Indications for the Appropriate Use of Damage Control Surgery and Damage Control Interventions in Civilian Trauma Patients
Bibliographic record
Abstract
In patients undergoing emergent operation for trauma, surgeons must decide whether to perform a definitive or damage control (DC) procedure. DC surgery (abbreviated initial surgery followed by planned reoperation after a period of resuscitation in the intensive care unit) has been suggested to most benefit patients more likely to succumb from the “vicious cycle” of hypothermia, acidosis, and coagulopathy and/or postoperative abdominal compartment syndrome (ACS) than the failure to complete organ repairs. However, there currently exists no unbiased evidence to support that DC surgery benefits injured patients. Further, the procedure is associated with substantial morbidity, long lengths of intensive care unit and hospital stay, increased healthcare resource utilization, and possibly a reduced quality of life among survivors. Therefore, it is important to ensure that DC laparotomy is only utilized in situations where the expected procedural benefits are expected to outweigh the expected procedural harms. In this manuscript, we review the comparative effectiveness and safety of DC surgery when used for different procedural indications. We also review recent studies suggesting variation in use of DC surgery between trauma centers and the potential harms associated with overuse of the procedure. We also review published consensus indications for the appropriate use of DC surgery and specific abdominal, pelvic, and vascular DC interventions in civilian trauma patients. We conclude by providing recommendations as to how the above list of published appropriateness indications may be used to guide medical and surgical education, quality improvement, and surgical practice.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".