Perinatal and maternal health inequalities: effects of places of residence and delivery

In the Netherlands, perinatal mortality has declined substantially since 1920, although the rate of decline seemed to have levelled off from 1978 onwards. Last decades the decline was as not as steep as in other European countries. As a consequence the Netherlands dropped from a number two position in 1960 to one at the bottom in 2004 in the ranking of the European countries according to perinatal mortality rate. The same stagnating trend is observed for maternal mortality. We may expect that in the Netherlands, an egalitarian prosperous society with universal access to education and (perinatal) health care, health inequalities by area of residence will be limited. But geographical health differences in the Netherlands are persistent, and extend to perinatal health. Hence in the Netherlands, both the general level of perinatal mortality and its geographical distribution deserve attention. New evidence has emerged on (a) factors that may be responsible, among which factors related to obstetric care provision, and on (b) the interrelationships between these individual, geographic, and care-related, factors. This thesis aims to capture the origin of, in particular, the inequalities in perinatal- and maternal outcomes in the Netherlands in relation to socio-economic and ethnic factors, to the area of residence, and to care-related factors in terms of setting and organization. The studies, reported in this thesis, address the following questions: 1. To what extent do ethnic, socioeconomic and geographic related differences exist in adverse perinatal and maternal outcomes in the Netherlands? How are ethnic and socio-economic effects, if existent, related? 2. Do perinatal adverse outcomes in the Netherlands differ according to time of birth (day, evening, night), and hospital-organisational aspects such as the annual number of deliveries (volume) and staffing during and outside office hours? 3. Is intrapartum and early neonatal death different between planned home and planned hospital births in the Netherlands, for assumed low risk women starting delivery under supervision of a community midwife? 4. Can a scavenging system for nitrous oxide-sedation during labour be safe used in a midwifery-led birth centre

Separator fluid volume requirements in multi-infusion settings

INTRODUCTION. Intravenous (IV) therapy is a widely used method for the administration of medication in hospitals worldwide. ICU and surgical patients in particular often require multiple IV catheters due to incompatibility of certain drugs and the high complexity of medical therapy. This increases discomfort by painful invasive procedures, the risk of infections and costs of medication and disposable considerably. When different drugs are administered through the same lumen, it is common ICU practice to flush with a neutral fluid between the administration of two incompatible drugs in order to optimally use infusion lumens. An important constraint for delivering multiple incompatible drugs is the volume of separator fluid that is sufficient to safely separate them. OBJECTIVES. In this pilot study we investigated whether the choice of separator fluid, solvent, or administration rate affects the separator volume required in a typical ICU infusion setting. METHODS. A standard ICU IV line (2m, 2ml, 1mm internal diameter) was filled with methylene blue (40 mg/l) solution and flushed using an infusion pump with separator fluid. Independent variables were solvent for methylene blue (NaCl 0.9% vs. glucose 5%), separator fluid (NaCl 0.9% vs. glucose 5%), and administration rate (50, 100, or 200 ml/h). Samples were collected using a fraction collector until <2% of the original drug concentration remained and were analyzed using spectrophotometry. RESULTS. We did not find a significant effect of administration rate on separator fluid volume. However, NaCl/G5% (solvent/separator fluid) required significantly less separator fluid than NaCl/NaCl (3.6 ± 0.1 ml vs. 3.9 ± 0.1 ml, p <0.05). Also, G5%/G5% required significantly less separator fluid than NaCl/NaCl (3.6 ± 0.1 ml vs. 3.9 ± 0.1 ml, p <0.05). The significant decrease in required flushing volume might be due to differences in the viscosity of the solutions. However, mean differences were small and were most likely caused by human interactions with the fluid collection setup. The average required flushing volume is 3.7 ml. CONCLUSIONS. The choice of separator fluid, solvent or administration rate had no impact on the required flushing volume in the experiment. Future research should take IV line length, diameter, volume and also drug solution volumes into account in order to provide a full account of variables affecting the required separator fluid volume

ESICM LIVES 2017 : 30th ESICM Annual Congress. September 23-27, 2017.

INTRODUCTION. Unplanned readmission to intensive care is highly undesirable in that it contributes to increased variance in care, disruption, difficulty in resource allocation and may increase length of stay and mortality particularly if subject to delays. Unlike the ICU admission from the ward, readmission prediction has received relatively little attention, perhaps in part because at the point of ICU discharge, full physiological information is systematically available to the clinician and so it is expected that readmission should be largely due to unpredictable factors. However it may be that there are multidimensional trends that are difficult for the clinician to perceive that may nevertheless be predictive of readmission. OBJECTIVES. We investigated whether machine learning (ML) techniques could be used to improve on the simple published SWIFT score [1] for the prediction of unplanned readmission to ICU within 48 hours. METHODS. We extracted systolic BP, pulse pressure, heart and respiration rate, temperature, SpO2, bilirubin, creatinine, INR, lactate, white cell count, platelet count, pH, FiO2, and total Glasgow Coma Score from ICU stays of over 2000 adult patients from our hospital electronic patient record system. We trained our own custom multidimensional / time-sensitive algorithmic ML system to predict failed discharges defined as either readmission or unexpected death within 48 hours of discharge. We used 10-fold cross validation to assess performance. We also assessed the effect of augmenting our system by transfer learning (TL) with 44,000 additional cases from the MIMIC III database. RESULTS. The SWIFT score performed relatively poorly with an AUROC of around 0.6 which our ML system trained on local data was also able to match. However when augmented with an additional dataset by TL, the AUROC for the ML system improved statistically and clinically significantly to over 0.7. CONCLUSIONS. Machine learning is able to improve on predictors based on simple multiple logistic regression. Thus there is likely to be information in the trends and in combinations of variables. A disadvantage with this technique is that ML approaches require large amounts of data for training. However, ML approaches can be improved by TL. Basing prediction models on locally derived data augmented by TL is a potentially novel approach to generating tools that customised to the institution yet can exploit the potential power of ML algorithms. REFERENCES [1] Gajic O, Malinchoc M, Comfere TB, et al. The Stability and Workload Index for Transfer score predicts unplanned intensive care unit patient readmission: initial development and validation. Crit Care Med. 2008;36(3):676–82. Grant Acknowledgement This work was internally funded

Compendium of good practices : harnessing civil registration and vital statistics (CRVS) systems in conflict, emergencies, and fragile settings

The compendium’s collection of case studies and real-world examples targets a range of audiences. Civil Registration and Vital Statistics (CRVS) data are essential for informing policymakers as they address humanitarian crises, respond to emergencies, and provide for displaced populations. Even before the COVID-19 pandemic, displaced people and the stateless struggled to obtain legal identity and work permits and get access to formal employment and social safety nets. No country or statistical system has been left untouched by conflict, disease, and climate change impacts. This series of 12 papers is commissioned by diverse experts such as civil registrars, practitioners, and researchers.Global Affairs Canada (GAC

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii