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Neonatal and Pediatric Medicine | Volume: 04

October 25-26, 2018 | Prague, Czech Republic

World Neonatology and Child Care Meeting

Neonat Pediatr Med 2018, Volume: 04

10.4172/2572-4983-C2-006

Neonatal lung ultrasound guidelines

Dalibor Kurepa

Huntington Hospital, USA

I

n the past several years lung ultrasound (LUS) has become one of the most exciting applications in the field of the neonatal point-of

care ultrasound (POC-US). Several recent articles have found ultrasound imaging to be an equal, if not a more effective diagnostic

modality than X-ray. LUS is quicker, less expensive and it does not expose patients to the increased risks inherent in exposure to

ionizing radiation. Aside from diagnosing specific lung diseases, ultrasound has shown a great promise in the functional monitoring

of lung processes and predicting the development of complications. Neonatal LUS examination follows the same principles as

adult ultrasound. As already mentioned, lung image map is created by interrogation of the pleural surfaces at three sites over each

hemithorax. One of the challenges to widespread use of LUS is a paradigm shift in which physicians have to accept a fundamentally

different way of thinking.Therefore, there is a need to develop creatively engaging strategies that would allow us this practice transition.

Clinical guidelines modeled through decision-making algorithms have proven to simplify diagnostic and management processes.

LUS algorithms or protocols have been described in the adult population. They cover vast amount of data and knowledge those are

well validated and reproducible. On the other hand, no such algorithm exists for the neonatal population known to have relatively

specific lung pathology. Acknowledging this fact, we reviewed neonatal LUS literature and developed neonatal LUS algorithms those

serve as guidelines for LUS application in the neonatal population. The goal is to better help neonatologists to embrace the daily use of

the ultrasound as a diagnostic modality. Further, the algorithms should allow neonatologists to transfer their insights and experiences

into new research ideas and better patient outcomes..