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Incidence of Statin-Associated Adverse Events in Kidney Transplant Recipients
CONCLUSIONS: Statins appear to be generally well-tolerated in kidney transplant recipients. However, statin use might be associated with slightly higher risk of post-transplant diabetes mellitus, cataract, and rhabdomyolysis.PMID:36800538 | DOI:10.2215/CJN.0000000000000124
Source: Clinical Journal of the American Society of Nephrology : CJASN - February 17, 2023 Category: Urology & Nephrology Authors: Sunjae Bae JiYoon B Ahn Kmd Corey Joseph Ryan Whisler Mark A Schnitzler Krista L Lentine Bernard S Kadosh Dorry L Segev Mara A McAdams-DeMarco Source Type: research

Janssen Submits Application to U.S. FDA for New Indication to Expand Use of XARELTO ® (rivaroxaban) in Patients with Peripheral Artery Disease
RARITAN, NJ, October 26, 2020 – The Janssen Pharmaceutical Companies of Johnson & Johnson announced today it has submitted a supplemental New Drug Application (sNDA) to the U.S. Food and Drug Administration (FDA) for a new indication to expand the use of XARELTO® (rivaroxaban) in patients with peripheral artery disease (PAD). If approved, this new indication for the XARELTO® vascular dose (2.5 mg twice daily plus aspirin 75-100 mg once daily) would include reducing the risk of major thrombotic vascular events such as heart attack, stroke and amputation in patients after recent lower-extremity revascularization, a c...
Source: Johnson and Johnson - October 26, 2020 Category: Pharmaceuticals Tags: Innovation Source Type: news

Developing a New Score: How Machine Learning Improves Risk Prediction
Composite risk scores have been used for decades to identify disease risk and health status in the general population. However, current approaches often fail to identify people who would benefit from intervention or recommend unnecessary intervention. Machine learning promises to improve accuracy, ensuring targeted treatment for patients that need it and reducing unnecessary intervention. Framingham Risk Score, the gold standard for predicting the likelihood of heart disease, predicts hospitalizations with about 56% accuracy. It uses factors such as age, gender, smoking, cholesterol levels, and systolic blood pressure to...
Source: MDDI - November 17, 2017 Category: Medical Devices Authors: Heather R. Johnson Tags: R & D Source Type: news