Czorlich Patrick, Sauvigny Thomas, Ricklefs Franz, Kluge Stefan, Vettorazzi Eik, Regelsberger Jan, Westphal Manfred, Schmidt Nils Ole
Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Department of Intensive Care, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Acta Neurochir (Wien). 2015 Dec;157(12):2051-9. doi: 10.1007/s00701-015-2605-3. Epub 2015 Oct 14.
Early prediction of increased morbidity and mortality in aneurysmal subarachnoid hemorrhage (aSAH) remains crucial to improving patient management. Most prediction models lack external validation and focus on disease-specific items without considering physiological parameters and the past medical history. The aim was to assess the validity of the established Simplified Acute Physiology Score II (SAPS-II) in an aSAH cohort for the prediction of hospital mortality and to identify additional physiological and clinical predictors.
The predictive value of SAPS-II for hospital mortality was assessed in a retrospective analysis of 263 consecutive patients with aSAH. Additional physiological and clinical parameters including the past medical history were analyzed by forward selection multivariate analysis to identify independent predictors of hospital mortality and to improve the prediction model.
The SAPS-II predicted hospital mortality with an area under the curve (AUC) of 0.834 with an odds ratio (OR) of 1.097 [95 % confidence interval 1.067-1.128) for each additional point. Forward selection multivariate analysis identified the Glasgow Coma Scale score (P < 0.001), history of chronic headache (P = 0.01) and medication with anticoagulants (P = 0.04) as independent predictors of hospital mortality. Adding these parameters to the SAPS-II, the AUC increased to 0.86.
This study validates the predictive accuracy of SAPS-II for hospital mortality in aSAH patients. Additional parameters from the past medical history increase its predictive power. From a practical viewpoint, SAPS-II alone already represents a sufficient and powerful score to predict hospital mortality at an early time point and may help to improve patient management.
早期预测动脉瘤性蛛网膜下腔出血（aSAH）患者发病率和死亡率的增加对于改善患者管理仍然至关重要。大多数预测模型缺乏外部验证，并且专注于疾病特异性项目，而未考虑生理参数和既往病史。本研究旨在评估既定的简化急性生理学评分II（SAPS-II）在aSAH队列中预测医院死亡率的有效性，并确定其他生理和临床预测因素。
通过对263例连续的aSAH患者进行回顾性分析，评估SAPS-II对医院死亡率的预测价值。通过向前选择多变量分析，分析包括既往病史在内的其他生理和临床参数，以确定医院死亡率的独立预测因素，并改进预测模型。
SAPS-II预测医院死亡率的曲线下面积（AUC）为0.834，每增加1分的比值比（OR）为1.097 [95%置信区间1.067-1.128]。向前选择多变量分析确定格拉斯哥昏迷量表评分（P < 0.001）、慢性头痛病史（P = 0.01）和抗凝药物治疗（P = 0.04）为医院死亡率的独立预测因素。将这些参数添加到SAPS-II中，AUC增加到0.86。
本研究验证了SAPS-II对aSAH患者医院死亡率的预测准确性。既往病史中的其他参数提高了其预测能力。从实际角度来看，单独使用SAPS-II已经是一个足够强大的评分，能够在早期预测医院死亡率，并可能有助于改善患者管理。
