Abstract Background The choice of a hospital should be based on individual need and accessibility. For maternity hospitals, this includes known or expected risk factors, the geographic accessibility and level of care provided by the hospital. This study aims to identify factors influencing hospital choice with the aim to analyze if and how many deliveries are conducted in a risk-appropriate and accessible setting in Bavaria, Germany. Methods This is a cross-sectional secondary data analysis based on all first births in Bavaria (2015-18) provided by the Bavarian Quality Assurance Institute for Medical Care. Information on the mother and on the hospital were included. The Bavarian Index of Multiple Deprivation 2010 was used to account for area-level socioeconomic differences. Multiple logistic regression models were used to estimate the strength of association of the predicting factors and to adjust for confounding. Results We included 195,087 births. Distances to perinatal centers were longer than to other hospitals (16 km vs. 12 km). 10% of women with documented risk pregnancies did not deliver in a perinatal center. Regressions showed that higher age (OR 1.03; 1.02–1.03 95%-CI) and risk pregnancy (OR 1.44; 1.41–1.47 95%-CI) were associated with choosing a perinatal center. The distances travelled show high regional variation with a strong urban-rural divide. Conclusion In a health system with free choice of hospitals, many women chose a hospital close to home and/or according to their risks. However, this is not the case for 10% of mothers, a group that would benefit from more coordinated care.

AimTo describe the incidence of term and preterm neonatal cerebral sinovenous thrombosis (CSVT) and identify perinatal risk factors.MethodThis was a national capture‐recapture calculation‐corrected surveillance and nested case–control study. Infants born preterm and at term with magnetic resonance imaging‐confirmed neonatal CSVT were identified by surveillance in all paediatric hospitals in Germany (2015–2017). Incidence was corrected for underreporting using a capture‐recapture method in one federal state and then extrapolated nationwide. We reviewed PubMed for comparisons with previously reported incidence estimators. We used a population‐based perinatal database for quality assurance to select four controls per case and applied univariate and multivariable regression for risk factor analysis.ResultsFifty‐one newborn infants (34 males, 17 females; 14 born preterm) with neonatal CSVT were reported in the 3‐year period. The incidence of term and preterm neonatal CSVT was 6.6 (95% confidence interval [CI] 4.4–8.7) per 100 000 live births. Median age at time of confirmation of the diagnosis was 9.95 days (range 0–39d). In the univariate analysis, male sex, preterm birth, hypoxia and related indicators (umbilical artery pH <7.1; 5‐minute Apgar score <7; intubation/mask ventilation; perinatal asphyxia), operative vaginal delivery, emergency Caesarean section, and pathological fetal Doppler sonography were associated (p<0.05) with neonatal CSVT. Multivariable regression yielded hypoxia (odds ratio=20.3; 95% CI 8.1–50.8) as the independent risk factor.InterpretationIncidence of neonatal CSVT was within the range of other population‐based studies. The results suggest that hypoxia is an important perinatal risk factor for the aetiology of neonatal CSVT.

In 2007 the German government passed smoke-free legislation, leaving the details of implementation to the individual federal states. In January 2008 Bavaria implemented one of the strictest laws in Germany. We investigated its impact on pregnancy outcomes and applied an interrupted time series (ITS) study design to assess any changes in preterm birth, small for gestational age (primary outcomes), and low birth weight, stillbirth and very preterm birth. We included 1,236,992 singleton births, comprising 83,691 preterm births and 112,143 small for gestational age newborns. For most outcomes we observed unclear effects. For very preterm births, we found an immediate drop of 10.4% (95%CI − 15.8, − 4.6%; p = 0.0006) and a gradual decrease of 0.5% (95%CI − 0.7, − 0.2%, p = 0.0010) after implementation of the legislation. The majority of subgroup and sensitivity analyses confirm these results. Although we found no statistically significant effect of the Bavarian smoke-free legislation on most pregnancy outcomes, a substantial decrease in very preterm births was observed. We cannot rule out that despite our rigorous methods and robustness checks, design-inherent limitations of the ITS study as well as country-specific factors, such as the ambivalent German policy context have influenced our estimation of the effects of the legislation.

Perinatal mortality is a major population health indicator conveying important signals about the state of maternity care and measures of the current and future health of mothers and newborns. International comparisons are used to encourage countries to improve their perinatal health and health systems. However, extensive evidence highlights methodological challenges to ensuring valid and robust comparisons, as a lack of standardised criteria can lead to bias and inappropriate inferences.1 One major issue is the wide international variation in the criteria for classification and registration of deaths as a stillbirth or neonatal death at the threshold of survival.2-5 Standard practice is to minimise this problem by using a gestational age cut-off of 24 or even 28 weeks for mortality rate calculations. However, this strategy excludes a significant number of stillbirths, at least one in five deaths before 24 weeks of gestation and over one in three deaths before 28 weeks.6 As the gestational age limit for initiation of neonatal care decreases,7 exclusion of these stillbirths limits the full evaluation of care provision and outcomes at early gestational ages. Further, it underestimates the burden of loss on parents' mental and physical health.8, 9 To identify ways to improve the comparability of data on early gestational age births, a workshop was held in Kerkrade, the Netherlands (April 2018), by the Euro-Peristat network.10 This European collaboration of 31 countries was set up to monitor perinatal health internationally by developing a list of valid and reliable indicators. Workshop participants comprised statisticians from national birth and death registers, obstetricians, midwives, neonatologists, epidemiologists, and population health researchers (Appendix S1). Discussion in small groups about national practices was structured around clinical scenarios to raise awareness about how legal requirements and clinical management affect registration and recording of deaths. Scenarios focused on antepartum death and preterm rupture of membranes, and explored the impact of multiple pregnancy, termination of pregnancy, induction of labour, and assessment of signs of life on recorded outcomes (Box S1). Results of the discussions were synthesised through a plenary presentation and participants provided comments on a written summary of the findings. This commentary summarises the workshop discussion and makes recommendations for the reporting of births at the threshold of survival in Europe (Box 1) in light of the 2015 Canadian Consensus Conference, which explored improving fetal death registration procedures.11 Reporting rates of mortality (stillbirth and neonatal death) from 22 weeks' gestational age. Ability to exclude terminations of pregnancy. Ability to provide mortality rates by gestational age sub-groups. Recording of all births and deaths from at least 22 weeks' gestational age in vital statistics or medical birth registers. Recording of gestational age at birth for all births and deaths. Identification of and ability to exclude terminations of pregnancy at ≥22 weeks. Reporting mortality rates based on alternative denominators: all births, births alive at onset of labour, births surviving to 1 day of life. Use of a lower gestational age reporting threshold, at least 20 weeks. Identification of antepartum and intrapartum fetal deaths. Survival time of live births reported in hours. Reporting of all pregnancy outcomes from at least 20 weeks' gestational age. Use a combination of medical registers and official birth and death registrations for complete ascertainment of births and deaths, including sources such as registrations of terminations of pregnancy and births in gynaecology units and emergency departments. Include ICD10 cause of death and other clinical data from death certificates and medical or hospital registers to facilitate classification of deaths as intrapartum or antepartum deaths. Recording time of death in hours for all neonatal deaths. Lobby for consistent approach to registration and access to aid, leave, and services based on gestational age rather than signs of life. Establishment of guidelines to increase consistency in the assessment of signs of life at or before the threshold of survival to increase internationally consistency of operationalisation of the WHO definition of live birth. Consensus recommendations to achieve a full population cohort of all live births and stillbirths from 22 weeks' gestational age as recommended by WHO (https://icd.who.int/dev11/l-m/en#/http://id.who.int/icd/entity/914150644) as well as Euro-Peristat were discussed. This definition was seen as achievable in Europe, as most of the 31 participating countries register fetal deaths from 22 weeks' gestation and live births of any gestation. However, some countries still have higher gestational age thresholds for legal registration of fetal deaths (Bulgaria: 26 weeks, UK: 24 weeks, and Italy: 180 days). Some countries register fetal deaths based on birthweight criteria only or based on gestation but with a birthweight threshold of 500 g (Austria, Belgium, Czech Republic, Germany, and Poland) so births from 22 weeks' gestation below 500 g in weight are not systematically registered. In France, registration of stillbirths is voluntary from 15 weeks. One way to fill the gaps in statutory registration data is to use data from medical registers or other sources. For instance, data on stillbirths from 22 weeks are available in Italy via a spontaneous abortion register and in the UK through national perinatal mortality surveillance. In France, Euro-Peristat data come from administrative hospital data. These data sources make a full population cohort from 22 weeks achievable (see Smith et al.6 for available data used in Euro-Peristat). It was noted that comparability of data from 22 weeks' gestation is reliant on the ability to exclude deaths following termination of pregnancy from reported rates or at the bare minimum to acknowledge where registrations include terminations. These deaths have a different origin to other perinatal death and their inclusion significantly changes the population cohorts and consequently the rates of stillbirth at early gestational ages, especially before 24 weeks.12 In most countries where late terminations are legal, fetal deaths following termination of pregnancy are registered and can be distinguished (see Blondel et al.12 for further detail). In some countries, however, the definition of registrable fetal deaths excludes those following termination of pregnancy. Obtaining information on all fetal deaths from 20 weeks, as recommended in Canada,1 was regarded as much more challenging, but aspirational, as understanding a wider scope of pregnancy loss is important for improving reproductive outcomes. In most countries with later gestational age registration cut-offs, a combination of registration data with medical registers would be necessary to achieve this aim. There are major challenges to achieving complete ascertainment of these deaths, particularly for those occurring outside midwifery and obstetric units such as emergency or gynaecology departments. Participants discussed whether it would be possible to identify the gestational age at the time of fetal death rather than the timing of the birth, as suggested by the Canadian Consensus Conference.11 Only the UK reported collection of information on gestation when in utero death was confirmed, in addition to gestation at birth for fetal deaths as part of their national perinatal mortality surveillance. For other countries, identifying gestation at confirmation of death would mean the instigation of systems to collect this information from medical notes, as it is not available through registration or current electronic medical records. Furthermore, participants expressed concerns that even in medical notes, this information could be missing or unreliable. An alternative target, which would be more achievable but still challenging for many countries, is to distinguish between intrapartum and antepartum fetal deaths. This would facilitate identification of a population cohort of live births and fetal deaths where the baby is alive at the onset of the birth process. This information is available from registration data in some countries that have introduced specific death certificates for stillbirths or perinatal deaths (including Croatia, Estonia, Latvia, Lithuania, Norway, Spain [Valencia only], UK) which may have the potential to provide information to determine whether fetal deaths occurred in the antepartum or intrapartum period. This is not routinely collected in other countries but could potentially be obtained through medical records relating to the cause of death and reasons for induction of labour associated with antepartum fetal death. The variation in categorisation of deaths as a stillbirth or neonatal death has a major impact on estimation of both overall mortality2, 3 and gestation-specific mortality rates.13 Discussion highlighted differences in the interpretation of signs of life at the threshold of survival, despite general use of WHO guidelines based on vital signs of life. These differences were considered to be closely related to local views regarding initiation of neonatal care. Some countries (Luxembourg, Netherlands) highlighted that parents' wishes can be included in the decision whether a baby is reported as liveborn or not. Although most countries reported that guidelines existed in their country regarding initiation of neonatal intensive care for births at or before the threshold of survival, no country reported guidance that aided interpretation of the WHO definition of signs of life. In the UK, consensus guidelines are being developed regarding the assessment of signs of life to reduce national variation in practice. Such work at an international level was seen as challenging but aspirational. Further improvements in comparisons could be facilitated in the intermediate term by collecting information on the timing of fetal deaths as antepartum and intrapartum as discussed earlier and, in addition, information on the survival time of neonatal deaths and where they occurred (labour ward or neonatal unit). This would allow identification of babies with extremely short survival times on the labour ward and could facilitate alternative reliable and robust cohort definitions such as all births alive at onset of labour or births surviving more than 1 hour. Such a definition would overcome legal registration differences but impacts such as variation in the quality of data between hospitals and additional clinician workload need to be borne in mind. Clinicians and parents are often not aware of the overall consequences of registration of the baby as a live or stillbirth. Participants discussed the impact of legislation and other factors leading to differentials in access to maternity and paternity pay and leave, funeral costs, bereavement care, and official birth and death registration based on whether the death is reported as a stillbirth or neonatal death. For example, the requirement for a funeral differed for stillbirths and neonatal deaths, and in some countries this leads to a higher financial burden for parents in the case of neonatal death.14 Access to maternity and paternity pay and leave may be different based on the type of registration. For example, in the UK, parents of babies born before 24 weeks' gestation are only eligible for maternity or paternity leave if the baby is liveborn and so a clinician's decision to look for signs of life may be partially dependent on their awareness of this legal difference. The participants strongly felt that the effect on parents of losing a baby should be acknowledged irrespective of whether the baby was born showing no signs of life or was born alive but died soon after. There was a call for harmonisation of practices for these early deaths, both stillbirths and neonatal deaths, relating to maternity benefits, registration, and funerals. International agreement could potentially facilitate national changes to improve care and financial provision for parents in these cases. These impacts turn a clinical issue (i.e. when did the death occur) into a social one and national lobbying to attain policies that treated stillbirth in the same way as neonatal death was seen as essential by the participants. These changes could also improve the accuracy and consistency of reporting of births by vital status. Bringing together researchers, clinicians, policy makers, and registration specialists from across Europe confirmed continuing variation in birth and death registration at or before the threshold of survival in European countries. It highlighted subtle nuances in reporting practices that are frequently overlooked and unrecognised but which may have a significant impact on comparisons of mortality rates. This type of work was seen as vital to ensure that international comparisons are robust and valid, and prevent inappropriate conclusions regarding care provision, which may have considerable financial and social implications. The working group identified minimum and aspirational standards, which we hope, will guide initiatives to improve national reporting and facilitate enhanced international monitoring and comparisons, and ultimately lead to improvements in perinatal care. LS reports grants from NIHR during the conduct of the study. BB and JZ declare no competing interests. Completed disclosure of interest forms are available to view online as Supporting Information. LS, BB, and JZ contributed to the overall conception and design of the workshop. LS wrote the first draft of the manuscript. LS, BB, and JZ contributed to the drafting of the manuscript, and read and approved the final manuscript. LS is the guarantor. Not required. The Euro-Peristat project currently receives funding from the European Commission as part of the InfAct (Information for Action) Joint Action (Consumers, Health, Agriculture and Food Executive Agency (CHAFEA) Grant no. 801553). LKS is funded by a National Institute for Health Research Career Development Fellowship. This article presents independent research funded by the National Institute for Health Research (NIHR). The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR or the Department of Health and Social Care. We would like to thank everyone who attended the Euro-Peristat 'Registration of births and deaths at the limit of viability' workshop at Abdij Rolduc Abbey, Kerkrade, the Netherlands, for their participation and for reviewing the manuscript. Euro-Peristat Scientific Committee Members: Austria – Gerald Haidinger (The Medical University of Vienna, Vienna); Belgium – Sophie Alexander (Université Libre de Bruxelles, Brussels); Bulgaria – Rumyana Kolarova (National Centre of Public Health and Analyses, Sofia); Croatia – Urelija Rodin (Croatian National Institute of Public Health, Zagreb); Cyprus – Theopisti Kyprianou (Ministry of Health, Nicosia); Czech Republic – Petr Velebil (Institute for the Care of Mother and Child, Prague); Denmark – Laust Mortensen (University of Copenhagen, Copenhagen); Estonia – Luule Sakkeus (Tallinn University, Tallinn); Finland – Mika Gissler (National Institute for Health and Welfare, Helsinki); France – Béatrice Blondel (National Institute of Health and Medical Research [INSERM] U1153, Paris); Germany – Günther Heller (Federal Institute for Quality Assurance and Transparency in Healthcare, Berlin), Nicholas Lack (Bavarian Institute for Quality Assurance, Munich); Greece – Aris Antsaklis (University of Athens, Athens); Hungary – István Berbik (MedCongress Ltd, Budapest); Iceland – Helga Sól Ólafsdóttir (Landspitali University Hospital, Reykjavík); Ireland – Sheelagh Bonham (Healthcare Pricing Office, Dublin); Italy – Marina Cuttini (Bambino Gesù Children's Hospital, Rome); Latvia – Janis Misins (Centre for Disease Prevention and Control of Latvia, Rīga); Lithuania – Jelena Isakova (Health Information Centre, Vilnius); Luxembourg – Yolande Wagener (Ministry of Health, Luxembourg); Malta – Miriam Gatt (Department of Health Information and Research, G'Mangia); Netherlands – Jan Nijhuis (Maastricht University Medical Centre, Maastricht); Norway – Kari Klungsøyr (Department of Global Public Health and Primary Care, University of Bergen, Bergen); Poland – Katarzyna Szamotulska (National Research Institute of Mother and Child, Warsaw); Portugal – Henrique Barros (University of Porto, Porto); Romania – Mihai Horga (East European Institute for Reproductive Health, Tirgu Mures); Slovakia – Jan Cap (National Health Information Centre, Bratislava); Slovenia – Natasa Tul (Ljubljana University, Ljubljana); Spain – Francisco Bolúmar (University of Alcala, Madrid); Sweden – Karin Gottvall and Karin Källén (National Board of Health and Welfare, Stockholm); Switzerland – Sylvan Berrut, Mélanie Riggenbach (Swiss Federal Statistical Office, Neuchâtel); UK – Alison Macfarlane (City University London, London). Project coordination: France – Jennifer Zeitlin, Marie Delnord, Mélanie Durox (National Institute of Health and Medical Research [INSERM] U1153, Paris); Netherlands – Ashna Hindori-Mohangoo (Netherlands Organisation for Applied Scientific Research, Leiden). Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

BACKGROUND:Statistical Process Monitoring (SPM) is not typically used in traditional quality assurance of inpatient care. While SPM allows a rapid detection of performance deficits, SPM results strongly depend on characteristics of the evaluated process. When using SPM to monitor inpatient care, in particular the hospital risk profile, hospital volume and properties of each monitored performance indicator (e.g. baseline failure probability) influence the results and must be taken into account to ensure a fair process evaluation. Here we study the use of CUSUM charts constructed for a predefined false alarm probability within a single process, i.e. a given hospital and performance indicator. We furthermore assess different monitoring schemes based on the resulting CUSUM chart and their dependence on the process characteristics.METHODS:We conduct simulation studies in order to investigate alarm characteristics of the Bernoulli log-likelihood CUSUM chart for crude and risk-adjusted performance indicators, and illustrate CUSUM charts on performance data from the external quality assurance of hospitals in Bavaria, Germany.RESULTS:Simulating CUSUM control limits for a false alarm probability allows to control the number of false alarms across different conditions and monitoring schemes. We gained better understanding of the effect of different factors on the alarm rates of CUSUM charts. We propose using simulations to assess the performance of implemented CUSUM charts.CONCLUSIONS:The presented results and example demonstrate the application of CUSUM charts for fair performance evaluation of inpatient care. We propose the simulation of CUSUM control limits while taking into account hospital and process characteristics.

BACKGROUND:We investigated associations of area-level deprivation with obstetric and perinatal outcomes in a large population-based routine dataset.METHODS:We used the data of n = 827,105 deliveries who were born in hospitals between 2009 to 2016 in Bavaria, Germany. The Bavarian Index of Multiple Deprivation (BIMD) on district level was assigned to each mother by the zip code of her residential address. We calculated odds ratios (ORs) with 95% confidence intervals (CIs) for preterm deliveries, Caesarian sections (CS), stillbirths, small for gestational age (SGA) births and low 5-minute Apgar scores by BIMD quintiles with and without adjustment for potential confounders.RESULTS:We observed a significantly increased risk for preterm deliveries in mothers from the most deprived compared to the least deprived districts (e.g. OR [95% CI] for highest compared to lowest deprivation quintile: 1.06 [1.03, 1.09]) in adjusted analyses. Increased deprivation was also associated with higher SGA and secondary CS rates, but with lower proportions of stillbirths, primary CS and low Apgar scores. When one large clinic with an unusually high stillbirth rate was excluded, the association of BIMD with stillbirths was attenuated and almost disappeared.CONCLUSIONS:We found that area-level deprivation in Bavaria was positively associated with preterm and SGA births, confirming previous studies. In contrast, the finding of an inverse association between deprivation and both stillbirth rates and low Apgar score came somewhat surprising. However, we conclude that the stillbirths finding is spurious and reflects regional bias due to a clinic which seems to specialize in termination of pregnancies.

BJOG: An International Journal of Obstetrics & GynaecologyVolume 126, Issue 13 p. 1518-1522 Commentary Perinatal health monitoring through a European lens: eight lessons from the Euro-Peristat report on 2015 births J Zeitlin, Corresponding Author J Zeitlin Jennifer.zeitlin@inserm.fr orcid.org/0000-0002-9568-2969 Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, FranceCorrespondence: J Zeitlin, Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Centre for Epidemiology and Biostatistics, INSERM U1153, 53 avenue de l'Observatoire, 75014 Paris, France. Email: Jennifer.zeitlin@inserm.frSearch for more papers by this authorS Alexander, S Alexander Perinatal Epidemiology and Reproductive Health Unit, CR2, School of Public Health, ULB, Brussels, BelgiumSearch for more papers by this authorH Barros, H Barros ISPUP-EPIUnit, Universidade do Porto, Porto, PortugalSearch for more papers by this authorB Blondel, B Blondel Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, FranceSearch for more papers by this authorM Delnord, M Delnord Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, France Department of Epidemiology and Public Health, Sciensano, Brussels, BelgiumSearch for more papers by this authorM Durox, M Durox Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, FranceSearch for more papers by this authorM Gissler, M Gissler THL National Institute for Health and Welfare, Helsinki, Finland Karolinska Institute, Stockholm, SwedenSearch for more papers by this authorAD Hindori-Mohangoo, AD Hindori-Mohangoo Department Child Health, Netherlands Organisation for Applied Scientific Research, TNO Healthy Living, Leiden, the Netherlands Perinatal Interventions Suriname, Perisur Foundation, Paramaribo, Suriname School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USASearch for more papers by this authorA Hocquette, A Hocquette Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, FranceSearch for more papers by this authorK Szamotulska, K Szamotulska Department of Epidemiology and Biostatistics, National Research Institute of Mother and Child, Warsaw, PolandSearch for more papers by this authorA Macfarlane, A Macfarlane Centre for Maternal and Child Health Research, City, University of London, London, UKSearch for more papers by this authorfor the Euro-Peristat Scientific Committee, the Euro-Peristat Scientific Committee The Euro-Peristat Scientific Committee members are listed in Appendix 1.Search for more papers by this author J Zeitlin, Corresponding Author J Zeitlin Jennifer.zeitlin@inserm.fr orcid.org/0000-0002-9568-2969 Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, FranceCorrespondence: J Zeitlin, Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Centre for Epidemiology and Biostatistics, INSERM U1153, 53 avenue de l'Observatoire, 75014 Paris, France. Email: Jennifer.zeitlin@inserm.frSearch for more papers by this authorS Alexander, S Alexander Perinatal Epidemiology and Reproductive Health Unit, CR2, School of Public Health, ULB, Brussels, BelgiumSearch for more papers by this authorH Barros, H Barros ISPUP-EPIUnit, Universidade do Porto, Porto, PortugalSearch for more papers by this authorB Blondel, B Blondel Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, FranceSearch for more papers by this authorM Delnord, M Delnord Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, France Department of Epidemiology and Public Health, Sciensano, Brussels, BelgiumSearch for more papers by this authorM Durox, M Durox Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, FranceSearch for more papers by this authorM Gissler, M Gissler THL National Institute for Health and Welfare, Helsinki, Finland Karolinska Institute, Stockholm, SwedenSearch for more papers by this authorAD Hindori-Mohangoo, AD Hindori-Mohangoo Department Child Health, Netherlands Organisation for Applied Scientific Research, TNO Healthy Living, Leiden, the Netherlands Perinatal Interventions Suriname, Perisur Foundation, Paramaribo, Suriname School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USASearch for more papers by this authorA Hocquette, A Hocquette Inserm UMR 1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), DHU Risks in Pregnancy, Paris Descartes University, Paris, FranceSearch for more papers by this authorK Szamotulska, K Szamotulska Department of Epidemiology and Biostatistics, National Research Institute of Mother and Child, Warsaw, PolandSearch for more papers by this authorA Macfarlane, A Macfarlane Centre for Maternal and Child Health Research, City, University of London, London, UKSearch for more papers by this authorfor the Euro-Peristat Scientific Committee, the Euro-Peristat Scientific Committee The Euro-Peristat Scientific Committee members are listed in Appendix 1.Search for more papers by this author First published: 01 July 2019 https://doi.org/10.1111/1471-0528.15857Citations: 15 Linked article: This article is commented on by JN Robinson and RM Ryan, p. 1523 in this issue. To view this mini commentary visit https://doi.org/10.1111/1471-0528.15928. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume126, Issue13December 2019Pages 1518-1522 RelatedInformation

AimTo identify maternal, obstetric, and neonatal risk factors related to perinatal arterial ischaemic stroke (PAIS) diagnosed within 28 days after birth and to understand the underlying pathophysiology.MethodFor case and control ascertainment, we used active surveillance in 345 paediatric hospitals and a population‐based perinatal database for quality assurance of hospital care. We analysed complete cases of PAIS using logistic regression. Multivariate analysis was guided by a directed acyclic graph.ResultsAfter exclusion of records with missing data, we analysed 134 individuals with PAIS and 576 comparison individuals. In univariate analysis, male sex, preterm birth (<37wks gestational age), small for gestational age (SGA), low umbilical artery pH (<7.1), low 5‐minute‐Apgar score (<7), multiple pregnancies, hypoxia, intubation/mask ventilation, nulliparity, Caesarean section, vaginal‐operative delivery, chorioamnionitis, and oligohydramnios were associated with an increased risk. Mutual adjustment yielded male sex (odds ratio [OR] 1.81; 95% confidence interval [CI] 1.20–2.73), multiple birth (OR 3.22; 95% CI 1.21–8.58), chorioamnionitis (OR 9.89; 95% CI 2.88–33.94), preterm birth (OR 1.86; 95% CI 1.01–3.43), and SGA (OR 3.05; 95% CI 1.76–5.28) as independent risk factors.InterpretationWe confirmed the increased risk in males and the role of chorioamnionitis and SGA for PAIS, pointing to the importance of inflammatory processes and fetal–placental insufficiency. Multiple birth and preterm birth were additional risk factors.What this paper adds Chorioamnionitis and small for gestational age (SGA) precede perinatal arterial ischaemic stroke (PAIS). Chorioamnionitis and SGA are independent risk factors for PAIS. Inflammatory processes and fetal–placental insufficiency are the likely underlying mechanisms. Multiple birth and preterm birth are additional risk factors.

Gestational diabetes mellitus (GDM) occurs in 2–6 % of all pregnancies. We investigated whether area level deprivation is associated with a higher risk for GDM and whether GDM detection rates in deprived regions changed after the introduction of charge-free GDM screening in Germany in 2012.

BACKGROUND:Stillbirth and neonatal mortality rates declined in Europe between 2004 and 2010. We hypothesised that declines might be greater for countries with higher mortality in 2004 and disproportionally affect very preterm infants at highest risk. METHODS:Data about live births, stillbirths and neonatal deaths by gestational age (GA) were collected using a common protocol by the Euro-Peristat project in 2004 and 2010. We analysed stillbirths at ≥28 weeks GA in 22 countries and live births ≥24 weeks GA for neonatal mortality in 18 countries. Per cent changes over time were assessed by calculating risk ratios (RR) for stillbirth, neonatal mortality and preterm birth rates in 2010 vs 2004. We used meta-analysis techniques to derive pooled RR using random-effects models overall, by GA subgroups and by mortality level in 2004. RESULTS:Between 2004 and 2010, stillbirths declined by 17% (95% CI 10% to 23%), with a range from 1% to 39% by country. Neonatal mortality declined by 29% (95% CI 23% to 35%) with a range from 9% to 67%. Preterm birth rates did not change: 0% (95% CI -3% to 3%). Mortality declines were of a similar magnitude at all GA; mortality levels in 2004 were not associated with RRs. CONCLUSIONS:Stillbirths and neonatal deaths declined at all gestational ages in countries with both high and low levels of mortality in 2004. These results raise questions about how low-mortality countries achieve continued declines and highlight the importance of improving care across the GA spectrum.

Background: Current attempts at centralization of neonatal care in Germany focus on a minimum volume of 30 very-low-birth-weight (VLBW, weighing < 1250 g) neonate admissions per year. However, the evidence for a selective referral strategy based on hospital volume is unclear. Method: A total of 5575 neonates weighing < 1250 g treated in 31 hospitals in Bavaria between 2000 and 2011 were analysed using population-based data. The relevance of different hospital characteristics (i.e. hospital volume, bed capacity and teaching status) for explaining individual in-hospital mortality as well as interhospital variation in mortality rates was analysed using multilevel logistic regression analysis. Results: In a risk-adjusted model, only dichotomized hospital volume (< 30 admissions) was significantly associated with higher mortality in VLBW neonates (odds ratio: 1.74; 95% confidence interval: 1.02-2.99). However, the higher mortality risk only applied to neonates with higher Clinical Risk Index for Babies (CRIB) scores. There was considerable heterogeneity in mortality rates between Bavarian hospitals. The median odds ratio for mortality between two neonates treated in a randomly chosen low-performing versus high-performing hospital was 1.62 in the null model (without explanatory variables). Hospital volume only explained 15.1% of interhospital variation in mortality rates after adjustment for case-mix. Other hospital characteristics were of minor relevance. A funnel plot of the standardized mortality ratio against the number of admissions showed that 41% of small-volume hospitals performed better than expected. Conclusion: A selective referral strategy based solely on hospital volume will fall short of the task of optimal allocation of neonatal care by means of centralization.

While international variations in overall cesarean delivery rates are well documented, less information is available for clinical sub-groups. Cesarean data presented by subgroups can be used to evaluate uptake of cesarean reduction policies or to monitor delivery practices for high and low risk pregnancies based on new scientific evidence. We studied differences and patterns in cesarean delivery rates by multiplicity and gestational age in Europe and the United States.

Abstract Aims: Regional and interinstitutional variations have been recognized in the increasing incidence of caesarean section. Modes of birth after previous caesarean section vary widely, ranging from elective repeat caesarean section (ERCS) and unplanned repeat caesarean section (URCS) after trial of labour to vaginal birth after caesarean section (VBAC). This study describes interinstitutional variations in mode of birth after previous caesarean section in relation to regional indicators in Germany. Material and methods: A cross-sectional study using the birth registers of six maternity units (n=12,060) in five different German states (n=370,209). Indicators were tested by χ2 and relative deviations from regional values were expressed as relative risks and 95% confidence intervals. Results: The percentages of women in the six units with previous caesarean section ranged from 11.9% to 15.9% (P=0.002). VBAC was planned for 36.0% to 49.8% (P=0.003) of these women, but actually completed in only 26.2% to 32.8% (P=0.66). Depending on the indicator, the units studied deviated from the regional data by up to 32% [relative risk 0.68 (0.47–0.97)] in respect of completed VBAC among all initiated VBAC. Conclusions: There is substantial interinstitutional variation in mode of birth following previous caesarean section. This variation is in addition to regional patterns.

BACKGROUNDTabulating annual national health indicators sorted by outcome may be misleading for two reasons. The implied rank order is largely a result of heterogeneous population sizes. Distinctions between geographically adjacent regions are not visible.METHODSRegional data are plotted in a geographical map shaded in terms of percentiles of the indicator value. Degree of departure is determined relative to control limits of a corresponding funnel plot. Five methods for displaying outcome and degree of departure from a reference level are proposed for four indicators selected from the 2004 European Perinatal Health Report.RESULTSSpread of indicator values was generally largest for small population sizes, with results for large populations lying mostly close to respective European medians. The high neonatal mortality rate for Poland (4.9 per 1000); high low-birthweight rates for England and Wales (7.8%), Germany (7.3%) and Estonia (4.5%); and high caesarean section rates for Italy (37.8%), Poland (26.3%), Portugal (33.1%) and Germany (27.3%) were statistically significant exceptions to this pattern. Estonia also showed an extreme result for maternal mortality (29.6 per 100 000).CONCLUSIONExtreme deviations from EU reference levels are either correlated with small population sizes or may be interpreted in terms of differing medical practices, as in the case of caesarean section rate. EURO-PERISTAT has now decided to use 5-year averages for maternal mortality to reduce the variance in outcome. Use of two colours in three intensities and solid fill versus crosshatching is best suited to display rate and significance of difference.

Judging the effectiveness of external quality assurance programmes by comparing current performance with unadjusted regional or national crude averages is misleading because the influence of the actual size of the populations under consideration as well as the variance of performance between hospitals is underestimated. Not only do these arte-facts lead to a general overestimation of changes in regional averages. They also may lead to a ranking confounded by regional size. An assessment at unit level circumvents these difficulties. The differential grading of degree of departure of a unit's performance from national targets available from funnel plots allows, in addition, for the discrimination between effects due to the monitoring institution and achievements attributable to the hospital under surveillance. A central role is played by the scoring system adopted for evaluating incremental changes of performance indicator values in successive years. The following proposal is intended to both assist the assessment of effectiveness of quality assurance programmes and identify areas requiring urgent improvement. Bavarian quality assurance data (BAQ 1995) are used to illustrate the method.

Data about deliveries, births, mothers and newborn babies are collected extensively to monitor the health and care of mothers and babies during pregnancy, delivery and the post-partum period, but there is no common approach in Europe. We analysed the problems related to using the European data for international comparisons of perinatal health. We made an inventory of relevant data sources in 25 European Union (EU) member states and Norway, and collected perinatal data using a previously defined indicator list. The main sources were civil registration based on birth and death certificates, medical birth registers, hospital discharge systems, congenital anomaly registers, confidential enquiries and audits. A few countries provided data from routine perinatal surveys or from aggregated data collection systems. The main methodological problems were related to differences in registration criteria and definitions, coverage of data collection, problems in combining information from different sources, missing data and random variation for rare events. Collection of European perinatal health information is feasible, but the national health information systems need improvements to fill gaps. To improve international comparisons, stillbirth definitions should be standardised and a short list of causes of fetal and infant deaths should be developed.

OBJECTIVE: To compare the risk for pregnancy outcomes by gestational weight gain with the Institute of Medicine criteria and empirically established average ranges of gestational weight gain. METHODS: In a population-based data set comprising 678,560 singleton deliveries in Bavarian obstetric units from 2000 to 2007, we calculated the prevalence of adverse short-term pregnancy outcomes within the gestational weight-gain ranges recommended by the Institute of Medicine. We then compared these for gestational weight gain within data-based interquartile ranges (25th to 75th percentile) and interdecile ranges (10th to 90th percentile) of gestational weight gain by maternal weight category (underweight, normal weight, overweight, and obese). RESULTS: In underweight and normal-weight mothers, adherence to Institute of Medicine criteria was significantly associated with fewer preterm deliveries and small-for-gestational-age births (prevalence [95% confidence interval] for preterm delivery in normal-weight women: 5.33 [5.23-5.43] within Institute of Medicine criteria compared with 5.45 [5.36-5.54] in interquartile range). Overweight and obese mothers gaining weight within the Institute of Medicine recommendations had less preeclampsia and nonelective caesarean deliveries but had higher risks for gestational diabetes, small-for-gestational-age births, preterm delivery, and perinatal mortality compared with gestational weight gain within the respective interquartile ranges and interdecile ranges (prevalence for preterm delivery in overweight women: 8.14% [7.87-8.42] within Institute of Medicine criteria compared with 5.77% [5.60-5.93] in interquartile range). CONCLUSION: Although underweight and normal-weight women should be encouraged to aim for a gestational weight gain according to Institute of Medicine guidelines, different gestational weight gain recommendations in overweight and obese women might lessen some adverse short-term pregnancy outcomes. LEVEL OF EVIDENCE: II

Aims: To assess temporal trends in birth weight and pregnancy weight gain in Bavaria from 2000 to 2007.Methods: Data on 695,707 mother and infant pairs (singleton term births) were available from a compulsory reporting system for quality assurance, including information on birth weight, maternal weight at delivery and at booking, maternal smoking, age, and further anthropometric and lifestyle factors. Pregnancy weight gain was defined as: weight prior to delivery minus weight at first booking minus weight of the newborn.Results: Although mean weight gain during pregnancy increased considerably from 10.10 to 10.73 kg in seven years, the mean birth weight in mature singletons decreased slightly from 3433 to 3414 g. These trends could not be explained by concurrent changes in the rates of primiparity, smoking and gestational diabetes.Conclusions: These German data confirm an increased weight gain during pregnancy with adjustment for potential confounders.

BACKGROUND Gestational weight gain (GWG) has been shown to be directly associated with birth weight. OBJECTIVE We aimed to define ranges for optimal GWG with respect to the risk of either small- or large-for-gestational-age offspring by using a new statistical approach. DESIGN For the purpose of an observational study, data on n = 177,079 mature singleton deliveries in Bavaria between 2004 and 2006 were extracted from a standard data set that is regularly collected for national benchmarking of obstetric units in terms of clinical performance. Joint predicted risks of either small- or large-for-gestational-age births in relation to GWG (continuous measurement) were estimated by logistic regression models with adjustment for potential confounders. RESULTS The estimated optimal GWG ranges as defined by a joint predicted risk of <or=20% were substantially wider than those recommended by the Institute of Medicine for underweight (8-25 compared with 12.5-18.0 kg) and normal-weight (2-18 compared with 11.5-16.0 kg) women. Overweight and obese women's optimal GWG ranged from -7 to 12 and -15 to 2 kg, respectively (Institute of Medicine recommendations: 7.0-11.5 and 5.0-9.0 kg, respectively). We observed considerable effect modifications by parity and smoking in pregnancy. In normal-weight primiparae, for example, the optimal GWG range was 10-26 kg for nonsmokers compared with 23-27 kg for smokers. CONCLUSIONS Considerably wider optimal GWG ranges than recommended by the Institute of Medicine might be tolerated with respect to avoidance of adverse birth weight outcome. Stratification by maternal body mass index category alone might not be sufficient.