Clinical significance of D-dimer levels during acute period in ischemic stroke

High preoperative D-dimer increases the risk of venous thromboembolism after gynecological tumor surgeries: a meta-analysis of cohort studies

The role of preoperative D-dimer in the prediction of postoperative venous thromboembolism (VTE) with gynecological tumor remains unclear. This meta-analysis sought to assess the association between preoperative D-dimer and the risk of VTE after gynecological tumor surgeries and to identify prognostic significance of D-dimer in the prediction of postoperative VTE. This study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement. Eight electronic databases were searched for cohort studies from the date of inception to April 2024. The Newcastle-Ottawa Scale scoring tool and the Risk of Bias in Non-Randomized Studies-Intervention tool were used to assess the quality of the literature and the risk of bias in cohort studies, respectively. The relative risk and 95% CIs of the highest vs the lowest category and per milligram per liter of D-dimer were pooled relative to the VTE risk after gynecological tumor surgeries. Fifteen studies that met the criteria were included. Among these studies, D-dimer was considered as a continuous variable in 8 studies. The random-effect model results showed that the VTE risk was increased by 42% (15%-69%) per milligram per liter increase in D-dimer. Furthermore, based on the cutoff thresholds of D-dimer, 7 studies that reported the effect estimates of postoperative VTE in women with gynecological tumor by D-dimer were categorized as binary variables. Compared with the reference levels, the pooled relative risk of VTE after gynecological tumor surgeries for the higher level was 2.58 (95% CI, 1.49-4.47). Elevated preoperative D-dimer was associated with higher VTE risks after gynecological tumor surgeries.

High fibrin and platelet clot predicts stroke recurrence or mortality after thrombectomy in patients with active cancer

BACKGROUND

Fibrin and platelet (FP)-rich clots have been shown to be associated with cancer-related stroke. This study aims to investigate the prognostic role of thrombus composition in clinical outcomes among cancer patients who experienced stroke and received endovascular thrombectomy (EVT).

METHODS

We included acute ischemic stroke patients who underwent EVT between March 2015 and November 2021. These patients were categorized into three groups: those with active cancer, those with non-active cancer, and those without cancer. The percentages of FP in clots were quantified under hematoxylin and eosin staining. The primary outcome was defined as any stroke recurrence or mortality within 90 days following the index stroke event.

RESULTS

A total of 420 patients with retrieved clots were included in the study. This cohort comprised 50 patients with active cancer, 23 patients with non-active cancer, and 347 patients without cancer. The percentage of FP was significantly higher in thrombi retrieved from patients with active cancer compared with the other two groups. Patients in the active cancer group exhibited a higher rate of the primary outcome compared with the other groups. After adjusting for clinical variables, a higher percentage of FP in thrombi remained significantly associated with the primary outcome in the active cancer group (adjusted odds ratio (aOR) =1.03 (1.00-1.06), P=0.028), but not in the other two groups.

CONCLUSION

Among stroke patients receiving EVT, thrombi with a higher percentage of FP not only identify individuals with active cancer but also predict stroke recurrence or mortality within 90 days.

Predictive Value of Plasma D-Dimer for Cerebral Herniation Post-Thrombectomy in Acute Ischemic Stroke Patients

Background

Cerebral hernia is a serious complication after thrombectomy in patients with acute ischemic stroke (AIS). This study aims to explore the predictive value of emergency preoperative plasma D-dimer levels in cerebral herniation after successful thrombectomy.

Methods

Between January 2019 and December 2023, patients with AIS who received a successful thrombectomy in our single comprehensive stroke center were retrospectively enrolled. We conducted a statistical analysis on the data using SPSS 26.0. Receiver operating characteristic curve (ROC) was used to evaluate the predictive value of D-dimer level for cerebral herniation.

Results

Among 278 enrolled patients, 20 cases (7.19%) experienced cerebral herniation. In patients with cerebral hernia, the score of the National Institutes of Health Stroke Scale was higher (16.5 vs 12.0, P < 0.001), the Alberta Stroke Plan early CT score was lower (6.5 vs 8.0, P < 0.001), the score of collateral circulation was lower (2.0 vs 3.0, P < 0.001), the proportion of eTICI blood flow grading of 3 of the occluded vessel was less (35% vs 75.19%), the proportion of pathogenesis of large atherosclerosis was less (5.00% vs 46.51%, P < 0.001), and the level of plasma D-dimer was higher (2.61 vs 0.82). After adjusting for potential confounders, the level of D-dimer (adjusted OR = 1.131, 95% CI 1.022-1.250, P = 0.017) was significantly correlated with cerebral hernia. Based on the ROC curve, the sensitivity and specificity of D-dimer in predicting cerebral herniation were 75.0% and 73.3%, respectively, and the area under the curve was 0.766.

Conclusion

Although our study had certain limitations, we found that elevated emergency preoperative plasma D-dimer level is an independent predictive factor for the cerebral herniation after successful thrombectomy in patients with AIS, which is of great clinical significance.

Incidence and risk factors of ischemic stroke in patients with cancer-associated venous thromboembolism: from the Contemporary Management and Outcomes in Patients With Venous Thromboembolism Registry-2

Background

Ischemic stroke is a serious complication in patients with cancer-associated venous thromboembolism (CAVTE), although data remain scarce in the direct oral anticoagulant era.

Objectives

This study aimed to investigate the incidence and identify predictive risk factors of ischemic stroke in patients with CAVTE.

Methods

From the Contemporary Management and Outcomes in Patients With Venous Thromboembolism Registry-2 enrolling 5197 venous thromboembolism (VTE) patients across 31 centers in Japan between January 2015 and August 2020, we selected 1507 patients with active cancer. We calculated the cumulative incidence function of ischemic stroke accounting for the competing risk of death and investigated risk factors for ischemic stroke in a subdistribution hazard model of multivariable analysis.

Results

During a median follow-up period of 1020 days, 71 patients (4.7%) developed ischemic stroke, and the cumulative incidence of ischemic stroke was 4.0% at 1 year and 4.7% at 3 years. Independent risk factors of ischemic stroke included pancreatic cancer (hazard ratio [HR], 4.24; 95% CI, 2.13-8.43), ovarian cancer (HR, 2.82; 95% CI, 1.31-6.08), lung cancer (HR, 2.35; 95% CI, 1.20-4.57), dyslipidemia (HR, 1.76; 95% CI, 1.01-3.09), metastasis (HR, 1.70; 95% CI, 1.02-2.82), higher D-dimer at VTE diagnosis (HR, 1.09; 95% CI, 1.04-1.14), and younger age (HR, 0.84; 95% CI, 0.71-0.999).

Conclusion

In this large VTE registry in the direct oral anticoagulant era, the cumulative incidence of ischemic stroke was 4.0% at 1 year and 4.7% at 3 years in patients with CAVTE, and several independent risk factors of ischemic stroke were identified, including pancreatic cancer, ovarian cancer, lung cancer, dyslipidemia, metastasis, higher D-dimer at VTE diagnosis, and younger age.

Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy

BACKGROUND

Epilepsy is a serious complication after an ischemic stroke. Although two studies have developed prediction model for post-stroke epilepsy (PSE), their accuracy remains insufficient, and their applicability to different populations is uncertain. With the rapid advancement of computer technology, machine learning (ML) offers new opportunities for creating more accurate prediction models. However, the potential of ML in predicting PSE is still not well understood. The purpose of this study was to develop prediction models for PSE among ischemic stroke patients.

METHODS

Patients with ischemic stroke from two stroke centers were included in this retrospective cohort study. At the baseline level, 33 input variables were considered candidate features. The 2-year PSE prediction models in the derivation cohort were built using six ML algorithms. The predictive performance of these machine learning models required further appraisal and comparison with the reference model using the conventional triage classification information. The Shapley additive explanation (SHAP), based on fair profit allocation among many stakeholders according to their contributions, is used to interpret the predicted outcomes of the naive Bayes (NB) model.

RESULTS

A total of 1977 patients were included to build the predictive model for PSE. The Boruta method identified NIHSS score, hospital length of stay, D-dimer level, and cortical involvement as the optimal features, with the receiver operating characteristic curves ranging from 0.709 to 0.849. An additional 870 patients were used to validate the ML and reference models. The NB model achieved the best performance among the PSE prediction models with an area under the receiver operating curve of 0.757. At the 20 % absolute risk threshold, the NB model also provided a sensitivity of 0.739 and a specificity of 0.720. The reference model had poor sensitivities of only 0.15 despite achieving a helpful AUC of 0.732. Furthermore, the SHAP method analysis demonstrated that a higher NIHSS score, longer hospital length of stay, higher D-dimer level, and cortical involvement were positive predictors of epilepsy after ischemic stroke.

CONCLUSIONS

Our study confirmed the feasibility of applying the ML method to use easy-to-obtain variables for accurate prediction of PSE and provided improved strategies and effective resource allocation for high-risk patients. In addition, the SHAP method could improve model transparency and make it easier for clinicians to grasp the prediction model's reliability.

Relationship between serum plasminogen activator and D-dimer levels and the severity of Kawasaki disease in children as well as their predictive value for coronary artery lesion

OBJECTIVE

To evaluate the relationships between serum plasminogen activator (PA) and D-dimer levels, the severity of Kawasaki disease (KD) in children, and their ability to predict coronary artery lesions (CAL).

METHODS

This retrospective study analyzed the clinical data of 102 children diagnosed with KD at the Affiliated Hospital of Jiangnan University from January 2020 to September 2023. The cohort was divided into two groups: 31 children with CAL in the CAL group and 71 without it in the non-CAL group. The study assessed the incidence of CAL and investigated the correlations between serum PA and D-dimer levels and various inflammatory markers (white blood cell (WBC) count, platelet count, and erythrocyte sedimentation rate (ESR)). Receiver operating characteristic (ROC) curves were used to evaluate the predictive value of these biomarkers for CAL.

RESULTS

CAL was present in 30.04% of the children. Pearson correlation analysis revealed that serum PA levels were inversely correlated with WBC count (P = 0.0187), platelet count (P = 0.0116), and ESR (P = 0.0041), while D-dimer levels were positively correlated with these markers (P < 0.001). A negative correlation between PA and D-dimer levels was also observed (P < 0.001). The combined use of PA and D-dimer levels to predict CAL achieved an area under the curve of 0.871.

CONCLUSION

Serum PA levels were negatively associated with the severity of KD, whereas D-dimer levels were positively associated. Together, these markers showed significant predictive value for CAL, highlighting their utility in assessing disease severity and guiding management in children with KD.

Factors impacting D-dimer levels in patients with acute ischemic cerebrovascular events

BACKGROUND AND OBJECTIVES

A better understanding of the factors influencing D-dimer levels in code stroke patients is needed to guide further investigations of concomitant thrombotic conditions. This study aimed to investigate the impact of time from symptom onset and other factors on D-dimer levels in patients with acute ischemic stroke (AIS) or transient ischemic attack (TIA).

METHODS

Data on consecutive AIS and TIA patients treated at our tertiary-care stroke center between January 2015 and December 2020 were retrospectively assessed. Patients with available D-dimer levels were evaluated for eligibility. Multivariable non-linear regression analyses were performed.

RESULTS

In total, 2467 AIS patients and 708 TIA patients were included. The median D-dimer levels differed between the AIS and TIA groups (746 µg/L [interquartile range 381-1468] versus 442 µg/L [interquartile range 244-800], p<0.001). In AIS patients, an early increase in D-dimer levels was demonstrated within the first 6 h (standardized beta coefficient [β] 0.728; 95% confidence interval [CI] 0.324-1.121). This was followed by an immediate decrease (β -13.022; 95% CI -20.401 to -5.643) and then by a second, late increase after 35 h (β 11.750; 95% CI 4.71-18.791). No time-dependent fluctuation in D-dimer levels was observed in TIA patients.

CONCLUSION

The time from symptom onset may affect D-dimer levels in patients with AIS but not those with TIA. Further studies confirming these findings and validating time-specific variations are needed to enable D-dimer levels to be used efficiently as an acute stroke and thrombotic risk biomarker.

Association between N-terminal pro-B-type natriuretic peptide and clinical outcomes in bedridden patients with stroke: a cross-sectional study

OBJECTIVES

Patients with stroke often remain bedridden despite rehabilitation. Serum N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) levels increase after stroke. Our study aimed to investigate the difference in NT-pro-BNP levels between bedridden and non-bedridden patients with stroke and to explore the factors influencing NT-pro-BNP levels in bedridden patients.

DESIGN

A single-centre, cross-sectional study.

SETTING

This study was conducted in a hospital, Shenzhen, China.

PARTICIPANTS

Between January 2019 and December 2022, 465 participants were included in this study.

OUTCOME MEASURES

The collected data included basic information, laboratory data and echocardiographic parameters. Binary logistic regression analysis and receiver operating characteristic curves were used to identify factors associated with high NT-pro-BNP levels.

RESULTS

Bedridden patients with stroke had higher levels of NT-pro-BNP, D-dimer, high-sensitivity C reactive protein (hs-CRP) and lower levels of creatinine, high-density lipoprotein cholesterol, albumin and haemoglobin, as well as lower left ventricular ejection fraction, fractional shortening and the ratio between the peak velocities of early and late diastolic filling than non-bedridden patients. In bedridden patients, age ≥75 years, high levels of hs-CRP and creatinine, and low levels of albumin were associated with high NT-pro-BNP levels. In non-bedridden patients, age ≥75 years and high creatinine levels were associated with high NT-pro-BNP levels. In bedridden patients with stroke, the area under the curve (AUC) of hs-CRP was 0.700 (p<0.001, 95% CI 0.638 to 0.762) with a cut-off value of 5.12 mg/L. The AUC of albumin was 0.671 (p<0.001, 95% CI 0.606 to 0.736) with a cut-off value of 37.15 g/L.

CONCLUSIONS

NT-pro-BNP levels were higher in bedridden patients with stroke than in non-bedridden patients. Decreased albumin and elevated hs-CRP levels were associated with high levels of NT-pro-BNP in bedridden patients. Further studies are needed to explore the risk stratification and potential treatments for elevated NT-pro-BNP in bedridden patients with stroke.

Systematic review and meta-analysis of studies comparing baseline D-dimer level in stroke patients with or without cancer: Strength of current evidence

Objectives

D-dimer levels are increased in stroke and cancer. Cancer patients are at a higher risk of stroke. However, the evidence is unclear if high D-dimer in stroke patients can suggest the diagnosis of concomitant cancer or the development of stroke in a cancer patient. The objective is to assess the evidence available on the baseline D-dimer level in stroke patients with and without cancer.

Materials and Methods

We conducted the systematic review and meta-analysis using the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. We searched PUBMED, Cochrane, ScienceDirect, and Scopus for potentially eligible articles published till June 2023. All the review steps were iterative and done independently by two reviewers. The Newcastle-Ottawa scale tool was used to assess the quality of included studies for case control and cohort studies and the Agency for Healthcare Research and Quality tool for cross-sectional studies. The qualitative synthesis is presented narratively, and quantitative synthesis is shown in the forest plot using the random effects model. I2 of more than 60% was considered as high heterogeneity.

Results

The searches from all the databases yielded 495 articles. After the study selection process, six papers were found eligible for inclusion in the qualitative and quantitative synthesis. In the present systematic review, 2651 patients with ischemic infarcts are included of which 404 (13.97%) patients had active cancer while 2247 (86.02%) did not. The studies included were of high quality and low risk of bias. There were significantly higher baseline D-dimer levels in stroke patients with cancer than in non-cancer patients with a mean difference of 4.84 (3.07-6.60) P < 0.00001.

Conclusion

D-dimer is a simple and relatively non-expensive biomarker that is increased to significant levels in stroke patients, who have cancer and therefore may be a tool to predict through screening for active or occult cancer in stroke patients.

Trends and hotspots related to traditional and modern approaches on acupuncture for stroke: A bibliometric and visualization analysis

BACKGROUND

Acupuncture role in stroke treatment and post-stroke rehabilitation has garnered significant attention. However, there is a noticeable gap in bibliometric studies on this topic. Additionally, the precision and comprehensive methodology of cluster analysis remain underexplored. This research sought to introduce an innovative cluster analysis technique (called follower-leading clustering algorithm, FLCA) to evaluate global publications and trends related to acupuncture for stroke in the recent decade.

METHODS

Publications pertaining to acupuncture for stroke from 2013 to 2022 were sourced from the Web of Science Core Collection. For the assessment of publication attributes-including contributing countries/regions (e.g., US states, provinces, and major cities in China) in comparison to others, institutions, departments, authors, journals, and keywords-we employed bibliometric visualization tools combined with the FLCA algorithm. The analysis findings, inclusive of present research status, prospective trends, and 3 influential articles, were presented through bibliometrics with visualizations.

RESULTS

We identified 1050 publications from 92 countries/regions. An initial gradual rise in publication numbers was observed until 2019, marking a pivotal juncture. Prominent contributors in research, based on criteria such as regions, institutions, departments, and authors, were Beijing (China), Beijing Univ Chinese Med (China), the Department of Rehabilitation Medicine, and Lidian Chen (Fujian). The journal "Evid.-based Complement Altern" emerged as the most productive. The FLCA algorithm was effectively employed for co-word and author collaboration analyses. Furthermore, we detail the prevailing research status, anticipated trends, and 3 standout articles via bibliometrics.

CONCLUSION

Acupuncture for stroke presents a vast research avenue. It is imperative for scholars from various global regions and institutions to transcend academic boundaries to foster dialogue and cooperation. For forthcoming bibliometric investigations, the application of the FLCA algorithm for cluster analysis is advocated.