ABSTRACT
D-bifunctional protein deficiency (D-BPD) is a rare, autosomal recessive peroxisomal disorder that affects the breakdown of long-chain fatty acids. Patients with D-BPD typically present during the neonatal period with hypotonia, seizures, and facial dysmorphism, followed by severe developmental delay and early mortality. While some patients have survived past two years of age, the detectable enzyme activity in these rare cases was likely a contributing factor. We report a D-BPD case and comment on challenges faced in diagnosis based on a narrative literature review. An overview of Romania's first patient diagnosed with D-BPD is provided, including clinical presentation, imaging, biochemical, molecular data, and clinical course. Establishing a diagnosis can be challenging, as the clinical picture is often incomplete or similar to many other conditions. Our patient was diagnosed with type I D-BPD based on whole-exome sequencing (WES) results revealing a pathogenic frameshift variant of the HSD17B4 gene, c788del, p(Pro263GInfs*2), previously identified in another D-BPD patient. WES also identified a variant of the SUOX gene with unclear significance. We advocate for using molecular diagnosis in critically ill newborns and infants to improve care, reduce healthcare costs, and allow for familial counseling.
Subject(s)
Mitochondrial Trifunctional Protein/deficiency , Peroxisomal Multifunctional Protein-2 , Humans , Peroxisomal Multifunctional Protein-2/deficiency , Peroxisomal Multifunctional Protein-2/genetics , Lipid Metabolism, Inborn Errors/diagnosis , Lipid Metabolism, Inborn Errors/genetics , Infant, Newborn , Infant , Male , Female , Exome Sequencing , Frameshift Mutation , 17-Hydroxysteroid Dehydrogenases/deficiency , 17-Hydroxysteroid Dehydrogenases/genetics , Resource-Limited Settings , Mitochondrial Myopathies , Cardiomyopathies , Nervous System Diseases , RhabdomyolysisABSTRACT
BACKGROUND: Transportation of sick newborns is a major predictor of outcome. Prompt identification of the sickest newborns allows adequate intervention and outcome optimization. An optimal scoring system has not yet been identified. AIM: To identify a rapid, accurate, and easy-to-perform score predictive for neonatal mortality in outborn neonates. MATERIAL AND METHODS: All neonates admitted by transfer in a level III regional neonatal unit between 1 January 2015 and 31 December 2021 were included. Infants with congenital critical abnormalities were excluded (N = 15). Gestational age (GA), birth weight (BW), Apgar score, place of birth, time between delivery and admission (AT), early onset sepsis, and sick neonatal score (SNS) were collected from medical records and tested for their association with mortality, including in subgroups (preterm vs. term infants); GA, BW, and AT were used to develop MSNS-AT score, to improve mortality prediction. The main outcome was all-cause mortality prediction. Univariable and multivariable analysis, including Cox regression, were performed, and odds ratio and hazard ratios were calculated were appropriate. RESULTS: 418 infants were included; 217/403 infants were born prematurely (53.8%), and 20 died (4.96%). Compared with the survivors, the non-survivors had lower GA, BW, and SNS scores (p < 0.05); only the SNS scores remained lower in the subgroup analysis. Time to admission was associated with an increased mortality rate in the whole group and preterm infants (p < 0.05). In multiple Cox regression models, a cut-off value of MSNS-AT score ≤ 10 was more precise in predicting mortality as compared with SNS (AUC 0.735 vs. 0.775) in the entire group and in the preterm infants group (AUC 0.885 vs. 0.810). CONCLUSIONS: The new MSNS-AT score significantly improved mortality prediction at admission in the whole study group and in preterm infants as compared with the SNS score, suggesting that, besides GA and BW, AT may be decisive for the outcome of outborn preterm infants.
