ABSTRACT
Acute transient respiratory distress in the first hours of life is usually defined as transient tachypnea of the newborn (TTN). TTN is a respiratory self-limiting disorder consequent to delayed lung fluid clearance at birth. While TTN is the most common etiology of respiratory distress near term, its pathogenesis and diagnostic criteria are not well-defined. Lung ultrasound and targeted neonatal echocardiography are increasingly being used to assess critically ill infants, although their combined use to improve diagnostic precision in neonatal intensive care units has not yet been described. This retrospective pilot analysis aimed to identify possible cardiopulmonary ultrasound (CPUS) patterns in term and late preterm infants suffering from transient respiratory distress and requiring non-invasive respiratory support. After retrospectively revising CPUS images, we found seven potential sonographic phenotypes of acute neonatal respiratory distress. Up to 50% of the patients presented with signs of increased pulmonary vascular resistance, suggesting that those patients may be diagnosed with mild forms of persistent pulmonary hypertension of the newborn. Approximately 80% of the infants with a history of meconium-stained amniotic fluid displayed irregular atelectasis, indicating that they may have suffered from mild meconium aspiration syndrome. CPUS evaluation may improve accuracy in the approach to the infants presenting with transient acute respiratory distress, supporting communication with the parents and carrying important epidemiological consequences.
ABSTRACT
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.
ABSTRACT
Visualization literacy of the broader audiences is becoming an important topic, as we are increasingly surrounded by misleading, erroneous, or confusing visualizations. How can we educate the general masses about data visualization? We propose a twofold model for designing educational games in visualization based on the concept of constructivism and learning-by-playing. We base our approach on the idea of deconstruction and construction, borrowed from the domain of mathematics. We describe the conceptual development and design of our model through two games. First, we present a deconstruction-based game that requires the inspection, identification, and categorization of visualization characteristics (data, users, tasks, visual variables, visualization vocabulary), starting from a finalized visualization. Second, we propose a construction-based game where it is possible to compose visualizations bottom-up from individual visual characteristics. The two games use the same deck of cards with a simple design based on visualization taxonomies, popular in visualization teaching.
