Outcomes of Endovascular Treatments of Aneurysms: Observer Variability and Implications for Interpreting Case Series and Planning Randomized Trials
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Angiographic results are commonly used as a surrogate marker of success of coiling of intracranial aneurysms. Inter- and intraobserver agreement in judging angiographic results remain poorly characterized. Our goal was to offer such an evaluation of a grading scale commonly used to evaluate results of endovascular treatment of aneurysms. MATERIALS AND METHODS: A portfolio of 90 angiographic images from 45 patients selected from the core lab data base of a randomized trial was sent to 12 observers on 2 occasions more than 3 months apart. The variability of a 3-value grading scale used to score angiographic results and of a final judgment regarding the presence of a recurrence was studied using κ statistics. RESULTS: Ten participants responded once and 6 responded twice. Agreement was poor to moderate (κ = 0.28-0.5) for senior and junior observers judging angiographic results immediately or 12-18 months after treatment. Agreement reached a reassuring "substantial" (κ = 0.62) level, with a dichotomous presence-absence of a major recurrence, and intraobserver agreement was better in experienced core lab assessors. CONCLUSIONS: There is an important variability in the assessment of angiographic outcomes of endovascular treatments, rendering comparisons between publications risky, if not invalid. A simple dichotomous judgment can be used as a surrogate outcome in randomized trials designed to assess the value of new endovascular devices.
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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 | 0.717 | 0.877 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".