Annals of Intensive Care (Aug 2020)

Accuracy of the clinical pulmonary infection score to differentiate ventilator-associated tracheobronchitis from ventilator-associated pneumonia

  • Alexandre Gaudet,
  • Ignacio Martin-Loeches,
  • Pedro Povoa,
  • Alejandro Rodriguez,
  • Jorge Salluh,
  • Alain Duhamel,
  • Saad Nseir,
  • TAVeM study group

DOI
https://doi.org/10.1186/s13613-020-00721-4
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 10

Abstract

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Abstract Background Differentiating Ventilator-Associated Tracheobronchitis (VAT) from Ventilator-Associated Pneumonia (VAP) may be challenging for clinicians, yet their management currently differs. In this study, we evaluated the accuracy of the Clinical Pulmonary Infection Score (CPIS) to differentiate VAT and VAP. Methods We performed a retrospective analysis based on the data from 2 independent prospective cohorts. Patients of the TAVeM database with a diagnosis of VAT (n = 320) or VAP (n = 369) were included in the derivation cohort. Patients admitted to the Intensive Care Centre of Lille University Hospital between January 1, 2016 and December 31, 2017 who had a diagnosis of VAT (n = 70) or VAP (n = 139) were included in the validation cohort. The accuracy of the CPIS to differentiate VAT from VAP was assessed within the 2 cohorts by calculating sensitivity and specificity values, establishing the ROC curves and choosing the best threshold according to the Youden index. Results The areas under ROC curves of CPIS to differentiate VAT from VAP were calculated at 0.76 (95% CI [0.72–0.79]) in the derivation cohort and 0.67 (95% CI [0.6–0.75]) in the validation cohort. A CPIS value ≥ 7 was associated with the highest Youden index in both cohorts. With this cut-off, sensitivity and specificity were respectively found at 0.51 and 0.88 in the derivation cohort, and at 0.45 and 0.89 in the validation cohort. Conclusions A CPIS value ≥ 7 reproducibly allowed to differentiate VAT from VAP with high specificity and PPV and moderate sensitivity and NPV in our derivation and validation cohorts.

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