External Validation of Multiple Predictive Models in AIS Patients Undergoing Intravenous Thrombolysis
Notice bibliographique
Résumé
Abstract Background and Purpose-ASPECTS (Alberta Stroke Program Early CT Score), ASTRAL (Acute Stroke Registry and Analysis of LausanneL), DRAGON (including intensive middle cerebral artery sign, pre-stroke modified Rankin Scale score, age, glucose, onset to treatment, NIH Stroke Scale score), THRIVE-c (Total Health Risks in Vascular Events- calculation score) and START (NIHSS Stroke Scale score, Age, pre-stroke mRS score, onset-to-treatment Time) are predictive models that have been gradually developed in recent years to predict functional outcome after acute stroke in patients treated with intravenous thrombolysis, respectively. We aimed to externally validate these scores to assess their predictive performance in this advanced stroke center in China. Methods- We examined the clinical data of 835 patients with AIS who were admitted to the emergency department for intravenous thrombolysis at the Advanced Stroke Center, First Central Hospital, Baoding, China, between January 2016 and May 2022, and scored the patients using the ASPECTS, ASTRAL, DRAGON, THRIVE-c, and START scales. The 3-month modified Rankin Scale scores were observed for each score point, and patients with scores 3 to 6 were defined as having a poor prognosis and compared with the proportions predicted based on risk scores. The ROC curve was used to analyze the predictive value of each score for poor prognosis at 3 months. The total area under the ROC curve showed that it was the C value, and the C value was compared with the predictive value of the five scores; The Hosmer-Lemeshow (H-L) goodness-of-fit [χ2 (P)] test was applied to evaluate the fit of each model to the actual results; two indicators, the calibration curve and the Brier score, were used to evaluate the calibration of the models. Multivariate logistic regression coefficients for the variables in the five scores were also compared with the original derivation cohort. Results-Finally, 728 patients were included, and 318 (43.68%) had a poor prognosis. roc curve analysis, ASPECTS, ASTRAL, DRAGON, THRIVE-c, and START scores corresponded to C values of 0.851, 0.825, 0.854, 0.809, and 0819 in the overall patients, respectively, and in the pre-circulation 0.853, 0.813, 0.833, 0.804, 0.807, and 0.848, 0.862, 0.909, 0.811, 0.857 in the posterior cycle, respectively (all P > 0.05).Hosmer-Lemeshow goodness-of-fit tests for ASPECTS, ASTRAL, DRAGON, THRIVE-c, and START scores with P values of P < 0.001, 0.000365, 0.8245, P < 0.001, P < 0.001, and P < 0.001, respectively, in the pre-loop, P < 0.001, 0.005187, 0.4182, P < 0.001, P < 0.001, and P < 0.001, respectively, in the post-loop, P < 0.0008213, 0.3502, and 0.7645, P < 0.001, P < 0.001. Brier scores, 0.2406, 0.0264, 0.1691, 0.2938, 0.2266 for ASPECTS, ASTRAL, THRIVE-c, DRAGON, START models, respectively. Conclusions-All five score prediction models, ASPECTS, ASTRAL, DRAGON, THRIVE-c, and START, predicted the 3-month adverse prognostic risk in AIS patients undergoing intravenous thrombolysis in both anterior circulation and posterior circulation lesions, but the DRAGON score had the highest predictive diagnostic value in the posterior circulation. the DRAGON score had the highest predictive models predicted prognosis in good agreement with the actual probabilities, and the calibration of the remaining four prediction models was less than optimal.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,027 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,005 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».