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首页> 外文期刊>Palliative care. >Clinical Prediction Rule for Patient Outcome after In-Hospital CPR: A New Model, Using Characteristics Present at Hospital Admission, to Identify Patients Unlikely to Benefit from CPR after In-Hospital Cardiac Arrest
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Clinical Prediction Rule for Patient Outcome after In-Hospital CPR: A New Model, Using Characteristics Present at Hospital Admission, to Identify Patients Unlikely to Benefit from CPR after In-Hospital Cardiac Arrest

机译：院内心肺复苏术后患者预后的临床预测规则：一种新模型，利用医院入院时存在的特征，识别出院内心脏骤停后不太可能受益于心肺复苏的患者

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Background Physicians and patients frequently overestimate likelihood of survival after in-hospital cardiopulmonary resuscitation. Discussions and decisions around resuscitation after in-hospital cardiopulmonary arrest often take place without adequate or accurate information. Methods We conducted a retrospective chart review of 470 instances of resuscitation after in-hospital cardiopulmonary arrest. Individuals were randomly assigned to a derivation cohort and a validation cohort. Logistic Regression and Linear Discriminant Analysis were used to perform multivariate analysis of the data. The resultant best performing rule was converted to a weighted integer tool, and thresholds of survival and nonsurvival were determined with an attempt to optimize sensitivity and specificity for survival. Results A 10-feature rule, using thresholds for survival and nonsurvival, was created; the sensitivity of the rule on the validation cohort was 42.7% and specificity was 82.4%. In the Dartmouth Score (DS), the features of age (greater than 70 years of age), history of cancer, previous cardiovascular accident, and presence of coma, hypotension, abnormal PaO2, and abnormal bicarbonate were identified as the best predictors of nonsurvival. Angina, dementia, and chronic respiratory insufficiency were selected as protective features. Conclusions Utilizing information easily obtainable on admission, our clinical prediction tool, the DS, provides physicians individualized information about their patients’ probability of survival after in-hospital cardiopulmonary arrest. The DS may become a useful addition to medical expertise and clinical judgment in evaluating and communicating an individual's probability of survival after in-hospital cardiopulmonary arrest after it is validated by other cohorts.
机译：背景医师和患者经常高估院内心肺复苏后存活的可能性。院内心肺骤停后复苏的讨论和决策往往没有足够或准确的信息。方法我们对470例院内心肺骤停后复苏的病例进行了回顾性图表回顾。将个体随机分配到派生队列和验证队列。使用Logistic回归和线性判别分析对数据进行多元分析。将得到的最佳执行规则转换为加权整数工具，并确定生存和非生存阈值，以优化生存的敏感性和特异性。结果使用生存和非生存阈值创建了10个特征规则;验证队列规则的敏感性为42.7％，特异性为82.4％。在达特茅斯评分（DS）中，年龄（大于70岁），癌症病史，先前的心血管意外以及昏迷，低血压，PaO2异常和碳酸氢盐异常的特征被确定为非存活的最佳预测指标。选择心绞痛，痴呆和慢性呼吸功能不全作为保护性特征。结论我们的临床预测工具DS利用可在入院时轻松获得的信息，为医生提供了有关患者在院内心肺骤停后存活可能性的个性化信息。在其他队列验证后，DS可能会成为医学专业知识和临床判断的有用补充，以评估和传达患者在院内心肺骤停后的生存可能性。

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