Objective: To study the structure of concomitant pathologies in low birth weight premature newborns with respiratory distress syndrome (RDS). To identify mortality risk factors in these newborns. Materials and methods: Data from 374 premature newborns weighing less than 1500 g and gestational age less than 32 weeks with RDS treated in the intensive care unit were analyzed. Results: Several comorbidities were more common among children with RDS compared to children without RDS. Thus, disseminated intravascular coagulation syndrome (DIC) occurred 2 times, atelectasis 1.3 times, necrotizing enterocolitis (NEC) 2.4 times, and anemia 1.8 times more often among children with RDS compared to those without RDS. In multivariate logistic regression, such factors as 1-3 points on the Apgar scale at 1 minute (OR - 2.478, 95% CI - 1.289-4.764, p = 0.007), 1-3 points on the Apgar scale at 5 minutes ( OR - 3.754, 95% CI - 1.788-7.878, p<0.0001), DIC (OR -4.428, 95% CI -2.206-8.887, p<0.0001), NEC (OR - 4.508, 95% CI - 2.270-8.954, p<0.0001) showed a positive association with death in children with RDS. When assessing the effect of the combination of DIC and NEC on death, it was found that the combination of these two pathologies in children with RDS increases the risk of death by more than 2 times. Thus, the area under the curve (AUC) for DIC was 0.283, for NEC the AUC was 0.335, and for the combination ICE+NEC it was 0.782). Conclusions: The structure of comorbidities in low birth weight infants with RDS differs from that of infants without RDS. Premature infants with RDS were more likely to develop anemia, DIC, atelectasis, and NEC. The presence of comorbidities increases the risk of death in low birth weight infants with RDS. Low Apgar score, DIC syndrome, and NEC can increase the risk of death in low birth weight premature infants with RDS. It is anticipated that the collected data will enhance personalized care for low birth weight, premature infants with multiple health conditions, ultimately reducing mortality rates in this vulnerable patient group.

Objective: To identify and characterize a unique set of biomarker genes in peripheral blood on day 5 of life in preterm infants with subsequent development of bronchopulmonary dysplasia. Methods: The open dataset GSE32472 was used to analyze gene expression profiles. The sample included preterm infants with a gestational age of less than 32 weeks and a body weight of ≤1500g. Peripheral blood samples collected within a 5-day window were analyzed to identify early transcriptional changes. Differential gene expression analysis was performed using the limma package with thresholds of |log_2FC|>0.5 and p.adj<0.05. Coexpression network analysis and functional enrichment were used to narrow the pool of potential target genes. At the final stage, three independent machine learning algorithms, such as SVM-RFE, LASSO, and Random Forest, were used to select the most prognostically significant genes. The diagnostic model based on the selected genes was visualized as a nomogram, and its predictive ability was assessed using ROC analysis and decision curve analysis. Results: Comparative analysis identified 451 differentially expressed genes in the BPD group on day 5 of life. WGCNA analysis identified the MEpink module as the one most significantly correlated with the BPD phenotype. The intersection of DEGs and genes within the MEpink module identified 106 common genes, functional analysis of which revealed significant enrichment for processes associated with T-cell activation and T-cell receptor signaling pathways. A combined machine learning approach reliably identified four key hub genes with high prognostic significance: BTN3A3, AK5, NOG, and GCSAM. A diagnostic model based on these four genes demonstrated high predictive ability (AUC = 0.888) and clinical utility. Regulatory analysis revealed that the AK5, BTN3A3, and GCSAM genes are central nodes in the miRNA–mRNA regulatory network. Conclusion: The identified day 5 gene window reflects key pathophysiological processes: developmental impairment, cellular stress, and inflammatory immune dysregulation. These results shift the focus from BPD diagnosis to early risk prediction. Day 5 molecular signatures possess high prognostic value and can be used to develop targeted therapeutic interventions.

Objective. To identify risk factors for fatal outcomes in small-for-gestational age infants with very low and extremely low birth weight. Study design. A retrospective case-control study. Patients and methods. The analysis included data on 459 premature infants with birth weight less than 1500 grams and gestational age less than 32 weeks who were in the intensive care unit of the Center of Perinatology and Pediatric Cardiac Surgery in Almaty between 2021 and 2023. Contingency tables with calculation of χ2 values were used to compare qualitative variables. Binary logistic regression with calculation of odds ratio (OR) and 95% confidence interval (CI) was used to identify factors associated with fatal outcome in premature infants. ROC analysis was performed to assess the prognostic value of all identified risk factors for fatal outcome. Differences were considered statistically significant at p ≤ 0.05. Results. Multivariate logistic regression showed a positive association of low Apgar score (OR = 4.287, 95% CI 2.444–7.519, p < 0.0001), primary atelectasis (OR = 2.134, 95% CI 1.189–3.833, p = 0.011), disseminated intravascular coagulation (DIC) (OR = 4.152, 95% CI 2.256–7.643, p < 0.0001), necrotizing enterocolitis (NEC) (OR = 4.243, 95% CI 2.225–8.089, p < 0.0001) and intraventricular hemorrhage (IVH) (OR = 1.693, 95% CI 1.010–2.839, p = 0.046) with fatal outcome in low-birth-weight premature infants. ROC analysis of individual factors such as IVH, DIC, NEC, and blood type did not show high prognostic value. The area under the curve (AUC) was less than 0.6 (0.393; 0.269; 0.340; 0.567, respectively). At the same time, the combination of blood group and each factor separately showed a significantly higher prognostic value (AUC above 0.7 in all cases). Conclusion. Diseases caused by prematurity such as NEC, IVH and DIC are associated with mortality risk in low-birth-weight infants. The risk of fatal outcome is significantly increased in infants with blood type 0 in combination with these diseases. Key words: fatal outcome, low-birth-weight infants, prematurity, preterm birth, risk factors

Introduction: Bronchopulmonary dysplasia (BPD) remains the most significant complication of extreme prematurity, affecting long-term respiratory outcomes. Because current diagnostic criteria identify only established lesions at 36 weeks postmenstrual age, early non-invasive biomarkers are needed. This pilot study aimed to identify a candidate salivary miRNA panel associated with BPD risk and to explore its pathogenetic relevance through in silico analysis. Methods: Saliva was collected from 20 preterm infants (10 with BPD and 10 controls), and miRNA expression was profiled using the GeneChip™ miRNA 4.1 Array Plate. Discriminatory performance was explored by ROC analysis within this discovery cohort, together with power and Spearman correlation analyses. Results: Expression of hsa-let-7b-5p, hsa-let-7c-5p, and hsa-miR-4454 was significantly elevated in the BPD group (p < 0.05, log₂FC ≥ 1.0), with no significant correlation with gestational age or birth weight. Bootstrap-corrected AUC values ranged from 0.905 to 0.937 and were supported by leave-one-out cross-validation. All three miRNAs showed very large effect sizes exceeding the minimum detectable effect at 80% power. Conclusions: In this pilot study, salivary miRNAs represent a hypothesis-generating candidate biomarker signal for BPD that requires external validation in larger, independent cohorts before any diagnostic or prognostic application can be considered.