The use of lung ultrasound, both alone and in combination with clinical and microbiologic data, can improve the early diagnosis of ventilator-associated pneumonia (VAP), according to the results of a study published in Chest.

The early diagnosis of VAP is challenging, and leaves intensivists with two options. The first is waiting for positive results from patients’ specimens, which delays treatment and increases mortality risk. The other is to administer antibiotics to all patients suspected of having VAP, which may be inappropriate and can lead to the development of multiresistant bacteria. “A pressing need therefore exists for reliable diagnostic tools to diagnose VAP early so that antibiotics can be promptly initiated, avoiding two extreme approaches,” wrote Dr. Silvia Mongodi of the Fondazione IRCCS Policlinico San Matteo in Pavia, Italy, and her colleagues.

Based on the results of previous research, the investigators hypothesized that lung ultrasound (LUS) could be used to diagnose VAP early and help to avoid treatment delays or mistakes. To test this hypothesis, the diagnostic performance of LUS alone and in combination with clinical and microbiologic data was evaluated prospectively in 99 patients with suspected VAP in ICUs at Saint Joseph Hospital (Paris), Fondazione IRCCS Policlinico San Matteo, and Centre Hospitalier de l’Université de Montréal (Chest. 2016 Apr;149[4]:969-80. doi: 10.1016/j.chest.2015.12.012).

The study results showed that subpleural consolidations and dynamic linear/arborescent air bronchograms were the principal LUS signs of VAP, and that the presence of both in the same individual made the diagnosis highly specific (88%), with a high positive predictive value (86%) and a positive likelihood ratio of 2.9. Furthermore, the addition of data from either of two different endotracheal aspirate assessment techniques (EAgram [direct Gram stain examination] or EAquant [direct

Gram stain culture]) to the data from the principal LUS signs showed 97% specificity with each technique and positive likelihood ratios of 6.6 and 7.1, respectively, Dr. Mongodi and her associates reported.

Additionally, areas under the curve (AUCs) generated by receiver-operating characteristic curves for LUS in combination with microbiologic data were higher than, or indistinguishable from, the AUCs of purely clinical data in combination with microbiologic data. The researchers found, for example, that the AUC for LUS plus one type of microbiologic data (VPLUS[ventilator-associated pneumonia lung ultrasound score]-EAgram) was higher than the area under the curve for clinical information plus the same type of microbiologic data (CPIS[clinical pulmonary infection score]-EAgram). They also determined that the AUC for VPLUS-EAgram was equivalent to the area under the curve for the clinical information plus a different kind of microbiogic data (CPIS-EAquant).

Dr. Mongodi and her colleagues said that their results were encouraging but would need to be validated in larger clinical trials.

No funding was received for this study. The authors reported no conflicts of interest.