Prognosis Of Acute Ischemic Stroke Patients Research Articles

Association between the stress hyperglycemia ratio and mortality in patients with acute ischemic stroke

The stress hyperglycemia ratio (SHR) is established as a reliable marker for assessing the severity of stress-induced hyperglycemia. While its effectiveness in managing patients with Acute Ischemic Stroke (AIS) remains to be fully understood. We aim to explore the relationship between SHR and clinical prognosis in AIS patients and to assess how diabetes status influences this relationship. In this study, we analyzed data from the Medical Information Mart for Intensive Care (MIMIC-IV) database, selecting patients with AIS who required ICU admission. These patients were categorized into tertiles based on their SHR levels. We applied Cox hazard regression models and used restricted cubic spline (RCS) curves to investigate relationships between outcomes and SHR. The study enrolled a total of 2029 patients. Cox regression demonstrated that a strong correlation was found between increasing SHR levels and higher all-cause mortality. Patients in the higher two tertiles of SHR experienced significantly elevated 30-day and 90-day mortality rates compared to those in the lowest tertile. This pattern remained consistent regardless of diabetes status. Further, RCS analysis confirmed a progressively increasing risk of all-cause mortality with higher SHR levels. The findings indicate that SHR is association with increased 30-day and 90-day mortality among AIS patients, underscoring its potential value in risk stratification. Although the presence of diabetes may weaken this association, significant correlations persist in diabetic patients.

A Role for Systemic Inflammation in Stroke-Associated Infection and the Long-Term Prognosis of Acute Ischemic Stroke: A Mediation Analysis.

The dynamic systemic inflammation level and stroke-associated infection (SAI) are related to the prognosis of acute ischemic stroke (AIS). We aimed to explore whether the systemic inflammatory response index (SIRI), systemic immune inflammation index (SII), and their dynamic changes possess predictability for SAI and long-term prognosis. A total of 1804 AIS patients without intravenous thrombolysis in two hospitals were included. We explored the relationship between SIRI, SII, and their dynamic changes and outcomes by constructing clusters. The mediating effects of SAI between prognosis and systemic inflammation were further evaluated. Each SD increase in the concentration of SIRI exhibited a significant correlation with the risk of poor functional outcome, mortality, and functional dependency. Through K-means clustering analysis, patients with dramatically elevated or decreased systemic inflammation levels of SIRI (OR: 2.293, 95% CI: 1.279-4.109) and SII (OR: 3.165, 95% CI: 1.627-6.156) within 7 days had a higher risk of functional outcome. Through mediation analysis, SAI mediated the association between systemic inflammation and poor prognosis (SIRI: 33.73%, SII: 16.01%). Dramatically changing dynamics of SIRI and SII were significantly associated with a higher risk of poor prognosis in AIS patients. SAI mediated the association between systemic inflammation and prognosis at 1 year.

Application Value of the Apolipoprotein in the Prediction of Acute Ischemic Death and in the Assessment of Functional Outcomes.

In recent years, research on the apolipoprotein E (APOE) gene has gradually proven that many diseases, including atherosclerosis, coronary heart disease, and neurological diseases, are closely related to ApoE gene diversity. However, the relationship between the APOE gene and the prediction and prognosis evaluation of ischemic stroke has not been determined or unified so far. The purpose of this study was to investigate the application value of APOE allele-4 combined with high-resolution vascular wall imaging in predicting the occurrence and prognosis of acute ischemic stroke. A total of 511 patients with acute ischemic stroke (AIS), who were admitted from January 2022 to December 2023, were included in the study, including 317 patients with intracranial artery stenosis. Blood lipids, lipoproteins, apolipoprotein E (including allelic typing), and lipoproteins (a) were measured in all cases, and high-resolution magnetic resonance imaging of the vascular walls was performed. At 6 months, the functional outcomes of the AIS patients were followed up, assessed by using the modified Rankin Scale (mRS) (a score of 2 - 6 was rated as poor prognosis), and the high-definition vascular wall imaging results were followed up as well. High-definition vascular wall imaging ensures the accurate location of vascular stenosis and the accurate diagnosis of acute stroke. There were no significant differences in the total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, or lipoprotein (a) in patients with and without intracranial artery stenosis, but the plasma apolipoprotein E (APOE) levels were significantly reduced in patients with intracranial artery stenosis (ICAS). At the 6-month follow-up, 230 patients with the APOE-ε4 gene were enrolled, out of which 104 had a poor prognosis (mRS score ≥ 2), accounting for 45.22%. Among 281 patients without the APOE-ε4 gene, 45 had a poor prognosis (mRS score ≥ 2), accounting for 16.01%. Patients with the APOE-ε4 gene had a worse functional prognosis after 6 months. It is suggested that low plasma APOE levels may be a high risk factor for ICAS in patients with acute ischemic stroke, and carrying the APOE-ε4 gene may be a high risk factor for a poor functional prognosis in AIS patients. The APOE-ε4 genotype, combined with high-resolution vascular wall imaging, has certain clinical application value in predicting the occurrence of acute ischemic death and evaluating the functional outcome.

Inflammatory biomarkers may be associated with poor outcomes after mechanical thrombectomy

BackgroundMechanical thrombectomy (MT) has become the mainstay of treatment for acute ischemic stroke (AIS) recently. This case-control study aimed to identify the pivotal role of inflammation in the prognosis of AIS patients after MT.MethodsAltogether, 70 AIS patients who underwent MT were retrospectively recruited for this study. Receiver operating characteristic analysis was performed to demonstrate the sensitivity and specificity of the inflammatory variables for predicting prognosis. A meta-analysis was performed to pool the published results together. Stata software was used for analysis.ResultsThere was no differences in pre-MT inflammatory biomarkers between patients who survived and those who died, as well as patients with modified Rankin Scale (mRS) 0–2 and mRS ≥ 3. In contrast, post-MT C-reactive protein (CRP) levels might be a potential parameter to predict death after thrombectomy [area under the curve (AUC), 95%confidence interval (CI), 0.737, 0.587–0.887; p = 0.005; optimal cutoff value = 4.565]. Moreover, post-MT monocyte count might be an appropriate parameter to predict poor long-term prognosis after thrombectomy (AUC, 95%CI, 0.704, 0.575–0.833; p = 0.017; optimal cutoff value = 0.345). A meta-analysis revealed that the pre-MT inflammatory indices, including white blood cell count (weighted mean difference, 95%CI, 1.32, 1.01—1.63), neutrophil count (1.23, 0.95—1.51), monocyte count (0.05, 0.02—0.09), neuthrophil-to-lymphocyte ratio (2.42, 1.98—2.87) and platelet-to-lymphocyte ratio (24.65, 7.99—41.32), were higher in patients with 3-month mRS ≥ 3, and the lymphocyte count (−0.31,−0.43 to −0.18) was lower in this cohort.ConclusionsInflammatory indices were significantly associated with the prognosis of patients undergoing MT, especially post-MT CRP and monocyte count, which can predict long-term outcomes.

Machine learning is an effective method to predict the 3-month prognosis of patients with acute ischemic stroke

Background and objectivesUpwards of 50% of acute ischemic stroke (AIS) survivors endure varying degrees of disability, with a recurrence rate of 17.7%. Thus, the prediction of outcomes in AIS may be useful for treatment decisions. This study aimed to determine the applicability of a machine learning approach for forecasting early outcomes in AIS patients.MethodsA total of 659 patients with new-onset AIS admitted to the Department of Neurology of both the First and Second Affiliated Hospitals of Bengbu Medical University from January 2020 to October 2022 included in the study. The patient’ demographic information, medical history, Trial of Org 10,172 in Acute Stroke Treatment (TOAST), National Institute of Health Stroke Scale (NIHSS) and laboratory indicators at 24 h of admission data were collected. The Modified Rankine Scale (mRS) was used to assess the 3-mouth outcome of participants’ prognosis. We constructed nine machine learning models based on 18 parameters and compared their accuracies for outcome variables.ResultsFeature selection through the Least Absolute Shrinkage and Selection Operator cross-validation (Lasso CV) method identified the most critical predictors for early prognosis in AIS patients as white blood cell (WBC), homocysteine (HCY), D-Dimer, baseline NIHSS, fibrinogen degradation product (FDP), and glucose (GLU). Among the nine machine learning models evaluated, the Random Forest model exhibited superior performance in the test set, achieving an Area Under the Curve (AUC) of 0.852, an accuracy rate of 0.818, a sensitivity of 0.654, a specificity of 0.945, and a recall rate of 0.900.ConclusionThese findings indicate that RF models utilizing general clinical and laboratory data from the initial 24 h of admission can effectively predict the early prognosis of AIS patients.

Association between gut microbiota dysbiosis and poor functional outcomes in acute ischemic stroke patients with COVID-19 infection.

Acute ischemic stroke (AIS) patients with active COVID-19 infection often have more severe symptoms and worse recovery. COVID-19 infection can cause gut microbiota dysbiosis, which is also a risk factor for poor outcomes in AIS patients. However, the association between gut microbiota and functional outcomes among AIS patients with COVID-19 infection has not been fully clarified yet. In this study, we performed 16S rRNA gene sequencing to characterize the gut microbial community among AIS patients with acute COVID-19 infection, AIS patients with post-acute COVID-19 infection, and AIS patients without COVID-19 infection. We found that AIS patients with acute COVID-19 experienced poorer recovery and significant gut dysbiosis, characterized by higher levels of Enterobacteriaceae and lower levels of Ruminococcaceae and Lachnospiraceae. Furthermore, a shorter time window (less than 28 days) between COVID-19 infection and stroke was identified as a risk factor for poor functional outcomes in AIS patients with COVID-19, and the enrichment of Enterobacteriaceae was indicated as a mediator in the relationship between infection time window and poor stroke outcomes. Our findings highlight the importance of early intervention after COVID-19 infection, especially by regulating the gut microbiota, which plays a role in the prognosis of AIS patients with COVID-19 infection.IMPORTANCEThe gut microbiota plays an important role in the association between respiratory system and cerebrovascular system through the gut-lung axis and gut-brain axis. However, the specific connection between gut bacteria and the functional outcomes of acute ischemic stroke (AIS) patients with COVID-19 is not fully understood yet. In our study, we observed a significant decrease in bacterial diversity and shifts in the abundance of key bacterial families in AIS patients with acute COVID-19 infection. Furthermore, we identified that the time window was a critical influence factor for stroke outcomes, and the enrichment of Enterobacteriaceae acted as a mediator in the relationship between the infection time window and poor stroke outcomes. Our research provides a new perspective on the complex interplay among AIS, COVID-19 infection, and gut microbiota dysbiosis. Moreover, recognizing Enterobacteriaceae as a potential mediator of poor stroke prognosis offers a novel avenue for future exploration and therapeutic interventions.

Left ventricular systolic dysfunction predicts clinical prognosis in patients with acute ischemic stroke after intravenous thrombolysis.

Although intravenous recombinant tissue plasminogen activator (rt-PA) thrombolysis is the most effective early treatment for acute ischemic stroke (AIS), outcomes vary greatly among patients. Left ventricular systolic dysfunction (LVSD) is prone to distant organ ischemia and may be a predictor for poor prognosis in AIS patients undergoing intravenous thrombolysis (IVT). Our aim was to investigate the predictivity of LVSD diagnosis (as measured by left ventricular ejection fraction (LVEF)) on 90-day clinical outcomes in AIS patients undergoing thrombolysis. The current prospective cohort study continuously enrolled 273 AIS patients from the National Stroke Prevention and Treatment Engineering Management Special Database who underwent IVT and completed echocardiography within 24 h of admission between 2021 and 2023. LVSD was examined by evaluation of the echocardiographic LVEF values using Simpson's biplane method of discs in line with international guidelines, and defined as a LVEF value < 50%. Multivariable ordinal logistic regression model was performed to analyze the association between LVEF and functional outcome at 3 months. Restricted cubic spline (RCS) was used to examine the shape of the dose-response association between reduced LVEF and poor functional outcomes. Subgroup analysis was also employed to further verify the reliability and practicability of the results. Baseline data analysis showed LVSD patients had more comorbidities including on multivariate analyses, LVSD (OR 2.78, 95% CI 1.23 to 6.24, P=0.014), pre-existing diabetes mellitus (OR 2.08, 95% CI 1.11 to 3.90, P=0.023) and NIHSS on arrival (OR 1.31, 95% CI 1.21 to 1.49, P<0.001) were independent predictors of poor functional outcomes (mRS ≥ 3) at 3 months. Multivariable-adjusted spline regression indicated a linear dose-response association between LVEF after IVT and poor functional outcomes (p for linearity < 0.001), with the optimal cutoff values of LVEF being 0.48. Our finding indicated that AIS patients with LVSD after IVT had poorer outcomes, suggesting the need to monitor and optimize LVEF in stroke management.

The effectiveness and safety of human urinary kallidinogenase in acute ischemic stroke patients undergoing endovascular therapy

The effectiveness and safety of human urinary kallidinogenase (HUK) in acute ischemic stroke (AIS) patients undergoing endovascular therapy (EVT) due to large vessel occlusion (LVO) was unclear. A pooled analysis was performed using individual data from the DEVT and RESCUE BT trials. Patients were divided into two groups based on HUK treatment. The primary outcome was the 90-day modified Rankin Scale (mRS) score. Safety outcomes included 90-day mortality and symptomatic intracranial hemorrhage (sICH) within 48 hours. A total of 1174 patients were included in the study. Of these, 150 (12.8%) patients received HUK. The adjusted common odds ratio (OR) of the mRS score was 1.458 (95% confidence interval [CI] = 1.072–1.983; p = 0.016) favoring HUK. The incidence of sICH (2.0% vs. 8.6%; adjusted OR: 0.198; 95% CI: 0.061–0.638; p = 0.007) and mortality (11.3% vs.18.5%; adjusted OR: 0.496; 95% CI: 0.286–0.862; p = 0.013) was lower in HUK group than non-HUK group. This association was consistent with propensity score-matching and the inverse probability of treatment weighting analysis. In conclusion, HUK was safe and associated with a preferable prognosis in AIS patients due to LVO in the anterior circulation.

Evaluation of ankle brachial index, serum miR-103 and LP-PLA2 in the prognosis of acute ischemic stroke.

To explore the prognostic value of ankle brachial index (ABI), serum microribonucleic acid-103 (miR-103), and lipoprotein associated phospholipase A2 (LP-PLA2) indicators in patients with acute ischemic stroke (AIS). A retrospective analysis was conducted using the medical records of 202 patients with AIS admitted to the First Affiliated Hospital of Hebei North University from June 2019 to December 2022. Patients were divided into two groups based on their prognosis: the Poor-group (n=72) and the Good-group (n=130). Levels of ABI, serum miR-103, and LP-PLA2 indicators were compared between the two groups. Multivariate logistic regression analysis was used to analyze the independent risk factors for the poor prognosis in patients with AIS, and the receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of ABI, serum miR-103, and LP-PLA2 levels on the prognosis of AIS. Seventy two patients had a poor prognosis (35.6%) and 130 had a good prognosis (64.4%). The Poor-group had a higher proportion of elderly patients, patients with a history of diabetes and hypertension, abnormal ABI, and elevations in serum miR-103 and LP-PLA2 compared to the Good-group (P<0.05). Multivariate logistic regression analysis showed that abnormal ABI, and high levels of serum miR-103 and LP-PLA2 were independent risk factors for the poor prognosis. ROC curve provided a combined AUC of 0.862, which was higher than that of the individual ABI, serum miR-103, and LP-PLA2 curves, with values of 0.625, 0.749, and 0.696, respectively (P<0.05). Abnormal ABI, and high serum miR-103 and LP-PLA2 levels are independent risk factors for poor prognosis in AIS patients. They can be used as important indicators for predicting the prognosis of AIS.

Association Between Insulin Resistance Markers and Poor Prognosis in Patients With Acute Ischemic Stroke After Intravenous Thrombolysis.

This study aims to investigate the significance of insulin resistance markers in predicting poor prognosis in acute ischemic stroke (AIS) patients after intravenous thrombolysis and to establish the corresponding nomogram. From January 2019 to March 2023, the data of 412 patients with AIS who received intravenous alteplase thrombolytic therapy in the Affiliated Taizhou People's Hospital of Nanjing Medical University were selected. Patients were randomly divided into training groups (70%, 288 cases) and validation groups (30%, 124 cases). In the training group, multivariate logistic regression analysis was used to establish the best nomogram prediction model. The predictive ability of the nomogram was further evaluated by the area under the receiver operating characteristic curve, calibration curve, decision curve analysis, and reclassification analysis. Furthermore, the model was further validated in the validation set. Multivariate logistic regression analysis showed that systolic blood pressure, diabetes, National Institutes of Health Stroke Scale score, triglyceride-glucose index, triglyceride-glucose-body mass index, ratio of low-density lipoprotein cholesterol to high-density lipoprotein cholesterol were associated with poor prognosis in AIS patients after intravenous thrombolysis ( P <0.05). Compared with conventional factors, the nomogram showed stronger prognostic ability, area under receiver operating characteristic curves were 0.948 (95% CI: 0.920-0.976, P <0.001) and 0.798 (95% CI: 0.747-0.849, P <0.001), respectively. Triglyceride-glucose index, triglyceride-glucose-body mass index, and low-density lipoprotein cholesterol to high-density lipoprotein cholesterol levels upon admission can serve as markers for poor prognosis in AIS patients after intravenous thrombolysis. The nomogram enables a more accurate prediction of poor prognosis in AIS patients after intravenous thrombolysis.

Association between stress hyperglycemia ratio and prognosis in acute ischemic stroke: a systematic review and meta-analysis.

Stress hyperglycemia is a relatively transient increase in blood glucose in response to inflammation of the body and neurohormonal disorders. It is still debated whether stress hyperglycemia ratio (SHR) in the acute phase, a new indicator of stress hyperglycemia, is related to poor prognosis in acute ischemic stroke (AIS) patients. This meta-analysis provides insight into the connection between SHR and prognosis in AIS patients. We screened all potentially relevant studies using a comprehensive database search. The standardized mean difference (SMD) and 95% confidence interval (CI) were utilized to investigate the relationship between SHR in the acute phase and the prognosis of AIS. The pooled results revealed that AIS patients with poor prognoses had significantly higher SHR values than those with good prognoses (SMD = 0.56, 95%CI: 0.37-0.75, p<0.001). Subgroup analysis indicated that study design and differences in post-stroke treatment might be the sources of heterogeneity in this meta-analysis. High SHR in the acute period is related to poor prognosis after AIS. SHR may be a new predictor of poor outcomes in AIS patients.

Association between fibrinogen-to-albumin ratio and functional prognosis of 3 months in patients with acute ischemic stroke after intravenous thrombolysis.

The presence of high fibrinogen and low albumin levels in serum is associated with a negative prognosis in acute ischemic stroke (AIS). Fibrinogen-to-albumin ratio (FAR), a new inflammatory biomarker, may provide better prognostic insights in patients with AIS than separate evaluation of fibrinogen or albumin. The objective of this investigation is to examine the correlation between FAR and 3-month functional prognosis after intravenous thrombolysis (IVT) in AIS patients. The retrospective study recruited AIS patients who received IVT from June 2014 to December 2021. The 3-month functional prognosis was assessed using the Modified Rankin Scale (mRS). A mRS score of ≤2 indicated a good outcome, whereas a mRS score of >2 suggested a poor outcome. A total of 591 AIS patients who underwent IVT were included and 147 patients (24.9 %) had a poor outcome. Among the 102 pairs of patients after propensity score matching, there was a significant association between FAR and 3-month prognosis (adjusted OR, 1.19; 95% CI, 1.03-1.38; p=.020). The optimal FAR cutoff value was found to be 7.57, and even after stratifying patients based on this value, we still observed a significant correlation between high FAR level and poor outcome (adjusted OR, 2.08; 95% CI, 1.28-3.40; p=.003). FAR may serve as a prospective biomarker of predicting 3-month prognosis in AIS patients after IVT.

Plasma S100A1 protein: An effective prognostic biomarker for 3-month clinical outcome in acute ischemic stroke patients

Background: Plasma S100A1 protein is a novel inflammation biomarker associated with acute myocardial infarction and neurodegenerative diseases. This study aimed to investigate the predictive value of S100A1 protein for the three-month prognosis of acute ischemic stroke (AIS) patients and the potential pathophysiological mechanisms of AIS. Methods: A total of 206 people in a stroke center from April 2020 to February 2021 were studied. Clinically relevant data and blood indicators were recorded. The clinical outcome was disability or death at discharge or 90 days (defined as a modified Rankin Scale score of 3-6). The relationship between S100A1 protein, NF-κB p65, and IL-6 and functional outcomes was investigated by binary logistic regression analysis and further assessed by the receiver operating characteristic curve (ROC). The correlation between S100A1, NF-κB p65, and IL-6 was detected by Pearson or Spearman correlation analysis. Results: A total of 206 subjects were enrolled (Age, 67.17±10.74; 40.3% female). Patients with unfavorable outcome showed higher S100A1, NF-κB p65, and IL-6 than those with favorable outcome (S100A1, [252.72±25.15]vs[219.84±23.24], P&lt;0.001; NF-κB p65, [4.45±0.71]vs[3.58±0.66], P&lt;0.001; IL-6, [13.86±1.41]vs[12.18±1.73], P&lt;0.001). In multivariate and ROC curve analysis, higher S100A1 (&gt;227.155) (Area under the curve [AUC], 0.864; odds ratio [OR], 1.093; 95% confidence interval [CI], 1.052- 1.135; P &lt;0.001) and higher NF-κB p65 (&gt;3.685) (AUC, 0.807; OR, 6.416; 95% CI, 1.852- 22.229; P=0.003), higher IL-6 (&gt;12.330) (AUC, 0.767; OR, 2.029; 95% CI, 1.136- 3.624; P=0.017) were independently associated with unfavorable outcome. The combined predictive value of the three indexes was higher than that of a single index. There was a significant statistical correlation between S100A1, NF-κB P65 and IL-6(P&lt;0.001). Conclusion: Higher S100A1 protein may be an independent risk factor for predicting the three-month poor prognosis in AIS patients. This protein may mediate inflammatory response through the NF-κB pathway during the pathogenesis of AIS.

Association between three-territory sign and prognosis of acute ischemic stroke patients with malignancy.

Multiple cerebral infarcts are usually secondary to cardiogenic embolism, particularly through atrial fibrillation (AF). The three-territory sign (TTS) is an imaging marker that reflects multiple cerebral lesions involving three vascular territories measured by diffusion-weighted imaging (DWI), and the most common etiology is an underlying malignancy. Recent studies have shown that TTS is six times more frequently observed in acute ischemic stroke (AIS) patients with malignancy than in those with AF-related AIS. However, the relevance of TTS to the prognosis of IS patients with malignancy remains unclear. Over a 5-year period (May 2016 to 31 June 2021), AIS admissions with DWI were identified from the First Affiliated Hospital of Xi'an Jiaotong University. Patients were divided into two groups according to whether they had malignancy or AF, resulting in a total of 80 patients with known malignancy (malignancy group) and 92 patients with AF (AF group). All DWI images were reviewed to determine the territory lesion count. Demographic, clinical, and laboratory data, together with radiographic examination data and modified Rankin Scale (mRS) score within a year, were collected. The main outcome was the association between TTS and the prognosis of AIS patients with malignancy, analyzed by a multivariate logistic regression model. A total of 172 patients met the selection criteria, including 17 (21.3%) patients in the malignancy group and 8 (8.7%) patients in the AF group with TTS. Age and sex distributions were similar for AIS patients of malignancy and AF. The TTS was 2.4 times more likely to be observed in AIS patients with malignancy compared to AF-related IS patients. The univariate analysis showed that hypertension (OR = 1.137, 95%CI: 1.002-1.291), D-dimer (OR = 1.328, 95%CI: 1.022-1.726), fibrin degradation product (OR = 1.117, 95%CI: 1.010-1.236), and lactate dehydrogenase (LDH; OR = 1.007, 95%CI: 1.000-1.015) were the risk factors for the high mortality rate. Multivariate analysis showed that TTS was the independent risk factor for mortality in AIS patients with malignancy (adjusted OR: 6.866, 95% CI: 1.371-34.395). TTS was more frequently observed in AIS patients with malignancy than AF-related AIS and substantially related to high poor outcome (mRS > 2) in AIS patients with malignancy, indicating diagnostic and prognostic value in malignancy-associated hypercoagulation stroke.

Corrected QTc interval combined with troponin value and mortality in acute ischemic stroke.

Cardiac biomarkers including, elevated troponin (ET) and prolonged heart rate-corrected QT (PQTc) interval on electrocardiography are known to frequent and have a prognostic significance in patients with acute ischemic stroke (AIS). However, it is still challenging to practically apply the results for appropriate risk stratification. This study evaluate whether combining ET and PQTc interval can better assess the long-term prognosis in AIS patients. In this prospectively registered observational study between May 2007 and December 2011, ET was defined as serum troponin-I ≥ 0.04 ng/ml and PQTc interval was defined as the highest tertile of sex-specific QTc interval (men ≥ 469 ms or women ≥ 487 ms). Among the 1,668 patients [1018 (61.0%) men; mean age 66.0 ± 12.4 years], patients were stratified into four groups according to the combination of ET and PQTc intervals. During a median follow-up of 33 months, ET (hazard ratio [HR]: 4.38, 95% confidence interval [CI]: 2.94-6.53) or PQTc interval (HR: 1.53, 95% CI: 1.16-2.01) alone or both (HR: 1.77, 95% CI: 1.16-2.71) was associated with increased all-cause mortality. Furthermore, ET, PQTc interval alone or both was associated with vascular death, whereas only ET alone was associated with non-vascular death. Comorbidity burden, especially atrial fibrillation and congestive heart failure, and stroke severity gradually increased both with troponin value and QTc-interval. In patients with AIS, combining ET and PQTc interval on ECG enhances risk stratification for long-term mortality while facilitating the discerning ability for the burden of comorbidities and stroke severity.

Development and validation of a machine learning-based prognostic risk stratification model for acute ischemic stroke

Acute ischemic stroke (AIS) is a most prevalent cause of serious long-term disability worldwide. Accurate prediction of stroke prognosis is highly valuable for effective intervention and treatment. As such, the present retrospective study aims to provide a reliable machine learning-based model for prognosis prediction in AIS patients. Data from AIS patients were collected retrospectively from the Second Affiliated Hospital of Xuzhou Medical University between August 2017 and July 2019. Independent prognostic factors were identified by univariate and multivariate logistic analysis and used to develop machine learning (ML) models. The ML model performance was assessed by area under the receiver operating characteristic curve (AUC) and radar plot. Shapley Additive explanations (SHAP) values were used to interpret the importance of all features included in the predictive model. A total of 677 AIS patients were included in the present study. Poor prognosis was observed in 209 patients (30.9%). Six variables, including neuron specific enolase (NSE), homocysteine (HCY), S-100β, dysphagia, C-reactive protein (CRP), and anticoagulation were included to establish ML models. Six different ML algorithms were tested, and Random Forest model was selected as the final predictive model with the greatest AUC of 0.908. Moreover, according to SHAP results, NSE impacted the predictive model the most, followed by HCY, S-100β, dysphagia, CRP and anticoagulation. Based on the RF model, an online tool was constructed to predict the prognosis of AIS patients and assist clinicians in optimizing patient treatment. The present study revealed that NSE, HCY, CRP, S-100β, anticoagulation, and dysphagia were important factors for poor prognosis in AIS patients. ML algorithms were used to develop predictive models for predicting the prognosis of AIS patients, with the RF model presenting the optimal performance.

Autonomic function may mediate the neuroprotection of remote ischemic postconditioning in stroke: A randomized controlled trial

ObjectivesTo evaluate the effect of remote ischemic postconditioning (RIPostC) on the prognosis of acute ischemic stroke(AIS) patients and investigate the mediating role of autonomic function in the neuroprotection of RIPostC. Materials and Methods132 AIS patients were randomized into two groups. Patients received four cycles of 5-min inflation to a pressure of 200 mmHg(i.e., RIPostC) or patients’ diastolic BP(i.e., shame), followed by 5 min of deflation on healthy upper limbs once a day for 30 days. The main outcome was neurological outcome including the National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), and Barthel index(BI). The second outcome measure was autonomic function measured by heart rate variability(HRV). ResultsCompared with the baseline, the post-intervention NIHSS score was significantly reduced in both groups (P<0.001). NIHSS score was significantly lower in the control group than intervention group at day 7.[RIPostC:3(1,5) versus shame:2(1,4); P=0.030]. mRS scored lower in the intervention group compared with the control group at day 90 follow-up(RIPostC:0.5±2.0 versus shame:1.0±2.0;P=0.016). The goodness-of-fit test revealed a significant difference between the generalized estimating equation model of mRS and BI scores of uncontrolled-HRV and controlled-HRV(P<0.05, both). The results of bootstrap revealed a complete mediation effect of HRV between group on mRS[indirect effect: −0.267 (LLCI = −0.549, ULCI = −0.048), the direct effect: −0.443 (LLCI = −0.831, ULCI = 0.118)]. ConclusionThis is the first human-based study providing evidence for a mediation role of autonomic function between RIpostC and prognosis in AIS patients. It indicated that RIPostC could improve the neurological outcome of AIS patients. Autonomic function may play a mediating role in this association. Trial registrationThe clinical trials registration number for this study is NCT02777099 (ClinicalTrials.gov Identifier)

Establishment of a dynamic nomogram including thyroid function for predicting the prognosis of acute ischemic stroke with standardized treatment.

Many patients with acute ischemic stroke (AIS) cannot undergo thrombolysis or thrombectomy because they have missed the time window or do not meet the treatment criteria. In addition, there is a lack of an available tool to predict the prognosis of patients with standardized treatment. This study aimed to develop a dynamic nomogram to predict the 3-month poor outcomes in patients with AIS. This was a retrospective multicenter study. We collected the clinical data of patients with AIS who underwent standardized treatment at the First People's Hospital of Lianyungang from 1 October 2019 to 31 December 2021 and at the Second People's Hospital of Lianyungang from 1 January 2022 to 17 July 2022. Baseline demographic, clinical, and laboratory information of patients were recorded. The outcome was the 3-month modified Rankin Scale (mRS) score. The least absolute shrinkage and selection operator regression were used to select the optimal predictive factors. Multiple logistic regression was performed to establish the nomogram. A decision curve analysis (DCA) was applied to assess the clinical benefit of the nomogram. The calibration and discrimination properties of the nomogram were validated by calibration plots and the concordance index. A total of 823 eligible patients were enrolled. The final model included gender (male; OR 0.555; 95% CI, 0.378-0.813), systolic blood pressure (SBP; OR 1.006; 95% CI, 0.996-1.016), free triiodothyronine (FT3; OR 0.841; 95% CI, 0.629-1.124), National Institutes of Health stroke scale (NIHSS; OR 18.074; 95% CI, 12.264-27.054), Trial of Org 10172 in Acute Stroke Treatment (TOAST; cardioembolic (OR 0.736; 95% CI, 0.396-1.36); and other subtypes (OR 0.398; 95% CI, 0.257-0.609). The nomogram showed good calibration and discrimination (C-index, 0.858; 95% CI, 0.830-0.886). DCA confirmed the clinical usefulness of the model. The dynamic nomogram can be obtained at the website: predict model (90-day prognosis of AIS patients). We established a dynamic nomogram based on gender, SBP, FT3, NIHSS, and TOAST, which calculated the probability of 90-day poor prognosis in AIS patients with standardized treatment.

Relationship between mean blood pressure during hospitalization and clinical outcome after acute ischemic stroke

ObjectiveThe optimal blood pressure (BP) targets for acute ischemic stroke are unclear. We aimed to assess the relationship between Mean BP and clinical outcomes during hospitalization.Materials and methodsWe included 649 patients with Acute ischemic stroke (AIS) from December 2020 to July 2021. BP was measured daily, and mean blood pressure was calculated. Clinical events recorded within 90 days of randomization were: recurrent ischemic stroke, symptomatic intracranial hemorrhage, and death. The modified Rankin Scale (mRS) was used to measure primary outcomes 3 months after AIS. Logistic multiple regression analysis was performed by statistical software R.ResultThere is a nonlinear U-shaped relationship between SBP and poor outcomes. This means higher SBP and lower SBP will increase the incidence of poor outcomes. The optimal mean SBP during hospitalization was 135-150 mmHg, and patients with SBP < 135mmhg OR 2.4 [95% Cl, (1.16 ~ 4.97)], P = 0.018; and > 150mmhg OR 2.04 [95% Cl, 1.02 ~ 4.08], p = 0.045 had a higher probability of poor outcomes.ConclusionOur study shows that the optimal SBP of patients with AIS during hospitalization was 135-150 mmHg. The findings suggest that the relationship between mean SBP and 3-month functional outcome after AIS was U-shaped. Both higher SBP and lower SBP lead to poor prognosis in AIS patients.

Correlation between serum parathyroid hormone-associated protein concentration and acute ischemic stroke

Objective To investigate the correlation between serum Parathyroid hormone-related protein (PTHrP) and acute ischemic stroke (AIS). Methods from October 2020 to March 2021, 134 patients with AIS and 34 healthy individuals were enrolled. Serum PTHrP concentration was measured by enzyme-linked immunosorbent assay (ELISA) and subgroup analysis was performed according to Trial of Org 10 172 in acute stroke treatment (TOAST) classification. The severity of AIS was assessed by the National Institutes of Health stroke scale (NIHSS) score and the volume of cerebral infarction was assessed based on head magnetic resonance imaging. The correlation of serum PTHrP concentration with various indicators was analyzed. The 90-day functional prognosis of patients was assessed by the modified Rankin scale. Patients were divided into favorable outcomes group and unfavorable outcomes group and the difference in serum PTHrP concentration between the two groups was compared. Whether serum PTHrP was associated with AIS prognosis was analyzed by Logistic regression.Results The serum PTHrP concentration in AIS group was higher than that in the control group (P=0.000), and the serum PTHrP concentrations of the three common etiological subtypes, LAA, CE and SAO, were higher than those in the control group (all P&lt;0.01). The AUC for distinguishing AIS patients and healthy control by serum PTHrP concentration was 0.751(P&lt;0.0001). The serum PTHrP concentration in the AIS group was associated with the cumulative smoking volume (r=0.201, P=0.021) and APTT (r=-0.188, p=0.034). Serum PTHrP was not associated with TOAST classification (P=0.091), NIHSS score and cerebral infarction volume (all P&gt;0.05), and there was no significant difference in serum PTHrP concentration between the favorable outcomes group and unfavorable outcomes group (P&gt; 0.05). Univariate logistic regression showed that serum PTHrP concentration was not a prognostic factor of AIS [OR=1.000 95% CI (0.999, 1.002) P=0.678]. Conclusion Serum PTHrP concentration was significantly increased in AIS patients. Serum PTHrP might be ancillary for early identification of AIS. Serum PTHrP concentration correlated with cumulative smoking volume and APTT in AIS patients, and could possibly be used to assess the true smoking volume of patients and analyze coagulation function. However, serum PTHrP concentration was not associated with TOAST classification, NIHSS score, cerebral infarction volume and 90-day prognosis, which meant it cannot be used to evaluated the etiology, severity and prognosis of AIS patients.