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Machine Learning-Based Model for Predicting Incidence and Severity of Acute Ischemic Stroke in Anterior Circulation Large Vessel Occlusion.

ABSTRACT: Objectives: Patients with anterior circulation large vessel occlusion are at high risk of acute ischemic stroke, which could be disabling or fatal. In this study, we applied machine learning to develop and validate two prediction models for acute ischemic stroke (Model 1) and severity of neurological impairment (Model 2), both caused by anterior circulation large vessel occlusion (AC-LVO), based on medical history and neuroimaging data of patients on admission. Methods: A total of 1,100 patients with AC- LVO from the Second Hospital of Hebei Medical University in North China were enrolled, of which 713 patients presented with acute ischemic stroke (AIS) related to AC- LVO and 387 presented with the non-acute ischemic cerebrovascular event. Among patients with the non-acute ischemic cerebrovascular events, 173 with prior stroke or TIA were excluded. Finally, 927 patients with AC-LVO were entered into the derivation cohort. In the external validation cohort, 150 patients with AC-LVO from the Hebei Province People's Hospital, including 99 patients with AIS related to AC- LVO and 51 asymptomatic AC-LVO patients, were retrospectively reviewed. We developed four machine learning models [logistic regression (LR), regularized LR (RLR), support vector machine (SVM), and random forest (RF)], whose performance was internally validated using 5-fold cross-validation. The performance of each machine learning model for the area under the receiver operating characteristic curve (ROC-AUC) was compared and the variables of each algorithm were ranked. Results: In model 1, among the included patients with AC-LVO, 713 (76.9%) and 99 (66%) suffered an acute ischemic stroke in the derivation and external validation cohorts, respectively. The ROC-AUC of LR, RLR and SVM were significantly higher than that of the RF in the external validation cohorts [0.66 (95% CI 0.57-0.74) for LR, 0.66 (95% CI 0.57-0.74) for RLR, 0.55 (95% CI 0.45-0.64) for RF and 0.67 (95% CI 0.58-0.76) for SVM]. In model 2, 254 (53.9%) and 31 (37.8%) patients suffered disabling ischemic stroke in the derivation and external validation cohorts, respectively. There was no difference in AUC among the four machine learning algorithms in the external validation cohorts. Conclusions: Machine learning methods with multiple clinical variables have the ability to predict acute ischemic stroke and the severity of neurological impairment in patients with AC-LVO.

SUBMITTER: Cui J

PROVIDER: S-EPMC8675605 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundEndovascular treatment (EVT) for acute ischemic stroke (AIS) patients presenting with Alberta Stroke Program Early CT Score (ASPECTS) 0-5 has not yet proven safe and effective by clinical trials.ObjectivesThe aim of the study was to assess whether EVT in AIS patients presenting with low ASPECTS is beneficial.DesignSystematic review and meta-analysis of available studies in accordance with the PRISMA statement.Data sources and methodsWe have searched MEDLINE, the Cochrane Central Register of Controlled Trials, and reference lists of articles published until 28 May 2022 with the aim to calculate (1) modified Rankin scale (mRS) score 0-3 at 3 months, (2) mRS score 0-2 at 3 months, (3) symptomatic intracranial hemorrhage (sICH), and (3) mortality at 3 months.ResultsOverall, 24 eligible studies were included in the meta-analysis, comprising a total of 2539 AIS patients with ASPECTS 0-5 treated with EVT. The pooled proportion of EVT-treated patients achieving mRS 0-3 at 3 months was calculated at 38.4%. The pooled proportion of EVT-treated patients achieving mRS 0-2 at 3 months was 25.7%. Regarding safety outcomes, sICH occurred in 12.8% of patients. The 3-month pooled mortality was 30%. In pairwise meta-analysis, patients treated with EVT had a higher likelihood of achieving mRS 0-3 at 3 months compared with patients treated with best medical therapy (BMT, OR: 2.41). sICH occurred more frequently in EVT-treated patients compared with the BMT-treated patients (OR: 2.30). Mortality at 3 months was not different between the two treatment groups (OR: 0.71).ConclusionEVT may be beneficial for AIS patients with low baseline ASPECTS despite an increased risk for sICH. Further data from randomized-controlled clinical trials are needed to elucidate the role of EVT in this subgroup of AIS patients.RegistrationThe protocol has been registered in the International Prospective Register of Ongoing Systematic Reviews PROSPERO; Registration Number: CRD42022334417.

Project description:Background and Purpose- Accurate prediction of acute ischemic stroke (AIS) caused by anterior large vessel occlusion (LVO) that is amendable to mechanical thrombectomy remains a challenge. We developed and validated a prediction model for anterior circulation LVO stroke using past medical history elements present on admission and neurological examination. Methods- We retrospectively reviewed AIS patients admitted between 2009 and 2017 to 3 hospitals within a large healthcare system in the United States. Patients with occlusions of the internal carotid artery or M1 or M2 segments of the middle cerebral artery were randomly split into 2/3 derivation and 1/3 validation cohorts for development of an anterior circulation LVO prediction model and score that was further curtailed for potential use in the prehospital setting. Results- A total of 1654 AIS were reviewed, including 248 (15%) with proximal anterior circulation LVO AIS. In the derivation cohort, National Institutes of Health Stroke Scale score at the time of cerebrovascular imaging, current smoking status, type 2 diabetes mellitus, extracranial carotid, and intracranial atherosclerotic stenosis was significantly associated with anterior circulation LVO stroke. The prehospital score was curtailed to National Institutes of Health Stroke Scale score, current smoking status, and type 2 diabetes mellitus. The areas under the curve for the prediction model, prehospital score, and National Institutes of Health Stroke Scale score alone were 0.796, 0.757, and 0.725 for the derivation cohort and 0.770, 0.689, and 0.665 for the validation cohort, respectively. The Youden index J was 0.46 for a score of >6 with 84.7% sensitivity and 62.0% specificity for the prediction model. Conclusions- Previously reported LVO stroke prediction scores focus solely on elements of the neurological examination. In addition to stroke severity, smoking, diabetes mellitus, extracranial carotid, and intracranial atherosclerotic stenosis were associated with anterior circulation LVO AIS. Although atherosclerotic stenosis may not be known until imaging is obtained, smoking and diabetes mellitus history can be readily obtained in the field and represent important elements of the prehospital score supplementing National Institutes of Health Stroke Scale score.

Project description:BackgroundNeurologic symptom severity and deterioration at 24 hours (h) predict long-term outcomes in patients with acute large vessel occlusion (LVO) stroke of the anterior circulation. We aimed to examine the association of baseline multiparametric CT imaging and clinical factors with the course of neurologic symptom severity in the first 24 h after endovascular treatment (EVT).MethodsPatients with LVO stroke of the anterior circulation were selected from a prospectively acquired consecutive cohort of patients who underwent multiparametric CT, including non-contrast CT, CT angiography and CT perfusion before EVT. The symptom severity was assessed on admission and after 24 h using the 42-point National Institutes of Health Stroke Scale (NIHSS). Clinical and imaging data were compared between patients with and without early neurological deterioration (END). END was defined as an increase in ≥4 points, and a significant clinical improvement as a decrease in ≥4 points, compared to NIHSS on admission. Multivariate regression analyses were used to determine independent associations of imaging and clinical parameters with NIHSS score increase or decrease in the first 24 h.ResultsA total of 211 patients were included, of whom 38 (18.0%) had an END. END was significantly associated with occlusion of the internal carotid artery (odds ratio (OR), 4.25; 95% CI, 1.90-9.47) and the carotid T (OR, 6.34; 95% CI, 2.56-15.71), clot burden score (OR, 0.79; 95% CI, 0.68-0.92) and total ischemic volume (OR, 1.01; 95% CI, 1.00-1.01). In a comprehensive multivariate analysis model including periprocedural parameters and complications after EVT, carotid T occlusion remained independently associated with END, next to reperfusion status and intracranial hemorrhage. Favorable reperfusion status and small ischemic core volume were associated with clinical improvement after 24 h.ConclusionsThe use of imaging parameters as a surrogate for early NIHSS progression in an acute LVO stroke after EVT reached limited performance with only carotid T occlusion as an independent predictor of END. Reperfusion status and early complications in terms of intracranial hemorrhage are critical factors that influence patient outcome in the acute stroke phase after EVT.

Project description:ObjectiveTo assess predictive factors for poststroke pneumonia (PSP) in patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) of the anterior circulation, with special regard to the impact of intravenous thrombolysis (IVT) and endovascular treatment (EVT) on the risk of PSP. As a secondary goal, the validity of the A2DS2, PNEUMONIA, and ISAN scores in LVO will be determined.MethodsAnalysis was based on consecutive data for the years 2017 to 2019 from the prospective inpatient stroke registry covering the entire federal state of Hesse, Germany, using the Kruskal-Wallis test and binary logistic regression.ResultsData from 4,281 patients with LVO were included in the analysis (54.8% female, median age = 78 years, range = 18-102), of whom 66.4% (n = 2,843) received recanalization therapy (RCT). In total, 19.4% (n = 832) of all LVO patients developed PSP. Development of PSP was associated with an increase in overall in-hospital mortality of 32.1% compared with LVO patients without PSP (16.4%; p < 0.001). Incidence of PSP was increased in 2132 patients with either EVT (n = 928; 25.9% PSP incidence) or combined EVT plus IVT (n = 1,204; 24.1%), compared with 2,149 patients with IVT alone (n = 711; 15.2%) or conservative treatment only (n = 1,438; 13.5%; p < 0.001). Multivariate analysis identified EVT (OR 1.5) and combined EVT plus IVT (OR 1.5) as significant independent risk factors for PSP. Furthermore, male sex (OR 1.9), age ≥ 65 years (OR 1.7), dysphagia (OR 3.2) as well as impaired consciousness at arrival (OR 1.7) and the comorbidities diabetes (OR 1.4) and atrial fibrillation (OR 1.3) were significantly associated risk factors (each p < 0.001). Minor stroke (NIHSS ≤ 4) was associated with a significant lower risk of PSP (OR 0.5). Performance of risk stratification scores varied between A2DS2 (96.1% sensitivity, 20.7% specificity), PNEUMONIA (78.2% sensitivity and 45.1% specificity) and ISAN score (98.0% sensitivity, 20.0% specificity).ConclusionNearly one in five stroke patients with LVO develops PSP during acute care. This risk of PSP is further increased if an EVT is performed. Other predictive factors are consistent with those previously described for all AIS patients. Available risk stratification scores proved to be sensitive tools in LVO patients but lack specificity.

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Machine Learning-Based Model for Predicting Incidence and Severity of Acute Ischemic Stroke in Anterior Circulation Large Vessel Occlusion.

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