Reliability of CT Angiography in Cerebral Vasospasm: A Systematic Review of the Literature and an Inter- and Intraobserver Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Computed tomography angiography offers a non-invasive alternative to DSA for the assessment of cerebral vasospasm following subarachnoid hemorrhage but there is limited evidence regarding its reliability. Our aim was to perform a systematic review (Part I) and to assess (Part II) the inter- and intraobserver reliability of CTA in the diagnosis of cerebral vasospasm. MATERIALS AND METHODS: In Part I, articles reporting the reliability of CTA up to May 2018 were systematically searched and evaluated. In Part II, 11 raters independently graded 17 arterial segments in each of 50 patients with SAH for the presence of vasospasm using a 4-category scale. Raters were additionally asked to judge the presence of any moderate/severe vasospasm (≥ 50% narrowing) and whether findings would justify augmentation of medical treatment or conventional angiography ± balloon angioplasty. Four raters took part in the intraobserver reliability study. RESULTS: In Part I, the systematic review revealed few studies with heterogeneous vasospasm definitions. In Part II, we found interrater reliability to be moderate at best (κ ≤ 0.6), even when results were stratified according to specialty and experience. Intrarater reliability was substantial (κ > 0.6) in 3/4 readers. In the per arterial segment analysis, substantial agreement was reached only for the middle cerebral arteries, and only when senior raters' judgments were dichotomized (presence or absence of ≥50% narrowing). Agreement on the medical or angiographic management of vasospasm based on CTA alone was less than substantial (κ ≤ 0.6). CONCLUSIONS: The diagnosis of vasospasm using CTA alone was not sufficiently repeatable among observers to support its general use to guide decisions in the clinical management of patients with SAH.
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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 | 0.048 | 0.196 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".