Albaeni Aiham, Eid Shaker M, Vaidya Dhananjay, Chandra-Strobos Nisha
Division of Hospital Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
J Neurol Transl Neurosci. 2014;2(1).
Despite 50 years of research, prognostication post cardiac arrest traditionally occurs at 72 hours. We tested the accuracy of a novel bedside score within 24 hours of hospital admission, in predicting neurologically intact survival.
We studied 192 adults following non-traumatic out-of-hospital cardiac arrest. In a 50% random modeling sample, a model for survival to discharge with good neurological outcome was developed using univariate analysis and stepwise multivariate logistic regression for predictor selection. The diagnostic efficiency of this modeled score was assessed in the remaining 50% sample using receiver operating characteristic (ROC) analysis.
In this study, 20% of patients survived to discharge with good neurological outcome. The final logistic regression model in the modeling sample retained three predictors: initial rhythm Ventricular Fibrillation, Return of Spontaneous Circulation ≤ 20 minutes from collapse, and Brainstem Reflex Score ≥ 3 within 24 hours. These variables were used to develop a three-point Out of Hospital Cardiac Arrest score. The area under the (ROC) curve was 0.84 [95% CI, 0.75-0.93] in the modeling sample and 0.92 [95% CI, 0.87-0.98] in the validation sample. A score ≥ 2 predicted good neurological outcome with a sensitivity of 79%, a specificity of 92%, and a negative predictive value of 93%. A score ≥1 had a sensitivity of 100% and a negative predictive value of 100%; however, the specificity was only 55%.
This study demonstrates that a score based on clinical and easily accessible variables within 24 hours can predict neurologically intact survival following cardiac arrest.
尽管经过了50年的研究,但心脏骤停后的预后评估传统上仍在72小时进行。我们测试了一种新型床边评分在入院24小时内预测神经功能完好存活的准确性。
我们研究了192例非创伤性院外心脏骤停的成年人。在一个50%的随机建模样本中,使用单变量分析和逐步多变量逻辑回归进行预测变量选择,建立了一个神经功能良好出院存活的模型。使用受试者工作特征(ROC)分析在其余50%的样本中评估该建模评分的诊断效率。
在本研究中,20%的患者神经功能良好出院存活。建模样本中的最终逻辑回归模型保留了三个预测变量:初始心律为室颤、心脏骤停至自主循环恢复≤20分钟、24小时内脑干反射评分≥3。这些变量用于制定一个三分的院外心脏骤停评分。建模样本中(ROC)曲线下面积为0.84[95%CI,0.75 - 0.93],验证样本中为0.92[95%CI,0.87 - 0.98]。评分≥2预测神经功能良好结局的敏感性为79%,特异性为92%,阴性预测值为93%。评分≥1的敏感性为100%,阴性预测值为100%;然而,特异性仅为55%。
本研究表明,基于24小时内临床且易于获取的变量的评分可以预测心脏骤停后神经功能完好的存活情况。