Proportion of confluent B-Lines predicts respiratory support in term infants shortly after birth.

OBJECTIVE: To develop and evaluate the predictive value of a simplified lung ultrasound (LUS) method for forecasting respiratory support in term infants. METHODS: This observational, prospective, diagnostic accuracy study was conducted in a tertiary academic hospital between June and December 2023. A total of 361 neonates underwent LUS examination within 1 h of birth. The proportion of each LUS sign was utilized to predict their respiratory outcomes and compared with the LUS score model. After identifying the best predictive LUS sign, simplified models were created based on different scan regions. The optimal simplified model was selected by comparing its accuracy with both the full model and the LUS score model. RESULTS: After three days of follow-up, 91 infants required respiratory support, while 270 remained healthy. The proportion of confluent B-lines demonstrated high predictive accuracy for respiratory support, with an area under the curve (AUC) of 89.1% (95% confidence interval [CI]: 84.5-93.7%). The optimal simplified model involved scanning the R/L 1-4 region, yielding an AUC of 87.5% (95% CI: 82.6-92.3%). Both the full model and the optimal simplified model exhibited higher predictive accuracy compared to the LUS score model. The optimal cut-off value for the simplified model was determined to be 15.9%, with a sensitivity of 76.9% and specificity of 91.9%. CONCLUSIONS: The proportion of confluent B-lines in LUS can effectively predict the need for respiratory support in term infants shortly after birth and offers greater reliability than the LUS score model.

Neonatal Adverse Events' Trigger Tool Setup With Random Forest.

OBJECTIVE: This study aimed to develop a trigger tool for detection of neonatal adverse events (AEs) and to validate its effectiveness. STUDY DESIGN: Random forest (RF) algorithm was used to build the predictive model by analyzing data from the medical records of 782 neonates in our previous study. Thirteen variables for each patient were used to predict neonatal AEs. Next, the critical variables were selected based on recursive elimination of variables to form the list of triggers. Then, a trigger tool with those triggers was established and tested by reviewing medical records. The positive predictive value of individual triggers and of the entire tool was evaluated. RESULTS: Data from 782 neonates, including 297 patients with and 485 patients without AEs, were collected to build the original RF model. Then, the 6 most important variables, including diarrhea, antibiotic use, fever, death, skin damage, and suspected necrotizing enterocolitis, were selected to establish a neonate-focused trigger tool. The forest with the 6 variables predicted AEs with a sensitivity of 70.7%, a specificity of 92.0%, and an error rate of 16.1%. In a validation study of the trigger tool, 655 neonates with birth weights ≥1500 g were enrolled, and review of their medical records revealed 1709 triggers and 1172 unique AEs. The 3 most common AEs identified were skin damage, iatrogenic diarrhea, and environmental factor-related fever. The total positive predictive value of the trigger tool was 0.686. CONCLUSIONS: The neonate-focused trigger tool developed using the RF algorithm efficiently and reliably identifies AEs among hospitalized neonates with birth weights ≥1500 g.

The accuracy of transcutaneous bilirubin to identify hyperbilirubinemia in jaundiced neonates.

OBJECTIVE: To compare transcutaneous bilirubin (TcB) to total serum bilirubin (TSB) in jaundiced neonates by using a JM-103 bilirubinometer. METHODS: We conducted a retrospective study in jaundiced infants ≥35 weeks' gestation. Infants' and maternal information, TcB measurements, and TSB levels were collected. The correlation and consistency between TcB and TSB were analyzed by Pearson's correlation analysis and the Bland-Altman plot. Multivariate regression analysis was used to identify characteristics associated with the difference between TcB and TSB, underestimation by TcB and overestimation by TcB. RESULTS: A total of 787 paired samples were collected. There was a strong correlation between TcB and TSB with a Pearson correlation coefficient of 0.708 (p < .001). In preterm infants, outpatients and infants with high TSB levels, the TcB measurements were less precise. The TcB-TSB difference was significantly associated with gender, maternal hypertension disease, ABO hemolytic disease, and outpatient setting (p < .05). Only the outpatient setting had statistical significance in the underestimation of TSB ≥2 mg/dL. CONCLUSIONS: Generally, TcB by a JM-103 bilirubinometer had a good correlation and consistency with the TSB values. However, small for gestational age, postnatal age of hour, ABO hemolytic disease, and outpatient setting may lead to inconsistencies between the TcB and TSB.

Maternal-Neonatal Serum Albumin Level and Neonatal Respiratory Distress Syndrome in Late-Preterm Infants.

Background: To determine the correlation between maternal-neonatal serum albumin level and respiratory distress syndrome (RDS) in late-preterm infants. Methods: This case-control study included 112 late-preterm newborns admitted to the neonatal intensive care unit of our hospital between January 2018 and July 2019. Those infants were divided into the RDS group (n = 56) and the non-RDS group (n = 56). Levels of maternal-neonatal serum albumin, pregnancy complications, and baseline information of the infants were compared between the two groups. Results: 1. There was no correlation between maternal and neonatal serum albumin measures. The maternal albumin level in the RDS group was lower than that in the control group (33.38 ± 3.31 vs. 33.60 ± 3.31, P > 0.05), but the difference was not statistically significant. The neonatal albumin level in the RDS group was significantly lower than that in the control group (32.70 ± 2.48 vs. 35.66 ± 3.27, P < 0.05). To predict RDS in late-preterm infants, using the albumin cutoff level of 34 g/L provides a sensitivity of 83.9% with a specificity of 62.5%. 2. Gestational age, primipara, placenta previa, antenatal corticosteroid therapy, delivery mode, and neonatal serum albumin level were associated with RDS in the late-preterm infant. 3. After adjustment for gestational age, logistic regression analysis showed that neonatal serum albumin level, placenta previa, and delivery mode were independent risk factors for RDS in late-preterm infants. However, albumin level did not related to the severity of RDS. Conclusion: The decrease in serum albumin within the first day after birth was closely related to the occurrence of RDS in late-preterm infants.