Clinical and Applied Thrombosis/Hemostasis最新文献

Background: Pulmonary embolism (PE) patients combined with heart failure (HF) have been reported to have a high short-term mortality. However, few studies have developed predictive tools of 30-day mortality for these patients in intensive care unit (ICU). This study aimed to construct and validate a machine learning (ML) model to predict 30-day mortality for PE patients combined with HF in ICU.

Methods: We enrolled patients with PE combined with HF in the Medical Information Mart for Intensive Care Database (MIMIC) and developed six ML models after feature selection. Further, eICU Collaborative Research Database (eICU-CRD) was utilized for external vali- dation. The area under curves (AUC), calibration curves, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were performed to evaluate the prediction performance. Shapley additive explanation (SHAP) was performed to enhance the interpretability of our models.

Results: A total of 472 PE patients combined with HF were included. We developed six ML models by the 13 selected features. After internal validation, the Support Vector Ma- chine (SVM) model performed best with an AUC of 0.835, a superior calibration degree, and a wider risk threshold (from 0% to 90%) for obtaining clinical benefit, which also outperformed traditional mortality risk evaluation systems,as evaluated by NRI and IDI. The SVM model was still reliable after external validation. SHAP was performed to explain the model. Moreover, an online application was developed for further clinical use.

Conclusion: This study developed a potential tool for identify short-term mortality risk to guide clinical decision making for PE patients combined with HF in the ICU. The SHAP method also helped clinicians to better understand the model.

Background: The stage of cerebral venous thrombosis (CVT) is crucial to guide treatment decisions. This study aims to examine changes in fibrinolytic indicators throughout CVT onset and validate a predictive model using admission fibrinolytic indicators to estimate the CVT stage.

Methods: Retrospective analysis was conducted on data from 292 CVT patients. We utilized linear regression, time series, and univariate ANOVA analyses to explore characteristics of change in fibrinolytic indicators with CVT duration and identified time point at which fibrinolysis indexes showed significant changes as the time point for acute and chronic stages of CVT. A nomogram was employed to construct a prediction model using a training set, which was then evaluated for discrimination, calibration, and clinical utility.

Results: Prolonged onset duration independently correlated with decreased fibrinogen and D-dimer after adjusting for all variables, with adjusted correlation coefficients of -0.003 (-0.005, -0.001) and -0.004 (-0.007, -0.001), respectively. Significant changes in fibrinolytic indicators were observed around 14 days after CVT onset. The training set demonstrated an area under the curve (AUC) of 0.851 (95% CI: 0.7989-0.904) for the prediction model. Internal validation showed that the nomogram accurately predicted acute CVT with an AUC of 0.828 (95% CI: 0.738-0.918).

Conclusion: According to the trend of fibrinolysis index, 14 days of onset can be used as the dividing point of acute and chronic stages of CVT. For patients with unclear onset, the present model, based on admission fibrinogen and D-dimer values, can accurately predict the stage of CVT. The high discriminative ability indicates the potential of this model for classifying the acute patient.

The objective of this survey was to gain a real-world perspective on coagulation testing by evaluating the availability of various coagulation laboratory tests, assessing specific analytic and postanalytic steps in clinical laboratories in Korea.Participants were surveyed using a 65-question questionnaire specifically focused on their coagulation testing practices related to prothrombin time (PT), activated partial thromboplastin time (aPTT), plasma-mixing studies, lupus anticoagulant (LA) tests, platelet function tests, coagulation factor assays, and the composition of hemostasis and thrombosis test panels. The survey was performed between July and September 2022.The survey achieved a 77.9% (81 of 104) response rate. PT or aPTT tests were performed directly at all participating institutions, followed by D-dimer and fibrinogen tests, platelet function test, and plasma-mixing studies in order of frequency. Variations existed in the performance of mixing test and LA assessment. Patterns of coagulating testing differed depending on the size of the hospital. The survey revealed that most laboratories conducted coagulation tests following the international guidelines such as Clinical Laboratory Standards Institute guidelines and the Korean Laboratory Certification system. However, some coagulation tests, including mixing test and LA tests, are yet to be standardized in Korea.Continuous education on coagulation test methods and internal and external quality control are required to encourage laboratories to enhance the performance of coagulation testing.

Cerebral venous sinus thrombosis (CVST) is a rare neurovascular condition that has been observed in individuals with coronavirus disease 2019 (COVID-19). This systematic review aimed to explore the sex differences and characteristics of concurrent COVID-19 and CVST cases. A total of 212 CVST patients were included in the study. Women with CVST had a slightly higher mean age compared to men (47.359 years vs 46.08 years). Women were more likely to report symptoms such as fever (56.1%) and decreased sense of smell or taste (71.4%), while men more frequently experienced nausea or vomiting (55.6%), headache (62.9%), and seizures (72%). Notably, current smokers, who were predominantly men, had a higher occurrence of CVST. On the other hand, women had a higher likelihood of CVST risk factors such as oral contraceptive pill (OCP) use and autoimmune diseases. Treatment approaches also showed sex-based differences. Unfractionated heparin was administered more often to women with CVST (63.2%). The in-hospital mortality rate for CVST patients was 21.3%, with men having a significantly higher mortality rate than women (65.2% vs 34.8%, P = .027). Survival analysis revealed that factors such as smoking history, diabetes mellitus, hypertension, OCP use, COVID-19 symptoms, CVST symptoms, and the need for intubation significantly influenced survival outcomes. Understanding these sex differences in COVID-19-related CVST is crucial for accurate diagnosis and effective management, ultimately leading to improved patient outcomes. Our findings highlight the importance of considering sex as a factor in the evaluation and treatment of individuals with COVID-19 and concurrent CVST.

The presence of both atrial fibrillation (AF) and heart failure (HF) increases the risk of an ischemic cerebrovascular event (CVE) by roughly fivefold. The HATCH score is a score used to predict new-onset AF. Although there are some differences, it contains risk factors similar to the CHA2DS2-VASc score. Our study aimed to investigate the relationship between the HATCH score and ischemic CVE. This retrospective study obtained data from 1719 HF patients between 2015 and 2022. About 673 patients with AF were included in the study. In the univariate and multivariate Cox regressions, we found that CHA2DS2-VASc and HATCH scores were independent predictors of ischemic CVE (p = 0.001 and < p = 0.001, respectively). The ROC analysis, AUC for the CHA2DS2-VASc score was 0.884 (95% CI 0.828-0.940, ). For the HATCH score, the AUC was 0.978 (95% CI 0.966-0.991, ). The HATCH score can be an independent predictor of the development of ischemic CVE in HF patients with AF.