The first thousand days of life from conception have a significant impact on the health status with short, and long-term effects. Among several anthropometric and maternal lifestyle parameters birth ...weight plays a crucial role on the growth and neurological development of infants. Recent genome wide association studies (GWAS) have demonstrated a robust foetal and maternal genetic background of birth weight, however only a small proportion of the genetic hereditability has been already identified. Considering the extensive number of phenotypes on which they are involved, we focused on identifying the possible effect of genetic variants belonging to taste receptor genes and birthweight. In the human genome there are two taste receptors family the bitter receptors (TAS2Rs) and the sweet and umami receptors (TAS1Rs). In particular sweet perception is due to a heterodimeric receptor encoded by the TAS1R2 and the TAS1R3 gene, while the umami taste receptor is encoded by the TAS1R1 and the TAS1R3 genes. We observed that carriers of the T allele of the TAS1R1-rs4908932 SNPs showed an increase in birthweight compared to GG homozygotes Coeff: 87.40 (35.13-139.68) p-value = 0.001. The association remained significant after correction for multiple testing. TAS1R1-rs4908932 is a potentially functional SNP and is in linkage disequilibrium with another polymorphism that has been associated with BMI in adults showing the importance of this variant from the early stages of conception through all the adult life.
Recent studies indicate the existence of a complex microbiome in the meconium of newborns that plays a key role in regulating many host health-related conditions. However, a high variability between ...studies has been observed so far. In the present study, the meconium microbiome composition and the predicted microbial metabolic pathways were analysed in a consecutive cohort of 96 full-term newborns. The effect of maternal epidemiological variables on meconium diversity was analysed using regression analysis and PERMANOVA. Meconium microbiome composition mainly included Proteobacteria (30.95%), Bacteroidetes (23.17%) and Firmicutes (17.13%), while for predicted metabolic pathways, the most abundant genes belonged to the class "metabolism". We observed a significant effect of maternal Rh factor on Shannon and Inverse Simpson indexes (p = 0.045 and p = 0.049 respectively) and a significant effect of delivery mode and maternal antibiotic exposure on Jaccard and Bray-Curtis dissimilarities (p = 0.001 and 0.002 respectively), while gestational age was associated with observed richness and Shannon indexes (p = 0.018 and 0.037 respectively), and Jaccard and Bray-Curtis dissimilarities (p = 0.014 and 0.013 respectively). The association involving maternal Rh phenotype suggests a role for host genetics in shaping meconium microbiome prior to the exposition to the most well-known environmental variables, which will influence microbiome maturation in the newborn.
Technology-enhanced simulation has emerged as a great educational tool for pediatric education. Indeed, it represents an effective method to instruct on technical and non-technical skills, employed ...by a large number of pediatric training programs. However, this unique pandemic era posed new challenges also on simulation-based education. Beyond the mere facing of the clinical and societal impacts, it is fundamental to take advantage from the current changes and investigate innovative approaches to improve the education of pediatric healthcare professionals. To this aim, we herein lay down the main pillars that should support the infrastructure of the future technology-enhanced simulation.
According to most early-onset sepsis (EOS) management guidelines, approximately 10% of the total neonatal population are exposed to antibiotics in the first postnatal days with subsequent increase of ...neonatal and pediatric comorbidities. A review of literature demonstrates the effectiveness of EOS calculator in reducing antibiotic overtreatment and NICU admission among neonates ≥34 weeks' gestational age (GA); however, some missed cases of culture-positive EOS have also been described.
Single-center retrospective study from 1st January 2018 to 31st December 2018 conducted in the Division of Neonatology at Santa Chiara Hospital (Pisa, Italy). Neonates ≥34 weeks' GA with birth weight ≤ 1500 g, 34-36 weeks' GA neonates with suspected intraamniotic infection and neonates ≥34 weeks' GA with three clinical signs of EOS or two signs and one risk factor for EOS receive empirical antibiotics. Neonates ≥34 weeks' GA with risk factors for EOS or with one clinical indicator of EOS undergo serial measurements of C-reactive protein and procalcitonin in the first 48-72 h of life; they receive empirical antibiotics in case of abnormalities at blood exams with one or more clinical signs of EOS. Two hundred sixty-five patients at risk for EOS met inclusion criteria; they were divided into 3 study groups: 34-36 weeks' GA newborns (n = 95, group A), ≥ 37 weeks' GA newborns (n = 170, group B), and ≥ 34 weeks' GA newborns (n = 265, group A + B). For each group, we compared the number of patients for which antibiotics would have been needed, based on EOS calculator, and the number of the same patients we treated with antibiotics during the study period. Comparisons between the groups were performed using McNemar's test and statistical significance was set at p < 0.05; post-hoc power analysis was carried out to evaluate the sample sizes.
32/265 (12.1%) neonates ≥34 weeks' GA received antibiotics within the first 12 h of life. According to EOS calculator 55/265 (20.7%) patients would have received antibiotics with EOS incidence 2/1000 live births (p < 0.0001).
Our evidence-based protocol entails a further decrease of antibiotic overtreatment compared to EOS calculator. No negative consequences for patients were observed.
Serious games, and especially digital game based learning (DGBL) methodologies, have the potential to strengthen classic learning methodology in all medical procedures characterized by a flowchart ...(e.g., neonatal resuscitation algorithm). However, few studies have compared short- and long-term knowledge retention in DGBL methodologies with a control group undergoing specialist training led by experienced operators. In particular, resident doctors' learning still has limited representation in simulation-based education literature.
A serious computer game DIANA (
gital
pplication in
ewborn
ssessment) was developed, according to newborn resuscitation algorithm, to train pediatric/neonatology residents in neonatal resuscitation algorithm knowledge and implementation (from procedure knowledge to ventilation/chest compressions rate). We analyzed user learning curves after each session and compared knowledge retention against a classic theoretical teaching session.
Pediatric/neonatology residents of the Azienda Ospedaliera Universitaria Pisana (AOUP) were invited to take part in the study and were split into a game group or a control group; both groups were homogeneous in terms of previous training and baseline scores. The control group attended a classic 80 min teaching session with a neonatal trainer, while game group participants played four 20 min sessions over four different days. Three written tests (pre/immediately post-training and at 28 days) were used to evaluate and compare the two groups' performances.
Forty-eight pediatric/neonatology residents participated in the study. While classic training by a neonatal trainer demonstrated an excellent effectiveness in short/long-term knowledge retention, DGBL methodology proved to be equivalent or better. Furthermore, after each game session, DGBL score improved for both procedure knowledge and ventilation/chest compressions rate.
In this study, DGBL was as effective as classic specialist training for neonatal resuscitation in terms of both algorithm memorization and knowledge retention. User appreciation for the methodology and ease of administration, including remotely, support the use of DGBL methodologies for pediatric/neonatology residents education.
In recent years, medical training has significantly increased the use of simulation for teaching and evaluation. The retraining of medical personnel in Italy is entrusted to the program of Continuous ...Education in Medicine, mainly based on theoretical training. The aim of this study is to assess whether the use of a new sensorized platform for the execution of the neonatal intubation procedure in simulation environment can complement theoretical retraining of experienced health professionals.
Neonatal intubation tests were performed using a commercial manikin and a modified video-laryngoscope by the addition of force and position sensors, which provide the user with feedback when the threshold is exceeded. Two categories carried out the simulation tests: anesthesiologists and pediatricians. The categories were divided into three groups each, and various configurations were tested: the first group of both specialists carried out the tests without feedback (i.e. control groups, gr. A and A1), the second groups received sound and visual feedback from the instrument (gr. B and B1) and the third ones had also the support of a physician expert in the use of the instrument (gr. C and C1). The instrumentation used by pediatricians was provided in a playful form, including a game with increasing difficulty levels.
Both in the case with feedback only and in the case with humans support, anesthesiologists did not show a specific trend of improvement. Pediatricians, in comparison with anesthesiologists, showed a positive reaction to both the presence of feedback and that of experienced personnel. Comparing the performance of the two control groups, the two categories of experienced doctors perform similar forces. Pediatricians enjoyed the "Level Game", through which they were able to test and confront themselves, trying to improve their own performance.
Our instrument is more effective when is playful and competitive, introducing something more than just a sound feedback, and allowing training by increasing levels. It is more effective if the users can adapt their own technique to the instrument by themselves, without any external help.
Errors in Neonatology Antonio Boldrini; Rosa T. Scaramuzzo; Armando Cuttano
Journal of pediatric and neonatal individualized medicine,
10/2013, Letnik:
2, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Introduction: Danger and errors are inherent in human activities. In medical practice errors can lean to adverse events for patients. Mass media echo the whole scenario. Methods: We reviewed recent ...published papers in PubMed database to focus on the evidence and management of errors in medical practice in general and in Neonatology in particular. We compared the results of the literature with our specific experience in Nina Simulation Centre (Pisa, Italy). Results: In Neonatology the main error domains are: medication and total parenteral nutrition, resuscitation and respiratory care, invasive procedures, nosocomial infections, patient identification, diagnostics. Risk factors include patients’ size, prematurity, vulnerability and underlying disease conditions but also multidisciplinary teams, working conditions providing fatigue, a large variety of treatment and investigative modalities needed. Discussion and Conclusions: In our opinion, it is hardly possible to change the human beings but it is likely possible to change the conditions under they work. Voluntary errors report systems can help in preventing adverse events. Education and re-training by means of simulation can be an effective strategy too. In Pisa (Italy) Nina (ceNtro di FormazIone e SimulazioNe NeonAtale) is a simulation center that offers the possibility of a continuous retraining for technical and non-technical skills to optimize neonatological care strategies. Furthermore, we have been working on a novel skill trainer for mechanical ventilation (MEchatronic REspiratory System SImulator for Neonatal Applications, MERESSINA). Finally, in our opinion national health policy indirectly influences risk for errors. Proceedings of the 9th International Workshop on Neonatology · Cagliari (Italy) · October 23rd-26th, 2013 · Learned lessons, changing practice and cutting-edge research
Training through simulation in neonatology relies on sophisticated simulation devices that give realistic feedback to trainees during simulated scenarios. It aims at training highly specialised ...medical teams in established operational skills, timely clinical manoeuvres, and successful synergy with other professionals. For effective teaching, it is essential to tailor simulation to trainees’ emotional status and communication abilities (human factors), which in turn affect their interaction with the equipment, the environment, and the rest of the team. These factors are crucial to achieving optimal timing and cooperation during a clinical intervention, to the point that they can determine the success of a complex operation such as neonatal resuscitation. Ineffective teams perform in a slow and/or poorly coordinated way and therefore jeopardise positive outcomes. Expert trainers consider human factors as crucial as technical skills. In this context, new technology can help measure learning improvement by quantitatively analysing verbal communication within a medical team. For example, Artificial Intelligence models can work on audio recordings, and draw from extensive historical archives, to extract useful human-factor related information for the trainers. In this study, we present an automatic workflow that supports training through simulation in neonatology by automatically detecting dialogue segments of a simulation session with potentially ineffective communication between team members due to anger, stress, fear, or misunderstandings. Rather than working on audio transcriptions, the workflow analyses syllabic-scale (100-200 ms) spoken dialogue energy and intonation. It uses cluster analysis to identify potentially ineffective communication and extracts the most important related words after audio transcription. Performance is measured against a gold standard containing annotations of 79 minutes of audio recordings from neonatal simulations, in Italian, under different noise conditions (from 4.63 to 14.17 SNR). Our workflow achieves a detection accuracy of 64% and a fair agreement with the gold standard in a challenging context for a speech-processing system, where a commercial automatic speech recogniser reaches just a 9.37% sentence accuracy. The workflow also identifies viable words for trainers to conduct the debriefing session, and can be easily extended to other languages and applications in healthcare. We consider it a promising first step towards introducing new technology to support training through simulation centred on human factors.
Abstract Objective To determine the effect of a simulation training program for residents in obstetrics and gynecology in terms of technical and nontechnical skills for the management of shoulder ...dystocia. Methods A prospective study was performed at a center in Italy in April–May 2015. Thirty-two obstetrics and gynecology residents were divided into two groups. Residents in the control group were immediately exposed to an emergency shoulder dystocia scenario, whereas those in the simulation group completed a 2-hour training session with the simulator before being exposed to the scenario. After 8 weeks, the residents were again exposed to the shoulder dystocia scenario and reassessed. Participants were scored on their demonstration of technical and nontechnical skills. Results In the first set of scenarios, the mean score was higher in the simulation group than the control group in terms of both technical skills ( P = 0.008) and nontechnical skills ( P < 0.001). This difference was retained after 8 weeks. Conclusion High-fidelity simulation programs could be used for the training of residents in obstetrics and gynecology to diagnose and manage obstetric emergencies such as shoulder dystocia.
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