Does trauma team activation associate with the time to CT scan for those suspected of serious head injuries?
Bibliographic record
Abstract
BACKGROUND: Traumatic brain injury (TBI) constitutes the leading cause of posttraumatic mortality. Practically, the major interventions required to treat TBI predicate expedited transfer to CT after excluding other immediately life-threatening conditions. At our center, trauma responses variably consist of either full trauma activation (FTA) including an attending trauma surgeon or a non-trauma team response (NTTR). We sought to explore whether FTAs expedited the time to CT head (TTCTH). METHODS: Retrospective review of augmented demographics of 88 serious head injuries identified from a Regional Trauma Registry within one year at a level I trauma center. The inclusion criteria consisted of a diagnosis of head injury recorded as intubated or GCS < 13; and CT-head scanning after arriving the emergency department. Data was analyzed using STATA. RESULTS: There were 58 FTAs and 30 NTTRs; 86% of FTAs and 17% of NTTRs were intubated prehospital out of 101 charts reviewed in detail; 13 were excluded due to missing data. Although FTAs were more seriously injured (median ISS 29, MAIS head 19, GCS score at scene 6.0), NTTRs were also severely injured (median ISS 25, MAIS head 21, GCS at scene 10) and older (median 54 vs. 26 years). Median TTCTH was double without dedicated FTA (median 50 vs. 26 minutes, p < 0.001), despite similar justifiable delays (53% NTTR, 52% FTA). Without FTA, most delays (69%) were for emergency intubation. TTCTH after securing the airway was longer for NTTR group (median 38 vs. 26 minutes, p =0.0013). Even with no requirements for ED interventions, TTCTH for FTA was less than half versus NTTR (25 vs. 61 minutes, p =0.0013). Multivariate regression analysis indicated age and FTA with an attending surgeon as significant predictors of TTCTH, although the majority of variability in TTCTH was not explained by these two variables (R² = 0.33). CONCLUSION: Full trauma activations involving attending trauma surgeons were quicker at transferring serious head injury patients to CT. Patients with FTA were younger and more seriously injured. Discerning the reasons for delays to CT should be used to refine protocols aimed at minimizing unnecessary delays and enhancing workforce efficiency and clinical outcome.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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 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".