Indications for use of thoracic, abdominal, pelvic, and vascular damage control interventions in trauma patients
Bibliographic record
Abstract
BACKGROUND: The use of abbreviated or damage control (DC) interventions may improve outcomes in severely injured patients when appropriately indicated. We sought to determine which indications for DC interventions have been most commonly reported in the peer-reviewed literature to date and evaluate the opinions of experts regarding the appropriateness (expected benefit-to-harm ratio) of the reported indications for use in practice. METHODS: Two investigators used an abbreviated grounded theory method to synthesize indications for 16 different DC interventions reported in peer-reviewed articles between 1983 and 2014 into a reduced number of named, content-characteristic codes representing unique indications. For each indication code, an international panel of trauma surgery experts (n = 9) then rated the appropriateness of conducting the DC intervention of interest in an adult civilian trauma patient. RESULTS: The 424 indications identified in the literature were synthesized into 101 unique indications. The panel assessed 12 (70.6%) of the coded indications for the 7 different thoracic, 47 (78.3%) for the 7 different abdominal/pelvic, and 18 (75.0%) for the 2 different vascular interventions to be appropriate for use in practice. These included indications for rapid lung-sparing surgery (pneumonorrhaphy, pulmonary tractotomy, and pulmonary wedge resection) (n = 1); pulmonary tractotomy (n = 3); rapid, simultaneously stapled pneumonectomy (n = 1); therapeutic mediastinal and/or pleural space packing (n = 4); temporary thoracic closure (n = 3); therapeutic perihepatic packing (n = 28); staged pancreaticoduodenectomy (n = 2); temporary abdominal closure (n = 12); extraperitoneal pelvic packing (n = 5); balloon catheter tamponade (n = 6); and temporary intravascular shunting (n = 11). CONCLUSION: This study identified a list of candidate appropriate indications for use of 12 different DC interventions that were suggested by authors of peer-reviewed articles and assessed by a panel of independent experts to be appropriate. These indications may be used to focus future research and (in the interim) guide surgical practice while studies are conducted to evaluate their impact on patient outcomes.
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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 | 0.023 | 0.166 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".