RESUMEN
Bronchopulmonary dysplasia (BPD) is a complex, multifactorial lung disease affecting preterm neonates that can result in long-term pulmonary and non-pulmonary complications. Current therapies mainly focus on symptom management after the development of BPD, indicating a need for innovative approaches to predict and identify neonates who would benefit most from targeted or earlier interventions. Clinical informatics, a subfield of biomedical informatics, is transforming healthcare by integrating computational methods with patient data to improve patient outcomes. The application of clinical informatics to develop and enhance clinical therapies for BPD presents opportunities by leveraging electronic health record data, applying machine learning algorithms, and implementing clinical decision support systems. This review highlights the current barriers and the future potential of clinical informatics in identifying clinically relevant BPD phenotypes and developing clinical decision support tools to improve the management of extremely preterm neonates developing or with established BPD. However, the full potential of clinical informatics in advancing our understanding of BPD with the goal of improving patient outcomes cannot be achieved unless we address current challenges such as data collection, storage, privacy, and inherent data bias.
RESUMEN
Inadequate intake of calcium and phosphorus during the perinatal period can result in metabolic bone disease (MBD), characterized by decreased bone mass, altered bone mineralization, and increased risk for fractures. Preterm neonates have higher risk of developing MBD. Treating MBD involves ensuring adequate calcium and phosphorus intake, early fortification, and vitamin D supplementation. Health care providers should closely monitor nutrient intake, postnatal growth, and screening of preterm neonates at risk for MBD. This review summarizes the critical roles of calcium and phosphorus in regulating bone physiology, how they regulate bone formation and resorption, and their influence on overall bone health.
Asunto(s)
Enfermedades Óseas Metabólicas , Calcio , Recién Nacido , Humanos , Calcio/uso terapéutico , Recien Nacido Prematuro/fisiología , Fósforo , Enfermedades Óseas Metabólicas/etiología , Calcificación FisiológicaRESUMEN
Background and Objective: Bronchopulmonary dysplasia (BPD) is the most common morbidity associated with prematurity and remains a significant clinical challenge. Bioinformatic approaches, such as genomics, transcriptomics, and proteomics, have emerged as novel methods for studying the underlying mechanisms driving BPD pathogenesis. These methods can be used alongside clinical data to develop a better understanding of BPD and potentially identify the most at risk neonates within the first few weeks of neonatal life. The objective of this review is to provide an overview of the current state-of-the-art in bioinformatics for BPD research. Methods: We conducted a literature review of bioinformatics approaches for BPD using PubMed. The following keywords were used: "biomedical informatics", "bioinformatics", "bronchopulmonary dysplasia", and "omics". Key Content and Findings: This review highlighted the importance of omic-approaches to better understand BPD and potential avenues for future research. We described the use of machine learning (ML) and the need for systems biology methods for integrating large-scale data from multiple tissues. We summarized a handful of studies that utilized bioinformatics for BPD in order to better provide a view of where things currently stand, identify areas of ongoing research, and concluded with challenges that remain in the field. Conclusions: Bioinformatics has the potential to enable a more comprehensive understanding of BPD pathogenesis, facilitating a personalized and precise approach to neonatal care. As we continue to push the boundaries of biomedical research, biomedical informatics (BMI) will undoubtedly play a key role in unraveling new frontiers in disease understanding, prevention, and treatment.