Thirty years of ANZICS CORE: A clinical quality success story.

In 2023, the Australian and New Zealand Intensive Care Society (ANZICS) Registry run by the Centre for Outcomes and Resources Evaluation (CORE) turns 30 years old. It began with the Adult Patient Database, the Australian and New Zealand Paediatric Intensive Care Registry, and the Critical Care Resources Registry, and it now includes Central Line Associated Bloodstream Infections Registry, the Extra-Corporeal Membrane Oxygenation Database, and the Critical Health Resources Information System. The ANZICS Registry provides comparative case-mix reports, risk-adjusted clinical outcomes, process measures, and quality of care indicators to over 200 intensive care units describing more than 200 000 adult and paediatric admissions annually. The ANZICS CORE outlier management program has been a major contributor to the improved patient outcomes and provided significant cost savings to the healthcare sector. Over 200 peer-reviewed papers have been published using ANZICS Registry data. The ANZICS Registry was a vital source of information during the COVID-19 pandemic. Upcoming developments include reporting of long-term survival and patient-reported outcome and experience measures.

Association Between Centralization and Outcome for Children Admitted to Intensive Care in Australia and New Zealand: A Population-Based Cohort Study.

OBJECTIVES: To describe regional differences and change over time in the degree of centralization of pediatric intensive care in Australia and New Zealand (ANZ) and to compare the characteristics and ICU mortality of children admitted to specialist PICUs and general ICUs (GICUs). DESIGN: A retrospective cohort study using registry data for two epochs of ICU admissions, 2003-2005 and 2016-2018. SETTING: Population-based study in ANZ. PATIENTS: A total of 43,256 admissions of children aged younger than 16 years admitted to an ICU in ANZ were included. Infants aged younger than 28 days without cardiac conditions were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was risk-adjusted ICU mortality. Logistic regression was used to investigate the association of mortality with the exposure to ICU type, epoch, and their interaction. Compared with children admitted to GICUs, children admitted to PICUs were younger (median 25 vs 47 mo; p < 0.01) and stayed longer in ICU (median 1.6 vs 1.0 d; p < 0.01). For the study overall, 93% of admissions in Australia were to PICUs whereas in New Zealand only 63% of admissions were to PICUs. The adjusted odds of death in epoch 2 relative to epoch 1 decreased (adjusted odds ratio [AOR], 0.50; 95% CI, 0.42-0.59). There was an interaction between unit type and epoch with increased odds of death associated with care in a GICU in epoch 2 (AOR, 1.63; 95% CI, 1.05-2.53 for all admissions; 1.73, CI, 1.002-3.00 for high-risk admissions). CONCLUSIONS: Risk-adjusted mortality of children admitted to specialist PICUs decreased over a study period of 14 years; however, a similar association between time and outcome was not observed in high-risk children admitted to GICUs. The results support the continued use of a centralized model of delivering intensive care for critically ill children.

Lactate, Base Excess, and the Pediatric Index of Mortality: Exploratory Study of an International, Multicenter Dataset.

OBJECTIVES: To investigate the relationship between ICU admission blood lactate, base excess, and ICU mortality and to explore the effect of incorporating blood lactate into the Pediatric Index of Mortality. DESIGN: Retrospective cohort study based on data prospectively collected on every PICU admission submitted to the U.K. Pediatric Intensive Care Audit Network and to the Australia and New Zealand Pediatric Intensive Care Registry. SETTING: Thirty-three PICUs in the United Kingdom/Republic of Ireland and nine PICUs and 20 general ICUs in Australia and New Zealand. PATIENTS: All ICU admissions between January 1, 2012, and December 31, 2015. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: One hundred twenty-three thousand two hundred fifty-two admissions were recorded in both datasets; 81,576 (66.2%) in the United Kingdom/Republic of Ireland and 41,676 (33.8%) in Australia and New Zealand. Of these 75,070 (61%) had a base excess recorded, 63,316 (51%) had a lactate recorded, and 60,876 (49%) had both base excess and lactate recorded. Median lactate value was 1.5 mmol/L (interquartile range, 1-2.4 mmol/L) (United Kingdom/Republic of Ireland: 1.5 [1-2.5]; Australia and New Zealand: 1.4 [1-2.3]). Children with a lactate recorded had a higher illness severity, were more likely to be invasively ventilated, admitted after cardiac surgery, and had a higher mortality rate, compared with admissions with no lactate recorded (p < 0.001). The relationship between lactate and mortality was stronger (odds ratio, 1.32; 95% CI, 1.31-1.34) than between absolute base excess and mortality (odds ratio, 1.13; 95% CI, 1.12-1.14). Addition of lactate to the Pediatric Index of Mortality score led to a small improvement in performance over addition of absolute base excess, whereas adding both lactate and absolute base excess achieved the best performance. CONCLUSIONS: At PICU admission, blood lactate is more strongly associated with ICU mortality than absolute base excess. Adding lactate into the Pediatric Index of Mortality model may result in a small improvement in performance. Any improvement in Pediatric Index of Mortality performance must be balanced against the added burden of data capture when considering potential incorporation into the Pediatric Index of Mortality model.

Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol.

INTRODUCTION: Approximately 20%-40% of comatose children with risk factors in intensive care have electrographic-only seizures; these go unrecognised due to the absence of continuous electroencephalography (EEG) monitoring (cEEG). Utility of cEEG with high-quality assessment is currently limited due to high-resource requirements. New software analysis tools are available to facilitate bedside cEEG assessment using quantitative EEG (QEEG) trends. The primary aim of this study is to describe accuracy of interpretation of QEEG trends by paediatric intensive care unit (PICU) nurses compared with cEEG assessment by neurologist (standard clinical care) in children at risk of seizures and status epilepticus utilising diagnostic test statistics. The secondary aims are to determine time to seizure detection for QEEG users compared with standard clinical care and describe impact of confounders on accuracy of seizure detection. METHODS AND ANALYSIS: This will be a single-centre, prospective observational cohort study evaluating a paediatric QEEG programme utilising the full 19 electrode set. The setting will be a 36-bed quaternary PICU with medical, cardiac and general surgical cases. cEEG studies in PICU patients identified as 'at risk of seizures' will be analysed. Trained bedside clinical nurses will interpret the QEEG. Seizure events will be marked as seizures if >3 QEEG criteria occur. Post-hoc dedicated neurologists, who remain blinded to the QEEG analysis, will interpret the cEEG. Determination of standard test characteristics will assess the primary hypothesis. To calculate 95% (CIs) around the sensitivity and specificity estimates with a CI width of 10%, the sample size needed for sensitivity is 80 patients assuming each EEG will have approximately 9 to 18 1-hour epochs. ETHICS AND DISSEMINATION: The study has received approval by the Children's Health Queensland Human Research Ethics Committee (HREC/19/QCHQ/58145). Results will be made available to the funders, critical care survivors and their caregivers, the relevant societies, and other researchers. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry (ANZCTR) 12621001471875.

Decision-making for children requiring interhospital transport: assessment of a novel triage tool.

OBJECTIVE: The use of specialist retrieval teams to transport critically ill children is associated with reduced risk-adjusted mortality and morbidity; however, there is a paucity of data to guide decision-making related to retrieval team activation. We aimed to assess the accuracy of a novel triage tool designed to identify critically ill children at the time of referral for interhospital transport. DESIGN: Prospective observational study. SETTING: Regional paediatric retrieval and transport services. PATIENTS: Data were collected for 1815 children referred consecutively for interhospital transport from 87 hospitals in Queensland and northern New South Wales. INTERVENTION: Implementation of the Queensland Paediatric Transport Triage Tool. MAIN OUTCOME MEASURES: Accuracy was assessed by calculating the sensitivity, specificity and negative predictive value for predicting transport by a retrieval team, or admission to intensive care following transport. RESULTS: A total of 574 (32%) children were transported with a retrieval team. Prediction of retrieval (95% CIs): sensitivity 96.9% (95% CI 95.1% to 98.1%), specificity 91.4% (95% CI 89.7% to 92.9%), negative predictive value 98.4% (95% CI 97.5% to 99.1%). There were 412 (23%) children admitted to intensive care following transport. Prediction of intensive care admission: sensitivity 96.8% (95% CI 94.7% to 98.3%), specificity 81.2% (95% CI 79.0% to 83.2%), negative predictive value 98.9% (95% CI 98.1% to 99.4%). CONCLUSIONS: The triage tool predicted the need for retrieval or intensive care admission with high sensitivity and specificity. The high negative predictive value indicates that, in our setting, children categorised as acutely ill rather than critically ill are generally suitable for interhospital transport without a retrieval team.

New sources of lentil germplasm for aluminium toxicity tolerance identified by high throughput hydroponic screening.

Aluminium (Al) toxicity in acid soils inhibits root elongation and development causing reduced water and nutrient uptake by the root system, which ultimately reduces the crop yield. This study established a high throughput hydroponics screening method and identified Al toxicity tolerant accessions from a set of putative acid tolerant lentil accessions. Four-day old lentil seedlings were screened at 5 µM Al (pH 4.5) for three days in hydroponics. Measured pre and post treatment root length was used to calculate the change in root length (ΔRL) and relative root growth (RRG%). A subset of 15 selected accessions were used for acid soil Al screening, and histochemical and biochemical analyses. Al treatment significantly reduced the ΔRL with an average of 32.3% reduction observed compared to the control. Approximately 1/4 of the focused identification of germplasm strategy accessions showed higher RRG% than the known tolerant line ILL6002 which has the RRG% of 37.9. Very tolerant accessions with RRG% of > 52% were observed in 5.4% of the total accessions. A selection index calculated based on all root traits in acid soil screening was highest in AGG70137 (636.7) whereas it was lowest in Precoz (76.3). All histochemical and biochemical analyses supported the hydroponic results as Northfield, AGG70137, AGG70561 and AGG70281 showed consistent good performance. The identified new sources of Al tolerant lentil germplasm can be used to breed new Al toxicity tolerant lentil varieties. The established high throughput hydroponic method can be routinely used for screening lentil breeding populations for Al toxicity tolerance. Future recommendations could include evaluation of the yield potential of the selected subset of accessions under acid soil field conditions, and the screening of a wider range of landrace accessions originating from areas with Al toxic acid soils.

Making the most of all data: Combining non-genotyped and genotyped potato individuals with HBLUP.

Using genomic information to predict phenotypes can improve the accuracy of estimated breeding values and can potentially increase genetic gain over conventional breeding. In this study, we investigated the prediction accuracies achieved by best linear unbiased prediction (BLUP) for nine potato phenotypic traits using three types of relationship matrices pedigree ABLUP, genomic GBLUP, and a hybrid matrix (H) combining pedigree and genomic information (HBLUP). Deep pedigree information was available for >3000 different potato breeding clones evaluated over four years. Genomic relationships were estimated from >180,000 informative SNPs generated using a genotyping-by-sequencing transcriptome (GBS-t) protocol for 168 cultivars, many of which were parents of clones. Two validation scenarios were implemented, namely "Genotyped Cultivars Validation" (a subset of genotyped lines as validation set) and "Non-genotyped 2009 Progenies Validation". Most of the traits showed moderate to high narrow sense heritabilities (range 0.22-0.72). In the Genotyped Cultivars Validation, HBLUP outperformed ABLUP on prediction accuracies for all traits except early blight, and outperformed GBLUP for most of the traits except tuber shape, tuber eye depth and boil after-cooking darkening. This is evidence that the in-depth relationship within the H matrix could potentially result in better prediction accuracy in comparison to using A or G matrix individually. The prediction accuracies of the Non-genotyped 2009 Progenies Validation were comparable between ABLUP and HBLUP, varying from 0.17-0.70 and 0.18-0.69, respectively. Better prediction accuracy and less bias in prediction using HBLUP is of practical utility to breeders as all breeding material is ranked on the same scale leading to improved selection decisions. In addition, our approach provides an economical alternative to utilize historic breeding data with current genotyped individuals in implementing genomic selection.

Queensland Paediatric Cardiac Service: Lessons from evolution to a unified service in a tertiary children's hospital.

We describe a complex change process for the paediatric cardiac service in Queensland that involved transitioning the service out of an essentially adult hospital into one of two children's hospitals in Brisbane. This initial step was complex as the governance was changed from Queensland Health to Mater Health, an independent faith-based organisation who became the new employer. Six years later, the service was again transitioned; this time to the newly constructed Queensland Children's Hospital, with a Hospital and Health Services Board as the employer under the aegis of Queensland Health. This was a complex journey. As with all change processes there was resistance to change on the part of some individuals. Five years on from the second major change, the service is settled, has an excellent workplace culture, has excellent clinical outcomes and has become research intensive.

Predicting Neurological Recovery after Traumatic Brain Injury in Children: A Systematic Review of Prognostic Models.

Predictive modeling is foundational to treatment and long-term management of children with traumatic brain injury (TBI). Assessment of injury severity in the acute-care setting enables early stratification of patients based on their risk of death, lifelong disability, or unfavorable outcome. This review evaluates predictive models that have been developed or validated for pediatric TBI patients. The predictive accuracy of these models, the outcomes and time points predicted, and the variables and statistical methods utilized in model development were compared. Embase, Scopus, MEDLINE®, and Web of Science were searched for studies that developed statistical models for predicting patient outcomes following pediatric TBI. Studies were excluded if they focused on adults or non-traumatic brain injury, or if they did not assess classification accuracy. A total of 4538 entries were identified and screened, with 7 studies included for analysis. This included five studies in which adult predictive models were validated for use in the pediatric setting, and two in which new models were derived from a pediatric cohort. Trials of adult prediction tools in pediatric cohorts, including the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) and Corticoid Randomisation After Significant Head Injury (CRASH)-TBI models, showed comparable accuracy between classification of adults and children. Models derived from pediatric cohorts showed improved accuracy. Most studies solely focused on clinical variables, with two studies incorporating biochemical and imaging variables. Predictive models for pediatric TBI are primarily based on methods and variables identified in adult studies. Although adult models have proven effective in select pediatric cohorts, they may be suboptimal when compared with models derived or adjusted for children.

Screening for Resistance to PVY in Australian Potato Germplasm.

Potatoes are an important human food crop, but have a number of yield limiting factors, including disease susceptibility. Potato virus Y (PVY) is found worldwide, and is one of the main virus problems for potato growers. PVY is transmitted by aphids and mechanically by machinery, tools and people, and symptoms are variable across cultivars and strains, including being symptomless in some cultivars. Therefore, breeding resistant cultivars is the best way to control this virus. This study phenotypically screened 74 of the main commercial cultivars and a few other select cultivars grown in Australia, in order to identify sources of resistance to PVY. The cultivars were screened against PVYO and PVYNTN, with 23 out of 71 resistant to PVYO and 13 out of 74 resistant to PVYNTN, and all these 13 were resistant to both strains. When the phenotypic screening was compared to the results listed on the European Cultivated Potato Database, the majority of results were found to be consistent. We then evaluated three molecular markers RYSC3, M45, and STM0003 for the extreme resistance genes Ryadg and Rysto, to validate the usefulness of the markers for marker-assisted selection (MAS) on Australian germplasm. The degree of correlation between the resistance phenotypes and the RYSC3, M45, and STM0003 markers for Ryadg and Rysto conferred PVY resistance was determined. Three cultivars amplified the RYSC3 marker, while the M45 marker amplified the same 3 and an additional 9. Of the 12 cultivars, 11 phenotyped as resistant, but 1 was susceptible. The STM0003 marker was amplified from only 2 cultivars that both had resistant phenotypes. The RYSC3, M45, and STM0003 markers were therefore able to identify all the 13 cultivars that were resistant to both strains of PVY. Therefore, these markers will enable the identification of genotypes with resistance to PVY, and enable PVY resistant parents to be used for the development of superior progeny; these genetic markers can be used for MAS in the Australian potato breeding program.

The Effect of Imputation of PaO2/FIO2 From SpO2/FIO2 on the Performance of the Pediatric Index of Mortality 3.

OBJECTIVES: To investigate if the performance of Pediatric Index of Mortality 3 is improved by including imputed values for the PaO2/FIO2 ratio where measurements of PaO2 or FIO2 are missing. DESIGN: A prospective observational study. SETTING: A bi-national pediatric intensive care registry. PATIENTS: The records of 37,983 admissions of children less than 16 years old admitted to 19 ICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Seven published equations describing an association between PaO2/FIO2 and oxygen saturation measured by pulse oximetry (SpO2)/FIO2 were used to derive an alternative variable d100 × FIO2/PaO2 for the Pediatric Index of Mortality 3 variable 100 × FIO2/PaO2. Six equations exclude SpO2/FIO2 values if SpO2 is greater than 96-98%. 100 × FIO2/PaO2 was missing in 72% of patient records primarily due to missing PaO2, d100 × FIO2/PaO2 was missing in 71% of patient records if values of SpO2greater than 97% were excluded or in 17% of patient records if all measurements of SpO2 were included. Univariable analysis supported the inclusion of SpO2 values greater than 97%. Compared to the standard Pediatric Index of Mortality 3 model, two alternative models imputing 100 × FIO2/PaO2 from d100 × FIO2/PaO2 only if 100 × FIO2/PaO2 was missing, or using d100 × FIO2/PaO2 values exclusively, resulted in a small but statistically significant improvements in discrimination of Pediatric Index of Mortality 3 (area under the receiver operator curve 0.9068 [0. 8965-0. 9171]; 0.9083 [0.8981-0.9184]; 0.9087 [0.8987-0.9188], respectively). CONCLUSIONS: Imputation of the PaO2/FIO2 ratio in cases where arterial sampling was not performed resulted in a large reduction in the rate of missing data if all values of SpO2 were included. The imputation technique improved the discrimination of Pediatric Index of Mortality 3; however, the magnitude of the increment in overall model performance was small. A possible benefit of the approach is reducing the potential for bias resulting from variation in practice for invasive monitoring of oxygenation.

RACHS - ANZ : A Modified Risk Adjustment in Congenital Heart Surgery Model for Outcome Surveillance in Australia and New Zealand.

Background Outcomes for pediatric cardiac surgery are commonly reported from international databases compiled from voluntary data submissions. Surgical outcomes for all children in a country or region are less commonly reported. We aimed to describe the bi-national population-based outcome for children undergoing cardiac surgery in Australia and New Zealand and determine whether the Risk Adjustment for Congenital Heart Surgery ( RACHS ) classification could be used to create a model that accurately predicts in-hospital mortality in this population. Methods and Results The study was conducted in all children's hospitals performing cardiac surgery in Australia and New Zealand between January 2007 and December 2015. The performance of the original RACHS -1 model was assessed and compared with an alternative RACHS - ANZ (Australia and New Zealand) model, developed balancing discrimination with parsimonious variable selection. A total of 14 324 hospital admissions were analyzed. The overall hospital mortality was 2.3%, ranging from 0.5% for RACHS category 1 procedures, to 17.0% for RACHS category 5 or 6 procedures. The original RACHS -1 model was poorly calibrated with death overpredicted (1161 deaths predicted, 289 deaths observed). The RACHS - ANZ model had better performance in this population with excellent discrimination (Az- ROC of 0.830) and acceptable Hosmer and Lemeshow goodness-of-fit ( P=0.216). Conclusions The original RACHS -1 model overpredicts mortality in children undergoing heart surgery in the current era. The RACHS - ANZ model requires only 3 risk variables in addition to the RACHS procedure category, can be applied to a wider range of patients than RACHS -1, and is suitable to use to monitor regional pediatric cardiac surgery outcomes.

Automated phenotyping for early vigour of field pea seedlings in controlled environment by colour imaging technology.

Early vigour of seedlings is a beneficial trait of field pea (Pisum sativum L.) that contributes to weed control, water use efficiency and is likely to contribute to yield under certain environments. Although breeding is considered the most effective approach to improve early vigour of field pea, the absence of a robust and high-throughput phenotyping tool to dissect this complex trait is currently a major obstacle of genetic improvement programs to address this issue. To develop this tool, separate trials on 44 genetically diverse field pea genotypes were conducted in the automated plant phenotyping platform of Plant Phenomics Victoria, Horsham and in the field, respectively. High correlation between estimated plant parameters derived from the automated phenotyping platform and important early vigour traits such as shoot biomass, leaf area and plant height indicated that the derived plant parameters can be used to predict vigour traits in field pea seedlings. Plant growth analysis demonstrated that the "broken-stick" model fitted well with the growth pattern of all field pea genotypes and can be used to determine the linear growth phase. Further analysis suggested that the estimated plant parameters collected at the linear growth phase can effectively differentiate early vigour across field pea genotypes. High correlation between normalised difference vegetation indices captured from the field trial and estimated shoot biomass and top-view area confirmed the consistent performance of early vigour field pea genotypes under controlled and field environments. Overall, our results demonstrated that this robust screening tool is highly applicable and will enable breeding programs to rapidly identify early vigour traits and utilise germplasm to contribute to the genetic improvement of field peas.

Genomic Prediction Using Prior Quantitative Trait Loci Information Reveals a Large Reservoir of Underutilised Blackleg Resistance in Diverse Canola (Brassica napus L.) Lines.

Genomic prediction is becoming a popular plant breeding method to predict the genetic merit of lines. While some genomic prediction results have been reported in canola, none have been evaluated for blackleg disease. Here, we report genomic prediction for seedling emergence, survival rate, and internal infection), using 532 Spring and Winter canola lines. These lines were phenotyped in two replicated blackleg disease nurseries grown at Wickliffe and Green Lake, Victoria, Australia. A transcriptome genotyping-by-sequencing approach revealed 98,054 single nucleotide polymorphisms (SNPs) after quality control. We assessed various genomic prediction scenarios based on Genomic Best Linear Unbiased Prediction (GBLUP), BayesR and BayesRC, which can make use of prior quantitative trait loci information, via cross-validation. Clustering based on genomic relationships showed that Winter and Spring lines were genetically distinct, indicating limited gene flow between sets. Genetic correlations within traits between Spring and Winter lines ranged from 0.68 and 0.90 (mean = 0.76). Based on GBLUP in the whole population, moderate to high genomic prediction accuracies were achieved within environments (0.35-0.74) and were reduced across environments (0.28-0.58). Prediction accuracy within the Spring set ranged from 0.30-0.69, and from 0.19-0.71 within the Winter set. The BayesR model resulted in slightly lower accuracy to GBLUP. The proportion of genetic variance explained by known blackleg quantitative trait loci (QTL) was < 30%, indicating that there is a large reservoir of genetic variation in blackleg traits that remains to be discovered, but can be captured with genomic prediction. However, providing prior information of known QTL in the BayesRC method resulted in an increased prediction accuracy for survival and internal infection, particularly with Spring lines. Overall, these promising results indicate that genomic prediction will be a valuable tool to make use of all genetic variation to improve blackleg resistance in canola.

A multiplex PCR for rapid identification of Brassica species in the triangle of U.

BACKGROUND: Within the Brassicaceae, six species from the genus Brassica are widely cultivated throughout the world as oilseed, condiment, fodder or vegetable crops. The genetic relationships among the six Brassica species are described by U's triangle model. Extensive shared traits and diverse morphotypes among Brassica species make identification and classification based on phenotypic data alone challenging and unreliable, especially when dealing with large germplasm collections. Consequently, a major issue for genebank collections is ensuring the correct identification of species. Molecular genotyping based on simple sequence repeat (SSR) marker sequencing or the Illumina Infinium Brassica napus 60K single nucleotide polymorphism (SNP) array has been used to identify species and assess genetic diversity of Brassica collections. However, these methods are technically challenging, expensive and time-consuming, making them unsuitable for routine or rapid screening of Brassica accessions for germplasm management. A cheaper, faster and simpler method for Brassica species identification is described here. RESULTS: A multiplex polymerase chain reaction (MPCR) consisting of new and existing primers specific to the Brassica A, B and C genomes was able to reliably distinguish all six Brassica species in the triangle of U with 16 control samples of known species identity. Further validation against 120 Brassica accessions previously genotyped showed that the MPCR is highly accurate and comparable to more advanced techniques such as SSR marker sequencing or the Illumina Infinium B. napus 60K SNP array. In addition, the MPCR was sensitive enough to detect seed contaminations in pooled seed samples of Brassica accessions. CONCLUSION: A cheap and fast multiplex PCR assay for identification of Brassica species in the triangle of U was developed and validated in this study. The MPCR assay can be readily implemented in any basic molecular laboratory and should prove useful for the management of Brassica germplasm collections in genebanks.

Burden of disease and change in practice in critically ill infants with bronchiolitis.

Bronchiolitis represents the most common cause of non-elective admission to paediatric intensive care units (ICUs).We assessed changes in admission rate, respiratory support, and outcomes of infants <24 months with bronchiolitis admitted to ICU between 2002 and 2014 in Australia and New Zealand.During the study period, bronchiolitis was responsible for 9628 (27.6%) of 34 829 non-elective ICU admissions. The estimated population-based ICU admission rate due to bronchiolitis increased by 11.76 per 100 000 each year (95% CI 8.11-15.41). The proportion of bronchiolitis patients requiring intubation decreased from 36.8% in 2002, to 10.8% in 2014 (adjusted OR 0.35, 95% CI 0.27-0.46), whilst a dramatic increase in high-flow nasal cannula therapy use to 72.6% was observed (p<0.001). We observed considerable variability in practice between units, with six-fold differences in risk-adjusted intubation rates that were not explained by ICU type, size, or major patient factors. Annual direct hospitalisation costs due to severe bronchiolitis increased to over USD30 million in 2014.We observed an increasing healthcare burden due to severe bronchiolitis, with a major change in practice in the management from invasive to non-invasive support that suggests thresholds to admittance of bronchiolitis patients to ICU have changed. Future studies should assess strategies for management of bronchiolitis outside ICUs.

Prediction of pediatric sepsis mortality within 1 h of intensive care admission.

PURPOSE: The definitions of sepsis and septic shock have recently been revised in adults, but contemporary data are needed to inform similar approaches in children. METHODS: Multicenter cohort study including children <16 years admitted with sepsis or septic shock to ICUs in Australia and New Zealand in the period 2012-2015. We assessed septic shock criteria at ICU admission to define sepsis severity, using 30-day mortality as outcome. Through multivariable logistic regression, a pediatric sepsis score was derived using variables available within 60 min of ICU admission. RESULTS: Of 42,523 pediatric admissions, 4403 children were admitted with invasive infection, including 1697 diagnosed as having sepsis/septic shock on admission. Mortality was 8.5% (144/1697) and 50.7% of deaths occurred within 48 h of admission. The presence of septic shock as defined by the 2005 consensus was sensitive but not specific in predicting mortality (AUC = 0.69; 95% CI 0.65-0.72). Combinations of hypotension, vasopressor therapy, and lactate >2 mmol/l discriminated poorly (AUC <0.60). Multivariate models showed that oxygenation markers, ventilatory support, hypotension, cardiac arrest, serum lactate, pupil responsiveness, and immunosuppression were the best-performing predictors (0.843; 0.811-0.875). We derived a pediatric sepsis score (0.817; 0.779-0.855), and every one-point increase was associated with a 28.5% (23.8-33.2%) increase in the odds of death. Children with a score ≥6 had 19.8% mortality and accounted for 74.3% of deaths. The sepsis score performed comparably when applied to all children admitted with invasive infection (0.810; 0.781-0.840). CONCLUSIONS: We observed mortality patterns specific to pediatric sepsis that support the need for specialized definitions of sepsis severity in children. We demonstrated the importance of lactate, cardiovascular, and respiratory derangements at ICU admission for the identification of children with substantially higher risk of sepsis mortality.

Improving Genetic Gain with Genomic Selection in Autotetraploid Potato.

Potato ( L.) breeders consider a large number of traits during cultivar development and progress in conventional breeding can be slow. There is accumulating evidence that some of these traits, such as yield, are affected by a large number of genes with small individual effects. Recently, significant efforts have been applied to the development of genomic resources to improve potato breeding, culminating in a draft genome sequence and the identification of a large number of single nucleotide polymorphisms (SNPs). The availability of these genome-wide SNPs is a prerequisite for implementing genomic selection for improvement of polygenic traits such as yield. In this review, we investigate opportunities for the application of genomic selection to potato, including novel breeding program designs. We have considered a number of factors that will influence this process, including the autotetraploid and heterozygous genetic nature of potato, the rate of decay of linkage disequilibrium, the number of required markers, the design of a reference population, and trait heritability. Based on estimates of the effective population size derived from a potato breeding program, we have calculated the expected accuracy of genomic selection for four key traits of varying heritability and propose that it will be reasonably accurate. We compared the expected genetic gain from genomic selection with the expected gain from phenotypic and pedigree selection, and found that genetic gain can be substantially improved by using genomic selection.

SNP-Based Linkage Mapping for Validation of QTLs for Resistance to Ascochyta Blight in Lentil.

Lentil (Lens culinaris Medik.) is a self-pollinating, diploid, annual, cool-season, food legume crop that is cultivated throughout the world. Ascochyta blight (AB), caused by Ascochyta lentis Vassilievsky, is an economically important and widespread disease of lentil. Development of cultivars with high levels of durable resistance provides an environmentally acceptable and economically feasible method for AB control. A detailed understanding of the genetic basis of AB resistance is hence highly desirable, in order to obtain insight into the number and influence of resistance genes. Genetic linkage maps based on single nucleotide polymorphisms (SNP) and simple sequence repeat (SSR) markers have been developed from three recombinant inbred line (RIL) populations. The IH × NF map contained 460 loci across 1461.6 cM, while the IH × DIG map contained 329 loci across 1302.5 cM and the third map, NF × DIG contained 330 loci across 1914.1 cM. Data from these maps were combined with a map from a previously published study through use of bridging markers to generate a consensus linkage map containing 689 loci distributed across seven linkage groups (LGs), with a cumulative length of 2429.61 cM at an average density of one marker per 3.5 cM. Trait dissection of AB resistance was performed for the RIL populations, identifying totals of two and three quantitative trait loci (QTLs) explaining 52 and 69% of phenotypic variation for resistance to infection in the IH × DIG and IH × NF populations, respectively. Presence of common markers in the vicinity of the AB_IH1- and AB_IH2.1/AB_IH2.2-containing regions on both maps supports the inference that a common genomic region is responsible for conferring resistance and is associated with the resistant parent, Indianhead. The third QTL was derived from Northfield. Evaluation of markers associated with AB resistance across a diverse lentil germplasm panel revealed that the identity of alleles associated with AB_IH1 predicted the phenotypic responses with high levels of accuracy (~86%), and therefore have the potential to be widely adopted in lentil breeding programs. The availability of RIL-based maps, a consensus map, and validated markers linked to AB resistance provide important resources for lentil improvement.