University of Texas at Southwestern Medical Center - Dallas, Texas, Estados Unidos.
Rev Bras Ter Intensiva. 2021 Jul-Sep;33(3):412-421. doi: 10.5935/0103-507X.20210065.
To calculate mean dilation velocities for Glasgow coma scale-derived injury severity classifications stratified by multiple confounding variables.
In this study, we examined 68,813 pupil readings from 3,595 patients to determine normal dilation velocity with brain injury categorized based upon a Glasgow coma scale as mild (13 - 15), moderate (9 - 12), or severe (3 - 8). The variables age, sex, race, pupil size, intensive care unit length of stay, intracranial pressure, use of narcotics, Glasgow coma scale, and diagnosis were considered as confounding and controlled for in statistical analysis. Machine learning classification algorithm-based logistic regression was employed to identify dilation velocity cutoffs for Glasgow coma scale categories.
The odds ratios and confidence intervals of these factors were shown to be statistically significant in their influence on dilation velocity. Classification based on the area under the curve showed that for the mild Glasgow coma scale, the dilation velocity threshold value was 1.2mm/s, with false probability rates of 0.1602 and 0.1902 and areas under the curve of 0.8380 and 0.8080 in the left and right eyes, respectively. For the moderate Glasgow coma scale, the dilation velocity was 1.1mm/s, with false probability rates of 0.1880 and 0.1940 and areas under the curve of 0.8120 and 0.8060 in the left and right eyes, respectively. Furthermore, for the severe Glasgow coma scale, the dilation velocity was 0.9mm/s, with false probability rates of 0.1980 and 0.2060 and areas under the curve of 0.8020 and 0.7940 in the left and right eyes, respectively. These values were different from the previous method of subjective description and from previously estimated normal dilation velocities.
Slower dilation velocities were observed in patients with lower Glasgow coma scores, indicating that decreasing velocities may indicate a higher degree of neuronal injury.
计算格拉斯哥昏迷量表（Glasgow coma scale，GCS）损伤严重程度分类的平均扩张速度，并按多个混杂变量进行分层。
本研究共检查了 3595 例患者的 68813 次瞳孔读数，根据 GCS 将脑损伤分为轻度（13-15 分）、中度（9-12 分）和重度（3-8 分），以确定正常的扩张速度。年龄、性别、种族、瞳孔大小、重症监护病房住院时间、颅内压、使用麻醉药物、GCS 和诊断等变量被认为是混杂因素，并在统计分析中进行了控制。采用基于机器学习分类算法的逻辑回归来确定 GCS 分类的扩张速度截断值。
这些因素的比值比和置信区间表明，它们对扩张速度的影响具有统计学意义。基于曲线下面积的分类表明，对于轻度 GCS，扩张速度的阈值为 1.2mm/s，左眼和右眼的假概率率分别为 0.1602 和 0.1902，曲线下面积分别为 0.8380 和 0.8080。对于中度 GCS，扩张速度为 1.1mm/s，左眼和右眼的假概率率分别为 0.1880 和 0.1940，曲线下面积分别为 0.8120 和 0.8060。此外，对于重度 GCS，扩张速度为 0.9mm/s，左眼和右眼的假概率率分别为 0.1980 和 0.2060，曲线下面积分别为 0.8020 和 0.7940。这些值与以前的主观描述方法和以前估计的正常扩张速度不同。
GCS 评分较低的患者扩张速度较慢，表明速度降低可能表明神经元损伤程度较高。
