Neonatal sepsis remains a significant cause of neonatal morbidity and mortality globally. At present, no clear consensus definition for sepsis in neonates exists, even though a positive blood culture is considered as the gold standard for definitive diagnosis. The accurate and timely diagnosis of sepsis in neonates presents significant difficulties, since “culture negative” or “suspected” sepsis varies widely worldwide. Antibiotic overuse and resistance are emerging problems, but on the other hand, under-recognition of sepsis and delayed antibiotic treatment could have serious or even fatal adverse outcomes in this vulnerable population. In the context of rapid recognition of sepsis and timely initiation of appropriate antibiotic therapy, various sepsis risk assessment tools have been developed, a variety of biomarkers are in clinical use or under research for future use, and new diagnostic techniques are under evaluation. In this review, we summarize the most recent data on neonatal sepsis, the utility of sepsis risk assessment tools for term and preterm infants with sepsis, and current diagnostic and preventive tools.

Recent studies support that acylcarnitines exert a significant role in cardiovascular disease development and progression. The aim of this metabolomics-based study was to investigate the association of serum acylcarnitine levels with coronary artery disease (CAD) severity, as assessed via SYNTAX Score. Within the context of the prospective CorLipid trial (NCT04580173), the levels of 13 circulating acylcarnitines were accurately determined through a newly developed HILIC-MS/MS method in 958 patients undergoing coronary angiography in the AHEPA University Hospital of Thessaloniki, Greece. Patients presenting with acute coronary syndrome had significantly lower median acylcarnitine C8, C10, C16, C18:1 and C18:2 values, compared to patients with chronic coronary syndrome (p = 0.012, 0.007, 0.018, 0.011 and <0.001, respectively). Among CAD subgroups, median C5 levels were significantly decreased in unstable angina compared to STEMI (p = 0.026), while median C10, C16, C18:1 and C18:2 levels were higher in stable angina compared to STEMI (p = 0.019 p = 0.012, p = 0.013 and p < 0.001, respectively). Moreover, median C2, C3, C4 and C8 levels were significantly elevated in patients with diabetes mellitus (p < 0.001, 22 (p = 0.002, 0.024, 0.044 and 0.012, respectively), indicating a potential prognostic capability of those metabolites and of the ratio C4/C18:2 for the prediction of CAD severity. In conclusion, serum acylcarnitines could serve as clinically useful biomarkers leading to a more individualized management of patients with CAD, once further clinically oriented metabolomics-based studies provide similar evidence.

Neonates do experience pain and its management is necessary in order to prevent long-term, as well as, short-term effects. The most common source of pain in the neonatal intensive care unit (NICU) is caused by medically invasive procedures. NICU patients have to endure trauma, medical adhesive related skin injuries, heel lance, venipuncture and intramuscular injection as well as nasogastric catheterization besides surgery. A cornerstone in pain assessment is the use of scales such as COMFORT, PIPP-R, NIPS and N-PASS. This narrative review provides an up to date account of neonate pain management used in NICUs worldwide focusing on non-pharmacological methods. Non-steroidal anti-inflammatory drugs have well established adverse side effects and opioids are addictive thus pharmacological methods should be avoided if possible at least for mild pain management. Non-pharmacological interventions, particularly breastfeeding and non-nutritive sucking as primary strategies for pain management in neonates are useful strategies to consider. The best non-pharmacological methods are breastfeeding followed by non-nutritive sucking coupled with sucrose sucking. Regrettably most parents used only physical methods and should be trained and involved for best results. Further research in NICU is essential as the developmental knowledge changes and neonate physiology is further uncovered together with its connection to pain.

The GRACE score constitutes a useful tool for risk stratification in patients with acute coronary syndrome (ACS), while the SYNTAX score determines the complexity of coronary artery disease (CAD). This study sought to correlate these scores and assess the accuracy of the GRACE score in predicting the extent of CAD. A total of 539 patients with ACS undergoing coronary angiography were included in this analysis. The patients were classified into those with a SYNTAX score < 33 and a SYNTAX score ≥ 33. Spearman’s correlation and receiver operator characteristic analysis were conducted to investigate the role of the GRACE score as a predictor of the SYNTAX score. There was a significantly positive correlation between the SYNTAX and the GRACE scores (r = 0.32, p < 0.001). The GRACE score predicted severe CAD (SYNTAX ≥ 33) moderately well (the area under the curve was 0.595 (0.522–0.667)). A GRACE score of 126 was documented as the optimal cut-off for the prediction of a SYNTAX score ≥ 33 (sensitivity = 53.5% and specificity = 66%). Therefore, our study reports a significantly positive correlation between the GRACE and the SYNTAX score in patients with ACS. Notably, NSTEMI patients with a high-risk coronary anatomy have higher calculated GRACE scores. A multidisciplinary approach by a heart team could possibly alter the therapeutic approach and management in patients presenting with ACS and a high calculated GRACE score.

Breastfeeding is the preferred method of infant feeding and its establishment is one of the primary goals for the infant. Allergic diseases are common in childhood, with increased morbidity. Food allergies are also associated with a strong negative impact on health-related quality of life and is a major public health problem. In addition, maternal exclusion of common allergens during pregnancy and/or lactation suggests that supplementation with regular cow’s milk formula during the first week of life should be avoided. Breast milk contains many active immune factors, such as cytokines, inflammatory mediators, signaling molecules and soluble receptors, which may also reduce the risk of allergic disease. The prophylactic effects of breastfeeding have been the subject of many studies, some with weak evidence. In this narrative review, we aim to provide an up-to-date account of the effects of prophylactic breastfeeding on food allergy and other common allergies in infants and children up to 5 years of age. Colostrum in particular has been shown to be prophylactic against food allergy. The American Academy of Pediatrics cautions that the relationship between duration of breastfeeding and incidence of food allergy in early childhood is unclear. The protective role of breastfeeding has a positive effect on allergy prevention, which is opposed by the early introduction of solid foods, but larger studies are needed to confirm the evidence. There is evidence that breastfeeding is effective in providing partial protection to infants.

Developing risk assessment tools for CAD prediction remains challenging nowadays. We developed an ML predictive algorithm based on metabolic and clinical data for determining the severity of CAD, as assessed via the SYNTAX score. Analytical methods were developed to determine serum blood levels of specific ceramides, acyl-carnitines, fatty acids, and proteins such as galectin-3, adiponectin, and APOB/APOA1 ratio. Patients were grouped into: obstructive CAD (SS > 0) and non-obstructive CAD (SS = 0). A risk prediction algorithm (boosted ensemble algorithm XGBoost) was developed by combining clinical characteristics with established and novel biomarkers to identify patients at high risk for complex CAD. The study population comprised 958 patients (CorLipid trial (NCT04580173)), with no prior CAD, who underwent coronary angiography. Of them, 533 (55.6%) suffered ACS, 170 (17.7%) presented with NSTEMI, 222 (23.2%) with STEMI, and 141 (14.7%) with unstable angina. Of the total sample, 681 (71%) had obstructive CAD. The algorithm dataset was 73 biochemical parameters and metabolic biomarkers as well as anthropometric and medical history variables. The performance of the XGBoost algorithm had an AUC value of 0.725 (95% CI: 0.691–0.759). Thus, a ML model incorporating clinical features in addition to certain metabolic features can estimate the pre-test likelihood of obstructive CAD.