ReviewFrontiers in pharmacology2026
Hyper-inflammation and immunosuppression: redefining sepsis therapy using modern approaches.
Review in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Review
- Crosstalk between innate immune signaling pathways and integrated TLR, NLRP3 inflammasome, cGAS-STING, and NF-κB networks in sepsis.Frontiers in cell and developmental biology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Sepsis is a life-threatening condition characterized by simultaneous hyperinflammation and immunosuppression, which leads to organ dysfunction and mortality. It is a global health concern, which is estimated to be approximately 166 million cases and 21.4 million global deaths in 2021. Aim: This review aimed to analyze sepsis epidemiology, pathophysiology, current therapeutic approaches and challenges, and assess the transformational role of modern therapeutic approaches, including precision medicine, and Artificial Intelligence (AI)/Machine Learning (ML) in sepsis. Methodology: A literature search was carried out across multiple databases, including PubMed, Web of Science, and Scopus. The search was focused on hyperinflammation, immunosuppression in sepsis, current therapy, and future advances. Result: The review integrated the search data from original articles, review papers, and clinical trials. After careful analysis, we observed that the efficacy of current therapy is limited due to the heterogeneity of sepsis patients, the lack of patient selection based on immune status, timing, and validated biomarkers. Precision methods based on classifying patient genotypes and multi-omics-based biomarkers suggest a potential approach to risk stratification and therapeutic guidance. Concurrently, AI/ML models exhibit improved predictive accuracy and early clinical diagnosis, facilitating early identification and risk stratification. Conclusion: The integration of AI/ML and precision medicine into sepsis care has the potential to reduce mortality in clinically significant endotypes and allow focused immunomodulatory treatments fulfilling Sustainable Development Goal 3.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.