR. To test this hypothesis, PEP will be statistically compared with the criterion standards of spirometry and specific airway resistance. (End of Abstract)