Managing older people with atrial fibrillation and preventing stroke: a review of anticoagulation approaches

Apixaban Inhibits Progression of Experimental Diabetic Nephropathy by Blocking Advanced Glycation End Product-Receptor Axis

Diabetes is associated with an increased risk of thromboembolism. However, the effects of apixaban, a factor Xa inhibitor on diabetic nephropathy, remain unknown. Six-week-old Wistar rats received a single 60 mg/kg intraperitoneal injection of streptozotocin to produce a model of type 1 diabetes. Type 1 diabetic and non-diabetic control rats were treated with or without apixaban orally for 8 weeks, and blood and kidneys were obtained for biochemical, real-time reverse transcription-polymerase chain reaction (RT-PCR) and morphological analyses. Although apixaban treatment did not affect glycemic or lipid parameters, it significantly (p < 0.01) inhibited the increases in advanced glycation end products (AGEs), the receptor for AGEs (RAGE) mRNA and protein levels, 8-hydroxy-2'-deoxyguanosine (8-OHdG), and NADPH oxidase-driven superoxide generation in diabetic rats at 14 weeks old. Compared with non-diabetic rats, gene and protein expression levels of monocyte chemoattractant protein-1 (MCP-1), vascular cell adhesion molecule-1 (VCAM-1), transforming growth factor-β (TGF-β), connective tissue growth factor (CTGF), and fibronectin were increased in 14-week-old diabetic rats, which were associated with enhanced renal expression of kidney injury molecule-1 (KIM-1) and Mac-3, increased extracellular matrix accumulation in the kidneys, and elevated urinary excretion levels of protein and KIM-1, all of which were significantly inhibited by the treatment with apixaban. Urine KIM-1 levels were significantly (p < 0.01) and positively correlated with AGEs (r = 0.690) and 8-OHdG (r = 0.793) in the kidneys and serum 8-OHdG levels (r = 0.823). Our present findings suggest that apixaban could ameliorate renal injury in streptozotocin-induced type 1 diabetic rats partly by blocking the AGE-RAGE-oxidative stress axis in diabetic kidneys.

Safety and Effectiveness of Oral Anticoagulants in Atrial Fibrillation: Real-World Insights Using Natural Language Processing and Machine Learning

Background/Objectives: We assessed the effectiveness and safety of vitamin K antagonists (VKAs) versus direct oral anticoagulants (DOACs) in patients with atrial fibrillation (AF) using artificial intelligence techniques. Methods: This is a retrospective study in 15 Spanish hospitals (2014-2020), including adult AF patients with no history of anticoagulation, thrombosis events, rheumatic mitral valvular heart disease, mitral valve stenosis, or pregnancy. We employed EHRead® technology based on natural language processing (NLP) and machine learning (ML), along with SNOMED-CT terminology, to extract clinical data from electronic health records (EHRs). Using propensity score matching (PSM), the effectiveness, safety, and hospital mortality of VKAs versus DOACs were analyzed through Kaplan-Meier curves and Cox regression. Results: Out of 138,773,332 EHRs from 4.6 million individuals evaluated, 44,292 patients were included, 79.6% on VKAs and 20.4% on DOACs. Most patients were elderly [VKA 78 (70, 84) and DOAC 75 (66, 83) years], with numerous comorbidities (75.5% and 70.2% hypertension, 47.2% and 39.9% diabetes, and 40.3% and 34.8% heart failure, respectively). Additionally, 60.4% of VKA and 48.7% of DOAC users had a CHA2DS2-VASc Score ≥4. After PSM, 8929 patients per subgroup were selected. DOAC users showed a lower risk of thrombotic events [HR 0.81 (95% CI 0.70-0.94)], minor bleeding [HR 0.89 (95% CI 0.83-0.96)], and mortality [HR 0.80 (95% CI 0.69-0.92)]. Conclusions: Applying NLP and ML, we generated valuable real-world evidence on anticoagulated AF patients in Spain. Even in complex populations, DOACs have demonstrated a better safety and effectiveness profile than VKAs.

Research Progress on Cognitive Frailty in Older Adults with Chronic Kidney Disease

BACKGROUND

As the medical challenges posed by the ageing population become increasingly severe, the proportion of older people among patients with chronic kidney disease (CKD) is increasing every year.

SUMMARY

The prevalence of frailty in patients with CKD is significantly higher than that in the general population, and older patients are also a high-risk group for frailty and cognitive impairment. Cognitive frailty, as an important subtype of frailty, is a syndrome characterised by cognitive dysfunction caused by physiological factors, excluding Alzheimer's disease and other types of dementia. It is characterised by the coexistence of physical frailty and cognitive impairment. Previous studies have mainly focused on cognitive impairment, and there is limited research on cognitive frailty, particularly in older patients with CKD.

KEY MESSAGES

This article provides a comprehensive review of the concept, epidemiology, screening methods, prevention, and treatment measures and possible pathogenesis of cognitive frailty in patients with CKD.

A Novel Nomogram for Predicting Warfarin-Related Bleeding: A Retrospective Cohort Study

Warfarin is a widely used anticoagulant, and bleeding complications are the main reason why patients discontinue the drug. Currently, there is no nomogram model for warfarin-associated bleeding risk. The aim of this study was to develop a risk-prediction nomogram model for warfarin-related major and clinically relevant non-major (CRNM) bleeding. A total of 280 heart disease outpatients taking warfarin were enrolled, 42 of whom experienced major or CRNM bleeding at the one-year follow-up. The Least Absolute Shrinkage and Selection Operator regression model was employed to identify potential predictors. Backward stepwise selection with the Akaike information criterion was used to establish the optimal predictive nomogram model. The receiver operating characteristic (ROC) curve, calibration plot, Hosmer-Lemeshow goodness-of-fit test, and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. The nomogram consisted of four predictors: female (OR = 1.85; 95% CI: 0.91-3.94), TIA (OR = 6.47; 95% CI: 1.85-22.7), TTR (OR = 0.99; 95% CI: 0.97-1.00), and anemia (OR = 2.30; 95% CI: 1.06-4.84). The model had acceptable discrimination (area under the ROC curve = 0.68, 95% CI: 0.59-0.78), and was significantly better than the existing nine warfarin-related bleeding prediction scoring systems. The calibration plot and Hosmer-Lemeshow test (χ² = 7.557; P = .478) indicated well-calibrated data in the model. The DCA demonstrated good clinical utility. In this study, we developed a nomogram to predict the risk of warfarin-related major or CRNM bleeding. The model has good performance, allows rapid risk stratification of warfarin users, and provides a basis for personalized treatment.