Profiling inflammatory markers in patients with pneumonia on intensive care.
David Benjamin AntcliffeArnaud M WolferKieran P O'DeaMasao TakataElaine HolmesAnthony C GordonPublished in: Scientific reports (2018)
Clinical investigations lack predictive value when diagnosing pneumonia, especially when patients are ventilated and develop ventilator associated pneumonia (VAP). New tools to aid diagnosis are important to improve outcomes. This pilot study examines the potential for a panel of inflammatory mediators to aid in the diagnosis. Forty-four ventilated patients, 17 with pneumonia and 27 with brain injuries, eight of whom developed VAP, were recruited. 51 inflammatory mediators, including cytokines and oxylipins, were measured in patients' serum using flow cytometry and mass spectrometry. The mediators could separate patients admitted to ICU with pneumonia compared to brain injury with an area under the receiver operating characteristic curve (AUROC) 0.75 (0.61-0.90). Changes in inflammatory mediators were similar in both groups over the course of ICU stay with 5,6-dihydroxyeicosatrienoic and 8,9-dihydroxyeicosatrienoic acids increasing over time and interleukin-6 decreasing. However, brain injured patients who developed VAP maintained inflammatory profiles similar to those at admission. A multivariate model containing 5,6-dihydroxyeicosatrienoic acid, 8,9-dihydroxyeicosatrienoic acid, intercellular adhesion molecule-1, interleukin-6, and interleukin-8, could differentiate patients with VAP from brain injured patients without infection (AUROC 0.94 (0.80-1.00)). The use of a selected group of markers showed promise to aid the diagnosis of VAP especially when combined with clinical data.
Keyphrases
- end stage renal disease
- brain injury
- intensive care unit
- ejection fraction
- newly diagnosed
- mass spectrometry
- oxidative stress
- prognostic factors
- chronic kidney disease
- peritoneal dialysis
- flow cytometry
- type diabetes
- subarachnoid hemorrhage
- escherichia coli
- adipose tissue
- cerebral ischemia
- big data
- respiratory failure
- risk assessment
- cystic fibrosis
- multiple sclerosis
- deep learning
- pseudomonas aeruginosa
- ms ms
- blood brain barrier
- biofilm formation
- simultaneous determination