Construction of a prognostic prediction model of endovascular mechanical thrombectomy for acute anterior circulation ischemic stroke based on collateral circulation score and clinical features
Notice bibliographique
Résumé
Objective To investigate the prognostic factors influencing patients who were diagnosed with acute ischemic stroke with anterior circulation large vessel occlusion (AIS-ACLVO) and underwent endovascular mechanical thrombectomy, and to construct a novel scoring model that incorporates collateral circulation score and clinical features for predicting patient prognosis. Methods This retrospective study included 159 patients with AIS-ACLVO who were admitted to the Emergency Stroke Green Channel or Neurology Department of Xuzhou Central Hospital and underwent endovascular mechanical thrombectomy from January 2021 to December 2023. According to the 90-day modified Rankin Scale (mRS) score, the patients were divided into two groups: a good prognosis group (mRS scores 0-2, n=68) and a poor prognosis group (mRS scores 3-6, n=91). Univariate analysis was used to identify factors influencing treatment outcomes, and the Boruta algorithm was applied to screen predictive variables related to the outcome indicators. Multivariate logistic regression was used to determine the independent risk factors for 90-day clinical prognosis of AIS-ACLVO patients after endovascular mechanical thrombectomy, and a prediction model was constructed. The model's discrimination was assessed using the area under the receiver operating characteristic (ROC) curve (AUC), and its calibration was evaluated using calibration curves. A nomogram was constructed. Results Univariate and Boruta algorithm analysis showed that age, smoking history, blood glucose level at admission, baseline National Institutes of Health Stroke Scale (NIHSS) score, lymphocyte ratio, Alberta Stroke Program Early CT Score (ASPECTS), Tan score, and the interval from onset to admission were closely related to prognosis.The above indicators were incorporated into the multivariate logistic regression analysis, which demonstrated that smoking history, baseline NHISS score, blood glucose level at admission, ASPECTS, Tan score, and the interval from onset to admission were independent risk factors for the 90-day clinical prognosis of patients with AIS-ACLVO after endovascular mechanical thrombectomy. The established prediction model showed an AUC of 0.918 (95%CI: 0.876~0.960,P<0.001), with a sensitivity of 0.901, a specificity of 0.794, and a maximum Youden index of 0.695. The calibration curve of the model approximated with the ideal curve. Decision curve analysis suggested that the model has clinical utility. Conclusions Smoking history, baseline NHISS score, blood glucose level at admission, ASPECTS, Tan score, and the interval from onset to admission are independent risk factors for 90-day clinical prognosis of AIS-ACLVO patients after endovascular mechanical thrombectomy. The predictive model based on collateral circulation score and clinical features has certain predictive value for assessing the 90-day clinical prognosis of AIS-ACLVO patients after endovascular mechanical thrombectomy.
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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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».