Factors influencing time to computed tomography in emergency department patients with suspected subarachnoid haemorrhage
Bibliographic record
Abstract
BACKGROUND: CT has excellent sensitivity for subarachnoid haemorrhage (SAH) when performed within 6 hours of headache onset, but it is unknown to what extent patients with more severe disease are likely to undergo earlier CT, potentially inflating estimates of sensitivity. Our objective was to evaluate which patient and hospital factors were associated with earlier neuroimaging in alert, neurologically intact ED patients with suspected SAH. METHODS: We analysed data from two large sequential prospective cohorts of ED patients with acute headache undergoing CT for suspected SAH. We examined the time interval from headache onset to CT, both overall and subdivided from headache onset to hospital registration and from registration to CT. RESULTS: Among 2412 patients with headache, 194 had SAH, with 178 identified on unenhanced CT. Of these, 91 (51.1%) were identified by CT within 6 hours of headache onset and 87 after 6 hours. Patients with SAH had a shorter time from headache onset to hospital presentation (median 4.5 hours, IQR 1.7-22.7 vs 9.6 hours, IQR 2.8-46.0, p<0.001) and were imaged sooner after headache onset (6.4 hours, IQR 3.5-27.1 vs 12.6 hours, IQR 5.5-48.0, p<0.001) compared with those without SAH. The median time from in-hospital registration to CT scan was significantly shorter in those patients with SAH although this difference was less than 1 hour (1.9 hours, IQR 1.2-2.8 vs 2.5 hours, IQR 1.5-3.9, p<0.001). Arrival by ambulance (OR 3.1, 95% CI 1.94 to 4.98, p<0.001) and higher acuity at triage (OR 1.39, 95% CI 1.02 to 1.88, p=0.032) were among the factors associated with having CT imaging within 6 hours of headache onset. CONCLUSIONS: Time from headache onset to imaging is moderately associated with positive imaging for SAH. Delay to hospital presentation accounts for the largest fraction of time to imaging, especially those without SAH. These findings suggest limited opportunity to reduce lumbar puncture rates simply by accelerating in-hospital processes when imaging delays are under 2 hours, as diagnostic yield of imaging decreases beyond the 6-hour imaging window from headache onset.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.039 | 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".