Hospital Acquired Sepsis, Disease Prevalence, and Recent Advances in Sepsis Mitigation.
Mary GarveyPublished in: Pathogens (Basel, Switzerland) (2024)
Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, commonly associated with nosocomial transmission. Gram-negative bacterial species are particularly problematic due to the release of the lipopolysaccharide toxins upon cell death. The lipopolysaccharide toxin of E. coli has a greater immunogenic potential than that of other Gram-negative bacteria. The resultant dysregulation of the immune system is associated with organ failure and mortality, with pregnant women, ICU patients, and neonates being particularly vulnerable. Additionally, sepsis recovery patients have an increased risk of re-hospitalisation, chronic illness, co-morbidities, organ damage/failure, and a reduced life expectancy. The emergence and increasing prevalence of antimicrobial resistance in bacterial and fungal species has impacted the treatment of sepsis patients, leading to increasing mortality rates. Multidrug resistant pathogens including vancomycin-resistant Enterococcus, beta lactam-resistant Klebsiella , and carbapenem-resistant Acinetobacter species are associated with an increased risk of mortality. To improve the prognosis of sepsis patients, predominantly high-risk neonates, advances must be made in the early diagnosis, triage, and control of sepsis. The identification of suitable biomarkers and biomarker combinations, coupled with machine learning and artificial intelligence, show promise in early detection protocols. Rapid diagnosis of sepsis in patients is essential to inform on clinical treatment, especially with resistant infectious agents. This timely review aims to discuss sepsis prevalence, aetiology, and recent advances towards disease mitigation and control.
Keyphrases
- end stage renal disease
- intensive care unit
- machine learning
- multidrug resistant
- newly diagnosed
- chronic kidney disease
- acute kidney injury
- ejection fraction
- pregnant women
- artificial intelligence
- cell death
- septic shock
- antimicrobial resistance
- peritoneal dialysis
- gram negative
- healthcare
- risk factors
- cardiovascular disease
- type diabetes
- patient reported outcomes
- big data
- inflammatory response
- deep learning
- risk assessment
- immune response
- signaling pathway
- acinetobacter baumannii
- smoking cessation
- low birth weight
- adverse drug
- combination therapy
- electronic health record