Challenges in the Management of Ruptured and Unruptured Brainstem Arteriovenous Malformations
Bibliographic record
Abstract
BACKGROUND: Brainstem arteriovenous malformations are challenging lesions, and benefits of treatment are uncertain. OBJECTIVE: To study the clinical course of Brainstem arteriovenous malformations and the influence of treatments on outcome. METHODS: We reviewed a prospective series of 31 brainstem arteriovenous malformations. Demographic, morphological, and clinical characteristics were recorded. Factors determining initial and final outcomes (modified Rankin Scale), results of treatments (cure rates, complications), and disease course were analyzed. RESULTS: Brainstem arteriovenous malformations were symptomatic and bled in 93% and 61% of cases, respectively. Examination was abnormal and initial modified Rankin Scale score was < 3 in 71% and 86% of patients, respectively. The average follow-up time was 6.2 years, and 26% of patients rebled (5.9 %/y). Treatment modalities included conservative, radiosurgical, endovascular, surgical, and multimodality treatment in 13%, 58%, 35%, 16%, and 26% of cases, respectively. The obliteration rate was 60% overall and 39% after radiosurgery, 40% after embolization, and 75% after microsurgery, with respective complication-free cure rates of 71%, 50%, and 0%. Overall procedural mortality and morbidity were 2.3% and 18.6%, respectively. Final modified Rankin Scale score was < 3 in 77% of cases. Neurological deterioration (35%) was related to treatment complications in 74% of cases with a negative impact of surgery (P = .04), palliative embolization (odds ratio = 16), and multimodality treatments (odds ratio = 24). Radiosurgery was inversely associated with worsening (odds ratio = 0.06). CONCLUSION: Brainstem arteriovenous malformations require individualized treatment decisions. Single-modality treatments with a reasonable chance of complete cure and low complication rate (such as radiosurgery) should be favored.
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 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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".