Cervical spine injuries requiring surgery in a Level I trauma centre in a major German city
Bibliographic record
Abstract
BACKGROUND: Cervical spine injuries (CSI) are rare in trauma patients, at about 9.2-16.5/100,000 inhabitants in Scandinavia and Canada, and the annual incidence of CSI surgeries in Norway is around 3.0/100,000 inhabitants. However, despite their rarity, the incidence of CSI has increased, thereby assuming an increasing need for surgery. Outside of Scandinavia, no data about the incidence of CSI and subsequent surgeries exist. Therefore, this study aimed to analyse CSI epidemiology and surgery in a German city with a Level I trauma centre both to understand the injury and improve needs-based planning. METHODS: This retrospective, monocentre study included all patients who presented with CSI from 2012-2017 at a university hospital with a Level I trauma centre in a major German city and had permanent residency within the city. Based on the assumption that the patients represented all CSI injuries in the city, as they were treated at the only available Level I trauma centre, the annual incidence of surgeries and neurologic deficits due to CSI were calculated. RESULTS: A total of 465 patients with 609 CSI were identified. Of these patients, 61 both received surgery and resided in the city (mean age, 68.1 ± 18.3 years; 26 female, 35 male). The incidence of CSI surgeries was calculated as 3.24/100,000 person years (1.75/100,000 in the upper and 1.54/100,000 in the subaxial cervical spine). Neurologic deficits occurred in 0.64/100,000 person years. The incidence of both surgeries and neurologic deficits showed no significant changes over the 6-year study period. CONCLUSIONS: Compared to Scandinavia, an increasing annual incidence for CSI surgeries and neurologic deficits were found. For long-term demand planning with adaptability to demographic changes, cross-regional studies including long-term follow-up are necessary.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".