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Development and Validation of a Predictive Model for Hemodynamic Responses to Resuscitation during Uncontrolled Hemorrhage*

机译:失血期间对复苏的血流动力学反应预测模型的开发和验证*

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We investigated whether a statistical model could predict mean arterial pressure (MAP) during uncontrolled hemorrhage; such a model could be used for automated decision support, to help clinicians decide when to provide intravascular volume to achieve MAP goals. This was a secondary analysis of adult swine subjects during uncontrolled splenic bleeding. By protocol, after developing severe hypotension (MAP < 60 mmHg), subjects were resuscitated with either saline (NS) or fresh frozen plasma (FFP), determined randomly. Vital signs were documented at quasi-regular time-step intervals, until either subject death or 300 min. Subjects were randomly separated 50%/50% into training/validation sets, and regression models were developed to predict MAP for each subsequent (i.e., future) time-step. Median time-steps for serially recorded vital signs were +15 min. 5 subjects survived the protocol; 17 died after a median time of 87 min (IQR 78 – 134). The final model consisted of: current MAP; heart rate (HR); prior NS; imminent NS; and imminent FFP. The 95% limits-of-agreement between true subsequent MAP vs. predicted subsequent MAP were +10/-11 mmHg for the 79 time-steps in the training set; and +14/-13 for the 64 time-steps in the validation set. A total of 10 sudden death events (i.e., rapid, fatal MAP decrease within one single time-step) were excluded from analysis. In conclusion, for uncontrolled hemorrhage in a swine model, it was possible to estimate the next documented MAP value on the basis of the subject’s current documented MAP; HR; prior NS; and the volume of resuscitation about to be administered. However, the model was unable to predict "sudden death" events. The applicability to populations with wider heterogeneity of hemorrhage patterns and with comorbidities requires further investigation.
机译:我们调查了统计模型是否可以预测失血期间的平均动脉压(MAP)。这样的模型可用于自动决策支持,以帮助临床医生决定何时提供血管内容积来实现MAP目标。这是在未控制的脾脏出血期间对成年猪受试者进行的次要分析。按照协议,在发生严重的低血压(MAP <60 mmHg)后,用生理盐水(NS)或新鲜冰冻血浆(FFP)对受试者进行复苏,以随机确定。以准规则的时间间隔记录生命体征,直到受试者死亡或300分钟为止。将受试者随机分为训练/验证集的50%/ 50%,并开发回归模型以预测每个后续(即未来)时间步长的MAP。连续记录的生命体征的中位时间步长为+15分钟。 5名受试者在实验方案中幸存;中位时间为87分钟(IQR 78 – 134)之后,有17人死亡。最终模型包括:当前的MAP;心率(HR);先前的NS;即将到来的NS;和即将到来的FFP。在训练集中的79个时间步中,真实的后续MAP与预测的后续MAP之间的95%协议限制为+ 10 / -11 mmHg。并在验证集中的64个时间步中输入+ 14 / -13。从分析中排除了总共10个突然死亡事件(即,在一个单一的时间步之内快速,致命的MAP降低)。总之,对于猪模型中的失血,可以根据受试者当前记录的MAP估算下一个记录的MAP值。人力资源;先前的NS;以及即将进行的复苏量。但是,该模型无法预测“突然死亡”事件。对于出血模式异质性较广且合并症的人群的适用性需要进一步研究。

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