Predictors of Respiratory Insufficiency in Amyotrophic Lateral Sclerosis

项目摘要/摘要 肌萎缩侧索硬化症(ALS)是一种进行性神经退行性疾病，发病率高，病死率高。 因呼吸衰竭而导致的普遍死亡。呼吸衰竭的出现预示着罹患 误吸与延髓肌肉无力和无效咳嗽、高碳酸血症所致呼吸衰竭有关 慢性换气不足和肺部感染，最终导致死亡。尽管关键的角色是 呼吸衰竭与肌萎缩侧索硬化症相关的发病率和死亡率仍然存在不确定性 对这种疾病的呼吸护理的最佳启动和维持。肌萎缩侧索硬化症的临床表现非常不同 临床表现和症状进展，导致呼吸道损害的不同演变。给定 对本病呼吸道发病的意义结合时机不清，有更好的认识 呼吸肌无力的发生和发展的危险因素可以改善生活质量和 甚至在肌萎缩侧索硬化症中存活。不幸的是，目前还没有ALS呼吸衰竭的预测模型，也没有建立 ALS呼吸进展的表型(最重要的是，“快速进展者”)，并且有显著的 肌萎缩侧索硬化症呼吸衰竭的临床医生和治疗中心之间的差异。一种预测 ALS中呼吸无力的模型和定义的表型可以提高干预的及时性， 促进沟通，为临床试验设计提供信息，并阐明新的疾病机制。 这项研究的目标是确定呼吸衰竭发作的预测因素，并确定不同的 呼吸功能障碍的发展速度和模式的表型。首先，我的目标是发展和 对诊断后6个月内发生呼吸功能不全的预测模型进行验证 Logistic回归模型和预测模型分析。第二，我的目标是根据 呼吸肌力随时间的变化率(通过肺活量测定法测量) 弹道建模。接下来，我将根据基线特征确定组成员身份概率 使用多项Logistic回归模型。 该项目将为职业发展奖提供必要的初步数据，该奖项将(1)审查 呼吸衰竭风险对肌萎缩侧索硬化症患者短期和长期预后的影响，(2)前瞻性 验证预测模型，(3)开发干预措施以减轻以患者为中心的相关结果 ALS的呼吸功能不全，以及(4)确定哪些特征与不同的 呼吸功能的轨迹，从而允许个性化的药物。

Project Summary/Abstract Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with high morbidity and universal mortality due to respiratory failure. The onset of respiratory weakness heralds an increased risk of aspiration related to bulbar muscle weakness and ineffective cough, hypercapnic respiratory failure due to chronic hypoventilation, and pulmonary infections, ultimately leading to death. Despite the key role of respiratory failure in the morbidity and mortality associated with ALS, there remains uncertainty concerning optimum initiation and maintenance of respiratory care for this disease. ALS has a very heterogeneous clinical presentation and symptom progression, which causes variable evolution of respiratory involvement. Given the significance of respiratory morbidity with this disease combined with the unclear timing, a better understanding of the risk factors for onset and progression of respiratory muscle weakness could improve quality of life and even survival in ALS. Unfortunately, there is no prediction model for respiratory failure in ALS, no established phenotypes for ALS respiratory progression (most importantly, “rapid progressors”), and there is significant variation between clinicians and centers regarding the management of respiratory failure in ALS. A prediction model and defined phenotypes of respiratory weakness in ALS could improve timeliness of interventions, facilitate communication, inform clinical trial design, and elucidate novel disease mechanisms. The goals of this study are to identify predictors of onset of respiratory failure and to identify distinct phenotypes of rapidity and pattern of the progression of respiratory dysfunction. First, I aim to develop and validate a prediction model for developing respiratory insufficiency within six months of diagnosis using a logistic regression model and predictive model analytics. Second, I aim to categorize individuals based on the rate of change of respiratory muscle strength (as measured by spirometry) over time using group-based trajectory modeling. Next, I will identify group membership probabilities according to baseline characteristics using a multinomial logistic regression model. This project will provide essential preliminary data for a Career Development Award that will (1) examine the impact of risk of respiratory failure on short and long-term outcomes of patients with ALS, (2) prospectively validate the prediction model, (3) develop an intervention to mitigate patient-centered outcomes associated with respiratory insufficiency in ALS, and (4) identify which characteristics are associated with different trajectories of respiratory function, thus allowing for personalized medicine.