Effects of intensive, targeted education by pharmacists on anticoagulant patients with atrial fibrillation: a multicenter randomized controlled trial from China.

AIMS: Many people diagnosed with atrial fibrillation (AF) may lack awareness of AF and anticoagulants. The purpose of this study is to investigate the effects of intensive, targeted education by pharmacists on anticoagulant patients with AF. METHODS AND RESULTS: Three hundred seventy-six AF patients were randomly assigned to receive standard care or pharmacist education. Follow-up is scheduled after 1, 3, 6, and 12 months. Pharmacists provided intensive education on knowledge deficits revealed by the Jessa Atrial Fibrillation Knowledge Questionnaire (JAKQ) during each visit. Patients also completed two questionnaires to assess their medication adherence and satisfaction. Clinical outcomes were recorded during follow-up. 361 patients completed follow-up. Baseline scores on the JAKQ were similar in the education group (median: 31.3%) and the standard care group (median: 31.3%) (p = 0.911). Over time, the knowledge score of the education group increased significantly (1 month: 68.8%, 3 months: 81.3%; P <0.001), while there was no significant improvement in the standard care group (1 month: 37.5%, 3 months: 37.5%; P = 0.314). Adherence scores improved significantly over time in the education group (P < 0.001) but not in the standard care group (P =0.101). Compared with standard care, pharmacist education was associated with a significantly lower risk of bleeding (P=0.034). CONCLUSIONS: Given the knowledge deficiency of AF patients in China, standardized patient education should be a part of their daily care. Pharmacist-led education intervention can significantly improve the disease-related knowledge, medication adherence, and drug treatment satisfaction of AF patients while significantly reducing the risk of bleeding.

Comparison of the Efficacy and Safety of Rivaroxaban and Low Molecular Heparin in Preventing Venous Thromboembolism in Inpatient Cancer Patients.

BACKGROUND: There are few studies on using rivaroxaban and low molecular heparin (LMWH) to prevent venous thromboembolism (VTE) in hospitalized cancer patients. OBJECTIVE: We conducted a retrospective study to evaluate the efficacy and safety of rivaroxaban versus LMWH for the primary prevention of VTE in inpatient cancer patients. METHODS: Information on patients was collected through 6-month follow-up and medical record inquiries. Clinical outcomes included VTE, total bleeding, thrombosis, major bleeding, minor bleeding, all-cause death, and a composite endpoint of bleeding, thrombosis, and death. RESULTS: A total of 602 hospitalized cancer patients were included in this study. During 6 months of follow-up, there were 26 VTE events (8.6%), 42 total bleeding events (7.0%), 62 all-cause deaths (10.3%), and 140 composite endpoints (23.3%). After adjusting for various confounding factors, there were no significant differences between the rivaroxaban and LMWH for VTE events (OR = 0.851, 95% CI [0.387-1.872], P=0.688), total bleeding (OR = 1.690, 95% CI [0.768-3.719], P = 0.192], thrombosis events (OR = 0.919, 95% CI [0.520-1.624], P = 0.772], major bleeding (OR = 0.276, 95% CI [0.037-2.059], P = 0.209), all-cause death (OR = 0.994, 95% CI [0.492-2.009], P = 0.987), and composite endpoints (OR = 0.994, 95% CI [0.492-2.009], P = 0.987), while minor bleeding (OR = 3.661 95% CI [1.000-7.083], P = 0.050) was significantly higher in the rivaroxaban than in the LMWH. CONCLUSIONS AND RELEVANCE: In thromboprophylaxis in inpatient cancer patients, rivaroxaban has a similar rate of VTE and bleeding events as LMWH. Our results may provide a reference for the clinical use of rivaroxaban to prevent VTE in hospitalized cancer patients.

New score for predicting thromboembolic events in patients with atrial fibrillation using direct oral anticoagulants.

Determinants of thrombotic events remain uncertain in patients with atrial fibrillation treated with direct oral anticoagulants (DOACs). Our aim was to identify risk factors associated with thromboembolism in patients with at atrial fibrillation on DOACs and to construct and externally validate a predictive model that would provide a validated tool for clinical assessment of thromboembolism. In the development cohort, prediction model was built by logistic regression, the area under the curve (AUC), and Nomogram. External validation and calibration of the model using AUC and Hosmer-Lemeshow test. This national multicenter retrospective study included 3263 patients with atrial fibrillation treated with DOACs. The development cohort consisted of 2390 patients from three centers and the external validation cohort consisted of 873 patients from 13 centers. Multifactorial analysis showed that heavy drinking, hypertension, prior stroke/transient ischemic attack (TIA), cerebral infarction during hospitalization were independent risk factors for thromboembolism. The Alfalfa-TE risk score was constructed using these four factors (AUC = 0.84), and in the external validation cohort, the model showed good discriminatory power (AUC = 0.74) and good calibration (Hosmer-Lemeshow test P value of 0.649). Based on four factors, we derived and externally validated a predictive model for thromboembolism with DOACs in patients with atrial fibrillation (Alfalfa-TE risk score). The model has good predictive value and may be an effective tool to help reduce the occurrence of thromboembolism in patients with DOACs.

Interpretable machine learning models for predicting venous thromboembolism in the intensive care unit: an analysis based on data from 207 centers.

BACKGROUND: Venous thromboembolism (VTE) is a severe complication in critically ill patients, often resulting in death and long-term disability and is one of the major contributors to the global burden of disease. This study aimed to construct an interpretable machine learning (ML) model for predicting VTE in critically ill patients based on clinical features and laboratory indicators. METHODS: Data for this study were extracted from the eICU Collaborative Research Database (version 2.0). A stepwise logistic regression model was used to select the predictors that were eventually included in the model. The random forest, extreme gradient boosting (XGBoost) and support vector machine algorithms were used to construct the model using fivefold cross-validation. The area under curve (AUC), accuracy, no information rate, balanced accuracy, kappa, sensitivity, specificity, precision, and F1 score were used to assess the model's performance. In addition, the DALEX package was used to improve the interpretability of the final model. RESULTS: This study ultimately included 109,044 patients, of which 1647 (1.5%) had VTE during ICU hospitalization. Among the three models, the Random Forest model (AUC: 0.9378; Accuracy: 0.9958; Kappa: 0.8371; Precision: 0.9095; F1 score: 0.8393; Sensitivity: 0.7791; Specificity: 0.9989) performed the best. CONCLUSION: ML models can be a reliable tool for predicting VTE in critically ill patients. Among all the models we had constructed, the random forest model was the most effective model that helps the user identify patients at high risk of VTE early so that early intervention can be implemented to reduce the burden of VTE on the patients.

An instrument to measure atrial fibrillation knowledge in Chinese patients: validation of the Jessa Atrial fibrillation Knowledge Questionnaire.

Background: There is no validated tool to assess patients' knowledge of oral anticoagulant therapy in atrial fibrillation in China. Methods: Using a standard translation program, the Jessa Atrial fibrillation Knowledge Questionnaire (JAKQ) was translated into Chinese. The reliability of the JAKQ was assessed by internal consistency (Cronbach's α coefficient), repeatability (test-retest reliability), and sensitivity tests. Effectiveness was assessed by hypothesizing that a lower JAKQ score was a risk factor for bleeding. A total of 447 patients with atrial fibrillation (AF) who were hospitalized between July 2019 and December 2021 were studied and followed up. Participants were followed up 1, 3, 6, and 12 months after enrollment. Bleeding during follow-up was recorded. Data were obtained from hospital databases and telephone follow-up. Result: A total of 447 patients with AF completed JAKQ. The mean age of patients was 67.7 ± 10.2 years. The median JAKQ score was 31.3% (12.5-43.8). The Cronbach's α coefficient of JAKQ was 0.616-0.637, and the test-retest reliability value was 0.902 (p < 0.001). Multivariate logistic regression showed that the higher knowledge level of AF was associated with secondary education or above, an income of more than 2000 yuan, and a history of AF of more than 1 year. Bleeding was associated with a lower JAKQ score, hypertension, and a history of bleeding. Non-bleeding patients on VKA had a better understanding of how often INR should be monitored and what to do if an OAC dose was missed. Conclusion: The Chinese version of JAKQ shows good reliability and validity, indicating that it is a valuable tool for AF and oral anticoagulation (OAC) knowledge assessment. It can be used in clinical practice to guide educational activities and improve the effectiveness and safety of treatment. It was shown that Chinese patients with AF have insufficient knowledge about AF and OAC. Lower JAKQ scores are associated with bleeding, so targeted education is necessary. Targeted educational efforts should focus on patients recently diagnosed with AF and those with lower formal education and income.