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院外心脏骤停后苏醒的预测。

Prediction of awakening after out-of-hospital cardiac arrest.

作者信息

Longstreth W T, Diehr P, Inui T S

出版信息

N Engl J Med. 1983 Jun 9;308(23):1378-82. doi: 10.1056/NEJM198306093082302.

Abstract

To develop a model that would forecast neurologic recovery after out-of-hospital cardiac arrest, we reviewed charts on 389 consecutive patients who were not awake on admission to the hospital after resuscitation from asystole or ventricular fibrillation. The outcome variable was "awakening," which was defined as having comprehensible speech or the ability to follow commands. Predictor variables that we considered included both preadmission and admission data. Using discriminant analysis, we derived models from a 60 per cent random sample of cases and tested the models on the remaining 40 per cent. We judged that the best model contained four variables from the admission examination: motor response, pupillary light response, spontaneous eye movements, and blood glucose (levels below 300 mg per deciliter predicted awakening). Overall correct classification was 80 per cent in the derivation sample and 77 per cent in the test sample. In a simplified form, the model's predictions of awakening had a sensitivity of 0.92, a specificity of 0.65, a positive predictive value of 0.80, and a negative predictive value of 0.84. This rule should be clinically useful in estimating the neurologic prognosis of patients resuscitated after out-of-hospital cardiac arrest.

摘要

为了开发一个能够预测院外心脏骤停后神经功能恢复情况的模型,我们回顾了389例复苏成功后入院时仍未苏醒的连续病例的病历。这些病例最初表现为心搏骤停或室颤。研究的输出变量是“苏醒”,定义为能够进行可理解的言语交流或具备听从指令的能力。我们考虑的预测变量包括入院前和入院时的数据。使用判别分析,我们从60%的随机样本病例中推导模型,并在其余40%的病例中对模型进行测试。我们判定最佳模型包含来自入院检查的四个变量:运动反应、瞳孔对光反应、自发眼球运动和血糖(血糖水平低于300mg/dL预示着苏醒)。在推导样本中,总体正确分类率为80%,在测试样本中为77%。以简化形式表示,该模型对苏醒的预测具有0.92的敏感度、0.65的特异度、0.80的阳性预测值和0.84的阴性预测值。该规则在评估院外心脏骤停复苏后患者的神经预后方面应具有临床实用性。

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