Plasma D-dimer level is associated with clinical outcomes in patients with atrial fibrillation related acute ischemic stroke after pneumonia

Machine learning-based model to predict composite thromboembolic events among Chinese elderly patients with atrial fibrillation

OBJECTIVE

Accurate prediction of survival prognosis is helpful to guide clinical decision-making. The aim of this study was to develop a model using machine learning techniques to predict the occurrence of composite thromboembolic events (CTEs) in elderly patients with atrial fibrillation(AF). These events encompass newly diagnosed cerebral ischemia events, cardiovascular events, pulmonary embolism, and lower extremity arterial embolism.

METHODS

This retrospective study included 6,079 elderly hospitalized patients (≥ 75 years old) with AF admitted to the People's Liberation Army General Hospital in China from January 2010 to June 2022. Random forest imputation was used for handling missing data. In the descriptive statistics section, patients were divided into two groups based on the occurrence of CTEs, and differences between the two groups were analyzed using chi-square tests for categorical variables and rank-sum tests for continuous variables. In the machine learning section, the patients were randomly divided into a training dataset (n = 4,225) and a validation dataset (n = 1,824) in a 7:3 ratio. Four machine learning models (logistic regression, decision tree, random forest, XGBoost) were trained on the training dataset and validated on the validation dataset.

RESULTS

The incidence of composite thromboembolic events was 19.53%. The Least Absolute Shrinkage and Selection Operator (LASSO) method, using 5-fold cross-validation, was applied to the training dataset and identified a total of 18 features that exhibited a significant association with the occurrence of CTEs. The random forest model outperformed other models in terms of area under the curve (ACC: 0.9144, SEN: 0.7725, SPE: 0.9489, AUC: 0.927, 95% CI: 0.9105-0.9443). The random forest model also showed good clinical validity based on the clinical decision curve. The Shapley Additive exPlanations (SHAP) showed that the top five features associated with the model were history of ischemic stroke, high triglyceride (TG), high total cholesterol (TC), high plasma D-dimer, age.

CONCLUSIONS

This study proposes an accurate model to stratify patients with a high risk of CTEs. The random forest model has good performance. History of ischemic stroke, age, high TG, high TC and high plasma D-Dimer may be correlated with CTEs.

Body fluids biomarkers associated with prognosis of acute ischemic stroke: progress and prospects

Acute ischemic stroke (AIS) is one of the most common strokes posing a grave threat to human life and health. Predicting the prognosis of AIS allows for an understanding of disease progress, and a better quality of life by making individualized treatment scheme. In this paper, we conducted a systematic search on PubMed, focusing on the relevant literature in the last 5 years. Summarizing the candidate prognostic biomarkers of AIS in body fluids such as blood, urine, saliva and cerebrospinal fluid is often of great significance for the management of acute ischemic stroke, which has the potential to facilitate early diagnosis, treatment, prevention and long-term outcome improvement.

Circulating Leukocyte as an Inflammatory Biomarker: Association with Fibrinogen and Neuronal Damage in Acute Ischemic Stroke

Background and Purpose

Leukocytes and fibrinogen are inflammatory markers involved in circulating and central inflammatory response after ischemic stroke. However, the interaction between circulating leukocytes and serum fibrinogen and neuronal injury in acute ischemic stroke (AIS) patients is still unclear. The present study aimed to investigate the association between circulating leukocyte and serum fibrinogen and neuronal injury respectively in AIS.

Methods

A cross-section study with 431 hospitalized AIS patients from department of neurology was performed. Circulating leukocytes and fibrinogen were measured, and neuron-specific enolase (NSE) was detected to evaluate central neuronal damage. A propensity score matching method was used to minimize the effects of confounding factors. The relationship between leukocytes and NSE and fibrinogen was analyzed by linear curve fitting analysis and multiple logistic regression models respectively.

Results

The mean levels of NSE, leukocyte, and fibrinogen were significantly higher in the matched AIS group (n=89) than those of in the healthy control group (n=89) (all p<0.05). Both serum NSE and fibrinogen were increased with the increasing of leukocyte in AIS patients (both p<0.05). Smoothed plots suggested that there are linear relationships between leukocyte and NSE and fibrinogen respectively. Multiple logistic regression analysis showed the OR (95%) for the relationship between leukocyte and high NSE were 1.13 (1.01-1.26, p=0.031) and 1.13 (1.00-1.28, p=0.048), and between leukocyte and high fibrinogen were 1.40 (1.22-1.61, p<0.001) and 1.35 (1.15-1.58, p<0.001) in all AIS patients before and after adjusting for potential confounders.

Conclusion

Our study suggests that elevated circulating leukocyte was associated with high fibrinogen and neuronal injury in AIS. Therefore, there may be potential targets among circulating leukocyte, fibrinogen and NSE that should be intervened to reduce inflammatory reaction after ischemic stroke.

Braden scale for predicting pneumonia after spontaneous intracerebral hemorrhage

OBJECTIVE

Stroke-associated pneumonia is an infection that commonly occurs in patients with spontaneous intracerebral hemorrhage and causes serious burdens. In this study, we evaluated the validity of the Braden scale for predicting stroke-associated pneumonia after spontaneous intracerebral hemorrhage.

METHODS

Patients with spontaneous intracerebral hemorrhage were retrospectively included and divided into pneumonia and no pneumonia groups. The admission clinical characteristics and Braden scale scores at 24 h after admission were collected and compared between the two groups. Receiver operating characteristic curve analysis was performed to assess the predictive validity of the Braden scale. Multivariable analysis was conducted to identify the independent risk factors associated with pneumonia after intracerebral hemorrhage.

RESULTS

A total of 629 intracerebral hemorrhage patients were included, 150 (23.8%) of whom developed stroke-associated pneumonia. Significant differences were found in age and fasting blood glucose levels between the two groups. The mean score on the Braden scale in the pneumonia group was 14.1±2.4, which was significantly lower than that in the no pneumonia group (16.5±2.6), p<0.001. The area under the curve for the Braden scale for the prediction of pneumonia after intracerebral hemorrhage was 0.760 (95%CI 0.717-0.804). When the cutoff point was 15 points, the sensitivity was 74.3%, the specificity was 64.7%, the accuracy was 72.0%, and the Youden's index was 39.0%. Multivariable analysis showed that a lower Braden scale score (OR 0.696; 95%CI 0.631-0.768; p<0.001) was an independent risk factor associated with stroke-associated pneumonia after intracerebral hemorrhage.

CONCLUSION

The Braden scale, with a cutoff point of 15 points, is moderately valid for predicting stroke-associated pneumonia after spontaneous intracerebral hemorrhage.

High Fibrinogen to Albumin Ratio: A Novel Marker for Risk of Stroke-Associated Pneumonia?

Background: Stroke-associated pneumonia (SAP) is associated with poor prognosis after acute ischemic stroke (AIS).

Purpose: This study aimed to describe the parameters of coagulation function and evaluate the association between the fibrinogen-to-albumin ratio (FAR) and SAP in patients with AIS.

Patients and methods: A total of 932 consecutive patients with AIS were included. Coagulation parameters were measured at admission. All patients were classified into two groups according to the optimal cutoff FAR point at which the sum of the specificity and sensitivity was highest. Propensity score matching (PSM) was performed to balance potential confounding factors. Univariate and multivariate logistic regression analyses were applied to identify predictors of SAP.

Results: A total of 100 (10.7%) patients were diagnosed with SAP. The data showed that fibrinogen, FAR, and D-dimer, prothrombin time (PT), activated partial thromboplastin time (aPTT) were higher in patients with SAP, while albumin was much lower. Patients with SAP showed a significantly increased FAR when compared with non-SAP (P < 0.001). Patients were assigned to groups of high FAR (≥0.0977) and low FAR (<0.0977) based on the optimal cut-off value. Propensity score matching analysis further confirmed the association between FAR and SAP. After adjusting for confounding and risk factors, multivariate regression analysis showed that the high FAR (≥0.0977) was an independent variable predicting the occurrence of SAP (odds ratio =2.830, 95% CI = 1.654–4.840, P < 0.001). In addition, the FAR was higher in the severe pneumonia group when it was assessed by pneumonia severity index (P = 0.008).

Conclusions: High FAR is an independent potential risk factor of SAP, which can help clinicians identify high-risk patients with SAP after AIS.

Plasma levels of leucocyte elastase-generated cross linked fibrin degradation products (E-XDP) are elevated in chronic venous disease

Patients with chronic venous disease (CVD) have elevated levels of leucocyte elastase (LE) released from the activation of leucocytes. In acute deep venous thrombosis (DVT), LE can degrade fibrin from the thrombus resulting in cross-linked fibrin degradation products (E-XDP) being released into the bloodstream. In patients with CVD the levels and significance of circulating E-XDP are unknown. We aimed to investigate the association between plasma E-XDP concentration and severity of CVD. Levels of E-XDP were quantified with a specific enzyme-linked immunosorbent assay (ELISA) in plasma from 142 consecutively recruited CVD patients (mean age 64 years, (range 23–89), 81 were females and 61 males). Patients were also divided into three groups based on CVD severity using the C-class of the Clinical-Etiological-Anatomical-Pathophysiological (CEAP) classification, with C 0–1 class as the reference group, C 2–3 as the second group and C 4–6 as the third group with the most severely affected patients. We found significantly elevated levels of E-XDP in patients with C 4–6 compared with patients with C 0–1 (p = 0.007) and increased with increasing disease severity across the groups (p = 0.02). Significant independent association was observed between levels of E-XDP and the classes C 4–6 after adjustment for age and sex (p < 0.05), but the association was no longer significant after further adjustment for use of statins, use of anticoagulants and history of DVT (p = 0.247). This exploratory study shows that E-XDP levels are elevated in patients with CVD, encouraging further studies on the role of E-XDP in CVD.