Efficacy and safety of damage control in experimental animal models of injury: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although abbreviated surgery with planned reoperation (damage control surgery) is now widely used to manage major trauma patients, the procedure and its component interventions have not been evaluated in randomized controlled trials (RCTs). While some have suggested the need for such trials, they are unlikely to be conducted because of patient safety concerns. As animal studies may overcome several of the limitations of existing observational damage control studies, the primary objective of this study is to evaluate the efficacy and safety of damage control versus definitive surgery in experimental animal models of injury. METHODS/DESIGN: We will search electronic databases (Medline, Embase, PubMed, Web of Science, Scopus, and the Cochrane Library), conference abstracts, personal files, and bibliographies of included articles. We will include RCTs and prospective cohort studies that utilized an animal model of injury and compared damage control surgery (or specific damage control interventions or adjuncts) to definitive surgery (or specific definitive surgical interventions). Two investigators will independently evaluate the internal and external/construct validity of individual studies. The primary outcome will be all-cause mortality. Secondary outcomes will include blood loss amounts; blood pressures and heart rates; urinary outputs; core body temperatures; arterial lactate, pH, and base deficit/excess values; prothrombin and partial thromboplastin times; international normalized ratios; and thromboelastography (TEG) results/activated clotting times. We will calculate summary relative risks (RRs) of mortality and mean differences (for continuous outcomes) using DerSimonian and Laird random effects models. Heterogeneity will be explored using subgroup meta-analysis and meta-regression. We will assess for publication bias using funnel plots and Begg's and Egger's tests. When evidence of publication bias exists, we will use the Duval and Tweedie trim and fill method to estimate the potential influence of this bias on pooled summary estimates. DISCUSSION: This study will evaluate the efficacy and safety of damage control in experimental animal models of injury. Study results will be used to guide future clinical evaluations of damage control surgery, determine which animal study outcomes may potentially be generalizable to the clinical setting, and to provide guidelines to strengthen the conduct and relevance of future pre-clinical studies.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.044 | 0.004 |
| 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 | 0.000 |
| 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".