Predictors of massive blood transfusion: a Delphi Study to examine the views of experts.

JOURNAL OF THE ROYAL ARMY MEDICAL CORPS(2017)

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摘要
Background Trauma patients requiring massive blood transfusion (MBT) have high morbidity and mortality: early and aggressive use of blood products during immediate resuscitation may improve survival. There is currently a lack of evidence to guide initial identification of these patients which is especially important in areas where plasma may need to be thawed. In the absence of this evidence, this study aimed to robustly evaluate expert opinion by using a Delphi process to identify predictors of massive transfusion. This process can be used to ensure that decision rules include variables that have clinical validity, which may improve translation of rules into clinical practice. Methods An international panel of 35 experts was identified through expert advice against specific criteria. Military and civilian experts from the fields of emergency medicine, critical care, anaesthesia, prehospital care, haematology and general/trauma surgery were included. The Delphi Study was carried out over three rounds. Consensus level was predefined at 80%. Results 195 statements were generated by the panel of which 97 (49.7%) achieved consensus at the 80% level by the end of round 3. Strikingly no clinical observations reached consensus individually. Metabolic acidosis of a base excess of -5.0 or worse, lactate >5 mmol/L and a low haematocrit on arrival were all considered predictive. Some patterns of injury, but few mechanisms of injury, were considered highly predictive of the need of MBT. Conclusions This Delphi process has produced a list of parameters that expert clinicians felt were predictive for MBT. This list can be used to inform the generation of decision rules. It is of note that many factors used in current decision rules were not valued by clinical experts -this may be a cause for poor uptake of those rules.
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关键词
Decision Rules,Haemorrhage,Massive Transfusion,Shock,Trauma,coagulopathy
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