Predictors of survival in trauma patients requiring resuscitative thoracotomy: A scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction Resuscitative thoracotomy (RT) is an emergent procedure to gain access to the thoracic cavity to control hemorrhage and other life-threatening injuries. Data predicting survival is variable. This review aims to highlight key predictors of survival and mortality following RT. Methods The EMBASE database was searched using the following terms: [exp. Thoracotomy] AND [Trauma.mp] AND [exp. Survival OR exp. Mortality]. The search was limited to full-text articles in the English language and publications released up to February 27, 2022. Reference lists of included articles were reviewed to identify other studies meeting inclusion criteria. Results Thirty-seven studies were included. Seventy-six outcome predictors were identified. Prehospital outcome predictors included prehospital vital signs, police transport, cardiopulmonary resuscitation, application of a cervical spine collar, and the number of total prehospital procedures performed. In-hospital variables associated with survival included traumatic cardiac arrest (TCA) in the emergency department (ED), initial ED vital signs and cardiac rhythm, Shock Index Pediatric Age-Adjusted score, location of RT, duration of RT, Focused Assessment with Sonography in Trauma findings, amount of blood products, and amount of administered fluids. Conclusions Our study highlights the disparity of data regarding prehospital outcome predictors for trauma patients requiring RT. Most studies focus on injury-specific and in-hospital variables and do not explicitly look at the TCA population. Further work is needed to better define specific variables implicated in enhanced survival across different care settings and to inform management guidelines within these clinical areas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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 it