Enhanced Recovery after Elective Colorectal Surgery - Reasons for Non-Compliance with the Protocol.

Enhanced recovery after surgery (ERAS) protocols for elective colorectal surgery reduce the intensity of postoperative complications, hospital stays and costs. Improvements in clinical outcome are directly proportional to the adherence to the recommended pathway (compliance). The aim of the present study was to analyze reasons for the non-compliance of colorectal surgeries with the ERAS protocol. A consecutive cohort of patients undergoing elective colorectal surgery was prospectively analyzed with regards to the surgery's compliance with the ERAS protocol. The reason for every single protocol deviation was documented and the decision was categorized based on whether it was medically justified or not. During the 8-month study period, 76 patients were included. The overall compliance with 22 ERAS items was 76% (96% in the preoperative, 82% in the perioperative, and 63% in the postoperative period). The decision to deviate from the clinical pathway was mainly a medical decision, while patients and nurses were responsible in 26 and 14% of the cases, respectively. However, reasons for non-compliance were medically justified in 78% of the study participants. 'Non-compliance' with the ERAS protocol was observed mostly in the postoperative period. Most deviations from the pathway were decided by doctors and in a majority of cases it appeared that they were due to a medical necessity rather than non-compliance. However, almost a quarter of deviations that were absolutely required are still amenable to improvement

A ranking of hydrological signatures based on their predictability in space

Hydrological signatures are now used for a wide range of purposes, including catchment classification, process exploration and hydrological model calibration. The recent boost in the popularity and number of signatures has however not been accompanied by the development of clear guidance on signature selection. Here we propose that exploring the predictability of signatures in space provides important insights into their drivers, their sensitivity to data uncertainties, and is hence useful for signature selection. We use three complementary approaches to compare and rank 15 commonly‐used signatures, which we evaluate in 671 US catchments from the CAMELS data set (Catchment Attributes and MEteorology for Large‐sample Studies). Firstly, we employ machine learning (random forests) to explore how attributes characterizing the climatic conditions, topography, land cover, soil and geology influence (or not) the signatures. Secondly, we use simulations of a conceptual hydrological model (Sacramento) to benchmark the random forest predictions. Thirdly, we take advantage of the large sample of CAMELS catchments to characterize the spatial auto‐correlation (using Moran's I) of the signature field. These three approaches lead to remarkably similar rankings of the signatures. We show i) that signatures with the noisiest spatial pattern tend to be poorly captured by hydrological simulations, ii) that their relationship to catchments attributes are elusive (in particular they are not correlated to climatic indices) and iii) that they are particularly sensitive to discharge uncertainties. We suggest that a better understanding of their drivers and better characterization of their uncertainties would increase their value in hydrological studies

CAMELS-GB : a large sample, open-source, hydro-meteorological dataset for Great Britain

Data underpins our knowledge and understanding of the hydrological system; they are used to drive, test and evaluate hydrological models and advance our understanding of hydrological processes and dynamics. With the increasing availability of observational datasets, the integration of information from many catchments for data and modelling analyses is becoming increasingly common. The production of new, open source, datasets for large samples of catchments is vital to advance knowledge on hydrological processes and to ensure hydrological research is reusable and reproducible through the use of common datasets and code. However, the availability of open source, large-sample catchment datasets is notably sparse. In this study, we present CAMELS-GB, the first large sample, open-source, hydro-meteorological catchment dataset for Great Britain (GB). CAMELS-GB integrates a wealth of different datasets derived from national, continental and global products based on observational, satellite and modelled data. The dataset consists of hydro-meteorological timeseries, catchment attributes and catchment boundaries for >800 catchments that cover a wide range of climatic, hydrological, landscape and human management characteristics across GB. Long daily timeseries is provided for a range of hydro-meteorological data (including rainfall, potential-evapotranspiration, temperature, radiation, humidity and flow) from 1970-2015 covering several major hydrological events. A comprehensive set of catchment attributes are provided describing a range of catchment characteristics including topography, climate, hydrology, land cover, soils and (hydro)-geology. Importantly, we also derive human impact attributes (including abstraction returns, percentage urban and gauge distance from reservoir), as well as attributes describing the quality of the flow data (including discharge uncertainty estimates and out of bank flow). The dataset and code used to derive the data will be made open source and provided with comprehensive metadata to allow its use in a wide range of hydro-meteorological data and environmental modelling analyses

Prevalence and risk of Down syndrome in monozygotic and dizygotic multiple pregnancies in Europe: implications for prenatal screening.

OBJECTIVE: To determine risk of Down syndrome (DS) in multiple relative to singleton pregnancies, and compare prenatal diagnosis rates and pregnancy outcome. DESIGN: Population-based prevalence study based on EUROCAT congenital anomaly registries. SETTING: Eight European countries. POPULATION: 14.8 million births 1990-2009; 2.89% multiple births. METHODS: DS cases included livebirths, fetal deaths from 20 weeks, and terminations of pregnancy for fetal anomaly (TOPFA). Zygosity is inferred from like/unlike sex for birth denominators, and from concordance for DS cases. MAIN OUTCOME MEASURES: Relative risk (RR) of DS per fetus/baby from multiple versus singleton pregnancies and per pregnancy in monozygotic/dizygotic versus singleton pregnancies. Proportion of prenatally diagnosed and pregnancy outcome. STATISTICAL ANALYSIS: Poisson and logistic regression stratified for maternal age, country and time. RESULTS: Overall, the adjusted (adj) RR of DS for fetus/babies from multiple versus singleton pregnancies was 0.58 (95% CI 0.53-0.62), similar for all maternal ages except for mothers over 44, for whom it was considerably lower. In 8.7% of twin pairs affected by DS, both co-twins were diagnosed with the condition. The adjRR of DS for monozygotic versus singleton pregnancies was 0.34 (95% CI 0.25-0.44) and for dizygotic versus singleton pregnancies 1.34 (95% CI 1.23-1.46). DS fetuses from multiple births were less likely to be prenatally diagnosed than singletons (adjOR 0.62 [95% CI 0.50-0.78]) and following diagnosis less likely to be TOPFA (adjOR 0.40 [95% CI 0.27-0.59]). CONCLUSIONS: The risk of DS per fetus/baby is lower in multiple than singleton pregnancies. These estimates can be used for genetic counselling and prenatal screening

Implementation of the Enhanced Recovery After Surgery (ERAS®) program in neurosurgery.

Over the past decade, Enhanced Recovery After Surgery (ERAS®) guidelines have been proven to simplify postoperative care and improve recovery in several surgical disciplines. The authors set out to create and launch an ERAS® program for cranial neurosurgery that meets official ERAS® Society standards. The authors summarize the successive steps taken to achieve this goal in two specific neurosurgical conditions and describe the challenges they faced. Pituitary neuroendocrine tumors (Pit-NET) resected by a transsphenoidal approach and craniosynostosis (Cs) repair were selected as appropriate targets for the implementation of ERAS® program in the Department of Neurosurgery. A multidisciplinary team with experience in managing these pathologies was created. A specialized ERAS® nurse coordinator was hired. An ERAS® certification process was performed involving 4 seminars separated by 3 active phases under the supervision of an ERAS® coach. The ERAS® Pit-NET team included 8 active members. The ERAS® Cs team included 12 active members. Through the ERAS® certification process, areas for improvement were identified, local protocols were written, and the ERAS® program was implemented. Patient-centered strategies were developed to increase compliance with the ERAS® protocols. A prospective database was designed for ongoing program evaluation. Certification was achieved in 18 months. Direct costs and time requirements are reported. Successful ERAS® certification requires a committed multidisciplinary team, an ERAS® coach, and a dedicated nurse coordinator

Beta-Blocker Use in Pregnancy and Risk of Specific Congenital Anomalies: A European Case-Malformed Control Study.

The prevalence of chronic hypertension is increasing in pregnant women. Beta-blockers are among the most prevalent anti-hypertensive agents used in early pregnancy. The objective of this study was to investigate whether first-trimester use of beta-blockers increases the risk of specific congenital anomalies in offspring. A population-based case-malformed control study was conducted in 117,122 registrations of congenital anomalies from 17 European Concerted Action on Congenital Anomalies and Twins (EUROCAT) registries participating in EUROmediCAT with data for all or part of the period between 1995 and 2013. Associations previously reported in the literature (signals) were tested and an exploratory analysis was performed to identify new signals. Odds ratios of exposure to any beta-blocker or to a beta-blocker subgroup were calculated for each signal anomaly compared with two control groups (non-chromosomal, non-signal anomalies and chromosomal anomalies). The exploratory analyses were performed for each non-signal anomaly compared with all the other non-signal anomalies. The signals from the literature (congenital heart defects, oral clefts, neural tube defects and hypospadias) were not confirmed. Our exploratory analysis revealed that multi-cystic renal dysplasia had significantly increased odds of occurring after maternal exposure to combined alpha- and beta-blockers (adjusted odds ratio 3.8; 95% confidence interval 1.3-11.0). Beta-blocker use in the first trimester of pregnancy was not found to be associated with a higher risk of specific congenital anomalies in the offspring, but a new signal between alpha- and beta-blockers and multi-cystic renal dysplasia was found. Future large epidemiological studies are needed to confirm or refute our findings

NeuralHydrology -- Interpreting LSTMs in Hydrology

Despite the huge success of Long Short-Term Memory networks, their applications in environmental sciences are scarce. We argue that one reason is the difficulty to interpret the internals of trained networks. In this study, we look at the application of LSTMs for rainfall-runoff forecasting, one of the central tasks in the field of hydrology, in which the river discharge has to be predicted from meteorological observations. LSTMs are particularly well-suited for this problem since memory cells can represent dynamic reservoirs and storages, which are essential components in state-space modelling approaches of the hydrological system. On basis of two different catchments, one with snow influence and one without, we demonstrate how the trained model can be analyzed and interpreted. In the process, we show that the network internally learns to represent patterns that are consistent with our qualitative understanding of the hydrological system.Comment: Pre-print of published book chapter. See journal reference and DOI for more inf

Atrioventricular septal defects among infants in Europe: a population-based study of prevalence, associated anomalies, and survival.

OBJECTIVE: To describe the epidemiology of chromosomal and non-chromosomal cases of atrioventricular septal defects in Europe. METHODS: Data were obtained from EUROCAT, a European network of population-based registries collecting data on congenital anomalies. Data from 13 registries for the period 2000-2008 were included. RESULTS: There was a total of 993 cases of atrioventricular septal defects, with a total prevalence of 5.3 per 10,000 births (95% confidence interval 4.1 to 6.5). Of the total cases, 250 were isolated cardiac lesions, 583 were chromosomal cases, 79 had multiple anomalies, 58 had heterotaxia sequence, and 23 had a monogenic syndrome. The total prevalence of chromosomal cases was 3.1 per 10,000 (95% confidence interval 1.9 to 4.3), with a large variation between registers. Of the 993 cases, 639 cases were live births, 45 were stillbirths, and 309 were terminations of pregnancy owing to foetal anomaly. Among the groups, additional associated cardiac anomalies were most frequent in heterotaxia cases (38%) and least frequent in chromosomal cases (8%). Coarctation of the aorta was the most common associated cardiac defect. The 1-week survival rate for live births was 94%. CONCLUSION: Of all cases, three-quarters were associated with other anomalies, both chromosomal and non-chromosomal. For infants with atrioventricular septal defects and no chromosomal anomalies, cardiac defects were often more complex compared with infants with atrioventricular septal defects and a chromosomal anomaly. Clinical outcomes for atrioventricular septal defects varied between regions. The proportion of termination of pregnancy for foetal anomaly was higher for cases with multiple anomalies, chromosomal anomalies, and heterotaxia sequence

Surveillance of multiple congenital anomalies; searching for new associations

\ua9 2023, The Author(s).Many human teratogens are associated with a spectrum of congenital anomalies rather than a single defect, and therefore the identification of congenital anomalies occurring together more frequently than expected may improve the detection of teratogens. Thirty-two EUROCAT congenital anomaly registries covering 6,599,765 births provided 123,566 cases with one or more major congenital anomalies (excluding chromosomal and genetic syndromes) for the birth years 2008–2016. The EUROCAT multiple congenital anomaly algorithm identified 8804 cases with two or more major congenital anomalies in different organ systems, that were not recognized as part of a syndrome or sequence. For each pair of anomalies, the odds of a case having both anomalies relative to having only one anomaly was calculated and the p value was estimated using a two-sided Fisher’s exact test. The Benjamini–Hochberg procedure adjusted p values to control the false discovery rate and pairs of anomalies with adjusted p values < 0.05 were identified. A total of 1386 combinations of two anomalies were analyzed. Out of the 31 statistically significant positive associations identified, 20 were found to be known associations or sequences already described in the literature and 11 were considered “potential new associations” by the EUROCAT Coding and Classification Committee. After a review of the literature and a detailed examination of the individual cases with the anomaly pairs, six pairs remained classified as new associations. In summary, systematically searching for congenital anomalies occurring together more frequently than expected using the EUROCAT database is worthwhile and has identified six new associations that merit further investigation