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Prediction of early neurological deterioration in acute ischemic stroke patients treated with intravenous thrombolysis.

ABSTRACT: A proportion of acute ischemic stroke (AIS) patients suffer from early neurological deterioration (END) within 24 hours following intravenous thrombolysis (IVT), which greatly increases the risk of poor prognosis of these patients. Therefore, we aimed to explore the predictors of early neurological deterioration of ischemic origin (END_i) in AIS patients after IVT and develop a nomogram prediction model. This study collected 244 AIS patients with post-thrombolysis END_i as the derivation cohort and 155 patients as the validation cohort. To establish a nomogram prediction model, risk factors were identified by multivariate logistic regression analysis. The results showed that neutrophil to lymphocyte ratio (NLR) (OR 2.616, 95% CI 1.640-4.175, P < 0.001), mean platelet volume (MPV) (OR 3.334, 95% CI 1.351-8.299, P = 0.009), body mass index (BMI) (OR 1.979, 95% CI 1.285-3.048, P = 0.002) and atrial fibrillation (AF) (OR 8.012, 95% CI 1.341-47.873, P = 0.023) were significantly associated with END_i. The area under the curve of the prediction model constructed from the above four factors was 0.981 (95% CI 0.961-1.000) and the calibration curve was close to the ideal diagonal line. Therefore, this nomogram prediction model exhibited good discrimination and calibration power and might be a reliable and easy-to-use tool to predict post-thrombolysis END_i in AIS patients.

SUBMITTER: Tian T

PROVIDER: S-EPMC10925869 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Prediction of early neurological deterioration in acute ischemic stroke patients treated with intravenous thrombolysis.

Tian Tian T Wang Lanjing L Xu Jiali J Jia Yujie Y Xue Kun K Huang Shuangfeng S Shen Tong T Luo Yumin Y Li Sijie S Min Lianqiu L

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism 20230905 12

A proportion of acute ischemic stroke (AIS) patients suffer from early neurological deterioration (END) within 24 hours following intravenous thrombolysis (IVT), which greatly increases the risk of poor prognosis of these patients. Therefore, we aimed to explore the predictors of early neurological deterioration of ischemic origin (END<sub>i</sub>) in AIS patients after IVT and develop a nomogram prediction model. This study collected 244 AIS patients with post-thrombolysis END<sub>i</sub> as th ...[more]

PMID: 37668997

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Project description:BackgroundThis investigation seeks to ascertain the efficacy of various machine learning models in forecasting early neurological deterioration (END) following thrombolysis in patients with acute ischemic stroke (AIS).MethodsEmploying data from the Shenyang Stroke Emergency Map database, this multicenter study compiled information on 7,570 AIS patients from 29 comprehensive hospitals who received thrombolytic therapy between January 2019 and December 2021. An independent testing cohort was constituted from 2,046 patients at the First People's Hospital of Shenyang. The dataset incorporated 15 pertinent clinical and therapeutic variables. The principal outcome assessed was the occurrence of END post-thrombolysis. Model development was executed using an 80/20 split for training and internal validation, employing classifiers like logistic regression with lasso regularization (lasso regression), support vector machine (SVM), random forest (RF), gradient-boosted decision tree (GBDT), and multi-layer perceptron (MLP). The model with the highest area under the curve (AUC) was utilized to delineate feature significance.ResultsBaseline characteristics showed variability in END incidence between the training (n = 7,570; END incidence 22%) and external validation cohorts (n = 2,046; END incidence 10%; p < 0.001). Notably, all machine learning models demonstrated superior AUC values compared to the reference model, indicating their enhanced predictive capacity. The lasso regression model achieved the highest AUC at 0.829 (95% CI: 0.799-0.86; p < 0.001), closely followed by the MLP model with an AUC of 0.828 (95% CI: 0.799-0.858; p < 0.001). The SVM, RF, and GBDT models also showed commendable AUCs of 0.753, 0.797, and 0.774, respectively. Decision curve analysis revealed that the SVM and MLP models demonstrated a high net benefit. Feature importance analysis emphasized "Onset To Needle Time" and "Admission NIHSS Score" as significant predictors.ConclusionOur research establishes the MLP and lasso regression as robust tools for predicting early neurological deterioration in acute ischemic stroke patients following thrombolysis. Their superior predictive accuracy, compared to traditional models, highlights the significant potential of machine learning approaches in refining prognosis and enhancing clinical decisions in stroke care management. This advancement paves the way for more tailored therapeutic strategies, ultimately aiming to improve patient outcomes in clinical practice.

Project description:ImportanceThe best reperfusion strategy in patients with acute minor stroke and large vessel occlusion (LVO) is unknown. Accurately predicting early neurological deterioration of presumed ischemic origin (ENDi) following intravenous thrombolysis (IVT) in this population may help to select candidates for immediate transfer for additional thrombectomy.ObjectiveTo develop and validate an easily applicable predictive score of ENDi following IVT in patients with minor stroke and LVO.Design, setting, and participantsThis multicentric retrospective cohort included 729 consecutive patients with minor stroke (National Institutes of Health Stroke Scale [NIHSS] score of 5 or less) and LVO (basilar artery, internal carotid artery, first [M1] or second [M2] segment of middle cerebral artery) intended for IVT alone in 45 French stroke centers, ie, including those who eventually received rescue thrombectomy because of ENDi. For external validation, another cohort of 347 patients with similar inclusion criteria was collected from 9 additional centers. Data were collected from January 2018 to September 2019.Main outcomes and measuresENDi, defined as 4 or more points' deterioration on NIHSS score within the first 24 hours without parenchymal hemorrhage on follow-up imaging or another identified cause.ResultsOf the 729 patients in the derivation cohort, 335 (46.0%) were male, and the mean (SD) age was 70 (15) years; of the 347 patients in the validation cohort, 190 (54.8%) were male, and the mean (SD) age was 69 (15) years. In the derivation cohort, the median (interquartile range) NIHSS score was 3 (1-4), and the occlusion site was the internal carotid artery in 97 patients (13.3%), M1 in 207 (28.4%), M2 in 395 (54.2%), and basilar artery in 30 (4.1%). ENDi occurred in 88 patients (12.1%; 95% CI, 9.7-14.4) and was strongly associated with poorer 3-month outcomes, even in patients who underwent rescue thrombectomy. In multivariable analysis, a more proximal occlusion site and a longer thrombus were independently associated with ENDi. A 4-point score derived from these variables-1 point for thrombus length and 3 points for occlusion site-showed good discriminative power for ENDi (C statistic = 0.76; 95% CI, 0.70-0.82) and was successfully validated in the validation cohort (ENDi rate, 11.0% [38 of 347]; C statistic = 0.78; 95% CI, 0.70-0.86). In both cohorts, ENDi probability was approximately 3%, 7%, 20%, and 35% for scores of 0, 1, 2 and 3 to 4, respectively.Conclusions and relevanceThe substantial ENDi rates observed in these cohorts highlights the current debate regarding whether to directly transfer patients with IVT-treated minor stroke and LVO for additional thrombectomy. Based on the strong associations observed, an easily applicable score for ENDi risk prediction that may assist decision-making was derived and externally validated.

Project description:BackgroundEarly neurologic deterioration occurs in up to one-third of patients with acute ischemic stroke (IS), often leading to poor functional outcomes. At present, few studies have applied amide proton transfer (APT) imaging to the evaluation of early neurological deterioration (END). This study analyzed the value of computed tomography perfusion (CTP) combined with multimodal magnetic resonance imaging (MRI) in patients with acute IS with END.MethodsThis retrospective study included patients with acute IS who were admitted to the neurology inpatient department in a tertiary hospital from October 2021 to June 2023. Patients with acute IS underwent CTP within 24 hours of stroke onset and MRI [arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), and APT] within 7 days. END was defined as an elevation of ≥2 points on the National Institute of Health Stroke Scale (NIHSS) within 7 days of stroke onset. Univariable and multivariable analyses were used to compare clinical and imaging biomarkers in patients with acute IS with and without END. The performance of potential biomarkers in distinguishing between the two groups was evaluated using receiver operating characteristic (ROC) curve analysis.ResultsAmong the 70 patients with acute IS, 20 (29%) had END. After conducting univariable analysis, variables were selected for entry into a binary logistic regression analysis based on our univariable analysis results, previous research findings, clinical experience, and methodological standards. The results indicated that relative cerebral blood volume (CBV) on CTP, relative cerebral blood flow (CBF) on ASL, and relative signal intensity on amide proton transfer-weighted (APTw) imaging were independent risk factors for END. The areas under the ROC curves for these risk factors were 0.710 [95% confidence interval (CI): 0.559-0.861, P=0.006], 0.839 (95% CI: 0.744-0.933, P<0.001), and 0.804 (95% CI: 0.676-0.932, P<0.001), respectively. The combined area under the curve (AUC), sensitivity, and specificity of the four indices (0.941, 100%, and 78%, respectively) were higher than those of the four indices alone.ConclusionsCTP combined with multi-modal MRI better evaluated hemodynamics, tissue metabolism, and other relevant patient information, providing an objective basis for the clinical assessment of patients with acute IS with END and facilitating the development of accurate and personalized treatment plans.

Dataset Information

Prediction of early neurological deterioration in acute ischemic stroke patients treated with intravenous thrombolysis.

Publications

Prediction of early neurological deterioration in acute ischemic stroke patients treated with intravenous thrombolysis.

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