Trauma triggers complex physiological responses with primary and secondary effects vital to understanding and managing trauma impact. "Damage Control" (DC), a concept adapted from naval practices, refers to abbreviated initial surgical care focused on controlling bleeding and contamination, critical for the survival of severely compromised patients. This impacts anaesthesia procedures and intensive care. "Damage Control Resuscitation" (DCR) is an interdisciplinary approach aimed at reducing mortality in severely injured patients, despite potentially increasing morbidity and ICU duration. Current medical guidelines incorporate DC strategies.DC is most beneficial for patients with severe physiological injury, where surgical trauma ("second hit") poses greater risks than delayed treatment. Patient assessment for DC includes evaluating injury severity, physiological reserves, and anticipated surgical and treatment strain. Inadequate intervention can worsen trauma-induced complications like coagulopathy, acidosis, hypothermia, and hypocalcaemia.DCR focuses on rapidly restoring homeostasis with minimal additional burden. It includes rapid haemostasis, controlled permissive hypotension, early blood transfusion, haemostasis optimization, and temperature normalization, tailored to individual patient needs."Damage Control Surgery" (DCS) involves phases like rapid haemostasis, contamination control, temporary wound closure, intensive stabilization, planned reoperations, and final wound closure. Each phase is crucial for managing severely injured patients, balancing immediate life-saving procedures and preparing for subsequent surgeries.Intensive care post-DCS emphasizes stabilizing patients hemodynamically, metabolically, and coagulopathically while restoring normothermia. Decision-making in trauma care is complex, involving precise patient assessment, treatment prioritization, and team coordination. The potential of AI-based decision support systems is noted for their ability to analyse patient data in real-time, aiding in decision-making through evidence-based recommendations.
Keyphrases
- end stage renal disease
- chronic kidney disease
- ejection fraction
- healthcare
- newly diagnosed
- oxidative stress
- peritoneal dialysis
- machine learning
- prognostic factors
- minimally invasive
- case report
- decision making
- risk assessment
- risk factors
- early onset
- atrial fibrillation
- coronary artery disease
- artificial intelligence
- climate change
- coronary artery bypass
- chronic pain
- acute coronary syndrome
- trauma patients
- drug induced
- diabetic rats
- extracorporeal membrane oxygenation
- high glucose
- surgical site infection