Rx for Sepsis Management with Artificial Intelligence SUMMARY: Artificial Intelligence is improving early sepsis detection within clinical decision support algorithms. The effectiveness of these algorithms can vary based on a variety of factors including parameters evaluated, patient populations and time to predictions. Future efforts should focus on identification of high
Clinical Decision Support Systems for Early Sepsis Detection SUMMARY: Artificial Intelligence is improving early sepsis detection within clinical decision support algorithms. The effectiveness of these algorithms can vary based on a variety of factors including parameters evaluated, patient populations and time to predictions. Future efforts should focus on identification of
Triglyceride-Glucose Index in Sepsis SUMMARY: Platelets play a key role in immune response and inflammation. Sepsis, which is characterized by systemic inflammation, often presents with thrombocytopenia. Initial evaluations of novel therapeutic approaches to sepsis associated thrombocytopenia is encouraging but requires further evaluation. REVIEW: Platelets are the most abundant cellular
Triglyceride-Glucose Index in Sepsis SUMMARY: Sepsis induces extensive release of inflammatory factors and stresses producing various imbalances. Insulin resistance diminishes peripheral tissue insulin sensitivity. The Triglyceride-Glucose Index (TyGI) has been presented as a surrogate marker of insulin resistance. TyGI has been associated with various diseases and is emerging as a possible indicator
Sepsis Clinical Scoring Systems SUMMARY:Sepsis scoring systems to identify patients with potential sepsis have been in use for decades.Very few have been incorporated into clinical practice due to a number of limitations.The evolution of machine learning algorithms will be a major disruptor in this area. REVIEW: The original sepsis scoring tool was
Smelling Sepsis with Electronic Nose (eNose) Technology SUMMARY:Microorganisms can release volatile organic compounds (VOCs) released through exhaled air, producing unique odors.Exhaled breath analysis is a likely and promising alternative to disease detection.eNose measurements can identify sepsis among patients with a suspected infection. REVIEW:Human exhaled air contains trace amounts of VOCs.A Breath Biopsy
Machine Learning Algorithms for Sepsis Detection SUMMARY:Early identification and treatment of sepsis is central for identification and successful treatment of sepsis.Widespread systematic sepsis screening (manual or automated) is the recommended approach to detecting early sepsis.To date, employing systematic screening with traditional sepsis scoring tools has been suboptimal.Machine learning algorithms for sepsis screening
Sepsis Major Cause of True Deterioration SUMMARY: Sepsis is a major cause of morbidity and mortality globally. Early identification and treatment of any causes of acute deterioration outside the ICU will help improve clinical outcomes. Sepsis, either alone or as part of multiple causes, is the most common cause of
Sepsis Biomarkers in Diagnosis and Prognosis SUMMARY: Biomarkers used for the early diagnosis or prognosis of sepsis have evolved over the past few years. Most still require further data before being placed into a routine bedside use with high reliability. Concerns over biomarker variability and well-defined thresholds remain. REVIEW:Over 250 sepsis biomarkers
The Challenge of Multi-Drug-Resistant Sepsis SUMMARY: Early use of antimicrobials in true cases of sepsis is of utmost significance. Sepsis often results in prescribing antibiotics before a precise diagnosis is made. Widespread misuse of antimicrobials contribute to multidrug resistance and mortality. Antibiotic stewardship programs can help enhance treatment and minimize
