The possible role of artificial intelligence in deciding postnatal steroid management in extremely premature ventilated infants

Article type: Research Article

Authors: Bottu, A. | Manzar, S.^{; *}

Affiliations: Department of Pediatrics, Louisiana State University Health Shreveport, Shreveport, LA, USA

Correspondence: [*] Address for correspondence: Shabih Manzar, MD, MPH, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Hwy, Shreveport, LA, 71103. Tel.: 318 675 7275; Fax: 318 675 6059; E-mail: shabih.manzar@lsuhs.edu/shabihman@hotmail.com.

Abstract: Clinical decision support (CDS) has shown a positive effect on physicians. There is variability among physicians about using postnatal steroids (PNS) in preterm (PT) infants. It is, therefore, essential to develop tools supporting the decision to use PNS in PT infants. We propose a model using online tools such as CDS in deciding to use PNS in PT infants. We combined the online bronchopulmonary dysplasia (BPD) estimator and extubation success calculator tools to be used as a simple bedside tool assisting decisions about using PNS in ventilated PT infants.

Keywords: Clinical decision support, postnatal steroids, preterm infants

DOI: 10.3233/NPM-230061

Journal: Journal of Neonatal-Perinatal Medicine, vol. 16, no. 4, pp. 689-692, 2023