When patients arrive at the Emergency Room (ER) with a critical illness, the main challenge for doctors is timely diagnosis and determining the precise course of treatment. A new achievement from Stanford Medicine will radically change this process. Researchers have managed to decode immune cell “signatures”—using genetic patterns present in blood immune cells that are crucial for determining the type, severity of infection, and the patient’s immune status.
Under the leadership of Professor of Biomedical Informatics, Purvesh Khatri, Stanford researchers created the Human Immune DisRegulation Evaluation Framework (HI-DEF), which converts the genetic activity of immune cells into actionable indicators for clinical assessment. This method, published in the journal Nature Medicine, uses HI-DEF to group patients based on their immune status: from a balanced immune response to various degrees of dysregulation. It was found that this data directly correlates with the outcomes of severe pathologies such as sepsis, burns, trauma, and acute respiratory distress syndrome (ARDS).
Additionally, the FDA-approved TriVerity test assesses 29 immune genes to predict the bacterial or viral nature of an infection, or its general presence. The test also assesses the probability of severe illness, which often requires the patient to be placed in the Intensive Care Unit (ICU). Since the result is obtained in just 30 minutes, TriVerity offers a powerful and rapid tool for emergency clinicians to make informed decisions.
This integrated method aims to solve a crucial problem: timely, accurate diagnosis of complex infections and the prescription of therapy tailored to the patient, especially for immunocompromised individuals.
The Effectiveness of TriVerity in Different Patient Groups
A study conducted on 1,222 ER patients (including up to 20% who were immunocompromised) proved that the diagnostic accuracy of TriVerity is not dependent on immune status. In terms of classifying infections into bacterial/viral types and predicting severity, the test outperformed traditional biomarkers (procalcitonin and C-reactive protein). This is particularly important because TriVerity maintained accuracy even in ethnic minority populations where traditional markers often yield inaccurate results.
The TriVerity severity score was characterized by high sensitivity and specificity, as it accurately predicted the need for resuscitative interventions (mechanical ventilation and vasopressors). Notably, TriVerity significantly improved prediction accuracy when used alongside clinical scores (e.g., qSOFA), thereby allowing doctors to more reliably identify high-risk patients.
Therapeutic Benefit and Antimicrobial Resistance Control
The study found that TriVerity effectively reduces the non-targeted use of antibiotics (both overtreatment and undertreatment) by better identifying patients who truly need these medications. This method will minimize patients who are incorrectly treated or left without treatment, which will help fight against antimicrobial resistance and significantly improve patient outcomes.
Thanks to the immune dysregulation scores, it became possible to target immunomodulatory therapies (such as steroids and anakinra) to maximize the benefit for patients who needed them most.
Despite the great potential, TriVerity and HI-DEF require additional prospective studies for integration into clinical practice. For their effective use, the final confirmation of gene panels, the optimization of clinical processes, and ensuring accessibility in all types of medical institutions are necessary.
Source:
A consensus immune dysregulation framework for sepsis and critical illnesses – nature
