Crush syndrome diagnosis and management in resource-constrained settings: A Delphi study

Crush syndrome is an important source of morbidity and mortality in resource-constrained settings including earthquake disaster zones, austere military environments, and countries where motor vehicle collisions and interpersonal violence are prevalent. In South Africa and other countries with high rates of community violence, patients develop crush due to a unique form of trauma called community assault, where individuals suspected of wrongdoing are assaulted by multiple persons as a form of mob justice. The purpose of this study is to generate consensus about crush syndrome definitions and endpoints to inform the development of scoring systems appropriate for community assault and usable in resource-limited settings.

This study used in-depth interviews of clinicans from South Africa to determine the challenges associated with crush management in resource-constrained environments. These qualitative findings informed a subsequent Delphi survey process which sought consensus regarding crush definitions, endpoints, and co-variates. Three surveys were administered to an international panel of clinicians with experience managing crush injuries in military, disaster, and civilian clinical environments. There was a pre-established consensus threshold of 75%.

There were 8 interview participants and 15 Delphi participants. These clinicians recommended maintaining a high index of suspicion for crush syndrome as this diagnosis can easily be overlooked in polytrauma patients, and advised early administration of intravenous fluids titrated to urine output and respiratory status. Crush injury was conceptualized as a localized process of muscle injury from trauma, whereas crush syndrome was viewed as the resulting systemic complications including renal failure and hemodynamic instability. Preferred clinical endpoints included acute kidney injury, renal replacement therapy, and need for respiratory support.

This study provided context related to crush injury management in resource-constrained environments. Clinical risk prediction models must account for the unique patient populations and data limitations commonly encountered in these settings.