Functional Outcomes and Symptomatic Intracranial Hemorrhage After Endovascular Treatment in Acute Vertebrobasilar Artery Occlusions: External Validation of Prediction Models
Bibliographic record
Abstract
Background: Vertebrobasilar artery occlusion (VBAO) is a severe type of stroke. Multiple prediction models for outcome and symptomatic intracranial hemorrhage (sICH) of patients with acute ischemic stroke treated with endovascular treatment have been developed to improve patient management, but few are based on VBAO. This study aimed to provide an overview of published models to predict functional outcome and sICH as well as to validate their ability in patients with acute VBAO treated with endovascular treatment. Methods: We performed a systematic search to identify models either developed or validated to predict functional outcomes or sICH after endovascular treatment. Models were externally validated in the Posterior Circulation Ischemic Stroke Registry (PERSIST) study (n = 2422). Outcome measures included the modified Rankin Scale (mRS) score at 90 days and sICH. Model performance was evaluated with discrimination (c-statistic) and calibration (slope and intercept). Results: A total of 65 models were included in overview. The most frequently used predictors were baseline National Institutes of Health Stroke Scale score (n = 57), age (n = 45), and glucose (n = 32). In the external validation cohort, 777 of 2353 patients (33.0%) achieved mRS score 0-2 at 90 days, 1061 of 2353 patients (45.1%) patients achieved mRS score 0-3 at 90 days, and sICH occurred in 170 of 2422 patients (7.0%). Finally, 27 models were included in external validation. For functional outcome models focusing on mRS score 0-2/3-6, discrimination ranged from 0.63 to 0.66 and best calibrated model was SC (Stroke Checkerboard) (intercept, -0.13 [95% CI, -0.27 to 0.01]; slope, 0.92 [95% CI, 0.67-1.17]). For functional outcome models focusing on mRS score 0-3/4-6, discrimination ranged from 0.64 to 0.74 and best calibrated model was modified Houston Intra-Arterial Therapy 2 (mHIAT2) (intercept, -0.12 [95% CI, -0.31 to 0.07]; slope, 0.85 [95% CI, 0.65-1.04]). For sICH models, discrimination ranged from 0.53 to 0.83 and best calibrated model was Thrombolysis in Cerebral Infarction score, Alberta Stroke Program Early CT Score, and glucose (TAG) (intercept, 0.13 [95% CI, -0.25 to 0.51]; slope, 0.93 [95% CI, 0.63-1.23]). Conclusions: The currently published models are inadequate for predicting functional outcomes and sICH in patients with acute VBAO undergoing endovascular treatment and, therefore, there is a need for more effective models specifically developed for VBAO conditions.
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 | 0.050 | 0.105 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".