Integrated Resuscitation Strategies in Orthopedic Trauma: A Systematic Review of Outcomes of Cardiopulmonary Resuscitation (CPR), Hemorrhage Control, and Damage Control
Bibliographic record
Abstract
Orthopedic trauma is a major cause of global morbidity and mortality, often resulting from high-energy mechanisms such as road traffic accidents, falls, and interpersonal violence. Early deaths are frequently due to hemorrhage, coagulopathy, and physiologic instability. This systematic review, following PRISMA 2020 guidelines, included six studies with a total of 28,549 patients. The majority came from the CRASH-2 randomized controlled trial (20,211 bleeding trauma patients, many with orthopedic injuries). The remaining five studies together contributed 8,338 patients to evaluate integrated resuscitation strategies: trauma-specific CPR, hemorrhage control (tourniquets, pelvic stabilization, massive transfusion protocols, tranexamic acid, resuscitative endovascular balloon occlusion of the aorta (REBOA)/embolization), and fracture fixation timing (damage control orthopedics vs early appropriate care/early total care). Evidence indicates that early hemorrhage control, physiologically guided resuscitation, and timely operative intervention improve survival, reduce complications, and optimize functional outcomes. Standardized, protocol-driven approaches and resource-sensitive adaptations remain essential for effective orthopedic trauma care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".