Patterns of anxiety in critically ill patients receiving mechanical ventilatory support.
Patterns of anxiety in critically ill patients receiving mechanical ventilatory support.
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DOI：
10.1097/nnr.0b013e318216009c
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发表时间：
2011-05
期刊：
影响因子：
2.5
通讯作者：
Savik K
中科院分区：
文献类型：
--
作者：
Chlan L;Savik K
机械通气是重症监护室最常用的技术治疗方法之一，给患者带来极大的焦虑。虽然机械通气和危重疾病给住院患者带来了极大的焦虑和痛苦，但对机械支持过程中的焦虑程度知之甚少。为了实施有效的症状管理干预措施，需要了解一段时间内的焦虑等级。这篇文章的目的是描述在一项多点临床试验中，一组机械通气患者在登记期间的焦虑评分，辨别焦虑评分的任何变化模式，确定焦虑是否随着时间的推移而减少，并探讨镇静剂暴露对焦虑评分的影响。参与者是57名机械通气患者，他们被随机分配到常规护理组，进行一项随机对照试验，旨在评估音乐干预对重症监护病房机械通气患者焦虑的疗效。焦虑评分在研究开始时和每天进行，最长持续30天。采用100 mm视觉模拟焦虑量表(VAS-A)测量焦虑程度。VAS-A分数被绘制为研究时间的函数，以天为单位，供每个参与者识别可能的变化模式。使用57名患者的251个观察数据进行混合模型分析，以评估随时间(斜率)变化的性质和大小。无条件均值模型的结果表明，进一步的建模是合适的。选择参与者为随机成分的自回归协方差结构(AR+RE)作为最适合建模的协方差结构。无条件增长模型表明，随着时间的推移，VAS-A下降缓慢，−为每天0.53点(p=0.09)。焦虑是一种患者个体经历，需要在机械通气支持期间进行持续的管理和适当的评估和干预。
Mechanical ventilation is one of the most frequently used technological treatments in critical care units and induces great anxiety in patients. While mechanical ventilation and critical illness induce great anxiety and distress in hospitalized patients, little is known about anxiety ratings over the course of ventilatory support. Knowledge of anxiety ratings over time is needed in order to implement effective symptom management interventions. The purposes of this paper were to describe anxiety ratings for a subgroup of mechanically ventilated patients over the duration of enrollment in a multi-site clinical trial, to discern any pattern of change in anxiety ratings, to determine if anxiety decreases over time, and to explore the influence of sedative exposure on anxiety ratings. Participants were 57 mechanically ventilated patients who were randomly assigned to the usual care group of a randomized controlled trial designed to assess the efficacy of music interventions on anxiety of mechanically ventilated patients in ICUs. Anxiety ratings were obtained at study entry and daily for up to 30 days. A 100-mm Visual Analog Scale-Anxiety (VAS-A) was used to measure anxiety. VAS-A scores were plotted as a function of study time in days for each participant to discern possible patterns of change. A mixed models analysis was performed to assess the nature and magnitude of change over time (slope) using 251 observations on 57 patients. Results of the unconditional means model indicated further modeling was appropriate. An autoregressive covariance structure with a random component for participant (AR + RE) was chosen as the most appropriate covariance structure for modeling. An unconditional growth model indicated that VAS-A declined slowly over time, −.53 points per day (p = .09). Anxiety is an individual patient experience which requires on-going management with appropriate assessment and intervention over the duration of mechanical ventilatory support.