Death and Emergency Readmission of Infants Discharged After Interventions for Congenital Heart Disease: A National Study of 7643 Infants to Inform Service Improvement.

Improvements in hospital-based care have reduced early mortality in congenital heart disease. Later adverse outcomes may be reducible by focusing on care at or after discharge. We aimed to identify risk factors for such events within 1 year of discharge after intervention in infancy and, separately, to identify subgroups that might benefit from different forms of intervention.Cardiac procedures performed in infants between 2005 and 2010 in England and Wales from the UK National Congenital Heart Disease Audit were linked to intensive care records. Among 7976 infants, 333 (4.2%) died before discharge. Of 7643 infants discharged alive, 246 (3.2%) died outside the hospital or after an unplanned readmission to intensive care (risk factors were age, weight-for-age, cardiac procedure, cardiac diagnosis, congenital anomaly, preprocedural clinical deterioration, prematurity, ethnicity, and duration of initial admission; c-statistic 0.78 [0.75-0.82]). Of the 7643, 514 (6.7%) died outside the hospital or had an unplanned intensive care readmission (same risk factors but with neurodevelopmental condition and acquired cardiac diagnosis and without preprocedural deterioration; c-statistic 0.78 [0.75-0.80]). Classification and regression tree analysis were used to identify 6 subgroups stratified by the level (3-24%) and nature of risk for death outside the hospital or unplanned intensive care readmission based on neurodevelopmental condition, cardiac diagnosis, congenital anomaly, and duration of initial admission. An additional 115 patients died after planned intensive care admission (typically following elective surgery).Adverse outcomes in the year after discharge are of similar magnitude to in-hospital mortality, warrant service improvements, and are not confined to diagnostic groups currently targeted with enhanced monitoring

Definition of important early morbidities related to paediatric cardiac surgery

BACKGROUND: Morbidity is defined as a state of being unhealthy or of experiencing an aspect of health that is "generally bad for you", and postoperative morbidity linked to paediatric cardiac surgery encompasses a range of conditions that may impact the patient and are potential targets for quality assurance. METHODS: As part of a wider study, a multi-disciplinary group of professionals aimed to define a list of morbidities linked to paediatric cardiac surgery that was prioritised by a panel reflecting the views of both professionals from a range of disciplines and settings as well as parents and patients. RESULTS: We present a set of definitions of morbidity for use in routine audit after paediatric cardiac surgery. These morbidities are ranked in priority order as acute neurological event, unplanned re-operation, feeding problems, the need for renal support, major adverse cardiac events or never events, extracorporeal life support, necrotising enterocolitis, surgical site of blood stream infection, and prolonged pleural effusion or chylothorax. It is recognised that more than one such morbidity may arise in the same patient and these are referred to as multiple morbidities, except in the case of extracorporeal life support, which is a stand-alone constellation of morbidity. CONCLUSIONS: It is feasible to define a range of paediatric cardiac surgical morbidities for use in routine audit that reflects the priorities of both professionals and parents. The impact of these morbidities on the patient and family will be explored prospectively as part of a wider ongoing, multi-centre study

Ethnic-specific mortality of infants undergoing congenital heart surgery in England and Wales

Purpose: To investigate ethnic differences in mortality for infants with congenital heart defects (CHDs) undergoing cardiac surgery or interventional catheterisation. Design: Observational study of survival to age 1 year using linked records from routine national paediatric cardiac surgery and intensive care audits. Mortality risk was investigated using multivariable Poisson models with multiple imputation. Predictors included sex, ethnicity, preterm birth, deprivation, comorbidities, prenatal diagnosis, age and weight at surgery, preprocedure deterioration and cardiac diagnosis. Setting: All paediatric cardiac surgery centres in England and Wales. Patients: 5350 infants with CHDs born from 2006 to 2009. Main outcome measure: Survival at age 1 year. Results: Mortality was 83.9 (95% CI 76.3 to 92.1) per 1000 infants, with variation by ethnic group. Compared with those of white ethnicity, infants in British Asian (Indian, Pakistani and Bangladeshi) and ‘all other’ (Chinese, mixed and other) categories experienced significantly higher mortality by age 1 year (relative risk [RR] 1.52[95% CI 1.19 to 1.95]; 1.62[95% CI 1.20 to 2.20], respectively), specifically during index hospital admission (RR 1.55 [95% CI 1.07 to 2.26]; 1.64 [95% CI 1.05 to 2.57], respectively). Further predictors of mortality included non-cardiac comorbidities, prenatal diagnosis, older age at surgery, preprocedure deterioration and cardiac diagnosis. British Asian infants had higher mortality risk during elective hospital readmission (RR 1.86 [95% CI 1.02 to 3.39]). Conclusions: Infants of British Asian and ‘all other’ non-white ethnicity experienced higher postoperative mortality risk, which was only partly explained by socioeconomic deprivation and access to care. Further investigation of case-mix and timing of risk may provide important insights into potential mechanisms underlying ethnic disparities

Quality assurance in psychiatry: quality indicators and guideline implementation

In many occasions, routine mental health care does not correspond to the standards that the medical profession itself puts forward. Hope exists to improve the outcome of severe mental illness by improving the quality of mental health care and by implementing evidence-based consensus guidelines. Adherence to guideline recommendations should reduce costly complications and unnecessary procedures. To measure the quality of mental health care and disease outcome reliably and validly, quality indicators have to be available. These indicators of process and outcome quality should be easily measurable with routine data, should have a strong evidence base, and should be able to describe quality aspects across all sectors over the whole disease course. Measurement-based quality improvement will not be successful when it results in overwhelming documentation reducing the time for clinicians for active treatment interventions. To overcome difficulties in the implementation guidelines and to reduce guideline non-adherence, guideline implementation and quality assurance should be embedded in a complex programme consisting of multifaceted interventions using specific psychological methods for implementation, consultation by experts, and reimbursement of documentation efforts. There are a number of challenges to select appropriate quality indicators in order to allow a fair comparison across different approaches of care. Carefully used, the use of quality indicators and improved guideline adherence can address suboptimal clinical outcomes, reduce practice variations, and narrow the gap between optimal and routine care

A computational model of excitation and contraction in uterine myocytes from the pregnant rat

Aberrant uterine myometrial activities in humans are major health issues. However, the cellular and tissue mechanism(s) that maintain the uterine myometrium at rest during gestation, and that initiate and maintain long-lasting uterine contractions during delivery are incompletely understood. In this study we construct a computational model for describing the electrical activity (simple and complex action potentials), intracellular calcium dynamics and mechanical contractions of isolated uterine myocytes from the pregnant rat. The model reproduces variant types of action potentials – from spikes with a smooth plateau, to spikes with an oscillatory plateau, to bursts of spikes – that are seen during late gestation under different physiological conditions. The effects of the hormones oestradiol (via reductions in calcium and potassium selective channel conductance), oxytocin (via an increase in intracellular calcium release) and the tocolytic nifedipine (via a block of L-type calcium channels currents) on action potentials and contractions are also reproduced, which quantitatively match to experimental data. All of these results validated the cell model development. In conclusion, the developed model provides a computational platform for further investigations of the ionic mechanism underlying the genesis and control of electrical and mechanical activities in the rat uterine myocytes

Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.

Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and poor versus good early language outcome. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in vivo window into identifying brain-relevant molecular mechanisms in ASD

Prioritization and Evaluation of Depression Candidate Genes by Combining Multidimensional Data Resources

Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results. There is a strong need to review and integrate multi-dimensional data for follow up validation. The present study aimed to apply prioritization procedures to build-up an evidence-based candidate genes dataset for depression.Depression candidate genes were collected in human and animal studies across various data resources. Each gene was scored according to its magnitude of evidence related to depression and was multiplied by a source-specific weight to form a combined score measure. All genes were evaluated through a prioritization system to obtain an optimal weight matrix to rank their relative importance with depression using the combined scores. The resulting candidate gene list for depression (DEPgenes) was further evaluated by a genome-wide association (GWA) dataset and microarray gene expression in human tissues.A total of 5,055 candidate genes (4,850 genes from human and 387 genes from animal studies with 182 being overlapped) were included from seven data sources. Through the prioritization procedures, we identified 169 DEPgenes, which exhibited high chance to be associated with depression in GWA dataset (Wilcoxon rank-sum test, p = 0.00005). Additionally, the DEPgenes had a higher percentage to express in human brain or nerve related tissues than non-DEPgenes, supporting the neurotransmitter and neuroplasticity theories in depression.With comprehensive data collection and curation and an application of integrative approach, we successfully generated DEPgenes through an effective gene prioritization system. The prioritized DEPgenes are promising for future biological experiments or replication efforts to discover the underlying molecular mechanisms for depression

Assessing the presence of shared genetic architecture between Alzheimer's disease and major depressive disorder using genome-wide association data

We are grateful to the families and individuals who took part in the GS:SFHS and UKB studies, and to all those involved in participant recruitment, data collection, sample processing and QC, including academic researchers, clinical staff, laboratory technicians, clerical workers, IT staff, statisticians and research managers. This work is supported by the Wellcome Trust through a Strategic Award, reference 104036/Z/ 14/Z. We acknowledge with gratitude the financial support received from the Dr Mortimer and Theresa Sackler Foundation. This research has been conducted using the GS:SFHS and UK Biobank (project #4844) resources. GS:SFHS received core funding from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. UKB was established using funding from the Wellcome Trust, Medical Research Council, the Scottish Government Department of Health, and the Northwest Regional Development Agency. DJP, IJD, TCR and AMM are members of the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1). TCR is supported by Alzheimer's Scotland, through the Marjorie MacBeath bequest. Funding from the Biotechnology and Biological Sciences Research Council and Medical Research Council is gratefully acknowledged. We are grateful for the use of summary data from the International Genomics of Alzheimer's Project and the Major Depressive Disorder working group of the Psychiatric Genomics Consortium.Peer reviewedPublisher PD

Genetic risk profiles for depression and anxiety in adult and elderly cohorts

The first generation of genome-wide association studies (GWA studies) for psychiatric disorders has led to new insights regarding the genetic architecture of these disorders. We now start to realize that a larger number of genes, each with a small contribution, are likely to explain the heritability of psychiatric diseases. The contribution of a large number of genes to complex traits can be analyzed with genome-wide profiling. In a discovery sample, a genetic risk profile for depression was defined based on a GWA study of 1738 adult cases and 1802 controls. The genetic risk scores were tested in two population-based samples of elderly participants. The genetic risk profiles were evaluated for depression and anxiety in the Rotterdam Study cohort and the Erasmus Rucphen Family (ERF) study. The genetic risk scores were significantly associated with different measures of depression and explained up to ∼0.7% of the variance in depression in Rotterdam Study and up to ∼1% in ERF study. The genetic score for depression was also significantly associated with anxiety explaining up to 2.1% in Rotterdam study. These findings suggest the presence of many genetic loci of small effect that influence both depression and anxiety. Remarkably, the predictive value of these profiles was as large in the sample of elderly participants as in the middle-aged samples