Size Matters: Comparing the MDMA content and weight of ecstasy tablets submitted to European drug checking services in 2012-2021

Purpose The 3,4-methylenedioxymetamphetamine (MDMA) content in ecstasy tablets has increased enormously throughout Europe across the past decade. This study aims to determine whether this is caused by the production of “stronger” tablets (more mg MDMA per mg of tablet), or if tablets have simply been getting larger and heavier (more mg of tablet in total). Design/methodology/approach A data set of 31,716 ecstasy tablets obtained in 2012–2021 by 10 members of the Trans European Drug Information (TEDI) network was analysed. Findings The MDMA mass fraction in ecstasy tablets has remained virtually unchanged over the past 10 years, with increased MDMA contents being attributed almost exclusively to increased tablet weight. These trends seem to be uniform across Europe, despite varying sampling and analytical techniques being used by the TEDI participants. The study also shows that while tablet weight correlates perfectly with MDMA content on a yearly basis, wide variations in the MDMA mass fraction make such relations irrelevant for determining the MDMA content of individual tablets. Research limitations/implications These results provide new opportunities for harm reduction, given that size is a tangible and apparently accurate characteristic to emphasise that one tablet does not simply equate to one dose. This is particularly useful for harm reduction services without the resources for in-house quantification of large numbers of ecstasy tablets, although the results of this study also show that chemical analysis remains crucial for accurate personalised harm reduction. Originality/value The findings are both new and pertinent, providing a novel insight into the market dynamics of ecstasy tablet production at a transnational level

Variations in Multiple Birth Rates and Impact on Perinatal Outcomes in Europe

Objective Infants from multiple pregnancies have higher rates of preterm birth, stillbirth and neonatal death and differences in multiple birth rates (MBR) exist between countries. We aimed to describe differences in MBR in Europe and to investigate the impact of these differences on adverse perinatal outcomes at a population level. Methods We used national aggregate birth data on multiple pregnancies, maternal age, gestational age (GA), stillbirth and neonatal death collected in the Euro-Peristat project (29 countries in 2010, N = 5 074 643 births). We also used European Society of Human Reproduction and Embryology (ESHRE) data on assisted conception and single embryo transfer (SET). The impact of MBR on outcomes was studied using meta-analysis techniques with random-effects models to derive pooled risk ratios (pRR) overall and for four groups of country defined by their MBR. We computed population attributable risks (PAR) for these groups. Results In 2010, the average MBR was 16.8 per 1000 women giving birth, ranging from 9.1 (Romania) to 26.5 (Cyprus). Compared to singletons, multiples had a nine-fold increased risk (pRR 9.4, 95% Cl 9.1–9.8) of preterm birth (<37 weeks GA), an almost 12-fold increased risk (pRR 11.7, 95% CI 11.0–12.4) of very preterm birth (<32 weeks GA). Pooled RR were 2.4 (95% Cl 1.5–3.6) for fetal mortality at or after 28 weeks GA and 7.0 (95% Cl 6.1–8.0) for neonatal mortality. PAR of neonatal death and very preterm birth were higher in countries with high MBR compared to low MBR (17.1% (95% CI 13.8–20.2) versus 9.8% (95% Cl 9.6–11.0) for neonatal death and 29.6% (96% CI 28.5–30.6) versus 17.5% (95% CI 15.7–18.3) for very preterm births, respectively). Conclusions Wide variations in MBR and their impact on population outcomes imply that efforts by countries to reduce MBR could improve perinatal outcomes, enabling better long-term child health

Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier

Cross-Country Individual Participant Analysis of 4.1 Million Singleton Births in 5 Countries with Very High Human Development Index Confirms Known Associations but Provides No Biologic Explanation for 2/3 of All Preterm Births.

BACKGROUND: Preterm birth is the most common single cause of perinatal and infant mortality, affecting 15 million infants worldwide each year with global rates increasing. Understanding of risk factors remains poor, and preventive interventions have only limited benefit. Large differences exist in preterm birth rates across high income countries. We hypothesized that understanding the basis for these wide variations could lead to interventions that reduce preterm birth incidence in countries with high rates. We thus sought to assess the contributions of known risk factors for both spontaneous and provider-initiated preterm birth in selected high income countries, estimating also the potential impact of successful interventions due to advances in research, policy and public health, or clinical practice. METHODS: We analyzed individual patient-level data on 4.1 million singleton pregnancies from four countries with very high human development index (Czech Republic, New Zealand, Slovenia, Sweden) and one comparator U.S. state (California) to determine the specific contribution (adjusting for confounding effects) of 21 factors. Both individual and population-attributable preterm birth risks were determined, as were contributors to cross-country differences. We also assessed the ability to predict preterm birth given various sets of known risk factors. FINDINGS: Previous preterm birth and preeclampsia were the strongest individual risk factors of preterm birth in all datasets, with odds ratios of 4.6-6.0 and 2.8-5.7, respectively, for individual women having those characteristics. In contrast, on a population basis, nulliparity and male sex were the two risk factors with the highest impact on preterm birth rates, accounting for 25-50% and 11-16% of excess population attributable risk, respectively (p<0.001). The importance of nulliparity and male sex on population attributable risk was driven by high prevalence despite low odds ratios for individual women. More than 65% of the total aggregated risk of preterm birth within each country lacks a plausible biologic explanation, and 63% of difference between countries cannot be explained with known factors; thus, research is necessary to elucidate the underlying mechanisms of preterm birth and, hence, therapeutic intervention. Surprisingly, variation in prevalence of known risk factors accounted for less than 35% of the difference in preterm birth rates between countries. Known risk factors had an area under the curve of less than 0.7 in ROC analysis of preterm birth prediction within countries. These data suggest that other influences, as yet unidentified, are involved in preterm birth. Further research into biological mechanisms is warranted. CONCLUSIONS: We have quantified the causes of variation in preterm birth rates among countries with very high human development index. The paucity of explicit and currently identified factors amenable to intervention illustrates the limited impact of changes possible through current clinical practice and policy interventions. Our research highlights the urgent need for research into underlying biological causes of preterm birth, which alone are likely to lead to innovative and efficacious interventions

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