ReviewNanotheranostics2024
Sepsis, Management & Advances in Metabolomics.
Review in Nanotheranostics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed, 48 citations in OpenAlex.
- Construction of an associative model for prolonged intensive care unit stay in sepsis patients combined with myocardial injury.Clinics (Sao Paulo, Brazil) · 2026Article
- HIPK2 mediated regulation of ferroptosis and inflammatory signaling in sepsis-induced myocardial injury.Journal of molecular histology · 2026Article
- Multi-omics insights into immunometabolic dysregulation in neonatal sepsis for precision medicine.Molecular biology reports · 2026Review
- Metabolic footprint of sepsis and septic shock: A narrative review.World journal of critical care medicine · 2026Review
- Plasma metabolomic signatures in patients with multidrug-resistant bacterial sepsis.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- Systemic immune-inflammation (SII) index as a novel prognostic biomarker in critically ill patients with sepsis: analysis of the MIMIC-IV cohort and predictive modeling based on machine learning.BMC infectious diseases · 2026Article
- Machine Learning Algorithms to Predict Venous Thromboembolism in Patients With Sepsis in the Intensive Care Unit: Multicenter Retrospective Study.JMIR medical informatics · 2026Article
- Artificial Intelligence Drives Advances in Multi-Omics Analysis and Precision Medicine for Sepsis.Biomedicines · 2026Review
- Cell death in sepsis: unveiling new perspectives on organ dysfunction.Frontiers in cell and developmental biology · 2026Review
- Metabolomics analysis identifies differential metabolites and potential diagnostic biomarkers among pediatric sepsis subtypes.PloS one · 2026Article
- Gut microbiota and serum metabolic profiles in patients with sepsis-induced cardiomyopathy and their association with the disease.Frontiers in cellular and infection microbiology · 2026Article
- Single-Cell Profiling Identifies JUNB/SPI1-Driven Inflammatory Programs and Novel Communication Axes in Myeloid Cells of SepsisEndocrine, metabolic & immune disorders drug targets · 2026Article
- Machine Learning-Guided Multi-Omics Integration Identifies UGCG as a Candidate Lipid Metabolic Biomarker and Potential Therapeutic Target in Sepsis.Journal of inflammation research · 2026Article
- Construction of a Risk Prediction Model for Stroke Occurrence in Septic Shock Patients: A Combined Analysis Using LASSO and Multivariate Logistic Regression.International journal of general medicine · 2026Article
- Recent advances in biomarkers for detection and diagnosis of sepsis and organ dysfunction: a comprehensive review.European journal of medical research · 2025Review
- Association between atherogenic index of plasma and sepsis in critically ill patients with ischemic stroke: a retrospective cohort study using propensity score and machine learning approaches.Lipids in health and disease · 2025Article
- A LASSO-based integrative model of serum biomarkers and gene polymorphisms for predicting poor sepsis prognosis.Biomarkers in medicine · 2025Article
- Multi-Omics and -Organ Insights into Energy Metabolic Adaptations in Early Sepsis Onset.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Metabolomic stratification of shock: pathophysiological insights for personalized critical care.Annals of intensive care · 2025Article
- Bug Wars: Artificial Intelligence Strikes Back in Sepsis Management.Diagnostics (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Though there have been developments in clinical care and management, early and accurate diagnosis and risk stratification are still bottlenecks in septic shock patients. Since septic shock is multifactorial with patient-specific underlying co-morbid conditions, early assessment of sepsis becomes challenging due to variable symptoms and clinical manifestations. Moreover, the treatment strategies are traditionally based on their progression and corresponding clinical symptoms, not personalized. The complex pathophysiology assures that a single biomarker cannot identify, stratify, and describe patients affected by septic shock. Traditional biomarkers like CRP, PCT, and cytokines are not sensitive and specific enough to be used entirely for a patient's diagnosis and prognosis. Thus, the need of the hour is a sensitive and specific biomarker after comprehensive analysis that may facilitate an early diagnosis, prognosis, and drug development. Integration of clinical data with metabolomics would provide means to understand the patient's condition, stratify patients better, and predict the clinical outcome.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.