IMPROVING SPEECH IN VENTILATOR SUPPORTED PATIENTS

改善呼吸机支持患者的言语能力

• 批准号: 6055841
• 负责人: Jeannette D. Hoit
• 金额: $ 14.28万
• 依托单位: UNIVERSITY OF ARIZONA
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-01 至 2001-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6055841
• 关键词: artificial respiration; behavioral /social science research tag; biomedical equipment safety; clinical research; data collection; functional ability; human subject; longitudinal human study; method development; neuromuscular disorder; outcomes research; positive pressure breathing; pulmonary respiration; respirators; respiratory airway pressure; respiratory function; speech; vocalization

In most patients who are tracheostomized and supported with positive- pressure ventilators, speech is characterized by phrases that are too short, silent pauses that are too long, and loudness and voice quality fluctuations that are too large. The research proposed in this application is designed to determine how to improve the speech of such patients, particularly those with neuromuscular disorders. Its focus will be to identify effective interventions that are simple, inexpensive, and safe. This research will be conducted in two phases, one that will evaluate short-term outcomes and another that will evaulate long-term outcomes. The first phase will examine the influence of a variety of different ventilator adjustments on speech. Those adjustments that are found to be most effective for improving speech without compromising cardiopulmonary function on a short-term basis will be examined further in the second phase of the research. The second phase will test the long-term efficacy of selected ventilator adjustments by monitoring cardiopulmonary status and speech behavior over many consecutive days. Functional outcome also will be assessed in appropriate cases. This research will have direct clinical applications. It will offer those professionals involved in the clinical care of ventilator-supported patients (e.g., pulmonologists, respiratory therapists, and speech- language pathologists) a data-based approach for determining ventilator settings for individual patients that will take into account not only cardiopulmonary needs, but speech-related needs as well.

在大多数被气管静态和受支持的患者中 压力呼吸机，语音的特征是短语 短而无声的停顿太长，响亮和声音质量 太大的波动。 这项研究提出了 应用旨在确定如何改善这种语音 患者，特别是患有神经肌肉疾病的患者。 它的重点意志 确定简单，便宜的有效干预措施，并且 安全的。 这项研究将分为两个阶段，一个将 评估短期结局，而另一种将避免长期的 结果。 第一阶段将检查各种各样的影响 语音上的不同呼吸机调整。 那些调整 发现在不妥协的情况下最有效地改善语音 短期内将进一步检查心肺功能 在研究的第二阶段。 第二阶段将测试 通过监视选定呼吸机调整的长期疗效 许多连续的心肺状态和语音行为 天。 在适当情况下，还将评估功能结果。 这项研究将有直接的临床应用。 它将提供那些 参与呼吸机支持的临床护理的专业人员 患者（例如，肺科医生，呼吸治疗师和语音 - 语言病理学家）一种基于数据的方法来确定呼吸机 单个患者的设置，不仅会考虑 心肺需求，但也需要与语音有关的需求。