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Electronic Medical Records Boot Camp
2025-06-30 - 2025-07-01    
10:30 am - 5:30 pm
The Electronic Medical Records Boot Camp is a two-day intensive boot camp of seminars and hands-on analytical sessions to provide an overview of electronic health [...]
AI in Healthcare Forum
2025-07-10 - 2025-07-11    
10:00 am - 5:00 pm
Jeff Thomas, Senior Vice President and Chief Technology Officer, shares how the migration not only saved the organization millions of dollars but also led to [...]
28th World Congress on  Nursing, Pharmacology and Healthcare
2025-07-21 - 2025-07-22    
10:00 am - 5:00 pm
To Collaborate Scientific Professionals around the World Conference Date:  July 21-22, 2025
5th World Congress on  Cardiovascular Medicine Pharmacology
2025-07-24 - 2025-07-25    
10:00 am - 5:00 pm
About Conference The 5th World Congress on Cardiovascular Medicine Pharmacology, scheduled for July 24-25, 2025 in Paris, France, invites experts, researchers, and clinicians to explore [...]
Events on 2025-06-30
Events on 2025-07-10
AI in Healthcare Forum
10 Jul 25
New York
Events on 2025-07-21
Events on 2025-07-24
Latest News

Leveraging AI to Improve ER Outcomes, Save Lives

Globally, about 4.5 million individuals succumb to traumatic injuries annually, often due to severe blood loss.

Administering tranexamic acid early can mitigate excessive bleeding by impeding blood clot breakdown. However, as this drug may induce adverse effects unnecessarily, precise patient selection based on objective criteria is crucial.

In a recent Critical Care publication, Osaka University researchers tackled this challenge by identifying trauma patient subgroups that could benefit most from tranexamic acid treatment. They discerned these subgroups by analyzing shared characteristics, termed phenotypes.

Lead author Jotaro Tachino elaborated, “We identified eight distinct trauma phenotypes and assessed the efficacy of tranexamic acid treatment across these groups.” They observed notably lower in-hospital mortality rates among certain patient subgroups receiving tranexamic acid, while others derived no advantage from the treatment.

Leveraging a machine learning model, the team categorized trauma patients into these subgroups. Analyzing data from over 50,000 patients in the Japan Trauma Data Bank, they discerned patterns correlating trauma, treatment, and survival.

The study revealed a correlation between trauma phenotypes and in-hospital mortality, suggesting that tranexamic acid treatment could influence this relationship.

The researchers emphasized the heterogeneous nature of trauma patients, whose injuries vary widely in type and severity, making individual treatment efficacy prediction challenging. They anticipate their findings will facilitate personalized care for trauma patients and enhance overall treatment quality.

Given the significant toll of traumatic injuries, strategies enhancing survival are paramount. This research represents a pivotal advancement in optimizing tranexamic acid utilization among trauma patients.