BACKGROUND: Recently, the first report of lung ultrasound (LUS) guided recruitment during open lung ventilation in neonates has been published. LUS guided recruitment can change the approach to open lung ventilation, which is currently performed without any measure of lung function/lung expansion in the neonatal population. METHODS: We included all the newborn infants that underwent a LUS-guided recruitment maneuver during mechanical ventilation as a rescue attempt for an extremely severe respiratory condition with oxygen saturation/fraction of inspired oxygen (SpO2/FIO2) ratio below 130 or the inability to wean off mechanical ventilation. RESULTS: We report a case series describing 4 LUS guided recruitment maneuvers, underlying crucial aspects of this technique that can improve the effectiveness of the procedure. In particular, we describe a novel pattern (the S-pattern) that allows us to distinguish the recruitable from the unrecruitable lung and guide the pressure titration phase. Additionally, we describe the optimal LUS-guided patient positioning. CONCLUSIONS: We believe that the inclusion of specifications regarding patient positioning and the S-pattern in the LUS-guided protocol may be beneficial for the success of the procedure.
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.
IntroductionPostnatal steroids during the first few weeks of life have been demonstrated to be effective in decreasing the incidence of bronchopulmonary dysplasia (BPD), a serious chronic respiratory condition affecting preterm infants. However, this preventive option is limited by the concern of neurological side effects. Steroids are used to treat established BPD in an attempt to reduce mortality, and length of stay and home oxygen therapy, both of which associated with high levels of parental stress and healthcare costs. Moreover, a late timing for steroid treatment may show a more favourable safety profile in terms of neurodevelopment outcomes, considering the added postnatal brain maturation of these infants. Here, we report a protocol for a systematic review, which aims to determine the efficacy and long-term safety of postnatal steroids for the treatment of established BPD in preterm infants.Methods and analysisMEDLINE, Embase, Cochrane databases and sources of grey literature for conference abstracts and trial registrations will be searched with no time or language restriction. We will include case–control studies, cohort studies and non-randomised or randomised trials that evaluate postnatal steroids for infants diagnosed with moderate or severe established BPD at 36 weeks’ postmenstrual age. We will pool data from studies that are sufficiently similar to make this appropriate. Data extraction forms will be developed a priori. Observational studies and non-randomised and randomised clinical trials will be analysed separately. We will combine OR with 95% CI for dichotomous outcomes and the mean difference (95% CI) for continuous outcomes. We will account for the expected heterogeneity by using a random-effects model. We will perform subgroup analysis based on the a priori determined covariate of interest.Ethics and disseminationSystematic reviews are exempted from approval by an ethics committee. Attempts will be sought to publish all results.PROSPERO registration numberCRD42021218881.
This study investigated the effectiveness of an original Lung UltraSound Targeted Recruitment (LUSTR) protocol to improve the success of lung recruitment maneuvers (LRMs), which are performed as a rescue approach in critically ill neonates. All the LUSTR maneuvers, performed on infants with an oxygen saturation/fraction of inspired oxygen (S/F) ratio below 200, were included in this case−control study (LUSTR-group). The LUSTR-group was matched by the initial S/F ratio and underlying respiratory disease with a control group of lung recruitments performed following the standard oxygenation-guided procedure (Ox-group). The primary outcome was the improvement of the S/F ratio (Delta S/F) throughout the LRM. Secondary outcomes included the rate of air leaks. Each group was comprised of fourteen LRMs. As compared to the standard approach, the LUSTR protocol was associated with a higher success of the procedure in terms of Delta S/F (110 ± 47.3 vs. 64.1 ± 54.6, p = 0.02). This result remained significant after adjusting for confounding variables through multiple linear regressions. The incidence of pneumothorax was lower, although not reaching statistical significance, in the LUSTR-group (0 vs. 14.3%, p = 0.15). The LUSTR protocol may be a more effective and safer option than the oxygenation-based procedure to guide open lung ventilation in neonates, potentially improving ventilation and reducing the impact of ventilator-induced lung injury.
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