A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke

Establishment and evaluation of a clinical prediction model for cognitive impairment in patients with cerebral small vessel disease

BACKGROUND

There are currently no effective prediction methods for evaluating the occurrence of cognitive impairment in patients with cerebral small vessel disease (CSVD).

AIMS

To investigate the risk factors for cognitive dysfunction in patients with CSVD and to construct a risk prediction model.

METHODS

A retrospective study was conducted on 227 patients with CSVD. All patients were assessed by brain magnetic resonance imaging (MRI), and the Montreal Cognitive Assessment (MoCA) was used to assess cognitive status. In addition, the patient's medical records were also recorded. The clinical data were divided into a normal cognitive function group and a cognitive impairment group. A MoCA score < 26 (an additional 1 point for education < 12 years) is defined as cognitive dysfunction.

RESULTS

A total of 227 patients (mean age 66.7 ± 6.99 years) with CSVD were included in this study, of whom 68.7% were male and 100 patients (44.1%) developed cognitive impairment. Age (OR = 1.070; 95% CI = 1.015 ~ 1.128, p < 0.05), hypertension (OR = 2.863; 95% CI = 1.438 ~ 5.699, p < 0.05), homocysteine(HCY) (OR = 1.065; 95% CI = 1.005 ~ 1.127, p < 0.05), lacunar infarct score(Lac_score) (OR = 2.732; 95% CI = 1.094 ~ 6.825, P < 0.05), and CSVD total burden (CSVD_score) (OR = 3.823; 95% CI = 1.496 ~ 9.768, P < 0.05) were found to be independent risk factors for cognitive decline in the present study. The above 5 variables were used to construct a nomogram, and the model was internally validated by using bootstrapping with a C-index of 0.839. The external model validation C-index was 0.867.

CONCLUSIONS

The nomogram model based on brain MR images and clinical data helps in individualizing the probability of cognitive impairment progression in patients with CSVD.

Serum levels of IL-9 and IL-11 serve as predictors for the occurrence of early neurologic deterioration in patients with cerebral infarction

BACKGROUND AND AIM

Early neurological deterioration (END) is a common complication of cerebral infarction and a significant contributor to poor prognosis. Our study aimed to investigate the predictive value of interleukin-9 (IL-9) and interleukin-11 (IL-11) in relation to the occurrence of END in patients with cerebral infarction.

MATERIALS AND METHODS

102 patients with cerebral infarction and 64 healthy controls were collected. Patients were categorized into two groups based on the development of END following admission: the END group (n = 44) and the non-END group (n = 58). Enzyme-linked immunosorbent assay was used to determine the serum levels of IL-9, IL-11, and BDNF.

RESULTS

Serum IL-9 was higher and IL-11 lower in the END group than those in the non-END group (P < 0.01). IL-9 correlated positively with NIHSS score (r = 0.627) and infarction volume (r = 0.686), while IL-11 correlated negatively (r = -0.613, -0.679, respectively). Logistic regression identified age, NIHSS score, and IL-9 as risk factors (P < 0.01), and IL-11 as protective (P < 0.01). Combined IL-9 and IL-11 had an ROC curve area of 0.849. BDNF correlated negatively with IL-9 (r = -0.703) and positively with IL-11 (r = 0.711).

CONCLUSION

Serum IL-9 and IL-11 levels can predict the occurrence of END in patient with cerebral infarction and are correlated with serum BDNF levels.

Predictive value of glycoprotein DKK3 for early neurological deterioration after ischemic stroke

OBJECTIVE

To explore the value of serum Dickkopf-3 (sDKK3) in predicting Early Neurological Deterioration (END) and in-hospital adverse outcomes in acute ischemic stroke (AIS) patients.

METHODS

AIS patients (n = 200) were included and assessed by the National Institutes of Health Stroke Rating Scale. Serum Dkk3 levels were assessed by ELISA. END was defined as an increase of ≥ 4 points in NIHSS score within 72h. The biological threshold of sDKK3 level and END occurrence were predicted based on X-tile software. Primary outcomes were END and all-cause death, and the secondary outcome was ICU admission during hospitalization. The logistic regression model and Cox risk regression model were applied to evaluate the relationship between DKK3 level and END incidence, all-cause in-hospital mortality, and in-hospital adverse outcomes (ICU admission).

RESULTS

During hospitalization, the incidence of END in patients with AIS was 13.0 %, and the mortality rate within 7 days after END was 11.54 % (3/26). In patients below the serum DKK3 cutoff (93.0 pg/mL), the incidence of END was 43.5 % (20/48). Patients with lower sDKK3 levels were associated with a 1.188-fold increased risk of developing END (OR = 1.188, 95 % CI 1.055‒1.369, p < 0.0001). However, there was no significant association with admission to the ICU. sDKK3 below the threshold (93.0 pg/mL) was a risk factor for death.

CONCLUSION

Predictive threshold levels of serum DKK3 based on X-tile software may be a potential predictive biomarker of in-hospital END in patients with AIS, and low levels of DKK3 are independently associated with increased in-hospital mortality.

Inflammatory marker profiles and in-hospital neurological deterioration in patients with acute minor ischemic stroke

AIM

The aim of the study was to analyze the association between inflammatory marker profiles and in-hospital neurological deterioration (ND) in acute ischemic stroke (AIS) patients.

METHODS

Data from patients with minor AIS from the Third China National Stroke Registry were analyzed. Inflammatory cytokine levels within 24 h of admission were measured. The primary outcome was in-hospital ND (an increase in National Institutes of Health Stroke Scale score ≥4 from admission to discharge). Associations were evaluated using odds ratios (ORs) and 95% confidence intervals (CIs) derived from logistic regression models. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to evaluate incremental predictive values.

RESULTS

A total of 4031 patients (1246 women, 30.9%) with a median age of 62 years were included. In-hospital ND occurred in 121 patients (3%). Each standard-deviation increase in interleukin (IL)-6 (OR, 1.17 [95% CI, 1.06-1.31]) and high-sensitivity C-reactive protein (hsCRP) (OR, 1.43 [95% CI, 1.24-1.66]) levels was associated with increased in-hospital ND risk. Incremental predictive values for adding IL-6 (IDI, 0.012; NRI, 0.329) but not hsCRP levels to the conventional risk factors were found.

CONCLUSION

In minor AIS, hsCRP and IL-6 levels were associated with in-hospital ND, including IL-6 levels in prognostic models improved risk classification.

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.

Higher fibrinogen and neutrophil-to-lymphocyte ratio are associated with the early poor response to intravenous thrombolysis in acute ischemic stroke

Background

Inflammation and platelet activation play pivotal roles in acute ischemic stroke (AIS) pathogenesis. Early response to thrombolysis is a vital indicator for the long-term prognosis of AIS. However, the correlation between fibrinogen or the neutrophil-to-lymphocyte ratio (NLR) and the early response to intravenous thrombolysis in patients with AIS remains unclear.

Methods

AIS patients undergoing intravenous thrombolysis were enrolled between January 2018 and May 2023. Blood cell counts were sampled before thrombolysis. A good response was defined as a National Institutes of Health Stroke Scale (NIHSS) score decreased ≥4 or complete recovery 24 h after thrombolysis treatment. A poor response was defined as any increase in the NIHSS score or a decrease in the NIHSS score <4 at the 24 h after thrombolysis treatment compared with that at admission. Logistic regression analysis was performed to explore the relationship of the fibrinogen level and NLR with a poor thrombolysis response. Receiver operating characteristic (ROC) analysis was used to assess the ability of the fibrinogen level and NLR to discriminate poor responders.

Results

Among 700 recruited patients, 268 (38.29%) were diagnosed with a good response, and 432 (61.71%) were diagnosed with a poor response to intravenous thrombolysis. A binary logistic regression model indicated that an elevated fibrinogen level (odds ratio [OR], 1.693; 95% confidence interval [CI] 1.325-2.122, P < 0.001) and NLR (OR, 1.253; 95% CI, 1.210-2.005, P = 0.001) were independent factors for a poor response. The area under the curve (AUC) values for the fibrinogen level, NLR and fibrinogen level combined with the NLR for a poor response were 0.708, 0.605, and 0.728, respectively.

Conclusions

Our research indicates that the levels of fibrinogen and NLR at admission can be used as a prognostic factor to predict early poor response to intravenous thrombolysis.

TG/HDL-c ratio as a predictor of progressive infarction in patients with anterior circulation single subcortical infarction

BACKGROUND

The contributors predicting progressive infarction (PI) in patients with anterior circulation single subcortical infarction (ACSSI) and pontine single infarction (PSI) may be unidentical. The role of triglyceride to high-density lipoprotein cholesterol (TG/HDL-c) ratio on PI is unclear. The purpose of our study is to evaluate the correlation between TG/HDL-c ratio and PI in patients with ACSSI or PSI.

METHODS

Between January 2020 and October 2022, we retrospectively enrolled 738 patients including 638 ACSSI patients and 100 PSI patients to analyze. Demographic characteristics, clinical information, and laboratory data were collected within 24 h of admission.

RESULTS

PI occurred in 143 (19.4%) patients. In univariate analysis, patients with PI had higher initial National Institutes of Health Stroke Scale (NIHSS) scores, higher discharge NIHSS scores, higher levels of fasting glucose, total cholesterol, TG, low-density lipoprotein cholesterol, and TG/HDL-c ratio, but lower levels of creatinine compared to patients with non-PI (p < .05). Furthermore, the results of the subgroup analyses revealed the independent association between TG/HDL-c ratio and PI in ACSSI patients (OR 1.079, 95% CI 1.009-1.153, p = .026) rather than in PSI patients. Additionally, a receiver operating characteristic curve indicated that the optimal predictive cutoff value of the TG/HDL-c ratio was 3.985, and a TG/HDL-c ratio ≥3.985 was more likely to experience PI in ACSSI patients.

CONCLUSION

In conclusion, the TG/HDL-c ratio was independently associated with PI in patients with ACSSI.

Early neurological deterioration in patients with minor stroke due to isolated M2 occlusion undergoing medical management: a retrospective multicenter study

BACKGROUND

Patients with minor stroke and M2 occlusion undergoing best medical management (BMM) may face early neurological deterioration (END) that can lead to poor long-term outcome. In case of END, rescue mechanical thrombectomy (rMT) seems beneficial. Our study aimed to define factors relevant to clinical outcome in patients undergoing BMM with the possibility of rMT on END, and find predictors of END.

METHODS

Patients with M2 occlusion and a baseline National Institutes of Health Stroke Scale (NIHSS) score≤5 that received either BMM only or rMT on END after BMM were extracted from the databases of 16 comprehensive stroke centers. Clinical outcome measures were a 90-day modified Rankin Scale (mRS) score of 0-1 or 0-2, and occurrence of END.

RESULTS

Among 10 169 consecutive patients with large vessel occlusion admitted between 2016 and 2021, 208 patients were available for analysis. END was reported in 87 patients that were therefore all subjected to rMT. In a logistic regression model, END (OR 3.386, 95% CI 1.428 to 8.032), baseline NIHSS score (OR 1.362, 95% CI 1.004 to 1.848) and a pre-event mRS score=1 (OR 3.226, 95% CI 1.229 to 8.465) were associated with unfavorable outcome. In patients with END, successful rMT was associated with favorable outcome (OR 4.549, 95% CI 1.098 to 18.851). Among baseline clinical and neuroradiological features, presence of atrial fibrillation was a predictor of END (OR 3.547, 95% CI 1.014 to 12.406).

CONCLUSION

Patients with minor stroke due to M2 occlusion and atrial fibrillation should be closely monitored for possible worsening during BMM and, in this case, promptly considered for rMT.

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.

External Validation and Recalibration of a Mortality Prediction Model for Patients with Ischaemic Stroke

BACKGROUND

Stroke is a highly prevalent disease that can provoke severe disability. We evaluate a predictive model based on the Minimum Basic Data Set (MBDS) compiled by the Spain Health Ministry, obtained for the period 2008-2012 for patients with ischaemic stroke in Spain, to establish the model's validity and to optimise its calibration. The MBDS is the main clinical-administrative database for hospitalisations recorded in Spain, and to our knowledge, no predictive models for stroke mortality have previously been developed using this resource. The main study aim is to perform an external validation and recalibration of the coefficients of this predictive model with respect to a chronologically later cohort.

MATERIAL AND METHODS

External validation (testing the model on a different cohort to assess its performance) and recalibration (validation with optimisation of model coefficients) were performed using the MBDS for patients admitted for ischaemic stroke in the period 2016-2018. A cohort study was designed, in which a recalibrated model was obtained by applying the variables of the original model without their coefficients. The variables from the original model were then applied to the subsequent cohort, together with the coefficients from the initial model. The areas under the curve (AUC) of the recalibration and the external validation procedure were compared.

RESULTS

The recalibrated model produced an AUC of 0.743 and was composed of the following variables: age (odds ratio, OR:1.073), female sex (OR:1.143), ischaemic heart disease (OR:1.192), hypertension (OR:0.719), atrial fibrillation (OR:1.414), hyperlipidaemia (OR:0.652), heart failure (OR:2.133) and posterior circulation stroke (OR: 0.755). External validation produced an AUC of 0.726.

CONCLUSIONS

The recalibrated clinical model thus obtained presented moderate-high discriminant ability and was generalisable to predict death for patients with ischaemic stroke. Rigorous external validation slightly decreased the AUC but confirmed the validity of the baseline model for the chronologically later cohort.

Prognostic utility of sTREM-1 in predicting early neurological deterioration in patients with acute ischemic stroke treated without reperfusion therapy

OBJECTIVE

Serum triggering receptor expressed on myeloid cells type 1 (sTREM-1) is a new type of immunoglobulin superfamily receptor related to inflammation that aggravates brain injury. This study aimed to assess the clinical value of sTREM-1 in predicting early neurological deterioration in patients with acute ischemic stroke (AIS) treated without reperfusion therapy.

METHODS

This prospective cohort study enrolled 315 patients with acute ischemic stroke admitted to the Affiliated Taizhou People's Hospital of Nanjing Medical University between October 2020 and October 2022. The study excluded patients treated with reperfusion therapy. sTREM-1 levels were evaluated within 24 h of the acute ischemic stroke. Early neurological deterioration (END) was defined as an increase in the National Institutes of Health Stroke Scale (NIHSS) score ≥ 4 points within three days after admission. Multivariable analyses were used to investigate the relationship between sTREM-1 levels and END.

RESULTS

A total of 81 (25.7 %) patients had early neurological deterioration. Patients in the END group had a higher NIHSS score at admission (P =0.007), CRP levels (P =0.011), white blood cell count (P =0.002), fasting blood glucose levels (P =0.028), and sTREM-1 levels (P <0.001). After adjusting for confounders, higher sTREM-1 levels were significantly associated with an increased risk of early neurological deterioration (OR, 1.98; 95 % CI, 1.17-3.38, P=0.012). Moreover, sTREM-1 levels efficiently differentiated END (area under the curve: 0.779; 95 % CI: 0.731-0.822). Furthermore, the results showed significant differences between the high sTREM-1 group and the low sTREM-1 group in NIHSS scores (P=0.019), C-reactive protein (P=0.018), white blood cell count (P=0.013), and the incidence of early neurological deterioration (P<0.001). According to the multivariate logistic regression model, we discovered that the high sTREM-1 group was a significant independent predictor of early neurological deterioration incidence (OR, 4.19; 95 % CI, 1.46-9.84; P= 0.003).

CONCLUSION

sTREM-1 could be a potential biomarker for predicting early neurological deterioration in AIS patients not treated with reperfusion therapy.

Development and Validation of a Prediction Model for 30-Day Mortality and Functional Outcome in Patients with Primary Brainstem Hemorrhage

INTRODUCTION

Primary brainstem hemorrhage (PBSH) is the most fatal subtype of intracerebral hemorrhage and is associated with poor prognosis. We aimed to develop a prediction model for predicting 30-day mortality and functional outcome in patients with PBSH.

METHODS

We reviewed records of 642 consecutive patients with first-time PBSH from three hospitals between 2016 and 2021. Multivariate logistic regression was used to establish a nomogram in a training cohort. Cutoff points of the variables were determined by receiver operating characteristic curve analysis, and certain points were assigned to these predictors to produce the PBSH score. The nomogram and PBSH score were compared with other scoring systems for PBSH.

RESULTS

Five independent predictors, comprised of temperature, pupillary light reflex, platelet-to-lymphocyte ratio, Glasgow Coma Scale (GCS) score on admission, and hematoma volume, were incorporated to construct the nomogram. The PBSH score consisted of 4 independent factors with individual points assigned as follows: temperature, ≥38°C (=1 point), <38°C (=0 points); pupillary light reflex, absence (=1 point), presence (=0 points); GCS score 3-4 (=2 points), 5-11 (=1 point), and 12-15 (=0 points); PBSH volume >10 mL (=2 points), 5-10 mL (=1 point), and <5 mL (=0 points). Results showed that the nomogram was discriminative in predicting both 30-day mortality (area under the ROC curve [AUC] of 0.924 in the training cohort, and 0.931 in the validation cohort) and 30-day functional outcome (AUC of 0.887). The PBSH score was discriminative in predicting both 30-day mortality (AUC of 0.923 in the training cohort and 0.923 in the validation cohort) and 30-day functional outcome (AUC of 0.887). The prediction performances of the nomogram and the PBSH score were superior to the intracranial hemorrhage (ICH) score, primary pontine hemorrhage (PPH) score, and new PPH score.

CONCLUSIONS

We developed and validated two prediction models for 30-day mortality and functional outcome in patients with PBSH. The nomogram and PBSH score could predict 30-day mortality and functional outcome in PBSH patients.

Association between Triglyceride-Glucose Index and Early Neurological Outcomes after Thrombolysis in Patients with Acute Ischemic Stroke

BACKGROUND

The triglyceride-glucose (TyG) index is a novel biomarker of insulin resistance which might plausibly influence endogenous fibrinolysis and thus early neurological outcomes in patients with acute ischemic stroke (AIS) treated with intravenous thrombolysis using recombinant tissue-plasminogen activator.

METHODS

We included consecutive AIS patients within 4.5 h of symptom onset undergoing intravenous thrombolysis between January 2015 and June 2022 in this multi-center retrospective observational study. Our primary outcome was early neurological deterioration (END), defined as ≥2 (END₂) or ≥ 4 (END₄) National Institutes of Health Stroke Scale (NIHSS) score worsening compared to the initial NIHSS score within 24 h of intravenous thrombolysis. Our secondary outcome was early neurological improvement (ENI), defined as a lower NIHSS score at discharge. TyG index was calculated using the log scale of fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2. We evaluated the association of END and ENI with TyG index using a logistic regression model.

RESULTS

A total of 676 patients with AIS were evaluated. The median age was 68 (Interquartile range, IQR (60-76) years old), and 432 (63.9%) were males. A total of 89 (13.2%) patients developed END₂, 61 (9.0%) patients developed END₄, and 492 (72.7%) experienced ENI. In multivariable logistic regression analysis, after adjustment for confounding factors, TyG index was significantly associated with increased risks of END₂ (categorical variable, vs. lowest tertile, medium tertile odds ratio [OR] 1.05, 95% confidence interval, CI 0.54-2.02, highest tertile OR 2.94, 95%CI 1.64-5.27, overall p < 0.001) and END₄ (categorical variable, vs. lowest tertile, medium tertile OR 1.21, 95%CI 0.54-2.74, highest tertile OR 3.80, 95%CI 1.85-7.79, overall p < 0.001), and a lower probability of ENI (categorical variable, vs. lowest tertile, medium tertile OR 1.00, 95%CI 0.63-1.58, highest tertile OR 0.59, 95%CI 0.38-0.93, overall p = 0.022).

CONCLUSIONS

Increasing TyG index was associated with a higher risk of END and a lower probability of ENI in patients with acute ischemic stroke treated with intravenous thrombolysis.

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.

Stress hyperglycemia predicts early neurological deterioration and poor outcomes in patients with single subcortical infarct

AIM

The goal of this study was to determine whether the stress hyperglycemia ratio (SHR) is associated with early neurological deterioration (END) and poor outcomes in patients with single subcortical infarct (SSI).

METHODS

For this study, we prospectively enrolled patients with SSI admitted between 2015 and 2021. SHR was distributed in quartiles according to the size of each subgroup. END was defined as an increase of ≥ 2 total points in the National Institutes of Health Stroke Scale (NIHSS) or ≥ 1 point in the motor items of the NIHSS within 7 days of hospital admission. The modified Rankin Scale (mRS) was used to evaluate patient prognosis. Good and poor outcomes were defined as mRS scores ≤ 2 and > 2, respectively. The relationships between SHR and risk of END as well as outcomes were analyzed using multivariate logistic regression models.

RESULTS

A total of 1049 patients with SSI with an average age of 59.49 years met the inclusion criteria for the analysis. The incidence of END markedly increased with increasing SHR. Multivariate logistic regression analysis revealed that the highest SHR quartile was independently associated with an increased risk of both END (OR 4.04, 95% CI, 2.43-6.69, P < 0.001) and 3-month poor outcomes (OR 2.34, 95% CI, 1.44-3.82, P = 0.001), compared to the lowest quartile. A receiver operating characteristic curve analysis of the SHR based on the area under the curve showed a diagnostic accuracy equal or greater than fasting plasma glucose .

CONCLUSION

SHR is a reliable predictor of END and poor outcomes in patients with SSI.

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.

Fibrinogen as a Predictor of Early Neurological Deterioration in Acute Ischemic Stroke - Evidence From the Indian Population

Background

Early neurological deterioration (END) is a common occurrence in ischemic stroke and contributes significantly to poor outcomes. Although multiple factors that predict END have already been identified, the role of fibrinogen - a key component of the coagulation pathway, is controversial.

Objective

To assess the role of fibrinogen in predicting END and poor hospital outcome in patients with acute ischemic stroke.

Design

Single-centre prospective observational study.

Methods

141 patients with acute ischemic stroke were analyzed in this prospective observational study from a single tertiary-care hospital in East India. END was defined as a worsening of ≥2 points on the National Institutes of Health Stroke Scale (NIHSS) within 7 days of admission. A score of 3-5 on the Modified Rankin Scale (mRS), a stroke recurrence event or death during hospital stay was considered poor hospital outcome. We performed univariate analysis using age, sex, body-mass index (BMI), hypertension, diabetes, NIHSS scores, stroke etiology, blood glucose and lipid parameters and plasma fibrinogen to develop a logistic regression model to establish the independent predictors of END and poor outcome.

Results

Age (Odds Ratio (OR) 1.034 [95% CI 1.001-1.069], P = .046), NIHSS score at admission (OR 1.152 [95% CI 1.070-1.240], P < .001) and fibrinogen (OR 1.011 [95%CI 1.006-1.015], P < .001) were independent predictors of END in patients with acute ischemic stroke. Factors independently associated with poor outcome were NIHSS score at admission (OR 1.257 [95% CI 1.150-1.357], P < .001), fasting plasma glucose (OR 1.007 [95% CI 1.001-1.013], P = .020), and fibrinogen [OR 1.004 [95% CI 1.000-1.007], P = .038).

Conclusion

The significant role of fibrinogen in determining neurological worsening and subsequent poor outcomes in patients with acute ischemic stroke may help in early prognostication and guided therapeutic interventions.

A nomogram for predicting the 4-year risk of chronic kidney disease among Chinese elderly adults

BACKGROUND

Chronic kidney disease (CKD) has become a major public health problem across the globe, leading to various complications. This study aimed to construct a nomogram to predict the 4-year risk of CKD among Chinese adults.

METHODS

The study was based on the China Health and Retirement Longitudinal Study (CHARLS). A total of 3562 participants with complete information in CHARLS2011 and CHARLS2015 were included, and further divided into the training cohort and the validation cohort by a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to select variables of the nomogram. The nomogram was evaluated by receiver-operating characteristic curve, calibration plots, and decision curve analysis (DCA).

RESULTS

In all, 2494 and 1068 participants were included in the training cohort and the validation cohort, respectively. A total of 413 participants developed CKD in the following 4 years. Five variables selected by multivariate logistic regression were incorporated in the nomogram, consisting of gender, hypertension, the estimated glomerular filtration rate (eGFR), hemoglobin, and Cystatin C. The area under curve was 0.809 and 0.837 in the training cohort and the validation cohort, respectively. The calibration plots showed agreement between the nomogram-predicted probability and the observed probability. DCA indicated that the nomogram had potential clinical use.

CONCLUSIONS

A predictive nomogram was established and internally validated in aid of identifying individuals at increased risk of CKD.

Prognostic Values Serum Cav-1 and NGB Levels in Early Neurological Deterioration After Intravenous Thrombolysis in Patients with Acute Ischemic Stroke

Early neurological deterioration after intravenous thrombolysis (IAT) leads to increased mortality and morbidity in patients with acute ischemic stroke (AIS). This study investigated the correlation between serum Cav-1 and NGB levels and END after IAT and explored their predictive values for poor prognosis of AIS. Totally 210 patients with AIS who underwent IAT within 4.5 h of onset were included and assigned into END group (n = 90) and Non-END group (n = 120). ELISA was used to detect serum Cav-1 and NGB levels before IAT in AIS patients. The prognosis of END patients after 3 months of treatment was evaluated using the modified Rankin Scale. Logistic multifactorial regression was used to analyze independent risk factors for END and poor prognosis after IAT. ROC curve was used to analyze the predictive effect of Cav-1 and NGB on END and poor prognosis after IAT. The area under the ROC curve was analyzed by MedCalc comparison. Compared with the Non-END group, serum Cav-1 was lower and NGB was higher in the END group. Cav-1 and NGB were independent risk factors for END after IAT. Cav-1 + NGB better predicted END after IAT than Cav-1 or NGB alone. Cav-1 and NGB were independent risk factors for END poor prognosis after IAT. Cav-1 combined with NGB better predicted poor prognosis of END after IAT than Cav-1 or NGB alone. Serum Cav-1 combined with NGB may assist in predicting the risk of END occurrence and poor prognosis after IAT in patients with AIS.

Analysis of risk factors for the development of cognitive dysfunction in patients with cerebral small vessel disease and the construction of a predictive model

Background

Cognitive dysfunction in cerebral small vessel disease (CSVD) is a common cause of vascular dementia. The purpose of this study was to find independent risk factors for the development of cognitive dysfunction in patients with CSVD and establish a risk prediction model, in order to provide a reference for clinical diagnosis and treatment of such patients.

Methods

In this study, clinical data of patients with CSVD admitted to the Department of Neurology in Gansu Provincial Hospital from December 2019 to December 2021 were collected, and 159 patients were finally included after strict screening according to the inclusion and exclusion criteria. There were 43 patients with normal function and 116 patients with cerebral small vessel disease cognitive impairment (CSVDCI). The logistic multivariable regression model was used to screen out the independent risk factors of cognitive dysfunction in patients with CSVD, and the nomogram of cognitive dysfunction in patients with CSVD was constructed based on the results of the logistic multivariable regression analysis. Finally, the accuracy of the prediction model was evaluated by C-index, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).

Results

The results of multivariable logistic regression analysis showed that hypertension (OR = 2.683, 95% CI 1.119–6.432, P = 0.027), homocysteine (Hcy) (OR = 1.083, 95% CI 1.026–1.143, P = 0.004), total CSVD MRI Score (OR = 1.593, 95% CI 1.025–2.475, P = 0.039) and years of schooling (OR = 0.883, 95% CI 0.798–0.978, P = 0.017) were independent risk factors for the development of cognitive dysfunction in patients with CSVD. The C-index of this prediction model was 0.806 (95% CI 0.735–0.877), and the calibration curve, ROC curve, and DCA curve all showed good predictive power in the nomogram.

Conclusions

The nomogram constructed in this study has high accuracy and clinical utility in predicting the occurrence of cognitive dysfunction in patients with CSVD. For patients with CSVD with the above risk factors, active clinical intervention and prevention are required during clinical consultation and disease management to avoid cognitive impairment as much as possible.

Interpretable machine learning for early neurological deterioration prediction in atrial fibrillation-related stroke

We aimed to develop a novel prediction model for early neurological deterioration (END) based on an interpretable machine learning (ML) algorithm for atrial fibrillation (AF)-related stroke and to evaluate the prediction accuracy and feature importance of ML models. Data from multicenter prospective stroke registries in South Korea were collected. After stepwise data preprocessing, we utilized logistic regression, support vector machine, extreme gradient boosting, light gradient boosting machine (LightGBM), and multilayer perceptron models. We used the Shapley additive explanation (SHAP) method to evaluate feature importance. Of the 3,213 stroke patients, the 2,363 who had arrived at the hospital within 24 h of symptom onset and had available information regarding END were included. Of these, 318 (13.5%) had END. The LightGBM model showed the highest area under the receiver operating characteristic curve (0.772; 95% confidence interval, 0.715–0.829). The feature importance analysis revealed that fasting glucose level and the National Institute of Health Stroke Scale score were the most influential factors. Among ML algorithms, the LightGBM model was particularly useful for predicting END, as it revealed new and diverse predictors. Additionally, the effects of the features on the predictive power of the model were individualized using the SHAP method.

The association of neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, and lymphocyte to monocyte ratio with post-thrombolysis early neurological outcomes in patients with acute ischemic stroke

Background and purpose

To investigate the association of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and lymphocyte to monocyte ratio (LMR) with post-thrombolysis early neurological outcomes including early neurological improvement (ENI) and early neurological deterioration (END) in patients with acute ischemic stroke (AIS).

Methods

AIS patients undergoing intravenous thrombolysis were enrolled from April 2016 to September 2019. Blood cell counts were sampled before thrombolysis. Post-thrombolysis END was defined as the National Institutes of Health Stroke Scale (NIHSS) score increase of ≥ 4 within 24 h after thrombolysis. Post-thrombolysis ENI was defined as NIHSS score decrease of ≥ 4 or complete recovery within 24 h. Multinomial logistic regression analysis was performed to explore the relationship of NLR, PLR, and LMR to post-thrombolysis END and ENI. We also used receiver operating characteristic curve analysis to assess the discriminative ability of three ratios in predicting END and ENI.

Results

Among 1060 recruited patients, a total of 193 (18.2%) were diagnosed with END and 398 (37.5%) were diagnosed with ENI. Multinomial logistic model indicated that NLR (odds ratio [OR], 1.385; 95% confidence interval [CI] 1.238–1.551, P = 0.001), PLR (OR, 1.013; 95% CI 1.009–1.016, P = 0.001), and LMR (OR, 0.680; 95% CI 0.560–0.825, P = 0.001) were independent factors for post-thrombolysis END. Moreover, NLR (OR, 0.713; 95% CI 0.643–0.791, P = 0.001) served as an independent factor for post-thrombolysis ENI. Area under curve (AUC) of NLR, PLR, and LMR to discriminate END were 0.763, 0.703, and 0.551, respectively. AUC of NLR, PLR, and LMR to discriminate ENI were 0.695, 0.530, and 0.547, respectively.

Conclusions

NLR, PLR, and LMR were associated with post-thrombolysis END. NLR and PLR may predict post-thrombolysis END. NLR was related to post-thrombolysis ENI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-021-02090-6.

Hypersensitive C-reactive protein-albumin ratio predicts symptomatic intracranial hemorrhage after endovascular therapy in acute ischemic stroke patients

Background

Approximately 10% of patients would develop symptomatic intracranial hemorrhage (sICH) after endovascular therapy. The aim of our study was to explore the ability of hypersensitive C-reactive protein-albumin ratio (HAR) in predicting sICH after endovascular therapy.

Methods

From April 2016 to December 2018, 334 consecutive patients with anterior circulation infarction undergoing endovascular therapy were enrolled in our study. sICH was defined using Heidelberg bleeding classification after endovascular therapy. Multiple regression analysis was used to investigate the potential risk factors of sICH after endovascular therapy. We used receiver operating characteristic curve analysis and nomogram analysis to assess the overall discriminative ability of the HAR in predicting sICH after endovascular therapy.

Results

Among these 334 patients enrolled, 37 (11.1%) patients with anterior circulation infarction were identified with sICH after endovascular therapy. Univariate logistic regression analysis demonstrated that patients with higher levels of HAR may be inclined to develop sICH (odds ratio, 10.994; 95% confidence interval, 4.567–26.463; P = 0.001). This association remained significant even after adjustment for potential confounders. Also, a cutoff value of 0.526× 10^− 3 for HAR was detected in predicting sICH (area under curve, 0.763). Furthermore, nomogram analysis also suggested that HAR was an indicator of sICH (c-index was 0.890, P< 0.001).

Conclusions

This study showed that high levels of HAR could predict sICH after endovascular therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02066-2.

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

OBJECTIVE

This study aimed to develop a predictive model of early neurological deterioration (END) in patients with acute ischemic stroke (AIS).

METHODS

The present retrospective cohort study considered patients with AIS who were admitted to a tertiary hospital in Shenzhen, China between January 2014 and December 2018. An increase of 2 points or more on the National Institute of Health Stroke Scale (NIHSS) within 7 days indicated END. We selected baseline clinical, laboratory, and neuroimaging variables to construct predictive models through multivariate logistic regression. The receiver operating characteristic curve and calibration plots were calculated.

RESULTS

A total of 391 patients with AIS were enrolled in the study. END was observed in 64 (16.4%) cases. A prediction model developed from the initial NIHSS score, middle cerebral artery stenosis, and carotid stenosis of≥ 50% showed good discriminative ability: area under the receiver operating characteristic curve, 0.870 (95%CI, 0.813-0.911); threshold, -1.570; specificity, 84.40%; sensitivity, 75.00%; positive predictive value, 48.48%; and a negative predictive value, 94.52%.

CONCLUSION

Our predictive model developed from the initial NIHSS score, middle cerebral artery stenosis, and carotid stenosis of ≥ 50% could identify patients with AIS who were at risk of developing END. The model requires validation by larger studies performed at other institutions.

Early prediction of the 3-month outcome for individual acute ischemic stroke patients who received intravenous thrombolysis using the N2H3 nomogram model

Background:

The aim of this study was to establish a nomogram model for individualized early prediction of the 3-month prognosis in patients with acute ischemic stroke (AIS) who were treated with intravenous recombinant tissue plasminogen activator (rt-PA) thrombolysis.

Methods:

A total of 691 patients were included in this study; 564 patients were included in the training cohort, while 127 patients were included in the test cohort. The main outcome measure was a 3-month unfavorable outcome (modified Rankin Scale 3–6). To construct the nomogram model, stepwise logistic regression analysis was applied to select the significant predictors of the outcome. The discriminative performance of the model was assessed by calculating the area under the receiver operating characteristic curve (AUC-ROC). A decision curve analysis was used to evaluate prognostic value of the model.

Results:

The initial National Institutes of Health Stroke Scale [NIHSS, odds ratio (OR), 1.35; 95% confidence interval (CI), 1.28–1.44; p < 0.001], delta NIHSS (changes in the NIHSS score from baseline to 24 h, OR, 0.75; 95% CI, 0.70–0.79; p < 0.001), hypertension (OR, 2.07; 95% CI, 1.32–3.31; p = 0.002), hyperhomocysteinemia (Hhcy, OR, 2.18; 95% CI, 1.20–4.11; p = 0.013), and the ratio of high-density lipoprotein cholesterol (HDL-C) to low-density lipoprotein cholesterol (LDL-C) (HDL-C/LDL-C, OR, 3.29; 95% CI, 1.00–10.89; p = 0.049) (N2H3) were found to be independent predictors of a 3-month unfavorable outcome from multivariate logistic regression analysis and were incorporated in the N2H3 nomogram model. The AUC-ROC of the training cohort was 0.872 (95% CI, 0.841–0.902), and the AUC-ROC of the test cohort was 0.900 (95% CI, 0.848–0.953).

Conclusion:

The study presented the N2H3 nomogram model, with initial NIHSS score, delta NIHSS, hypertension, Hhcy, and HDL-C/LDL-C as predictors. It therefore provides an individualized early prediction of the 3-month unfavorable outcome in AIS patients treated with intravenous rt-PA thrombolysis.