Antibiotics are the most frequently prescribed drugs in neonatal intensive care units (NICUs) due to the severity of complications accompanying neonatal sepsis. However, antimicrobial drugs are often used inappropriately due to the difficulties in diagnosing sepsis in the neonatal population. The reckless use of antibiotics leads to the development of resistant strains, rendering multidrug-resistant pathogens a serious problem in NICUs and a global threat to public health. The aim of this narrative review is to provide a brief overview of neonatal sepsis and an update on the data regarding indications for antimicrobial therapy initiation, current guidance in the empirical antimicrobial selection and duration of therapy, and indications for early discontinuation.

Invasive Candida infections represent a significant cause of morbidity and mortality in neonatal intensive care units (NICUs), with a particular impact on preterm and low-birth-weight neonates. In addition to prematurity, several predisposing factors for Candida colonization and dissemination during NICU hospitalization have been identified, including prolonged exposure to broad-spectrum antibiotics, central venous catheters, parenteral nutrition, corticosteroids, H2 antagonist administration, and poor adherence to infection control measures. According to the literature, the implementation of antifungal prophylaxis, mainly fluconazole, in high-risk populations has proven to be an effective strategy in reducing the incidence of fungal infections. This review aims to provide an overview of risk factors for invasive Candida infections and current perspectives regarding antifungal prophylaxis use. Recognizing and reducing people’s exposure to these modifiable risk factors, in conjunction with the administration of antifungal prophylaxis, has been demonstrated to be an effective method for preventing invasive candidiasis in susceptible neonatal populations.

Early-onset sepsis (EOS) is a global health issue, considered one of the primary causes of neonatal mortality. Diagnosis of EOS is challenging because its clinical signs are nonspecific, and blood culture, which is the current gold-standard diagnostic tool, has low sensitivity. Commonly used biomarkers for sepsis diagnosis, including C-reactive protein, procalcitonin, and interleukin-6, lack specificity for infection. Due to the disadvantages of blood culture and other common biomarkers, ongoing efforts are directed towards identifying innovative molecular approaches to diagnose neonates at risk of sepsis. This review aims to gather knowledge and recent research on these emerging molecular methods. PCR-based techniques and unrestricted techniques based on 16S rRNA sequencing and 16S–23S rRNA gene interspace region sequencing offer several advantages. Despite their potential, these approaches are not able to replace blood cultures due to several limitations; however, they may prove valuable as complementary tests in neonatal sepsis diagnosis. Several microRNAs have been evaluated and have been proposed as diagnostic biomarkers in EOS. T2 magnetic resonance and bioinformatic analysis have proposed potential biomarkers of neonatal sepsis, though further studies are essential to validate these findings.

Data regarding the nutritional management of preterm small for gestational age (SGA) infants are scarce. In the recent report of ESPGHAN, the recommended energy for very preterm infants during hospitalization has been increased, yet this may not fit the needs of all preterm infants. It is important to distinguish fetal growth-restricted (FGR) infants from constitutional SGA infants, as well as preterm SGA from preterm AGA infants, since they may have different nutritional needs. Preterm FGR infants, and specifically infants < 29 weeks’ gestation, accumulate nutrient deficits due to intrauterine malnutrition, prematurity, morbidities, delayed initiation of feeding, and feeding intolerance. Therefore, these infants may need more aggressive nutrition for optimal catch-up growth and neurologic development. However, a balance should be kept between optimal and excessive catch-up growth, since the combination of intrauterine malnutrition and excessive postnatal growth has been linked with later adverse metabolic consequences. Furthermore, multiple gestation is often complicated by FGR and prematurity. There is controversy in the definition of FGR in multiple gestations, and it should be noted that FGR in multiple gestation usually differs etiologically from FGR in singletons. The aim of this review is to summarize existing knowledge regarding the nutritional needs of preterm FGR and FGR infants of multiple gestation.

Artificial intelligence (AI) refers to computer algorithms that replicate the cognitive function of humans. Machine learning is widely applicable using structured and unstructured data, while deep learning is derived from the neural networks of the human brain that process and interpret information. During the last decades, AI has been introduced in several aspects of healthcare. In this review, we aim to present the current application of AI in the neonatal intensive care unit. AI-based models have been applied to neurocritical care, including automated seizure detection algorithms and electroencephalogram-based hypoxic-ischemic encephalopathy severity grading systems. Moreover, AI models evaluating magnetic resonance imaging contributed to the progress of the evaluation of the neonatal developing brain and the understanding of how prenatal events affect both structural and functional network topologies. Furthermore, AI algorithms have been applied to predict the development of bronchopulmonary dysplasia and assess the extubation readiness of preterm neonates. Automated models have been also used for the detection of retinopathy of prematurity and the need for treatment. Among others, AI algorithms have been utilized for the detection of sepsis, the need for patent ductus arteriosus treatment, the evaluation of jaundice, and the detection of gastrointestinal morbidities. Finally, AI prediction models have been constructed for the evaluation of the neurodevelopmental outcome and the overall mortality of neonates. Although the application of AI in neonatology is encouraging, further research in AI models is warranted in the future including retraining clinical trials, validating the outcomes, and addressing serious ethics issues.

Invasive Candida infections represent a significant cause of morbidity and mortality in the neonatal intensive care unit (NICU), particularly among preterm and low birth weight neonates. The nonspecific clinical presentation of invasive candidiasis, resembling that of bacterial sepsis with multiorgan involvement, makes the diagnosis challenging. Given the atypical clinical presentation and the potential detrimental effects of delayed treatment, empirical treatment is often initiated in cases with high clinical suspicion. This underscores the need to develop alternative laboratory methods other than cultures, which are known to have low sensitivity and a prolonged detection time, to optimize therapeutic strategies. Serum biomarkers, including mannan antigen/anti-mannan antibody and 1,3-β-D-glucan (BDG), both components of the yeast cell wall, a nano-diagnostic method utilizing T2 magnetic resonance, and Candida DNA detection by PCR-based techniques have been investigated as adjuncts to body fluid cultures and have shown promising results in improving diagnostic efficacy and shortening detection time in neonatal populations. This review aims to provide an overview of the diagnostic tools and the current management strategies for invasive candidiasis in neonates. Timely and accurate diagnosis followed by targeted antifungal treatment can significantly improve the survival and outcome of neonates affected by Candida species.