Predictive Model of Early Neurological Deterioration in Patients with Acute Ischemic Stroke: A Retrospective Cohort Study

A novel score to predict progression in anterior circulation single subcortical infarction patients

OBJECTIVE

Progressive infarction (PI) has a negative effect on functional prognosis. Our study aimed to develop and validate a risk score for predicting PI in patients with anterior circulation single subcortical infarction (ACSSI).

METHODS

Between January 2020 and October 2022, we retrospectively enrolled 638 eligible patients with ACSSI. Two-thirds of the eligible patients were randomly allocated to the training cohort (n = 425). Another resampling sample was formed through the bootstrap method and was used as the validation group (n = 425). Multivariate logistic regression analysis was used to identify the independent factors associated with PI. Each factor was then point assigned based on β-coefficient and a risk scoring system was developed. This scoring system was internally validated through 1000-bootstrap resamplings. The C-statistic and Hosmer-Lemeshow test were used to assess model discrimination and calibration.

RESULTS

PI occurred in 121 patients, accounting for 19.0% of the total patients. A 7-point NTS score system based on the initial NIHSS score, triglyceride-glucose index, and the number of infarct slices on axial diffusion-weighted imaging was developed. The NTS score showed good discrimination and calibration in the training cohort (C-statistic = 0.686; p value of Hosmer-Lemeshow test = 0.797) and validation cohort (C-statistic = 0.681; p value of Hosmer-Lemeshow test = 0.451). The three risk levels for predicting PI in the training and validation cohorts based on NTS score were as follows: low (0-2, 9.6% vs. 9.3%), intermediate (3-5, 28.2% vs. 26.7%), and high risk (6-7, 60.2% vs. 57.4%).

INTERPRETATION

The NTS score is a valid and convenient risk score for predicting PI in ACSSI patients.

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

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 (ENDi) in AIS patients after IVT and develop a nomogram prediction model. This study collected 244 AIS patients with post-thrombolysis ENDi 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 ENDi. 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 ENDi in AIS patients.

Post-thrombolysis early neurological deterioration occurs with or without hemorrhagic transformation in acute cerebral infarction: risk factors, prediction model and prognosis

Objectives

Early neurological deterioration (END) after ischemic stroke is a severe clinical event and can be caused by hemorrhagic and ischemic injury. We studied the difference between the risk factors of END occurs with or without hemorrhagic transformation after intravenous thrombolysis.

Materials and methods

Consecutive cerebral infarction patients who underwent intravenous thrombolysis from 2017 to 2020 in our hospital were retrospectively recruited. END was defined as a ≥2 points increase on 24-h National Institutes of Health Stroke Scale (NIHSS) score after therapy compared with the best neurological status after thrombolysis and divided into two types based on the computed tomography (CT): symptomatic intracranial hemorrhage (ENDh) and non-hemorrhagic factors (ENDn). Potential risk factors of ENDh and ENDn were assessed by multiple logistic regression and applied to establish the prediction model.

Results

A total of 195 patients were included. In multivariate analysis, the previous history of cerebral infarction (odds ratio [OR],15.19; 95% confidence interval [CI],1.43-161.17; P = 0.025), previous history of atrial fibrillation (OR,8.43; 95%CI,1.09-65.44; P = 0.043), higher baseline NIHSS score (OR,1.19; 95%CI,1.03-1.39; P = 0.022) and higher alanine transferase level (OR,1.05; 95%CI, 1.01-1.10; P = 0.016) were independently associated with ENDh. While higher systolic blood pressure (OR,1.03; 95%CI,1.01-1.05; P = 0.004), higher baseline NIHSS score (OR,1.13; 95%CI,2.86-27.43; P < 0.000) and large artery occlusion (OR,8.85, 95%CI,2.86-27.43; P < 0.000) were independent risk factors of ENDn. The prediction model showed good specificity and sensitivity in predicting the risk of ENDn.

Conclusions

There are differences between the major contributors to ENDh and ENDn, while a severe stroke can increase the occurrence of both sides.

Multiple chronic lacunes predicting early neurological deterioration and long-term functional outcomes according to TOAST classification in acute ischemic stroke

INTRODUCTION

Studies regarding multiple chronic lacunes (MCLs) and clinical outcome according to stroke etiology are scarce. We sought to evaluate the association between MCL and short-term/long-term clinical outcomes according to stroke etiology.

PATIENTS AND METHODS

We analyzed a prospectively collected stroke registry of acute ischemic stroke patients over 4 years. The enrolled patients were classified as having large artery atherosclerosis (LAA), small vessel occlusion (SVO), cardioembolic (CE) stroke, and other etiology. The early neurological deterioration (END) and favorable outcome at 3 months were assessed.

RESULTS

A total of 1070 patients were enrolled. Patients with MCL had significantly more END compared to those without MCL both in total population (adjusted odds ratio (OR), 1.7; 95% confidence interval [CI], 1.1-2.5; p = 0.013*) and in the LAA group (adjusted OR, 2.3; 95% CI, 1.3-4.2, p < 0.006). Patients with MCL had a significantly lower OR for favorable outcome at 3 months compared to those without MCL both in total population (adjusted OR, 0.7; 95% CI, 0.5-1.0, p = 0.035) and in the LAA group (adjusted OR, 0.6; 95% CI, 0.3-1.0, p = 0.043). However, MCL was not associated with END or long-term functional outcome in patients with SVO, CE, or other etiology.

CONCLUSIONS

The presence of MCL was an independent predictive factor for END as well as long-term poor functional outcome in acute ischemic stroke patients. These associations were only observed in patients with LAA, not in those with SVO, CE, or other etiology.

Machine Learning Models for Predicting Early Neurological Deterioration and Risk Classification of Acute Ischemic Stroke

This study aimed to create machine learning models for predicting early neurological deterioration and risk classification in acute ischemic stroke (AIS) before intravenous thrombolysis (IVT). The study included 704 AIS patients categorized into END and non-END groups. The least absolute shrinkage and selection operator (LASSO) regression was employed to select the best predictors from clinical indicators, leading to the creation of Model 1. Univariate and multivariate logistic regression analyses identified independent predictive factors for END from inflammatory cell ratios. These factors were combined with clinical indicators, forming Model 2. Receiver operating characteristic (ROC) curves assessed the models' predictive performance. Key variables for Model 1 included the NIHSS score, systolic blood pressure, and lymphocyte percentage. Neutrophil-to-Lymphocyte ratio, Platelet-to-Neutrophil ratio, and Platelet-to-Lymphocyte ratio independently predicted END. Model 1 exhibited moderate predictive ability (AUC 0.721 in training, AUC 0.635 in test). Model 2, which integrated clinical indicators and inflammatory cell ratios, demonstrated strong performance in both training (AUC 0.862) and test (AUC 0.816). Machine learning models, combining clinical indicators and inflammatory cell ratios before IVT, accurately predict END and associated risk in AIS.

Association of ischemic stroke onset time with presenting severity, acute progression, and long-term outcome: A cohort study

BACKGROUND

Preclinical data suggest circadian variation in ischemic stroke progression, with more active cell death and infarct growth in rodent models with inactive phase (daytime) than active phase (nighttime) stroke onset. We aimed to examine the association of stroke onset time with presenting severity, early neurological deterioration (END), and long-term functional outcome in human ischemic stroke.

METHODS AND FINDINGS

In a Korean nationwide multicenter observational cohort study from May 2011 to July 2020, we assessed circadian effects on initial stroke severity (National Institutes of Health Stroke Scale [NIHSS] score at admission), END, and favorable functional outcome (3-month modified Rankin Scale [mRS] score 0 to 2 versus 3 to 6). We included 17,461 consecutive patients with witnessed ischemic stroke within 6 hours of onset. Stroke onset time was divided into 2 groups (day-onset [06:00 to 18:00] versus night-onset [18:00 to 06:00]) and into 6 groups by 4-hour intervals. We used mixed-effects ordered or logistic regression models while accounting for clustering by hospitals. Mean age was 66.9 (SD 13.4) years, and 6,900 (39.5%) were women. END occurred in 2,219 (12.7%) patients. After adjusting for covariates including age, sex, previous stroke, prestroke mRS score, admission NIHSS score, hypertension, diabetes, hyperlipidemia, smoking, atrial fibrillation, prestroke antiplatelet use, prestroke statin use, revascularization, season of stroke onset, and time from onset to hospital arrival, night-onset stroke was more prone to END (adjusted incidence 14.4% versus 12.8%, p = 0.006) and had a lower likelihood of favorable outcome (adjusted odds ratio, 0.88 [95% CI, 0.79 to 0.98]; p = 0.03) compared with day-onset stroke. When stroke onset times were grouped by 4-hour intervals, a monotonic gradient in presenting NIHSS score was noted, rising from a nadir in 06:00 to 10:00 to a peak in 02:00 to 06:00. The 18:00 to 22:00 and 22:00 to 02:00 onset stroke patients were more likely to experience END than the 06:00 to 10:00 onset stroke patients. At 3 months, there was a monotonic gradient in the rate of favorable functional outcome, falling from a peak at 06:00 to 10:00 to a nadir at 22:00 to 02:00. Study limitations include the lack of information on sleep disorders and patient work/activity schedules.

CONCLUSIONS

Night-onset strokes, compared with day-onset strokes, are associated with higher presenting neurologic severity, more frequent END, and worse 3-month functional outcome. These findings suggest that circadian time of onset is an important additional variable for inclusion in epidemiologic natural history studies and in treatment trials of neuroprotective and reperfusion agents for acute ischemic stroke.

Predictors of Early Neurological Deterioration and Functional Outcome in Acute Ischemic Stroke: The Importance of Large Artery Disease, Hyperglycemia and Inflammatory Blood Biomarkers

BACKGROUND

Early neurological deterioration (END) in acute ischemic stroke (AIS) can be associated with poor outcome. The aim of this study was to investigate the association between infarction subtypes, biomarkers and END, and to identify patients with risk of unfavorable functional outcome.

MATERIALS AND METHODS

This prospective study enrolled 101 patients with AIS. Neurological status was evaluated according to NIHSS at acute onset, on days 2, 3, and 90. END was defined as ≥2-point increase of NIHSS within 72 hours. Functional outcome was assessed using NIHSS and the modified Rankin Scale (mRS) at day 90.

RESULTS

END was observed in 20, 8%. Patients with large artery disease had higher risk of developing END compared with patients with cardioembolism or small vessel disease (p <0.01). Significant higher blood glucose level and leukocytes were observed in the END group. Patients with END had higher scores of mRS at day 90 (p <0.01). Levels of NSE, IL-6, hsCRP and NT-proBNP were higher in the patients with unfavorable compared with favorable functional outcome.

CONCLUSION

Large artery disease, high blood glucose and leukocytes levels are associated with END. Elevated levels of blood markers NSE, IL-6, HsCRP and NT-proBNP indicate poor functional outcome at 90 days after AIS. These patients must be identified and be offered treatment immediately in order to improve the functional outcome after AIS.