The Treatment of Brain AVMs Study (TOBAS): an all-inclusive framework to integrate clinical care and research
Bibliographic record
Abstract
OBJECTIVE The management of brain arteriovenous malformations (bAVMs) remains controversial. The Treatment of Brain AVMs Study (TOBAS) was designed to manage patients with bAVMs within a clinical research framework. The objective of this study was to study trial feasibility, recruitment rates, patient allocation to the various management groups, and compliance with treatment allocation. METHODS TOBAS combines two randomized care trials (RCTs) and a registry. Designed to be all-inclusive, the study offers randomized allocation of interventional versus conservative management to patients eligible for both options (first RCT), a second RCT testing the role of preembolization as an adjunct to surgery or radiotherapy, and a registry of patients managed using clinical judgment alone. The primary outcome of the first RCT is death from any cause or disabling stroke (modified Rankin Scale score > 2) at 10 years. A pilot phase was initiated at one center to test study feasibility, record the number and characteristics of patients enrolled in the RCTs, and estimate the frequency of crossovers. RESULTS All patients discussed at the multidisciplinary bAVM committee between June 2014 and June 2016 (n = 107) were recruited into the study; 46 in the randomized trials (23 in the first RCT with 21 unruptured bAVMs, 40 in the second RCT with 17 unruptured bAVMs, and 17 in both RCTs), and 61 patients in the registry. Three patients crossed over from surgery to observation (first RCT). CONCLUSIONS Clinical research was successfully integrated with normal practice using TOBAS. Recruitment rates in a single center are encouraging. Whether the trial will provide meaningful results depends on the recruitment of a sufficient number of participating centers. Clinical trial registration no.: NCT02098252 (clinicaltrials.gov).
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 | 0.256 | 0.185 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".