Evidence for Use of Damage Control Surgery and Damage Control Interventions in Civilian Trauma Patients: A Systematic Review
Bibliographic record
Abstract
Abstract Background: Although damage control (DC) surgery is widely assumed to reduce mortality in critically injured patients, survivors often suffer substantial morbidity, suggesting that it should only be used when indicated. The purpose of this systematic review was to determine which indications for DC have evidence that they are reliable and/or valid (and therefore in which clinical situations evidence supports use of DC or that DC improves outcomes). Methods: We searched 11 databases (1950-April 1, 2019) for studies that enrolled exclusively civilian trauma patients and reported data on the reliability (consistency of surgical decisions in a given clinical scenario) or content (surgeons would perform DC in that clinical scenario or the indication predicted use of DC in practice), construct (were associated with poor outcomes), or criterion (were associated with improved outcomes when DC was conducted instead of definitive surgery) validity for suggested indications for DC surgery or DC interventions. Results: Among 34,979 citations identified, we included 36 cohort studies and three cross-sectional surveys in the systematic review. Of the 59 unique indications for DC identified, 10 had evidence of content validity [e.g., a major abdominal vascular injury or a packed red blood cell (PRBC) exceeding the critical administration threshold], nine had evidence of construct validity (e.g., unstable patients with combined abdominal vascular and pancreas gunshot injuries or an iliac vessel injury and intraoperative acidosis), and six had evidence of criterion validity (e.g., penetrating trauma patients requiring >10 U PRBCs with an abdominal vascular and multiple abdominal visceral injuries or intraoperative hypothermia, acidosis, or coagulopathy). No studies evaluated the reliability of indications. Conclusions: Few indications for DC surgery or DC interventions have evidence supporting that they are reliable and/or valid. DC should be used with respect for the uncertainty regarding its effectiveness, and only in circumstances where definitive surgery cannot be entertained.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".