Brain arteriovenous malformations associated with hereditary hemorrhagic telangiectasia: Gene–phenotype correlations
Bibliographic record
Abstract
Hereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant genetic disease with a wide spectrum of vascular malformations (VMs) involving multiple organs. Nine to 16% of patients with HHT harbor brain arteriovenous malformations (AVMs), which can cause intracranial hemorrhage (ICH). Our objective was to study clinical manifestations of brain AVMs in patients with HHT and correlate these with the specific gene mutated. We reviewed records of 171 patients with HHT and brain AVMs. A history of ICH was found in 27% (41/152) patients, with a mean age of 26 ± 18 range, (0-68) years. All of patients with ICH were neurologically asymptomatic prior to ICH. Multiple brain AVMs were found in 23% (170/39) of patients on initial examination. Genetic test results were available in 109 (64%) patients. Mutations in ENG, ACVRL1, and SMAD4 were present in 75 (69%), 18 (17%), and 2 (2%), respectively. A history of ICH was reported in 24% of patients with an ENG mutation and 27% of patients with an ACVRL1 mutation, with a mean age of 26 ± 16 (range, 2-50) and 18 ± 21 (0-48) years, respectively. No statistically significant differences in age at first brain AVM diagnosis, prevalence of ICH history, age at ICH, or other manifestations of brain AVMs were observed among gene groups. In conclusion, no evidence for differences in brain AVM characteristics was observed among HHT gene groups, although we cannot exclude clinically important differences. Larger studies are needed to further guide brain AVM screening decisions in patients with HHT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".