Is older age an appropriate criterion alone for ordering cervical spine <scp>CT</scp> after trauma
Bibliographic record
Abstract
The authors raise an interesting question. To date, studies evaluating cervical spine clearance in elderly patients are limited to retrospective, single institution studies. The authors add to this body of literature and frame it in the context of radiology resource utilization. Indeed, significant numbers of unnecessary scans could delay the reading of other critical imaging. It is a worthy goal to continually reevaluate our current standards of practice to optimize patient care. The Canadian C-Spine Rule1 is the most commonly used clearance guideline in current practice, and it recommends universal imaging for patients aged 65 and older. There are currently no additional evidence-based guidelines or expert consensus recommendations on geriatric cervical spine clearance from our professional trauma societies. As Healy et al.2 describe in their discussion, the Eastern Association for the Surgery of Trauma practice management guidelines for identification of cervical spine injuries following trauma does not mention age,3 the evaluation and management of geriatric trauma guideline makes no recommendations on imaging,4 and the cervical spine collar clearance guideline is only for obtunded patients.5 In this study, the authors reviewed cervical spine imaging from two hospitals from 2018 to 2023 for patients aged 65 and older. They identified 9455 scans in 7114 patients, as 514 patients had two scans and 244 had more than two scans in the study period. Out of all scans, 192 had cervical spine fractures and 28 (14.6%) were categorized as asymptomatic. The authors subsequently stratified by age groups and reported a 1.68% rate of fracture and 0.18% rate of asymptomatic fractures in patients aged 65–70. In their discussion, they raise the question of whether this number of positive studies is worth the workload implications for radiologists. There are several important limitations of this study. First, the small number of asymptomatic patients with fractures (28) in the study and how the rates were calculated limit the conclusions that can be drawn. They calculated the rate of asymptomatic fracture in patients aged 65–70 by taking the number of asymptomatic fractures and dividing by the total number of cervical spine CT scans in this age category. However, 758 patients had more than one scan. It is unclear whether this represented serial imaging in the same hospital stay or separate encounters. There is also no detail regarding the indications for the scans, particularly for the repeat scans performed on a single patient. Was there a new trauma mechanism or were these follow-up scans? This changes whether they should be included in the analysis. The authors did not review the 9263 patients without fracture for indications for the scans or to determine if the patients were symptomatic versus asymptomatic. Some scans may not have been performed for trauma. It is also likely that a significant number of these patients would have met indications for scanning other than age and would, therefore, not represent the true burden of asymptomatic scanning. Without the true denominator, it is impossible to accurately estimate the burden in terms of radiology workload. Second, the authors made an estimate of stable versus unstable fracture based on the number who underwent surgical fixation. This is not an accurate proxy for clinically significant fractures, as some significant fractures may be successfully treated with bracing, and some patients may choose not to undergo fixation. Thus, no definitive conclusions can be drawn from the paper on how many clinically significant fractures would have been missed. Third, a retrospective review of the chart may have limited accuracy in determining whether the patient was truly symptomatic or asymptomatic. Copy and pasting and default normal physical examination template usage in the electronic medical record may, unfortunately, make the written record less accurate. Lastly, we must consider other literature on this topic. For example, Healy et al.2 performed a retrospective study of patients aged 55 and older over a 4-year study period. They identified 173 patients with cervical spine fractures, of whom 36 patients (21%) were asymptomatic. The authors concluded that one in five patients with a cervical spine fracture reported no pain on initial presentation and recommended liberal cervical spine imaging for older trauma patients. Kania et al.6 evaluated the concept of scanning the head, cervical spine, and chest/abdomen/pelvis (pan-scan) regardless of physical examination in the elderly with low-energy mechanism. They found that 107/256 asymptomatic patients had an injury identified with imaging and concluded that physical examination lacks adequate sensitivity in the geriatric population. Essentially, we can conclude from the available literature that some clinically significant asymptomatic injuries may be missed when imaging is not performed in patients aged 65 and older. The real, more difficult question is how many injuries are we willing to miss as clinicians? Considering the potential harm of a missed cervical spine injury, this paper lacks sufficient evidence to change practice. However, we should continue to examine our clinical guidelines and gather data to determine whether continued practice is supported or whether the evidence suggests it is time for practice change. Specifically, can we better study the characteristics of asymptomatic patients with injuries to attempt to better identify those whose examinations are less reliable and those that might be sufficiently sensitive to exclude injury? The authors declare no conflicts of interest.
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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 | 0.005 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".