Sepsis: Challenges and Recent Biomedical Advances

 Sepsis, a life-threatening condition caused by the body's overwhelming response to an infection, poses a significant global health threat with millions of deaths annually. Despite substantial progress, managing sepsis remains challenging for healthcare professionals. However, biomedical research has shown promising advancements that could result in better outcomes and reduced mortality rates.

Early detection of sepsis remains a challenge as the symptoms might be nonspecific and may reflect other common infections. Identifying and eliminating the source of infection, such as abscesses or infected body parts, remains a vital aspect of successful sepsis treatment. Therefore, early detection of sepsis is a crucial step where rapid interventions will lead to improved patient outcomes. A keystone of sepsis treatment is to stabilize vital functions and often involves close monitoring of the patient in intensive care, where intravenous fluids, vasopressors to maintain blood pressure, or respiratory support are often required.

As sepsis involves a cascade of dysregulated immune responses that can result in widespread inflammation and organ dysfunction, a better understanding of the underlying pathophysiology is essential for developing targeted therapies. Another aspect of the difficulties that come along with sepsis, is the rise of antibiotic-resistant bacteria. Inappropriate or delayed antibiotic administration can impair the condition and even contribute to the global threat of antimicrobial resistance.

Researchers have made progress in identifying biomarkers that will support physicians in early sepsis detection. A study finds that sTREM-1 and PCT levels are significantly higher in patients who do not survive compared to those who do survive and therefore have shown promise in distinguishing sepsis from other infections and predicting sepsis prognosis. Moreover, biomarkers and cytokines, such as NT-pro-BNP, CRP, IL-6, and IL-10, were found to have lower prognostic utility.

Another way to improve the outcome of sepsis patients is to target immune dysregulation with immunomodulatory therapies. These therapies aim to restore the immune system's balance to prevent further excessive inflammation and organ damage. 

While intensive care units have improved the treatment of sepsis, many patients still develop delayed sepsis with suppressed immune responses and subsequently die from secondary infections. A recent study stated that by blocking or enhancing IFN-β levels (in combination with other cytokines), immunosuppression in delayed sepsis patients could be modulated. According to the researchers, IFN-β could reverse monocyte deactivation and enhance antimicrobial action. 

With the importance of early detection to prevent sepsis-related mortality, using artificial intelligence (AI) for an early diagnosis of sepsis might be a game changer. A study investigated the use of clinical data and emphasized the value of unstructured data, such as clinical notes, which contain additional clinical details that will not be captured in structured subjects. The authors, therefore, propose a topic-based AI algorithm that combines (unstructured) clinical notes with structured EMR data to improve sepsis prediction. In comparison with other predictive scoring systems and physician diagnoses, the suggested algorithm was able to provide superior results. 

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