Predicting Functional Outcome Based on Linked Data After Acute Ischemic Stroke: S-SMART Score.
Functional outcome
Ischemic stroke
Prediction score
Stroke registry
Journal
Translational stroke research
ISSN: 1868-601X
Titre abrégé: Transl Stroke Res
Pays: United States
ID NLM: 101517297
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
06
02
2020
accepted:
06
04
2020
revised:
30
03
2020
pubmed:
20
4
2020
medline:
25
2
2023
entrez:
20
4
2020
Statut:
ppublish
Résumé
Prediction of outcome after stroke may help clinicians provide effective management and plan long-term care. We aimed to develop and validate a score for predicting good functional outcome available for hospitals after ischemic stroke using linked data. A total of 22,005 patients with acute ischemic stroke from the Clinical Research Center for Stroke Registry between July 2007 and December 2014 were included in the derivation group. We assessed functional outcomes using a modified Rankin scale (mRS) score at 3 months after ischemic stroke. We identified predictors related to good 3-month outcome (mRS score ≤ 2) and developed a score. External validations (geographic and temporal validations) of the developed model were performed. The prediction model performance was assessed using the area under the receiver operating characteristic curve (AUC) and the calibration test. Stroke severity, sex, stroke mechanism, age, pre-stroke mRS, and thrombolysis/thrombectomy treatment were identified as predictors for 3-month good functional outcomes in the S-SMART score (total 34 points). Patients with higher S-SMART scores had an increased likelihood of a good outcome. The AUC of the prediction score was 0.805 (0.798-0.811) in the derivation group and 0.812 (0.795-0.830) in the geographic validation group for good functional outcome. The AUC of the model was 0.812 (0.771-0.854) for the temporal validation group. Moreover, they had good calibration. The S-SMART score is a valid and useful tool to predict good functional outcome following ischemic stroke. This prediction model may assist in the estimation of outcomes to determine care plans after stroke.
Identifiants
pubmed: 32306239
doi: 10.1007/s12975-020-00815-y
pii: 10.1007/s12975-020-00815-y
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1296-1305Subventions
Organisme : Ministry of Health and Welfare
ID : HI 16C1078
Pays : International
Organisme : Asan Institute for Life Sciences, Asan Medical Center
ID : 2015-9003
Pays : International