AI Blood Test for Infection & Sepsis Diagnosis & Prognosis

Based on the provided text and Figure 3, hear’s a ⁢suggestion about how TriVerity results coudl have helped avoid antibiotic overprescription in emergency departments:

TriVerity, by providing a more nuanced assessment of bacterial⁢ infection risk (through its “Bacterial score bands”),⁤ could have helped ED providers make more informed antibiotic prescribing decisions.

Here’s how, based on the information:

* Post-test Probability Adjustment: ⁣Figure 3B demonstrates how TriVerity ⁤scores‍ can shift a physician’s probability assessment of bacterial infection, based on their initial (pre-test) assessment. This is crucial. A patient a doctor initially thinks has a low chance of infection could be re-evaluated with a TriVerity score,‍ potentially confirming that low suspicion and avoiding unneeded antibiotics. Conversely, a patient initially suspected ⁤of infection could be shown to have a lower risk with TriVerity, ⁣again preventing overuse.
* Decision Thresholds: The figure highlights a physician decision threshold of 69% probability for antibiotic prescription (reference 23). TriVerity scores, ‍by providing a post-test probability, could have helped more patients fall ⁢ below this threshold, leading to fewer prescriptions.
* Risk Stratification: The different “Bacterial score bands” (Very High to very Low) offer a clear stratification of risk. This allows for a more targeted approach to antibiotic use, reserving them for patients with a genuinely high likelihood of bacterial infection.
* contextualization: The text emphasizes⁤ that physicians will use the score in patients with varying pre-test⁣ probabilities. TriVerity doesn’t operate in a vacuum; it integrates with⁤ clinical⁣ judgment.

In essence, TriVerity⁣ appears to offer‍ a tool to refine risk assessment, potentially moving prescribing practices closer to evidence-based guidelines and reducing the inappropriate use of antibiotics.