Tumor necrosis factor receptor 1 (TNFRI) for ventilator-associated pneumonia diagnosis by cytokine multiplex analysis

Ignacio Martin-Loeches, Lieuwe D Bos, Pedro Povoa, Paula Ramirez, Marcus J Schultz, Antoni Torres, Antonio Artigas, Ignacio Martin-Loeches, Lieuwe D Bos, Pedro Povoa, Paula Ramirez, Marcus J Schultz, Antoni Torres, Antonio Artigas

Abstract

Background: The diagnosis of ventilator-associated pneumonia (VAP) is challenging. An important aspect to improve outcome is early recognition of VAP and the initiation of the appropriate empirical treatment. We hypothesized that biological markers in plasma can rule out VAP at the moment of clinical suspicion and could rule in VAP before the diagnosis can be made clinically.

Methods: In this prospective study, patients with VAP (n = 24, microbiology confirmed) were compared to controls (n = 19) with a similar duration of mechanical ventilation. Blood samples from the day of VAP diagnosis and 1 and 3 days before were analyzed with a multiplex array for markers of inflammation, coagulation, and apoptosis. The best biomarker combination was selected and the diagnostic accuracy was given by the area under the receiver operating characteristic curve (ROC-AUC).

Results: TNF-receptor 1 (TNFRI) and granulocyte colony-stimulating factor (GCSF) were selected as optimal biomarkers at the day of VAP diagnosis, which resulted in a ROC-AUC of 0.96, with excellent sensitivity. Three days before the diagnosis TNFRI and plasminogen activator inhibitor-1 (PAI-1) levels in plasma predicted VAP with a ROC-AUC of 0.79. The slope of IL-10 and PAI-1 resulted in a ROC-AUC of 0.77. These biomarkers improved the classification of the clinical pulmonary infection score when combined.

Conclusions: Concentration of TNFRI and PAI-1 and the slope of PAI-1 and IL-10 may be used to predict the development of VAP as early as 3 days before the diagnosis made clinically. TNFRI and GCSF may be used to exclude VAP at the moment of clinical suspicion. Especially TNFRI seems to be a promising marker for the prediction and diagnosis of VAP.

Figures

Fig. 1
Fig. 1
Patient flow
Fig. 2
Fig. 2
Calibration plots at the three different time points. Calibration plots for the biomarker models. X-axis: predicted probability of VAP by the biomarker concentrations. Y-axis: the proportion of patients that actually had VAP. The grey dots show the predicted probabilities of the individual patients. The black triangles show the quantile summary and the black line the smoothed association between predicted and actual probability of VAP. The grey dotted line shows the ideal situation where predicted and actual probability are equal. a TNFRI and GCSF at the day of VAP diagnosis. b TNFRI and PAI-1 3 days before VAP. c IL-10 and PAI-1 slope before the diagnosis of VAP

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