The clinical course and outcomes of sepsis vary widely, but early recognition and intervention with fluids, vasoactive agents, and antimicrobials significantly reduce morbidity and mortality. However, beyond supportive care, therapeutic options for sepsis are limited. Many biomarkers are associated with sepsis severity and outcomes, but their clinical utility in optimising targeted therapies is yet unproven.
Identifying future sepsis biomarkers will benefit from the rapid growth in cellular and molecular knowledge facilitated by advances in "omics" technologies. Recent concepts in sepsis research highlight the crucial role of the host response, the dynamic nature of the immune response, and the balance between resistance and tolerance. Genome studies have identified genes related to sepsis susceptibility, and their functionality (transcriptomics) and protein expression (proteomics) are now being investigated. Gene expression biomarkers have shown promise, particularly in distinguishing different infectious aetiologies. Integrating host transcriptomics and plasma metagenomics has potential diagnostic value for sepsis, and single-cell transcriptomics is emerging as a tool for discovering biomarkers by defining cellular states.
Sepsis clinical characterisation and outcome prediction require more than clinical parameters and scores, as trials testing single molecules have generally failed, indicating the complexity of sepsis mechanisms. Studying sepsis subtypes aims to characterise the host response and identify targeted therapies. The timing of the host response to infection, immune profile-related timing, pathogen virulence, and clinical subtypes must all be considered for effective therapeutic modulation.
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A detailed roadmap for clinical application of sepsis biomarkers is necessary, addressing challenges and categorising the serial timeframe for clinical management. Diagnostic biomarkers are needed to distinguish patients without bacterial sepsis to safely withhold antibiotics, and prognostic biomarkers are required for triaging patients at risk of deteriorating. Biomarkers track sepsis trajectory by assessing organ dysfunction severity. Predictive biomarkers could identify patients benefiting from targeted treatments for faster recovery. Biomarkers could help prevent complications by stimulating immunity or diagnosing and treating secondary infections early.
Rapid decision-making in the ED is crucial to assess infections and prevent progression to severe organ dysfunction and death. Differentiating viral from bacterial infections is essential to avoid unnecessary antimicrobials. Current tests, like procalcitonin (PCT) and C-reactive protein (CRP), have limitations in accurately identifying infections. New genomic/molecular methods show promise but need improved specificity. Fast result times are crucial for implementing safe therapeutic strategies.
Most sepsis literature focuses on patients in their 50s and 60s, but studies on very young and very old patients are limited yet important due to the incidence of sepsis in these age groups. In early life, sepsis is common, particularly in children under five, with prematurity and low birth weight as significant risk factors. Children with genetic, metabolic disorders, congenital malformations, or chronic conditions like oncologic, respiratory, cardiac, and neuromuscular disorders also face higher sepsis risks. Primary immunodeficiencies, though rare, can present as severe sepsis in childhood.
In the elderly (over 80), immunosenescence leads to decreased immune cell counts, diminished receptor gene variety in B and T cells, and increased susceptibility to infections. Older adults often have multiple comorbidities linked to distinct pathophenotypes, while healthy young adults have robust immune responses. Understanding age-related differences is essential for developing effective sepsis biomarkers across the lifespan.
Traditionally, biomarker research has focused on single time points, primarily on ICU admission. This approach risks missing important changes in biomarker levels. Repeated measurements at multiple intervals provide a comprehensive perspective on host responses. Serial biomarker monitoring can offer insights into patient responses to treatments and disease progression, potentially allowing for the modification of antibiotic therapy duration.
Despite significant progress in sepsis biomarker research, several barriers hinder their widespread clinical adoption, including scientific, clinical, logistical, and regulatory aspects. A major obstacle is the lack of evidence demonstrating the clinical utility of biomarkers for diagnosis, stratification, or prognosis. Concerted clinical validation through adaptive design randomised clinical trials is needed. Multicentre trials, like those conducted during the COVID-19 pandemic, should be emulated, focusing on specific patient cohorts and including diverse geographical and ethnic contexts. Simplistic biomarker evaluations across all septic patients often lead to failures, emphasising the need for targeted studies on relevant patient subsets.
There are no clear guidelines defining performance requirements for sepsis biomarker tests beyond routine design and statistical criteria from national regulatory agencies. Given sepsis's complexity, performance requirements for biomarker evaluation should vary based on the outcome and population assessed. Additionally, the lack of universally accepted management guidelines and consensus on biomarker use is a significant barrier. While numerous international initiatives have been undertaken, challenges remain, such as determining which biomarkers to incorporate into guidelines and the need for comprehensive research and clinical validation. International collaboration is also lacking, with diverse regions employing different sepsis management methodologies. Limited resources and funding further hinder the development and implementation of international guidelines, highlighting the need for concerted resource mobilisation and collaboration efforts to advance sepsis management.
Integrating AI and ML algorithms marks a transformative shift in sepsis biomarker development, offering unprecedented opportunities for innovation. These technologies combine biological, clinical, and digital data to predict patient outcomes with high accuracy and precision. AI and ML streamline the selection of biomarkers by handling vast datasets and enhancing feature prioritisation, though overfitting risks must be managed.
The progress in sepsis biomarker research has been slow and marked by numerous setbacks, yet the research community is urged to persist in advancing this critical area. Recent advancements highlight promising directions, emphasising the need for novel biomarkers with high sensitivity and specificity.
Future biomarker research in sepsis aims to develop multi-marker panels akin to liquid biopsies in cancer, providing a nuanced understanding of sepsis's complex manifestations. Integrating omics-based technologies and AI-driven analytics holds potential to unravel intricate molecular pathways, enhancing diagnostic accuracy and prognostic precision across various clinical settings.
Source: Critical Care
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