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Infarct Volume Predicts Hospitalization Costs in Anterior Circulation Large-Vessel Occlusion Stroke.

ABSTRACT: BACKGROUND AND PURPOSE:Anterior circulation large-vessel occlusion stroke, one of the most devastating stroke subtypes, is associated with substantial economic burden. We aimed to identify predictors of increased acute care hospitalization costs associated with anterior circulation large-vessel occlusion stroke. MATERIALS AND METHODS:Comprehensive cost-tracking software was used to calculate acute care hospitalization costs for patients with anterior circulation large-vessel occlusion stroke admitted July 2012 to October 2014. Patient demographics and stroke characteristics were analyzed, including final infarct volume on follow-up neuroimaging. Predictors of hospitalization costs were determined using multivariable linear regression including subgroup cost analyses by treatment technique (endovascular, IV tPA-only, and no reperfusion therapy) and sensitivity analyses incorporating patients initially excluded due to early withdrawal of care. RESULTS:Three hundred forty-one patients (median age, 69 years; interquartile range, 57-80 years; median NIHSS score, 16; interquartile range, 13-21) were included in our primary analysis. Final infarct volume, parenchymal hematoma, baseline NIHSS score, ipsilateral carotid stenosis, age, and obstructive sleep apnea were significant predictors of acute care hospitalization costs. Final infarct volume alone accounted for 20.87% of the total cost variance. Additionally, final infarct volume was consistently the strongest predictor of increased cost in primary, subgroup, and sensitivity analyses. CONCLUSIONS:Final infarct volume was the strongest predictor of increased hospitalization costs in anterior circulation large-vessel occlusion stroke. Acute stroke therapies that reduce final infarct volume may not only improve clinical outcomes but may also prove cost-effective.

SUBMITTER: Streib CD

PROVIDER: S-EPMC6348151 | biostudies-other | 2019 Jan

REPOSITORIES: biostudies-other

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Infarct Volume Predicts Hospitalization Costs in Anterior Circulation Large-Vessel Occlusion Stroke.

Streib C D CD Rangaraju S S Campbell D T DT Winger D G DG Paolini S L SL Zhang A J AJ Jankowitz B T BT Jadhav A P AP Jovin T G TG

AJNR. American journal of neuroradiology 20181227 1

<h4>Background and purpose</h4>Anterior circulation large-vessel occlusion stroke, one of the most devastating stroke subtypes, is associated with substantial economic burden. We aimed to identify predictors of increased acute care hospitalization costs associated with anterior circulation large-vessel occlusion stroke.<h4>Materials and methods</h4>Comprehensive cost-tracking software was used to calculate acute care hospitalization costs for patients with anterior circulation large-vessel occlu ...[more]

PMID: 30591512

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Project description: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.

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:Importance:Achieving complete reperfusion is a key determinant of good outcome in patients treated with mechanical thrombectomy (MT). However, data on treatments geared toward improving reperfusion after incomplete MT are sparse. Objective:To determine whether administration of intra-arterial urokinase is safe and improves reperfusion after failed or incomplete MT. Design, Setting, and Participants:This observational cohort study included a consecutive sample of patients treated with second-generation MT from January 1, 2010, through August 4, 2017. Data were collected from the prospective registry of a tertiary care stroke center. Of 1274 patients screened, 69 refused to participate, and 993 met the observational studies inclusion criteria of a large vessel occlusion in the anterior circulation. Data were analyzed from September 1, 2017, through September 20, 2019. Intervention:One hundred patients received intra-arterial urokinase after failed or incomplete MT using manual microcatheter injections. Main Outcomes and Measures:Primary safety outcome was the occurrence of symptomatic intracranial hemorrhage (sICH) according to the Prolyse in Acute Cerebral Thromboembolism II criteria. Secondary end points included 90-day mortality and 90-day functional independence (defined as modified Rankin Scale score of ?2). Efficacy was evaluated angiographically, applying the Thrombolysis in Cerebral Infarction (TICI) scale. Results:After exclusion of patients with posterior circulation strokes and those treated with intra-arterial thrombolytics only, 993 patients were included in the final analyses (median age, 74.6 [interquartile range, 62.6-82.2] years; 505 [50.9%] women). Additional intra-arterial urokinase was administered in 100 patients (10.1%). The most common reason for administering intra-arterial urokinase was incomplete reperfusion (TICI<3) after MT (53 [53.0%]). After adjusting for baseline characteristics underlying case selection, intra-arterial urokinase was not associated with an increased risk of sICH (adjusted odds ratio [aOR], 0.81; 95% CI, 0.31-2.13) or 90-day mortality (aOR, 0.78; 95% CI, 0.43-1.40). Among 53 cases of partial or near-complete reperfusion and treated with intra-arterial urokinase, 32 (60.4%) had early reperfusion improvement, and 18 of 53 (34.0%) had an improvement in TICI grade. Correspondingly, patients treated with intra-arterial urokinase had higher rates of functional independence after adjusting for the selection bias favoring a priori poor TICI grades in the intra-arterial urokinase group (aOR, 1.93; 95% CI, 1.11-3.37). Conclusions and Relevance:In selected patients, adjunctive treatment with intra-arterial urokinase during or after MT was safe and improved angiographic reperfusion. Systemic evaluation of this approach in a multicenter prospective registry or a randomized clinical trial seems warranted.

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.

Dataset Information

Infarct Volume Predicts Hospitalization Costs in Anterior Circulation Large-Vessel Occlusion Stroke.

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Infarct Volume Predicts Hospitalization Costs in Anterior Circulation Large-Vessel Occlusion Stroke.

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