Dynamic and visual nomograms to online predict unfavorable outcome of mechanical thrombectomy for acute basilar artery occlusion.

BACKGROUND: The evidence of mechanical thrombectomy (MT) in basilar artery occlusion (BAO) was limited. This study aimed to develop dynamic and visual nomogram models to predict the unfavorable outcome of MT in BAO online. METHODS: BAO patients treated with MT were screened. Preoperative and postoperative nomogram models were developed based on clinical parameters and imaging features. An independent dataset was collected to perform external validation. Web-based calculators were constructed to provide convenient access. RESULTS: A total of 127 patients were included in the study, and 117 of them were eventually included in the analysis. The nomogram models showed robust discrimination, with an area under the receiver operating characteristic (ROC) of 0.841 (preoperative) and 0.916 (postoperative). The calibration curves showed good agreement. The preoperative predictors of an unfavorable outcome were previous stroke, the National Institutes of Health Stroke Scale (NIHSS) at admission, and the posterior circulation Alberta Stroke Program Early Computed Tomography Score (pc-ASPECTS). The postoperative predictors were previous stroke, NIHSS at 24 h, and pc-ASPECTS. CONCLUSION: Dynamic and visual nomograms were constructed and validated for the first time for BAO patients treated with MT, which provided precise predictions for the risk of an unfavorable outcome. The preoperative model may assist clinicians in selecting eligible patients, and the postoperative model may facilitate individualized poststroke management.

Interpretable Machine Learning Model Predicting Early Neurological Deterioration in Ischemic Stroke Patients Treated with Mechanical Thrombectomy: A Retrospective Study.

Early neurologic deterioration (END) is a common and feared complication for acute ischemic stroke (AIS) patients treated with mechanical thrombectomy (MT). This study aimed to develop an interpretable machine learning (ML) model for individualized prediction to predict END in AIS patients treated with MT. The retrospective cohort of AIS patients who underwent MT was from two hospitals. ML methods applied include logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost). The area under the receiver operating characteristic curve (AUC) was the main evaluation metric used. We also used Shapley Additive Explanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) to interpret the result of the prediction model. A total of 985 patients were enrolled in this study, and the development of END was noted in 157 patients (15.9%). Among the used models, XGBoost had the highest prediction power (AUC = 0.826, 95% CI 0.781-0.871). The Delong test and calibration curve indicated that XGBoost significantly surpassed those of the other models in prediction. In addition, the AUC in the validating set was 0.846, which showed a good performance of the XGBoost. The SHAP method revealed that blood glucose was the most important predictor variable. The constructed interpretable ML model can be used to predict the risk probability of END after MT in AIS patients. It may help clinical decision making in the perioperative period of AIS patients treated with MT.

Influence of tirofiban on stroke outcome after mechanical thrombectomy in acute vertebrobasilar artery occlusion.

BACKGROUND: Even undergoing mechanical thrombectomy (MT), patients with acute vertebrobasilar artery occlusion (AVBAO) still have a high rate of mortality. Tirofiban is a novel antiplatelet agent which is now widely empirically used in acute ischemic stroke (AIS). In this study, we aimed to evaluate the safety and efficacy of tirofiban as adjunctive therapy for MT in AVBAO. METHODS: From October 2016 to July 2021, consecutive AVBAO patients receiving MT were included in the prospective stroke registry. The short-term outcomes were (1) symptomatic intracerebral hemorrhage (sICH); (2) in-hospital death; (3) National Institute of Health Stroke Scale (NIHSS) at discharge. The Long-term outcomes were: (1) modified Rankin Scale (mRS) at 3 months; (2) death at 3 months. RESULTS: A total of 130 eligible patients were included in the study, 64 (49.2%) patients received tirofiban. In multivariate regression analysis, no significant differences were observed in all outcomes between the tirofiban and non-tirofiban group [sICH (adjusted OR 0.96; 95% CI, 0.12-7.82, p = 0.97), in-hospital death (adjusted OR 0.57; 95% CI, 0.17-1.89, p = 0.36), NIHSS at discharge (95% CI, -2.14-8.63, p = 0.24), mRS (adjusted OR 1.20; 95% CI, 0.40-3.62, p = 0.75), and death at 3 months (adjusted OR 0.83; 95% CI, 0.24-2.90, p = 0.77)]. CONCLUSIONS: In AVBAO, tirofiban adjunctive to MT was not associated with an increased risk of sICH. Short-term (in-hospital death, NIHSS at discharge) and long-term outcomes (mRS and death at 3 months) seem not to be influenced by tirofiban use.

Machine learning to predict futile recanalization of large vessel occlusion before and after endovascular thrombectomy.

Background and purpose: Futile recanalization occurs when the endovascular thrombectomy (EVT) is a technical success but fails to achieve a favorable outcome. This study aimed to use machine learning (ML) algorithms to develop a pre-EVT model and a post-EVT model to predict the risk of futile recanalization and to provide meaningful insights to assess the prognostic factors associated with futile recanalization. Methods: Consecutive acute ischemic stroke patients with large vessel occlusion (LVO) undergoing EVT at the National Advanced Stroke Center of Nanjing First Hospital (China) between April 2017 and May 2021 were analyzed. The baseline characteristics and peri-interventional characteristics were assessed using four ML algorithms. The predictive performance was evaluated by the area under curve (AUC) of receiver operating characteristic and calibration curve. In addition, the SHapley Additive exPlanations (SHAP) approach and partial dependence plot were introduced to understand the relative importance and the influence of a single feature. Results: A total of 312 patients were included in this study. Of the four ML models that include baseline characteristics, the "Early" XGBoost had a better performance {AUC, 0.790 [95% confidence intervals (CI), 0.677-0.903]; Brier, 0.191}. Subsequent inclusion of peri-interventional characteristics into the "Early" XGBoost showed that the "Late" XGBoost performed better [AUC, 0.910 (95% CI, 0.837-0.984); Brier, 0.123]. NIHSS after 24 h, age, groin to recanalization, and the number of passages were the critical prognostic factors associated with futile recanalization, and the SHAP approach shows that NIHSS after 24 h ranks first in relative importance. Conclusions: The "Early" XGBoost and the "Late" XGBoost allowed us to predict futile recanalization before and after EVT accurately. Our study suggests that including peri-interventional characteristics may lead to superior predictive performance compared to a model based on baseline characteristics only. In addition, NIHSS after 24 h was the most important prognostic factor for futile recanalization.

A novel visual dynamic nomogram to online predict the risk of unfavorable outcome in elderly aSAH patients after endovascular coiling: A retrospective study.

Background: Aneurysmal subarachnoid hemorrhage (aSAH) is a significant cause of morbidity and mortality throughout the world. Dynamic nomogram to predict the prognosis of elderly aSAH patients after endovascular coiling has not been reported. Thus, we aimed to develop a clinically useful dynamic nomogram to predict the risk of 6-month unfavorable outcome in elderly aSAH patients after endovascular coiling. Methods: We conducted a retrospective study including 209 elderly patients admitted to the People's Hospital of Hunan Province for aSAH from January 2016 to June 2021. The main outcome measure was 6-month unfavorable outcome (mRS ≥ 3). We used multivariable logistic regression analysis and forwarded stepwise regression to select variables to generate the nomogram. We assessed the discriminative performance using the area under the curve (AUC) of receiver-operating characteristic and the risk prediction model's calibration using the Hosmer-Lemeshow goodness-of-fit test. The decision curve analysis (DCA) and the clinical impact curve (CIC) were used to measure the clinical utility of the nomogram. Results: The cohort's median age was 70 (interquartile range: 68-74) years and 133 (36.4%) had unfavorable outcomes. Age, using a ventilator, white blood cell count, and complicated with cerebral infarction were predictors of 6-month unfavorable outcome. The AUC of the nomogram was 0.882 and the Hosmer-Lemeshow goodness-of-fit test showed good calibration of the nomogram (p = 0.3717). Besides, the excellent clinical utility and applicability of the nomogram had been indicated by DCA and CIC. The eventual value of unfavorable outcome risk could be calculated through the dynamic nomogram. Conclusion: This study is the first visual dynamic online nomogram that accurately predicts the risk of 6-month unfavorable outcome in elderly aSAH patients after endovascular coiling. Clinicians can effectively improve interventions by taking targeted interventions based on the scores of different items on the nomogram for each variable.

Predicting 6-Month Unfavorable Outcome of Acute Ischemic Stroke Using Machine Learning.

Background and Purpose: Accurate prediction of functional outcome after stroke would provide evidence for reasonable post-stroke management. This study aimed to develop a machine learning-based prediction model for 6-month unfavorable functional outcome in Chinese acute ischemic stroke (AIS) patient. Methods: We collected AIS patients at National Advanced Stroke Center of Nanjing First Hospital (China) between September 2016 and March 2019. The unfavorable outcome was defined as modified Rankin Scale score (mRS) 3-6 at 6-month. We developed five machine-learning models (logistic regression, support vector machine, random forest classifier, extreme gradient boosting, and fully-connected deep neural network) and assessed the discriminative performance by the area under the receiver-operating characteristic curve. We also compared them to the Houston Intra-arterial Recanalization Therapy (HIAT) score, the Totaled Health Risks in Vascular Events (THRIVE) score, and the NADE nomogram. Results: A total of 1,735 patients were included into this study, and 541 (31.2%) of them had unfavorable outcomes. Incorporating age, National Institutes of Health Stroke Scale score at admission, premorbid mRS, fasting blood glucose, and creatinine, there were similar predictive performance between our machine-learning models, while they are significantly better than HIAT score, THRIVE score, and NADE nomogram. Conclusions: Compared with the HIAT score, the THRIVE score, and the NADE nomogram, the RFC model can improve the prediction of 6-month outcome in Chinese AIS patients.

Influence of renal function on stroke outcome after mechanical thrombectomy: a prospective cohort study.

BACKGROUND: For acute ischemic stroke (AIS) patient receiving mechanical thrombectomy (MT), renal dysfunction was an independent risk factor of contrast-induced nephropathy which may affect clinical outcomes. However, the influence of renal function on stroke outcomes is still controversial. Thus, we aim to investigate the association between renal function and outcomes of AIS patients receiving MT. METHODS: All consecutive stroke patients receiving MT were included in a prospective stroke registry in China from April 2015 to February 2019. Estimated glomerular filtration rate (eGFR) was measured on admission and categorized into G1 (≥ 90 ml/min/1.73 m2), G2 (60-89 ml/min/1.73 m2), G3a (45-59 ml/min/1.73 m2) and G3b-5 (≤44 ml/min/1.73 m2). Multivariable logistic regression analysis was performed to evaluate the association between eGFR and recanalization rate (thrombolysis in cerebral infarction scale 2b-3), symptomatic intracranial hemorrhage (sICH), death in hospital, death at 3 months and poor functional outcome (modified Rankin Scale 3-6 at 3 months). RESULTS: A total of 373 patients were included in the study. Of them, 130 (34.9%) patients were in the eGFR group G1, 170 (45.6%) in G2, 46 (12.3%) in G3a, 27 (7.2%) in G3b-5. In multivariable logistic regression analysis, reduced eGFR was associated with increased risk of sICH (G3a, p = 0.016) and 3-month death (G3b-5, p = 0.025). However, no significant effects were observed between reduced eGFR and the risk of recanalization rate (p = 0.855), death in hospital (p = 0.970), and poor functional outcome (p = 0.644). CONCLUSIONS: For AIS patients underwent MT, reduced eGFR was associated with increased risk of sICH and 3-month death. However, there were no appreciable effects of reduced eGFR on recanalization rate, death in hospital and 3-month functional outcome.

A NADE nomogram to predict the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke.

BACKGROUND: Early prediction of unfavorable outcome after ischemic stroke is of great significance to the clinical and therapeutic management. A nomogram is a better visual tool than earlier models and prognostic scores to predict clinical outcomes, which incorporates different factors to develop a graphic continuous scoring system and calculates accurately the risk probability of poor outcome entirely based on individual characteristics. However, to date, no nomogram models have been found to predict the probability of 6-month poor outcome after ischemic stroke. We aimed to develop and validate a nomogram for individualized prediction of the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke. METHODS: Based on the retrospective stroke registry, a single-center study which included 499 patients from May, 2013 to May, 2018 was conducted in Nanjing First Hospital (China) for ischemic stroke within 12 h of symptoms onset. The main outcome measure was 6-month unfavorable outcome (mRS > 2). To generate the nomogram, NIHSS score on admission, Age, previous Diabetes mellitus and crEatinine (NADE) were integrated into the model. We assessed the discriminative performance by using the area under the curve (AUC) of receiver-operating characteristic (ROC) and calibration of risk prediction model by using the Hosmer-Lemeshow test. RESULTS: A visual NADE nomogram was constructed that NIHSS score on admission (OR: 1.190, 95%CI: 1.125-1.258), age (OR: 1.068, 95%CI: 1.045-1.090), previous diabetes mellitus (OR: 1.995, 95%CI: 1.236-3.221) and creatinine (OR: 1.010, 95%CI: 1.002-1.018) were found to be significant predictors of 6-month unfavorable outcome after acute ischemic stroke in Chinese patients. The AUC-ROC of nomogram was 0.791. Calibration was good (p = 0.4982 for the Hosmer-Lemeshow test). CONCLUSION: The NADE is the first nomogram developed and validated in Chinese ischemic stroke patients to provide an individual, visual and precise prediction of the risk probability of 6-month unfavorable outcome.

Safety and efficacy of early antiplatelet therapy in acute ischemic stroke patients receiving endovascular treatment: A systematic review and meta-analysis.

BACKGROUND: Endovascular treatment (ET) has been proved as safety and effective in acute ischemic stroke. However, early reocclusion is an inevitable complication following ET. There is uncertainty effect of early antiplatelet therapy on outcomes in patients with acute ischemic stroke undergoing endovascular treatment. METHODS: We searched major databases for articles published from 2011 to 2019 in the present study. Safety outcomes were any intracranial hemorrhage (ICH), symptomatic intracranial hemorrhage (sICH) and mortality. Efficacy outcomes were recanalization rate and follow-up functional outcome. Review Manager 5.3 and Stata Software Package 14.0 were used to perform the meta-analysis. RESULTS: Seven studies with a total of 1251 patients were included. A total of 451 (36.1%) patients were administrated by antiplatelet agent following ET. Meta-analysis suggested that early antiplatelet did not increase the risk for ICH (OR 1.15; 95% CI 0.56-2.37; P = 0.70), sICH (OR 1.29; 95% CI 0.79-2.09; P = 0.31) and mortality (OR 0.71; 95% CI 0.45-1.12; P = 0.14). There was no association between antiplatelet therapy and recanalization rate (OR 1.03; 95% CI 0.73-1.46; P = 0.30) or functional outcome (OR 0.97; 95% CI 0.55-1.69; P = 0.90). Sensitivity analysis indicated tirofiban did not associated with any ICH and mortality, nor improve the recanalization rate and functional outcome in patients receiving ET or mechanical thrombectomy (all p > 0.05). CONCLUSIONS: Early antiplatelet therapy may be safe in acute ischemic stroke patients, further studies are needed to confirm the efficacy.

Profile and 1-Year Outcome of Ischemic Stroke in East China: Nanjing First Hospital Stroke Registry.

BACKGROUND: The profile and 1-year outcome after acute ischemic stroke (AIS) in Nanjing, China, is uncertain. This study aimed to investigate the profile and outcome after 1-year follow-up of AIS in East China. METHODS: In a prospective cohort study, 2168 patients with AIS were recruited consecutively. The primary outcome was death or dependency defined as a modified Rankin Scale score of 3-6 at 12 months. Plausible risk factors of death or dependency, such as demographics, risk factors of cardiovascular diseases, clinical features, laboratory results, and complications after a stroke, were selected from available variables to perform multivariable logistic regression analyses. RESULTS: Eight hundred thirty-seven (38.6%) patients died or suffered from dependency. Multivariate logistic regression analysis showed that age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.03-1.05), history of diabetes mellitus (OR, 1.50; 95% CI, 1.10-2.04), prior stroke (OR, 2.08; 95% CI, 1.51-2.87), National Institutes of Health Stroke Scale (NIHSS) score (OR, 23.06; 95% CI, 14.24-37.34), estimated glomerular filtration rate (OR, 1.65; 95% CI, 1.02-2.66), pulmonary infection (OR, 2.98; 95% CI, 2.17-4.09), and gastrointestinal bleeding (OR, 7.81; 95% CI, 2.76-22.09) were significantly and independently associated with higher rates of mortality or disability (all P values < .05). Male gender (P values < .001) was the only factor associated with lower mortality or disability. CONCLUSIONS: The main dominating predictors for death or dependency were older age, female gender, diabetes mellitus, prior stroke, NIHSS score, estimated glomerular filtration rate, pulmonary infection, and gastrointestinal bleeding.

Prior antiplatelet agent use and outcomes after intravenous thrombolysis with recombinant tissue plasminogen activator in acute ischemic stroke: a meta-analysis of cohort studies and randomized controlled trials.

BACKGROUND: There is uncertainty surrounding the influence of prior antiplatelet agent use on outcomes after intravenous thrombolysis with recombinant tissue plasminogen activator in acute ischemic stroke. AIM: We performed a systematic review with a final meta-analysis to evaluate the efficacy and safety of prior antiplatelet use before intravenous recombinant tissue plasminogen activator for acute ischemic stroke. SUMMARY OF REVIEW: We searched PubMed and Embase databases from 1997 to 2014. Primary outcome was functional outcome at the end of follow-up; secondary outcomes were symptomatic intracranial hemorrhage and recanalization rate. The meta-analysis was performed with Review Manager 5.2 (Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2012). Eleven studies with a total of 19,453 patients were included. A total of 6517 (33.5%) patients who had received intravenous recombinant tissue plasminogen activator were taking antiplatelet agent before stroke onset. Pooled analysis demonstrated a clear trend that previous antiplatelet users had a reduced probability of good outcome, although it was not conventionally statistically significant (OR 0.86; 95% CI 0.73-1.01; P = 0.06). There was no difference in recanalization rate between two groups (OR 1.23; 95% CI 0.30-4.99; P = 0.77). The risk of symptomatic intracranial hemorrhage was significantly increased in the antiplatelet group (OR 1.65; 95% CI 1.44-1.90; P < 0.01). CONCLUSIONS: In acute ischemic stroke patients receiving intravenous recombinant tissue plasminogen activator therapy, prior antiplatelet agent use did not lead to a significant difference in functional outcome, although it significantly increased the risk of symptomatic intracranial hemorrhage. Recanalization rate was not different between two groups. In the subgroup analysis, prior clopidogrel mono therapy may not increase the risk of symptomatic intracranial hemorrhage, which will need further studies to confirm.