Abstract TP187: Automated Assessment of Intracerebral Hemorrhage Volumes using the VIOLA tool Performs Similarly to ABC/2 in Predictive Modelling
Notice bibliographique
Résumé
Introduction: Hemorrhage volume is a key prognostic characteristic for intracerebral hemorrhage (ICH) patients and has been included as an aspect of critical assessments, such as the ICH score. Hemorrhage measurement can be time consuming, prompting the value of automated hemorrhage assessment tools. Many of these, however, remain unvalidated in predictive models. We compared the performance of the VIOLA deep learning model (developed at www.crai.no) against the conventional ABC/2 method. Methods: An ICH group was created by randomly sampling from the Registry for Neurological Endpoint Assessment among patients with Ischemic and Hemorrhagic Stroke (REINAH) database, which that includes completed hemorrhage characteristic assessments (location, laterality, volume calculated via ABC/2, and intraventricular hemorrhage (IVH) presence). Computed tomography (CT) images used for ABC/2 calculations were retrieved, and the previous trained VIOLA deep learning tool was deployed locally to calculate the volume of parenchymal and intraventricular hemorrhage. ICH volumes were compared using the Wilcoxon Signed Rank test, and separate multivariable logistic regression models to predict in-hospital mortality were fit, including patient demographics, comorbidities, clinical characteristics, and volume quartiles, and adjusted odds ratios are reported. Akaike information criteria (AIC) was used to compare separate ABC/2 and VIOLA models. Results: A total of 407 patients were retrieved from RIENAH. Included patients had a median age of 68 [55-77], were 42.8% female, 43.7% White, 18.7% Black, 22.4% Hispanic, 9.6% Asian, and 5.7% Other/Declined. IVH was present in 48.4% of the cohort and 24.6% experienced in-hospital mortality. Hemorrhages assessed via VIOLA yielded a median of 23.70 [7.02-69.18] cm 3 , significantly higher than those determined by ABC/2 (14.33 [5.19-37.47] cm 3 ,p<0.001), and more patients showed volumes over 30cm 3 using VIOLA (78 (43.7%) vs 131 (32.2%)). In logistic regression modelling, patients with top-quartile hemorrhage volumes in either ABC/2 or VIOLA assessment had higher odds of in-hospital mortality (ABC/2 aOR: 3.32 [1.01-10.94]; VIOLA: 4.50 [1.33-15.19]). The VIOLA-based model showed similar AIC to the ABC/2 model, indicating roughly equivalent model fit (263.9 vs 261.9) Discussion: Hemorrhage volume assessment using the VIOLA tool performed comparably than ABC/2 in prognostic modelling and provides a viable alternative to manual assessment.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».