Publications by authors named "Jarren Santos"
Background Artificial intelligence (AI) and machine learning (ML) are currently used in the clinical field to improve the outcome predictions on disease diagnosis and prognosis. However, to date, few AI/ML applications have been reported in rare diseases, such as hemophilia. In this study, taking advantage of the ATHNdataset, an extensive repository of hemostasis and thrombosis data, we aimed to demonstrate the application of AI/ML approaches to build predictive models to identify persons with hemophilia (PwH) who are at risk of poor outcome and to inform providers in clinical decision-making towards helping patients prevent long-term complications.
View Article and Find Full Text PDFIntroduction: Gene therapy is now a reality for individuals with haemophilia, yet little is known regarding the quality-of-life impact of factor correction. As few data exist, and recognizing the analogy to liver transplantation (OLTX), we identified OLTX+ and OLTX- men in the ATHNdataset to compare post-OLTX factor VIII and IX on quality of life (QoL) by Haem-A-QoL and PROMIS-29.
Methods: OLTX- were matched to OLTX+ by age, race, and haemophilia type and severity.
Article Synopsis
- Pediatric hematologists in the US have been using direct oral anticoagulants (DOACs) off-label for treating venous thromboembolism (VTE) in kids and teens before official FDA approval in 2021.
- The ATHN 15 study analyzed the use of DOACs from 2015 to 2021 across 15 specialized pediatric centers, focusing on their safety and effectiveness in patients aged 0 to 21 years.
- Results indicated that rivaroxaban was the most commonly prescribed DOAC, with a bleeding complication rate of 13.8% and a recurrence rate of 4%, showing that DOACs have an adequate safety and effectiveness profile for young patients.