Cardim Danilo, Robba Chiara, Donnelly Joseph, Bohdanowicz Michal, Schmidt Bernhard, Damian Maxwell, Varsos Georgios V, Liu Xiuyun, Cabeleira Manuel, Frigieri Gustavo, Cabella Brenno, Smielewski Peter, Mascarenhas Sergio, Czosnyka Marek
1 Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge , Cambridge, United Kingdom .
2 Neurosciences Critical Care Unit, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust , Cambridge, United Kingdom .
J Neurotrauma. 2016 Apr 15;33(8):792-802. doi: 10.1089/neu.2015.4134. Epub 2015 Dec 17.
Elevation of intracranial pressure (ICP) may occur in many diseases, and therefore the ability to measure it noninvasively would be useful. Flow velocity signals from transcranial Doppler (TCD) have been used to estimate ICP; however, the relative accuracy of these methods is unclear. This study aimed to compare four previously described TCD-based methods with directly measured ICP in a prospective cohort of traumatic brain-injured patients. Noninvasive ICP (nICP) was obtained using the following methods: 1) a mathematical "black-box" model based on interaction between TCD and arterial blood pressure (nICP_BB); 2) based on diastolic flow velocity (nICP_FVd); 3) based on critical closing pressure (nICP_CrCP); and 4) based on TCD-derived pulsatility index (nICP_PI). In time domain, for recordings including spontaneous changes in ICP greater than 7 mm Hg, nICP_PI showed the best correlation with measured ICP (R = 0.61). Considering every TCD recording as an independent event, nICP_BB generally showed to be the best estimator of measured ICP (R = 0.39; p < 0.05; 95% confidence interval [CI] = 9.94 mm Hg; area under the curve [AUC] = 0.66; p < 0.05). For nICP_FVd, although it presented similar correlation coefficient to nICP_BB and marginally better AUC (0.70; p < 0.05), it demonstrated a greater 95% CI for prediction of ICP (14.62 mm Hg). nICP_CrCP presented a moderate correlation coefficient (R = 0.35; p < 0.05) and similar 95% CI to nICP_BB (9.19 mm Hg), but failed to distinguish between normal and raised ICP (AUC = 0.64; p > 0.05). nICP_PI was not related to measured ICP using any of the above statistical indicators. We also introduced a new estimator (nICP_Av) based on the average of three methods (nICP_BB, nICP_FVd, and nICP_CrCP), which overall presented improved statistical indicators (R = 0.47; p < 0.05; 95% CI = 9.17 mm Hg; AUC = 0.73; p < 0.05). nICP_PI appeared to reflect changes in ICP in time most accurately. nICP_BB was the best estimator for ICP "as a number." nICP_Av demonstrated to improve the accuracy of measured ICP estimation.
颅内压（ICP）升高可能发生在多种疾病中，因此无创测量颅内压的能力将很有用。经颅多普勒（TCD）的血流速度信号已被用于估计颅内压；然而，这些方法的相对准确性尚不清楚。本研究旨在在前瞻性队列的创伤性脑损伤患者中，将四种先前描述的基于TCD的方法与直接测量的颅内压进行比较。使用以下方法获得无创颅内压（nICP）：1）基于TCD与动脉血压相互作用的数学“黑箱”模型（nICP_BB）；2）基于舒张期血流速度（nICP_FVd）；3）基于临界关闭压（nICP_CrCP）；4）基于TCD衍生的搏动指数（nICP_PI）。在时域中，对于颅内压自发变化大于7 mmHg的记录，nICP_PI与测量的颅内压显示出最佳相关性（R = 0.61）。将每个TCD记录视为一个独立事件，nICP_BB通常显示为测量颅内压的最佳估计值（R = 0.39；p < 0.05；95%置信区间[CI] = 9.94 mmHg；曲线下面积[AUC] = 0.66；p < 0.05）。对于nICP_FVd，尽管它与nICP_BB呈现相似的相关系数且AUC略好（0.70；p < 0.05），但它在预测颅内压时显示出更大的95% CI（14.62 mmHg）。nICP_CrCP呈现中等相关系数（R = 0.35；p < 0.05）且与nICP_BB的95% CI相似（9.19 mmHg），但未能区分正常和升高的颅内压（AUC = 0.64；p > 0.05）。使用上述任何统计指标，nICP_PI均与测量的颅内压无关。我们还引入了一种基于三种方法（nICP_BB、nICP_FVd和nICP_CrCP）平均值的新估计器（nICP_Av），其总体呈现出改进的统计指标（R = 0.47；p < 0.05；95% CI = 9.17 mmHg；AUC = 0.73；p < 0.05）。nICP_PI似乎最准确地反映了颅内压随时间的变化。nICP_BB是颅内压“数值”的最佳估计器。nICP_Av证明提高了测量颅内压估计的准确性。
