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Introduction: Traumatic brain injury (TBI) remains a leading cause of mortality and disability in Colombia and other low- and middle-income countries (LMICs), where disparities in resource availability limit implementation of standardized care. The first edition of BOOTStraP (Beyond One Option for Treatment of Traumatic Brain Injury: A Stratified Protocol), published in 2020, provided guidance for TBI management across variable healthcare settings. Advances in neurotrauma care prompted development of an updated protocol. Research question: How can TBI management be optimized across prehospital care, emergency care, neurosurgical surgery, and intensive care phases in settings with varying resource availability? Material and methods: A multidisciplinary panel of 17 national experts in prehospital care, emergency medicine, neurosurgery, and intensive care conducted a structured consensus process using Delphi principles and Nominal Group Technique. Eleven predefined clinical questions were addressed. Recommendations were developed through subgroup work, literature review, and iterative voting, requiring ≥70% agreement at subgroup level and ≥90% plenary consensus. Final algorithms were stratified according to resource availability and healthcare complexity. Results: The second BOOTStraP edition produced 9 integrated management algorithms covering prehospital transport, emergency care, neurosurgical decision-making, and critical care. Interventions are stratified and color-coded by resource requirements, enabling feasible actions in low-, intermediate-, and high-resource settings. Algorithms integrate neuroprotection goals, triage criteria, surgical indications, and monitoring strategies. Discussion and conclusion: BOOTStraP provides a pragmatic, phase-based, resource-sensitive framework bridging evidence-based recommendations with real-world constraints. This approach supports context-adapted decision-making and may reduce secondary brain injury while improving standardization of TBI care in resource-limited environments.
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Rubiano et al. (2026) studied this question.
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