Treatment of monogenic autoinflammatory disorders, an expanding group of hereditary diseases characterized by apparently unprovoked recurrent episodes of inflammation, without high-titre autoantibodies or antigen-specific T cells, has been revolutionized by the discovery that several of these conditions are caused by mutations in proteins involved in the mechanisms of innate immune response, including components of the inflammasome, cytokine receptors, receptor antagonists, and oversecretion of a network of proinflammatory molecules. Aim of this review is to synthesize the current experience and the most recent evidences about the therapeutic approach with biologic drugs in pediatric and adult patients with monogenic autoinflammatory disorders.

In selected cases, childhood's recurrent fevers of unknown origin can be referred to systemic autoinflammatory diseases as mevalonate kinase deficiency (MKD), caused by mutations in the mevalonate kinase gene (MVK), previously named "hyper-IgD syndrome" due to its characteristic increase in serum IgD level. There is no clear evidence for studying MVK genotype in these patients. From a cohort of 305 children evaluated for recurrent fevers in our outpatient clinic during the decade 2001-2011, we have retrospectively selected 10 unrelated Italian children displaying febrile episodes, associated with recurrent inflammatory signs (variably involving gastrointestinal tube, joints, lymph nodes, and skin) and persistently increased serum IgD levels. All these patients were examined for MVK genotype: only 2 presented bonafide MVK mutations, 5 showed the same S52N MVK polymorphism, while the remaining 3 had a wild-type MVK sequence. Clinical details of these patients have been reviewed through the critical analysis of their medical charts. Our report underscores the pitfalls of MKD diagnosis based on clinical grounds and IgD levels, emphasizing the uncertain contribution of MVK polymorphisms in the diagnostic assessment of the syndrome.

ObjectiveTo evaluate the efficacy of a strict glycaemic control protocol using a continuous glucose monitoring (CGM) in infants at high risk of dysglycaemia with the aim of reducing the number of dysglycaemic episodes.DesignRandomised controlled trial.SettingNeonatal intensive care unit, Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome.PatientsAll infants <1500 g fed on parental nutrition (PN) since birth were eligible. A total of 63 infants were eligible and 48 were randomised.InterventionAll participants wore a CGM sensor and were randomised in two arms with alarms set at different cut-off values (2.61–10 mmol/L (47–180 mg/dL) vs 3.44–7.78 mmol/L (62–140 mg/dL)), representing the operative threshold requiring modulation of glucose infusion rate according to an innovative protocol.Main outcome measuresThe primary outcome was the number of severe dysglycaemic episodes (<2.61 mmol/L (47 mg/dL) or >10 mmol/L (180 mg/dL)) in the intervention group versus the control group, during the monitoring time.ResultsWe enrolled 47 infants, with similar characteristics between the two arms. The number of dysglycaemic episodes and of infants with at least one episode of dysglycaemia was significantly lower in the intervention group (strict group): respectively, 1 (IQR 0–2) vs 3 (IQR 1–7); (p=0.005) and 12 (52%) vs 20 (83%); p=0.047. Infants managed using the strict protocol had a higher probability of having normal glycaemic values: relative risk 2.87 (95% CI 1.1 to 7.3). They spent more time in euglycaemia: 100% (IQR 97–100) vs 98% (IQR 94–99), p=0.036. The number needed to treat to avoid dysglycaemia episodes is 3.2 (95% CI 1.8 to 16.6).ConclusionWe provide evidence that CGM, combined with a protocol for adjusting glucose infusion, can effectively reduce the episodes of dysglycaemia and increase the percentage of time spent in euglycaemia in very low birthweight infants receiving PN in the first week of life.

The development of artificial intelligence methods has impacted therapeutics, personalized diagnostics, drug discovery, and medical imaging. Although, in many situations, AI clinical decision-support tools may seem superior to rule-based tools, their use may result in additional challenges. Examples include the paucity of large datasets and the presence of unbalanced data (i.e., due to the low occurrence of adverse outcomes), as often seen in neonatal medicine. The most recent and impactful applications of AI in neonatal medicine are discussed in this review, highlighting future research directions relating to the neonatal population. Current AI applications tested in neonatology include tools for vital signs monitoring, disease prediction (respiratory distress syndrome, bronchopulmonary dysplasia, apnea of prematurity) and risk stratification (retinopathy of prematurity, intestinal perforation, jaundice), neurological diagnostic and prognostic support (electroencephalograms, sleep stage classification, neuroimaging), and novel image recognition technologies, which are particularly useful for prompt recognition of infections. To have these kinds of tools helping neonatologists in daily clinical practice could be something extremely revolutionary in the next future. On the other hand, it is important to recognize the limitations of AI to ensure the proper use of this technology.

Infantile hemangiomas may affect the quality of life (QoL) of patients and their family members, as anxiety and worry may commonly occur in parents, also linked to the social adversion they experience. We underline the beneficial impact of oral propranolol therapy on QoL of patients with infantile hemangiomas (IH) and of their relatives. A specific questionnaire measuring QoL was administered to parents of IH patients at beginning and end of a treatment with oral propranolol. Different aspects were investigated: site of the lesion, age of patients at starting therapy, length of treatment, occurrence of adverse effects and persistence/recurrence of the vascular anomaly. In all cases the questionnaire revealed a significant improvement of QoL, which was independent from all analyzed factors. It showed that oral propranolol administration in these patients combines optimal clinical results with relevant improvement of QoL, especially in cases of early management. The improvement of QoL seems unrelated to site of lesion, timing and duration of therapy, occurrence of drug-related adverse effects and persistence/recurrence of disease.