Procalcitonin (PCT) levels for ruling-out bacterial coinfection in ICU patients with influenza: A CHAID decision-tree analysis

Abstract

PCT has a high negative predictive value (94%) and lower PCT levels seems to be a good tool for excluding coinfection, particularly for patients without shock.

Combination of procalcitonin and C‐reactive protein levels in the early diagnosis of bacterial co‐infections in children with H1N1 influenza

“…Guervilly et al reported that PCT values were significantly higher in patients with bacterial co‐infections. In addition, PCT has been suggested to exclude bacterial co‐infections in patients with H1N1 infection and to reliably and accurately reduce inappropriate antibiotic exposure . Our results showed that serum PCT levels were significantly higher in patients with bacterial co‐infection compared with those infected with H1N1 alone, confirming that PCT is associated with bacterial co‐infection.…”

“…Plasma PCT concentrations are low in healthy individuals and increase during bacterial, parasitic, or fungal infections, whereas they remain at normal levels during viral infections or non‐infectious inflammatory reactions . Studies attempting to assess PCT levels in patients with H1N1 infection have found that PCT helped to distinguish bacterial co‐infections from H1N1 infections alone . Nevertheless, to the best of our knowledge, previous studies published to date have focused on adults and patients with severe disease but have included few pediatric patients with H1N1 infections.…”

Predictors of treatment failure and clinical stability in patients with community acquired pneumonia

“…However, recently this was disputed when a study of 972 patients with H1N1 found that a cut off PCT of <0.29 ng/mL in a population with a 20% prevalence of community acquired respiratory coinfection has a high negative predictive value of 92%. PCT, therefor, appears to be effective at excluding co-infection in this group of patients (47). That said, it is important to interpret biomarker results cautiously and to correlate the results with clinical findings.…”

Focus on infection and sepsis in intensive care patients

“…These technologies are still promising but not fully validated yet. Another promising area of research is the right use of biomarkers [6] in either decision-based algorithms like CHAID (Chi-squared Automatic Interaction Detection) [7] or biomarker combinations to increase diagnostic accuracy [8].An important "My paper 10 years later" described the trends in infective endocarditis in the ICU [9]. The authors pointed to sustained high mortality rates in patients with infective endocarditis, rates that may exceed 60 % mortality in ICU.…”

“…These technologies are still promising but not fully validated yet. Another promising area of research is the right use of biomarkers [6] in either decision-based algorithms like CHAID (Chi-squared Automatic Interaction Detection) [7] or biomarker combinations to increase diagnostic accuracy [8].…”