119 research outputs found
Genotype-Phenotype Correlation in 153 Adult Patients With Congenital Adrenal Hyperplasia due to 21-Hydroxylase Deficiency: Analysis of the United Kingdom Congenital Adrenal Hyperplasia Adult Study Executive (CaHASE) Cohort
CONTEXT: In congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency, a strong genotype-phenotype correlation exists in childhood. However, similar data in adults are lacking. OBJECTIVE: The objective of the study was to test whether the severity of disease-causing CYP21A2 mutations influences the treatment and health status in adults with CAH. RESEARCH DESIGN AND METHODS: We analyzed the genotype in correlation with treatment and health status in 153 adults with CAH from the United Kingdom Congenital adrenal Hyperplasia Adult Study Executive cohort. RESULTS: CYP21A2 mutations were distributed similarly to previously reported case series. In 7 patients a mutation was identified on only 1 allele. Novel mutations were detected on 1.7% of alleles (5 of 306). Rare mutations were found on 2.3% of alleles (7 of 306). For further analysis, patients were categorized into CYP21A2 mutation groups according to predicted residual enzyme function: null (n = 34), A (n = 42), B (n = 36), C (n = 34), and D (n = 7). Daily glucocorticoid dose was highest in group null and lowest in group C. Fludrocortisone was used more frequently in patients with more severe genotypes. Except for lower female height in group B, no statistically significant associations between genotype and clinical parameters were found. Androgens, blood pressure, lipids, blood glucose, and homeostasis model assessment of insulin resistance were not different between groups. Subjective health status was similarly impaired across groups. CONCLUSIONS: In adults with classic CAH and women with nonclassic CAH, there was a weak association between genotype and treatment, but health outcomes were not associated with genotype. The underrepresentation of males with nonclassic CAH may reflect that milder genotypes result in a milder condition that is neither diagnosed nor followed up in adulthood. Overall, our results suggest that the impaired health status of adults with CAH coming to medical attention is acquired rather than genetically determined and therefore could potentially be improved through modification of treatment
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data
In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience
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Using Robson's Ten‐Group Classification System for comparing caesarean section rates in Europe: an analysis of routine data from the Euro‐Peristat study
Objective
Robson's Ten Group Classification System (TGCS) creates clinically relevant sub‐groups for monitoring caesarean birth rates. This study assesses whether this classification can be derived from routine data in Europe and uses it to analyse national caesarean rates.
Design
Observational study using routine data.
Setting
Twenty‐seven EU member states plus Iceland, Norway, Switzerland and the UK.
Population
All births at ≥22 weeks of gestational age in 2015.
Methods
National statistical offices and medical birth registers derived numbers of caesarean births in TGCS groups.
Main outcome measures
Overall caesarean rate, prevalence and caesarean rates in each of the TGCS groups.
Results
Of 31 countries, 18 were able to provide data on the TGCS groups, with UK data available only from Northern Ireland. Caesarean birth rates ranged from 16.1 to 56.9%. Countries providing TGCS data had lower caesarean rates than countries without data (25.8% versus 32.9%, P = 0.04). Countries with higher caesarean rates tended to have higher rates in all TGCS groups. Substantial heterogeneity was observed, however, especially for groups 5 (previous caesarean section), 6, 7 (nulliparous/multiparous breech) and 10 (singleton cephalic preterm). The differences in percentages of abnormal lies, group 9, illustrate potential misclassification arising from unstandardised definitions.
Conclusions
Although further validation of data quality is needed, using TGCS in Europe provides valuable comparator and baseline data for benchmarking and surveillance. Higher caesarean rates in countries unable to construct the TGCS suggest that effective routine information systems may be an indicator of a country's investment in implementing evidence‐based caesarean policies.
Tweetable abstract
Many European countries can provide Robson's Ten‐Group Classification to improve caesarean rate comparisons
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study.
OBJECTIVE: To generate a global reference for caesarean section (CS) rates at health facilities. DESIGN: Cross-sectional study. SETTING: Health facilities from 43 countries. POPULATION/SAMPLE: Thirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10,045,875 women giving birth from 43 countries for model testing. METHODS: We hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. MAIN OUTCOME MEASURES: Area under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. RESULTS: According to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (www.who.int/reproductivehealth/publications/maternal_perinatal_health/c-model/en/). CONCLUSIONS: This article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. TWEETABLE ABSTRACT: The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems
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