Noh ES, et al. Yonsei Med J. 2019 Oct;60(10):984-991. https://doi.org/10.3349/ymj.2019.60.10.984

The difference in sodium ion levels determined with direct and indirect methods often exceeds the permissible limit clinically. Additionally, no previous study has assessed the difference in the sodium ion levels between direct and indirect methods in premature infants. Therefore, the present study aimed to compare sodium ion levels obtained using an arterial blood gas analyzer (ABGA; direct method) and an autoanalyzer (indirect method) to determine whether they are equivalent in premature infants. The present retrospective study included 450 preterm infants (weight, <2500 g) who were admitted to the neonatal intensive care unit (NICU) of our hospital between March 2012 and April 2014. We compared sodium ion levels in 1041 samples analyzed using an ABGA (Stat Profile® CCX Series, Nova Biomedical, Waltham, MA) and an autoanalyzer (ADVIA® 2400 Clinical Chemistry System, Siemens, Tarrytown, NY). The data were evaluated using Spearman’s correlation coefficient analysis, Bland-Altman plot, Deming regression analysis, and multivariate logistic regression analysis. The mean sodium ion levels were 134.6 ± 3.5 mmol/L using the ABGA and 138.8 ± 4.7 mmol/L using the autoanalyzer (P < 0.001). Among the 1041 samples, 957 (91.9 %) showed lower sodium ion levels with the ABGA than with the autoanalyzer and 74 (7.1 %) showed lower sodium ion levels with the autoanalyzer than with the ABGA. The incidence of hyponatremia identified using the ABGA was 51.9 % (541/1041), while the incidence of hyponatremia identified using the autoanalyzer was only 14.0 % (146/1041). The Deming regression analysis of the sodium ion levels between the ABGA and the autoanalyzer yielded the following formula: autoanalyzer Na (mmol/L) = 20.7 + (0.9 × ABGA Na [mmol/L]). In the multivariate logistic regression analysis, low plasma protein level (4 mmol/L between the two methods (odds ratio = 2.870, P < 0.001). The sodium ion levels determined using the ABGA and the autoanalyzer might not be equivalent in premature infants admitted to the NICU. Therefore, clinicians should be careful when diagnosing sodium ion imbalance in premature infants and providing treatment.

Sung SI, et al. J Korean Med Sci. 2019 Oct;34(43):e271. https://doi.org/10.3346/jkms.2019.34.e271

Echocardiography is the gold standard of diagnosis and evaluation of patent ductus arteriosus (PDA), a common condition among preterm infants that can cause hemodynamic abnormalities and increased mortality rates, but this technique requires a skilled specialist and is not always available. Meanwhile, chest X-ray (CXR) imaging is also known to exhibit signs of PDA and is a routine imaging modality in neonatal intensive care units. In this study, we aim to find and objectively define CXR image features that are associated with PDA by training and visually analyzing a deep learning model. We first collected 4617 echocardiograms from neonatal intensive care unit patients and 17,448 CXR images that were taken 4 days before to 3 days after the echocardiograms were obtained. We trained a deep learning model to predict the presence of severe PDA using the CXR images, and then visualized the model using GradCAM++ to identify the regions of the CXR images important for the model’s prediction. The visualization results showed that the model focused on the regions around the upper thorax, lower left heart, and lower right lung. Based on these results, we hypothesized and evaluated three radiographic features of PDA: cardiothoracic ratio, upper heart width to maximum heart width ratio, and upper heart width to thorax width ratio. We then trained an XGBoost model to predict the presence of severe PDA using these radiographic features combined with clinical features. The model achieved an AUC of 0.74, with a high specificity of 0.94. Our study suggests that the proposed radiographic features of CXR images can be used as an auxiliary tool to predict the presence of PDA in preterm infants. This can be useful for the early detection of PDA in neonatal intensive care units in cases where echocardiography is not available.

Kim ST, et al. Yonsei Med J. 2019 May;60(5):484-486. https://doi.org/10.3349/ymj.2019.60.5.484

X-linked recessive ichthyosis (XLI) is clinically characterized by dark brown, widespread dryness with polygonal scales. We describe the identification of STS and PUDP deletions using targeted panel sequencing combined with copy-number variation (CNV) analysis in XLI. A 9-month-old infant was admitted for genetic counseling. Since the second day after birth, the infant’s skin tended to be dry and polygonal scales had accumulated over the abdomen and upper extremities. The infant’s maternal uncle and brother (who had also exhibited similar skin symptoms from birth) presented with polygonal scales on their trunks. CNV analysis revealed a hemizygous deletion spanning 719.3 Kb on chromosome Xp22 (chrX:7,108,996–7,828,312), which included a segment of the STS gene and exhibited a Z ratio of −2 in the proband. Multiplex ligation-dependent probe amplification (MLPA) confirmed this interstitial Xp22.31 deletion. Our report underscores the importance of implementing CNV screening techniques, including sequencing data analysis and gene dosage assays such as MLPA, to detect substantial deletions that encompass the STS gene region of Xq22 in individuals suspected of having XLI.