Optimising frontline learning and engagement between consultant-led neonatal teams in the West Midlands: a survey on the utility of an augmented simulation training technique.

BACKGROUND: In England, neonatal care is delivered in operational delivery networks, comprising a combination of the Neonatal Intensive Care (NICU), Local-Neonatal (LNU) or Special-Care Units (SCU), based on their ability to care for babies with different degrees of illness or prematurity. With the development of network care pathways, the most premature and sickest are mostly triaged for delivery in services linked to NICU. This has created anxiety for teams in LNU and SCU. Less exposure to sicker babies has resulted in limited opportunities to maintain expertise for when these babies unexpectedly deliver at their centre and thereafter require transfer for care, to NICU. Simultaneously, LNU and SCU teams develop skills in the care of the less ill and premature baby which would also be of benefit to NICU teams. A need for mutual learning through inter-unit multidirectional collaborative learning and engagement (hereafter also called neonatal networking) between teams of different designations emerged. Here, neonatal networking is defined as collaboration, shared clinical learning and developing an understanding of local systems strengths and challenges between units of different and similar designations. We describe the responses to the development of a clinical and systems focussed platform for this engagement between different teams within our neonatal ODN. METHOD: An interactive 1-day programme was developed in the West Midlands, focussing on a non-hierarchical, equal partnership between neonatal teams from different unit designations. It utilised simulation around clinical scenarios, with a slant towards consultant engagement. Four groups rotating through four clinical simulation scenarios were developed. Each group participated in a clinical simulation scenario, led by a consultant and supported by nurses and doctors in training together with facilitators, with a further ~two consultants, as observers within the group. All were considered learners. Consultant candidates took turns to be participants and observers in the simulation scenarios so that at the end of the day all had led a scenario. Each simulation-clinical debrief session was lengthened by a further ~ 20 min, during which freestyle discussion with all learners occurred. This was to promote further bonding, through multidirectional sharing, and with a systems focus on understanding the strengths and challenges of practices in different units. A consultant focus was adopted to promote a long-term engagement between units around shared care. There were four time points for this neonatal networking during the course of the day. Qualitative assessment and a Likert scale were used to assess this initiative over 4 years. RESULTS: One hundred fifty-five individuals involved in frontline neonatal care participated. Seventy-seven were consultants, supported by neonatal trainees, staff grade doctors, clinical fellows, advanced neonatal nurse practitioners and nurses in training. All were invited to participate in the survey. The survey response rate was 80.6%. Seventy-nine percent felt that this learning strategy was highly relevant; 96% agreed that for consultants this was appropriate adult learning. Ninety-eight percent agreed that consultant training encompassed more than bedside clinical management, including forging communication links between teams. Thematic responses suggested that this was a highly useful method for multi-directional learning around shared care between neonatal units. CONCLUSION: Simulation, enhanced with systems focussed debrief, appeared to be an acceptable method of promoting multidirectional learning within neonatal teams of differing designations within the WMNODN.

Congenital Methemoglobinemia Identified by Pulse Oximetry Screening.

Congenital methemoglobinemia is a rare condition caused by cytochrome b5 reductase deficiency, cytochrome b5 deficiency, or hemoglobin M disease. Newborn pulse oximetry screening was developed for the early detection of critical congenital heart disease; however, it also enables the early identification of other hypoxemic conditions. We present the case of a term neonate who was admitted to the neonatal unit after a failed pulse oximetry screening at 3 hours of age. Oxygen saturations remained between 89% and 92% despite an increase in oxygen therapy. Chest radiograph and echocardiogram results were normal. A capillary blood gas test had normal results except for a raised methemoglobin level of 16%. Improvement was seen on the administration of methylene blue, which also resulted in an increase in oxygen saturations to within normal limits. Further investigation revealed evidence of type I hereditary cytochrome b5 reductase deficiency as a result of a CYB5R3 gene mutation with 2 pathogenic variants involving guanine-to-adenine substitutions. Although mild cyanosis is generally the only symptom of type I disease, patients may later develop associated symptoms, such as fatigue and shortness of breath. If an early diagnosis is missed, these patients are likely to present later with a diagnostic conundrum and be subject to extensive investigation. This case represents the success of pulse oximetry screening in the early identification of subclinical hypoxemia in this infant. After the exclusion of other pathologies, a routine investigation of capillary blood gas provided the information that led to a diagnosis, which allowed for early and effective management.

Meta-analysis of genome-wide linkage studies in BMI and obesity.

OBJECTIVE: The objective was to provide an overall assessment of genetic linkage data of BMI and BMI-defined obesity using a nonparametric genome scan meta-analysis. RESEARCH METHODS AND PROCEDURES: We identified 37 published studies containing data on over 31,000 individuals from more than >10,000 families and obtained genome-wide logarithm of the odds (LOD) scores, non-parametric linkage (NPL) scores, or maximum likelihood scores (MLS). BMI was analyzed in a pooled set of all studies, as a subgroup of 10 studies that used BMI-defined obesity, and for subgroups ascertained through type 2 diabetes, hypertension, or subjects of European ancestry. RESULTS: Bins at chromosome 13q13.2- q33.1, 12q23-q24.3 achieved suggestive evidence of linkage to BMI in the pooled analysis and samples ascertained for hypertension. Nominal evidence of linkage to these regions and suggestive evidence for 11q13.3-22.3 were also observed for BMI-defined obesity. The FTO obesity gene locus at 16q12.2 also showed nominal evidence for linkage. However, overall distribution of summed rank p values <0.05 is not different from that expected by chance. The strongest evidence was obtained in the families ascertained for hypertension at 9q31.1-qter and 12p11.21-q23 (p < 0.01). CONCLUSION: Despite having substantial statistical power, we did not unequivocally implicate specific loci for BMI or obesity. This may be because genes influencing adiposity are of very small effect, with substantial genetic heterogeneity and variable dependence on environmental factors. However, the observation that the FTO gene maps to one of the highest ranking bins for obesity is interesting and, while not a validation of this approach, indicates that other potential loci identified in this study should be investigated further.

Genome-wide linkage analysis of a composite index of neuroticism and mood-related scales in extreme selected sibships.

There is considerable evidence to suggest that the genetic vulnerabilities to depression and anxiety substantially overlap and quantitatively act to alter risk to both disorders. Continuous scales can be used to index this shared liability and are a complementary approach to the use of clinical phenotypes in the genetic analysis of depression and anxiety. The aim of this study (Genetic and Environmental Nature of Emotional States in Siblings) was to identify genetic variants for the liability to depression and anxiety after the application of quantitative genetic methodology to a large community-based sample (n = 34,371), using four well-validated questionnaires of depression and anxiety. Genetic model fitting was performed on 2658 unselected sibships, which provided evidence for a single common familial factor that accounted for a substantial proportion of the genetic variances and covariances of the four scales. Using the parameter estimates from this model, a composite index of liability (G) was constructed. This index was then used to select a smaller--but statistically powerful--sample for DNA collection (757 individuals, 297 sibships). These individuals were genotyped with more than 400 microsatellite markers. After the data were checked and cleaned, linkage analysis was performed on G and the personality scale of neuroticism using the regression-based linkage program MERLIN-REGRESS. The results indicated two potential quantitative trait loci (QTL): one on chromosome 1p (LOD 2.2) around 64 cM (43-70 cM) near marker D1S2892 and another on chromosome 6p (LOD 2.7) around 47 cM (34-63 cM) near marker D6S1610. Further exploratory sex-specific analyses suggested that these QTLs might have sex-limited effects.