Background and Objectives: Retinopathy of prematurity (ROP) is the leading cause of blindness in preterm infants. We studied the relationship between different perinatal characteristics, i.e., sex; gestational age (GA); birth weight (BW); C-reactive protein (CRP) and lactate dehydrogenase (LDH) concentrations; ventilation, continuous positive airway pressure (CPAP), and surfactant administration; and the incidence of Stage 1–3 ROP. Materials and Methods: This study included 247 preterm infants with gestational age (GA) < 32 weeks that were successfully screened for ROP. Univariate and multivariate binary analyses were performed to find the most significant risk factors for ROP (Stage 1–3), while multivariate multinomial analysis was used to find the most significant risk factors for specific ROP stages, i.e., Stage 1, 2, and 3. Results: The incidence of ROP (Stage 1–3) was 66.40% (164 infants), while that of Stage 1, 2, and 3 ROP was 15.38% (38 infants), 27.53% (68 infants), and 23.48% (58 infants), respectively. Following univariate analysis, multiple perinatal characteristics, i.e., GA; BW; and ventilation, CPAP, and surfactant administration, were found to be statistically significant risk factors for ROP (p < 0.001). However, in a multivariate model using the same characteristics, only BW and ventilation were significant ROP predictors (p < 0.001 and p < 0.05, respectively). Multivariate multinomial analysis revealed that BW was only significantly correlated with Stage 2 and 3 ROP (p < 0.05 and p < 0.001, respectively), while ventilation was only significantly correlated with Stage 2 ROP (p < 0.05). Conclusions: The results indicate that GA; BW; and the use of ventilation, CPAP, and surfactant were all significant risk factors for ROP (Stage 1–3), but only BW and ventilation were significantly correlated with ROP and specific stages of the disease, namely Stage 2 and 3 ROP and Stage 2 ROP, respectively, in multivariate models.

Background and Objectives: Prematurity of birth occurs before the 37th week of gestation and affects up to 10% of births worldwide. It is correlated with critical outcomes; therefore, constant monitoring in neonatal intensive care units or home environments is required. The aim of this work was to develop solutions for remote neonatal intensive supervision systems, which should assist medical diagnosis of premature infants and raise alarm at cardiac abnormalities, such as bradycardia. Additionally, the COVID-19 pandemic has put a worldwide stress upon the medical staff and the management of healthcare units. Materials and Methods: A traditional medical diagnosing scheme was set up, implemented with the aid of powerful mathematical operators. The algorithm was tailored to the infants’ personal ECG characteristics and was tested on real ECG data from the publicly available PhysioNet database “Preterm Infant Cardio-Respiratory Signals Database”. Different processing problems were solved: noise filtering, baseline drift removal, event detection and compression of medical data using the à trous wavelet transform. Results: In all 10 available clinical cases, the bradycardia events annotated by the physicians were correctly detected using the RR intervals. Compressing the ECG signals for remote transmission, we obtained compression ratios (CR) varying from 1.72 to 7.42, with the median CR value around 3. Conclusions: We noticed that a significant amount of noise can be added to a signal while monitoring using standard clinical sensors. We tried to offer solutions for these technical problems. Recent studies have shown that persons infected with the COVID-19 disease are frequently reported to develop cardiovascular symptoms and cardiac arrhythmias. An automatic surveillance system (both for neonates and adults) has a practical medical application. The proposed algorithm is personalized, no fixed reference value being applied, and the algorithm follows the neonate’s cardiac rhythm changes. The performance depends on the characteristics of the input ECG. The signal-to-noise ratio of the processed ECG was improved, with a value of up to 10 dB.

Background and objectives: The postpartum maternal physical and psychological state played a fundamental role in the mother–child relationship at the beginning of the COVID-19 pandemic. The aim of the study is to analyze the influence of maternal psychological manifestations on the mother–child couple through three objectives (briefly expressed): (I) Determination of the main acute and chronic conditions of newborns/infants. (II) Verification of the hypothesis of the existence of a link between the following neonatal variables: gestational age, birth weight, number of days of hospitalization, and specific neonatal therapies (oxygen, surfactant, and blood products’ transfusion). (III) Verification of the influence of postpartum maternal psychological status on the mother–child couple through three hypotheses. Materials and methods: This cross-sectional study was conducted in two hospitals in Timișoara, Romania, between 1 March and 1 September 2020, and included 165 mothers and their 175 newborns. Mothers answered the Edinburgh Postnatal Depression Scale, Spielberger’s Inventory of State-Trait Anxiety, and the Collins and Read Revised Adult Attachment Scale. Results: (I) The acute and chronic pathology of the infants in the study group was polymorphic. (II) Large correlations were identified between the following infant variables: gestational age with birth weight, and number of hospitalization days with birth weight, gestational age, and use of blood product transfusion (all p < 0.001). (III) (1) State anxiety was the only significant predictor of number of hospitalization days (p = 0.037), number of acute disorders (p = 0.028), and number of infant chronic diseases (p = 0.037). (2) Maternal depressive symptoms were the only predictor of postpartum maternal attachment (p = 0.018). (3) Depressive symptoms, state, and trait anxiety were non-significant in all models studied (all p > 0.05). Conclusions: Postpartum maternal physical and psychological state plays a fundamental role on the mother–child relationship in the new social and complex family conditions.

(1) Background: The prevention of critical situations is a key ability in medicine. Hip ultrasound for neonates is a standard procedure to prevent later critical outcomes, such as hip dysplasia. Additionally, the SARS-CoV-2 pandemic has put worldwide stress upon healthcare units, resulting often in a lack of sufficient medical personnel. This work aims to develop solutions to ease and speed up the process of coming to a correct diagnosis. (2) Methods: Traditional medical procedures are envisaged, but they are enhanced to reduce diagnosing errors due to the movements of the neonates. Echographic noise filtering and contrast correction methods are implemented the Hyperanalytic Wavelet Transform, combined with an adaptive Soft Thresholding Filter. The algorithm is tailored to infants’ structure and is tested on real ultrasounds provided by the “Victor Babes” University of Medicine and Pharmacy. Denoising and contrast correction problems are targeted. (3) Results: In available clinical cases, the noise affecting the image was reduced and the contrast was enhanced. (4) Discussion: We noticed that a significant amount of noise can be added to the image, as the patients are neonates and can hardly avoid movements. (5) Conclusions: The algorithm is personalized with no fixed reference value. Any device easing the clinical procedures of physicians has a practical medical application.