CT Angiography-for-All: Beyond “Diagnostic Nihilism” in Acute Intracerebral Hemorrhage Care – A Personal View
Bibliographic record
Abstract
INTRODUCTION: The role of CTA in acute intracerebral hemorrhage (ICH) remains debated, yet its benefits are clear. In this viewpoint, we provide a case for the routine use of CTA in the initial assessment of patients with acute ICH. METHOD: To argue for the clinical value of immediate CTA in acute ICH, six key domains were considered: (i) diagnostic performance (does it improve diagnosis?), (ii) prognostic performance (does it improve prognosis?), (iii) predictive performance (does it predict the treatment effect of an intervention?), (iv) safety (does it pose any risks?), (v) costs (is it too expensive?), and (vi) implementation (is it practical to implement?). RESULTS: CTA (i) enhances the etiological diagnosis of ICH, allowing prompt and appropriate early secondary prevention and specific acute treatment, (ii) improves prognostication, (iii) enables better prediction of ICH expansion with possible implications for acute treatment effect, and (iv) has a favorable safety profile, with minimal concern for contrast nephropathy, radiation exposure, or procedural delay, (v) a CTA-for-all-ICH approach seems economically justified, and (vi) its implementation is straightforward - simply continue the ischemic stroke imaging protocol. CONCLUSION: We advocate for routine CTA in all suspected stroke cases - ischemic or hemorrhagic - supporting a unified "CTA-for-all" approach. Minimizing imaging in ICH ("diagnostic nihilism") reflects the same mindset that once limited early treatment ("therapeutic nihilism"), contributing to persistently poor outcomes in this population.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".