Head Computed Tomography Utilization for Concussion Patients: Role of the Aging Population
Bibliographic record
Abstract
To the Editor: We read with great interest the brief report published by Zonfrillo et al.,1 in the July 2015 issue of Academic Emergency Medicine, which described the change in emergency department (ED) visits and head computed tomography (CT) for concussion patients over a 6-year period. The study demonstrated that ED visits for concussions had increased with 28.1%, and while injury severity as defined by the Injury Severity Score (ISS) declined, the number of head CTs increased. The authors conclude that adherence to evidence-based clinical guidelines is of the utmost importance, to prevent rising radiation exposure and health care costs. While we agree with the authors’ plea to continue guideline reinforcements for ED management of concussion patients, we would like to add some remarks to their conclusions. The observed increase in head CT scanning gives rise to the question whether this increase is due to a higher number of cases meeting criteria for CT scan indication or whether the guideline compliance by physicians has altered over the years. The decline in injury severity implies the latter, since most risk factors for deterioration after head trauma pertain to injury characteristics that become more frequent with rising severity (e.g., anterograde amnesia, vomiting, clinical signs of skull fracture). Apart from these clinical characteristics, most national and international guidelines include a cutoff value for age, above which a CT scan is strongly recommended. For instance, two of the most commonly applied guidelines for head CT indication, the Canadian CT Head Rule2 and the New Orleans Criteria,3 recommend a CT scan for all patients above the cutoffs of 65 and 60 years, respectively. Regarding the data provided by Zonfrillo and colleagues, we calculated that the strongest increase in concussion-related ED visits was within the older age groups: 45 to 65 years (from 92,016 to 129,709, an increase of 41%) and 65+ years (from 49,949 to 74,897, an increase of 50%). The authors did not comment on the guideline regulation in the U.S. hospitals. However, there is the possibility that the observed increase in CT scans can be (partly) explained by the ageing traumatic brain injury population. It might even be argued that the existing guidelines should age along with the population, to prevent the risks of increased radiation exposure and health care costs, about which Zonfrillo and colleagues are warning us.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".