Clinical and subclinical microemboli following neuroangiography in children
Bibliographic record
Abstract
BACKGROUND: To assess the frequency, imaging appearances, and risk factors of brain microemboli following pediatric neuroangiography, as assessed by early diffusion-weighted MRI imaging (DWI). METHODS: This single-center, retrospective analysis investigated early DWI post-pediatric neuroangiography. Patients aged 0-18 years who had diagnostic neuroangiography and DWI within a week postprocedure were included. Data on clinical and procedural parameters and MRI findings were recorded. Univariate and multivariate analyses were performed on the following risk factors: age, weight, vasculopathy, antiplatelet drug use, access type, intraprocedural heparin, procedure duration, neck arteries catheterized, and angiographic runs. A p-value<0.05 indicated statistical significance. RESULTS: Eighty-two children were included (40.2% female), mean age 10.1±4.5 years (range: 7 months-17 years). There were no intraprocedural thromboembolic complications recognized. DWI positivity was seen following 3.6% (3/82) procedures: two with transient symptoms, and one instance of silent microemboli. There were no territorial infarcts or clinical stroke. Children with underlying vasculopathy had a higher risk of microemboli from angiography than children without vasculopathy (OR 31.6, p=0.02), and the OR of microemboli following transradial angiography was 79.1 (p=0.005) as compared with transfemoral angiography. Univariate and multivariate analysis showed a significant association between microemboli and number of angiographic runs (p=0.004). Follow-up MRI in all three patients showed no residual abnormal signal. CONCLUSIONS: Cerebral microemboli are unusual following uncomplicated neuroangiography in children. However, in the presence of underlying vasculopathy and with transradial technique, the incidence approaches that reported in the adult literature. An increased association with the number of angiographic runs is an important and controllable factor.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| 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) | 0.000 | 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".