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Póvoa P, Martin-Loeches I, Ramirez P, et al. Biomarker kinetics in the prediction of VAP diagnosis: results from the BioVAP study. Ann Intensive Care. 2016;6(1):32doi: 10.1186/s13613-016-0134-8.
Póvoa, P., Martin-Loeches, I., Ramirez, P., Bos, L. D., Esperatti, M., Silvestre, J., Gili, G., Goma, G., Berlanga, E., Espasa, M., Gonçalves, E., Torres, A., & Artigas, A. (2016). Biomarker kinetics in the prediction of VAP diagnosis: results from the BioVAP study. Annals of intensive care, 6(1), 32. https://doi.org/10.1186/s13613-016-0134-8
Póvoa, Pedro, et al. "Biomarker kinetics in the prediction of VAP diagnosis: results from the BioVAP study." Annals of intensive care vol. 6,1 (2016): 32. doi: https://doi.org/10.1186/s13613-016-0134-8
Póvoa P, Martin-Loeches I, Ramirez P, Bos LD, Esperatti M, Silvestre J, Gili G, Goma G, Berlanga E, Espasa M, Gonçalves E, Torres A, Artigas A. Biomarker kinetics in the prediction of VAP diagnosis: results from the BioVAP study. Ann Intensive Care. 2016 Dec;6(1):32. doi: 10.1186/s13613-016-0134-8. Epub 2016 Apr 14. PMID: 27076187; PMCID: PMC4830786.
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Ann Intensive Care. 2016 Dec;6(1):32. doi: 10.1186/s13613-016-0134-8. Epub 2016 Apr 14.

Biomarker kinetics in the prediction of VAP diagnosis: results from the BioVAP study.

Annals of intensive care

Pedro Póvoa, Ignacio Martin-Loeches, Paula Ramirez, Lieuwe D Bos, Mariano Esperatti, Joana Silvestre, Gisela Gili, Gema Goma, Eugenio Berlanga, Mateu Espasa, Elsa Gonçalves, Antoni Torres, Antonio Artigas

Affiliations

  1. Polyvalent Intensive Care Unit, Centro Hospitalar de Lisboa Ocidental, São Francisco Xavier Hospital, Estrada do Forte do Alto do Duque, 1449-005, Lisbon, Portugal. [email protected].
  2. NOVA Medical School, CEDOC, New University of Lisbon, Lisbon, Portugal. [email protected].
  3. Critical Care Center, Sabadell Hospital, Corporación Sanitaria Universitaria Parc Taulí, Universitat Autonoma de Barcelona, Sabadell, Spain.
  4. CIBER de Enfermedades Respiratorias (CIBERES), Madrid, Spain.
  5. Intensive Care Unit, University Hospital La Fe, Valencia, Spain.
  6. Department of Intensive Care, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
  7. Respiratory Disease Department, Hospital Clínic i Provincial de Barcelona, IDIBAPS, Barcelona, Spain.
  8. Polyvalent Intensive Care Unit, Centro Hospitalar de Lisboa Ocidental, São Francisco Xavier Hospital, Estrada do Forte do Alto do Duque, 1449-005, Lisbon, Portugal.
  9. NOVA Medical School, CEDOC, New University of Lisbon, Lisbon, Portugal.
  10. Laboratory Department, UDIAT, Corporación Sanitaria Universitaria Parc Taulí, Sabadell, Spain.
  11. Microbiology Department, Centro Hospitalar de Lisboa Ocidental, Egas Moniz Hospital, Lisbon, Portugal.

PMID: 27076187 PMCID: PMC4830786 DOI: 10.1186/s13613-016-0134-8

Abstract

BACKGROUND: Prediction of diagnosis of ventilator-associated pneumonia (VAP) remains difficult. Our aim was to assess the value of biomarker kinetics in VAP prediction.

METHODS: We performed a prospective, multicenter, observational study to evaluate predictive accuracy of biomarker kinetics, namely C-reactive protein (CRP), procalcitonin (PCT), mid-region fragment of pro-adrenomedullin (MR-proADM), for VAP management in 211 patients receiving mechanical ventilation for >72 h. For the present analysis, we assessed all (N = 138) mechanically ventilated patients without an infection at admission. The kinetics of each variable, from day 1 to day 6 of mechanical ventilation, was assessed with each variable's slopes (rate of biomarker change per day), highest level and maximum amplitude of variation (Δ (max)).

RESULTS: A total of 35 patients (25.4 %) developed a VAP and were compared with 70 non-infected controls (50.7 %). We excluded 33 patients (23.9 %) who developed a non-VAP nosocomial infection. Among the studied biomarkers, CRP and CRP ratio showed the best performance in VAP prediction. The slope of CRP change over time (adjusted odds ratio [aOR] 1.624, confidence interval [CI]95% [1.206, 2.189], p = 0.001), the highest CRP ratio concentration (aOR 1.202, CI95% [1.061, 1.363], p = 0.004) and Δ (max) CRP (aOR 1.139, CI95% [1.039, 1.248], p = 0.006), during the first 6 days of mechanical ventilation, were all significantly associated with VAP development. Both PCT and MR-proADM showed a poor predictive performance as well as temperature and white cell count.

CONCLUSIONS: Our results suggest that in patients under mechanical ventilation, daily CRP monitoring was useful in VAP prediction. Trial registration NCT02078999.

Keywords: Biomarkers; C-reactive protein; Clinical Pulmonary Infection Score; Diagnosis; Mid-region fragment of pro-adrenomedullin; Prediction; Procalcitonin; Ventilator-associated pneumonia

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