Flow diversion in the treatment of aneurysms: a randomized care trial and registry
Bibliographic record
Abstract
OBJECTIVE The Flow Diversion in the Treatment of Intracranial Aneurysm Trial (FIAT) was designed to guide the clinical use of flow diversion, an innovative method to treat intracranial aneurysms, within a care trial and to study safety and efficacy. METHODS FIAT, conducted in 3 Canadian hospitals, proposed randomized allocation to flow diversion or standard management options (observation, coil embolization, parent vessel occlusion, or clip placement), and a registry of non-randomized patients treated with flow diversion. The primary safety outcome was death or dependency (modified Rankin Scale score > 2) at 3 months, to be determined for all patients who received flow diversion at any time. The primary efficacy outcome was angiographic occlusion at 3-12 months combined with an independent clinical outcome. RESULTS Of 112 participating patients recruited between May 2, 2011, and February 25, 2015, 78 were randomized (39 in each arm), and 34 received flow diversion within the registry. The study was halted due to safety concerns. Twelve (16%) of 75 patients (95% CI 8.9%-26.7%) who were allocated to or received flow diversion at any time were dead (n = 8) or dependent (n = 4) at 3 months or more, crossing a predefined safety boundary. Death or dependency occurred in 5 (13.2%) of 38 patients randomly allocated and treated by flow diversion (95% CI 5.0%-28.9%) and in 5 (12.8%) of 39 patients allocated to standard treatment (95% CI 4.8%-28.2%). Efficacy was below expectations of the trial hypothesis: 16 (42.1%) of 38 patients (95% CI 26.7%-59.1%) randomly allocated to flow diversion failed to reach the primary outcome, as compared with 14 (35.9%) of 39 patients allocated to standard treatment (95% CI 21.7%-52.9%). CONCLUSIONS Flow diversion was not as safe and effective as hypothesized. More randomized trials are needed to determine the role of flow diversion in the management of aneurysms. Clinical trial registration no.: NCT01349582 (clinicaltrials.gov).
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".