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ObjectiveThere is a paucity of data relating to neurodevelopmental outcomes in infants born late and moderately preterm (LMPT; 32+0–36+6 weeks). This paper present the results of a prospective, population-based study of 2-year outcomes following LMPT birth.Design1130 LMPT and 1255 term-born children were recruited at birth. At 2 years corrected age, parents completed a questionnaire to assess neurosensory (vision, hearing, motor) impairments and the Parent Report of Children's Abilities-Revised to identify cognitive impairment. Relative risks for adverse outcomes were adjusted for sex, socio-economic status and small for gestational age, and weighted to account for over-sampling of term-born multiples. Risk factors for cognitive impairment were explored using multivariable analyses.ResultsParents of 638 (57%) LMPT infants and 765 (62%) controls completed questionnaires. Among LMPT infants, 1.6% had neurosensory impairment compared with 0.3% of controls (RR 4.89, 95% CI 1.07 to 22.25). Cognitive impairments were the most common adverse outcome: LMPT 6.3%; controls 2.4% (RR 2.09, 95% CI 1.19 to 3.64). LMPT infants were at twice the risk for neurodevelopmental disability (RR 2.19, 95% CI 1.27 to 3.75). Independent risk factors for cognitive impairment in LMPT infants were male sex, socio-economic disadvantage, non-white ethnicity, preeclampsia and not receiving breast milk at discharge.ConclusionsCompared with term-born peers, LMPT infants are at double the risk for neurodevelopmental disability at 2 years of age, with the majority of impairments observed in the cognitive domain. Male sex, socio-economic disadvantage and preeclampsia are independent predictors of low cognitive scores following LMPT birth.

ObjectivesTo investigate inequalities in stillbirth rates by ethnicity to facilitate development of initiatives to target those at highest risk.DesignPopulation-based perinatal mortality surveillance linked to national birth and death registration (Mothers and Babies: Reducing Risk through Audits and Confidential Enquiries across the UK).SettingUK.Participants4 391 569 singleton births at ≥24+0 weeks gestation between 2014 and 2019.Main outcome measuresStillbirth rate difference per 1000 total births by ethnicity.ResultsAdjusted absolute differences in stillbirth rates were higher for babies of black African (3.83, 95% CI 3.35 to 4.32), black Caribbean (3.60, 95% CI 2.65 to 4.55) and Pakistani (2.99, 95% CI 2.58 to 3.40) ethnicities compared with white ethnicities. Higher proportions of babies of Bangladeshi (42%), black African (39%), other black (39%) and black Caribbean (37%) ethnicities were from most deprived areas, which were associated with an additional risk of 1.50 stillbirths per 1000 births (95% CI 1.32 to 1.67). Exploring primary cause of death, higher stillbirth rates due to congenital anomalies were observed in babies of Pakistani, Bangladeshi and black African ethnicities (range 0.63–1.05 per 1000 births) and more placental causes in black ethnicities (range 1.97 to 2.24 per 1000 births). For the whole population, over 40% of stillbirths were of unknown cause; however, this was particularly high for babies of other Asian (60%), Bangladeshi (58%) and Indian (52%) ethnicities.ConclusionsStillbirth rates declined in the UK, but substantial excess risk of stillbirth persists among babies of black and Asian ethnicities. The combined disadvantage for black, Pakistani and Bangladeshi ethnicities who are more likely to live in most deprived areas is associated with considerably higher rates. Key causes of death were congenital anomalies and placental causes. Improved strategies for investigation of stillbirth causes are needed to reduce unexplained deaths so that interventions can be targeted to reduce stillbirths.

ObjectiveTo explore international variations in the management and survival of extremely low gestational age and birthweight births.DesignArea-based prospective cohort of birthsSetting12 regions across Belgium, France, Italy, Portugal and the UKParticipants1449 live births and fetal deaths between 22+0 and 25+6 weeks gestation born in 2011–2012.Main outcome measuresPercentage of births; recorded live born; provided antenatal steroids or respiratory support; surviving to discharge (with/without severe morbidities).ResultsThe percentage of births recorded as live born was consistently low at 22 weeks and consistently high at 25 weeks but varied internationally at 23 weeks for those weighing 500 g and over (range 33%–70%) and at 24 weeks for those under 500 g (range 5%–71%). Antenatal steroids and provision of respiratory support at 22–24 weeks gestation varied between countries, but were consistently high for babies born at 25 weeks. Survival to discharge was universally poor at 22 weeks gestation (0%) and at any gestation with birth weight <500 g, irrespective of treatment provision. In contrast, births at 23 and 24 weeks weighing 500 g and over showed significant international variation in survival (23 weeks: range: 0%–25%; 24 weeks range: 21%–50%), reflecting levels of treatment provision.ConclusionsWide international variation exists in the management and survival of extremely preterm births at 22–24 weeks gestation. Universally poor outcomes for babies at 22 weeks and for those weighing under 500 g suggest little impact of intervention and support the inclusion of birth weight along with gestational age in ethical decision-making guidelines.

ObjectiveIn the UK, 1 in 10 babies require specialist neonatal care. This care can last from hours to months depending on the need of the baby. The increasing survival of very preterm babies has increased neonatal care resource use. Evidence from multiple studies is crucial to identify factors which may be important for predicting length of stay (LOS). The ability to predict LOS is vital for resource planning, decision-making and parent counselling. The objective of this review was to identify which factors are important to consider when predicting LOS in the neonatal unit.DesignA systematic review was undertaken which searched MEDLINE, EMBASE and Scopus for papers from 1994 to 2016 (May) for research investigating prediction of neonatal LOS. Strict inclusion and exclusion criteria were applied. Quality of each study was discussed, but not used as a reason for exclusion from the review.Main outcome measurePrediction of LOS in the neonatal unit.Results9 studies were identified which investigated the prediction of neonatal LOS indicating a lack of evidence in the area. Inherent factors, particularly birth weight, sex and gestational age allow for a simple and objective prediction of LOS, which can be calculated on the first day of life. However, other early occurring factors may well also be important and estimates may need revising throughout the baby's stay in hospital.ConclusionsPredicting LOS is vital to aid the commissioning of services and to help clinicians in their counselling of parents. The lack of evidence in this area indicates a need for larger studies to investigate methods of accurately predicting LOS.

Objective To investigate regional variation in the registration of preterm births <24 weeks of gestation and the impact on infant death rates for English Primary Care Trusts (PCTs). Design Cohort study. Setting England. Participants All registered births (1 January 2005–31 December 2008) by gestational age and PCT (147 trusts) linked to infant deaths (up to 1 year of life). Late-fetal deaths at 22 and 23 weeks gestation (1 January 2005–31 December 2006). Main outcome measures Extremely preterm (<24 weeks) birth rate per 1000 live births and percentage of births registered as live born by PCT. Infant death rate and rank of mortality for (1) all live births and (2) live births over 24 weeks gestation by PCT. Results Wide between-PCT variation existed in extremely preterm birth (<24 weeks) rates (per 1000 births) (90% central range (0.31, 1.91)) and percentages of births <24 weeks of gestation registered as live born (median 52.6%, 90% central range (26.3%, 79.5%)). Consequently, the percentage of infant deaths arising from these births varied (90% central range (6.7%, 31.9%)). Excluding births <24 weeks, led to significant changes in infant mortality rankings of PCTs, with a median worsening of 12 places for PCTs with low rates of live born preterm births <24 weeks of gestation compared with a median improvement of four ranks for those with higher live birth registration rates. Conclusions Infant death rates in PCTs in England are influenced by variation in the registration of births where viability is uncertain. It is vital that this variation is minimised before infant mortality is used as indicator for monitoring health and performance and targeting interventions.

Background Emphasis is increasingly being placed on the monitoring of clinical outcomes for health care providers. Funnel plots have become an increasingly popular graphical methodology used to identify potential outliers. It is assumed that a provider only displaying expected random variation (i.e. ‘in-control’) will fall outside a control limit with a known probability. In reality, the discrete count nature of these data, and the differing methods, can lead to true probabilities quite different from the nominal value. This paper investigates the true probability of an ‘in control’ provider falling outside control limits for the Standardised Mortality Ratio (SMR). Methods The true probabilities of an ‘in control’ provider falling outside control limits for the SMR were calculated and compared for three commonly used limits: Wald confidence interval; ‘exact’ confidence interval; probability-based prediction interval. Results The probability of falling above the upper limit, or below the lower limit, often varied greatly from the nominal value. This was particularly apparent when there were a small number of expected events: for expected events ≤50 the median probability of an ‘in-control’ provider falling above the upper 95% limit was 0.0301 (Wald), 0.0121 (‘exact’), 0.0201 (prediction). Conclusions It is important to understand the properties and probability of being identified as an outlier by each of these different methods to aid the correct identification of poorly performing health care providers. The limits obtained using probability-based prediction limits have the most intuitive interpretation and their properties can be defined a priori. Funnel plot control limits for the SMR should not be based on confidence intervals.

Emphasis is increasingly being placed on the monitoring and comparison of clinical outcomes between healthcare providers. Funnel plots have become a standard graphical methodology to identify outliers and comprise plotting an outcome summary statistic from each provider against a specified 'target' together with upper and lower control limits. With discrete probability distributions it is not possible to specify the exact probability that an observation from an 'in-control' provider will fall outside the control limits. However, general probability characteristics can be set and specified using interpolation methods. Guidelines recommend that providers falling outside such control limits should be investigated, potentially with significant consequences, so it is important that the properties of the limits are understood. Control limits for funnel plots for the Standardised Mortality Ratio (SMR) based on the Poisson distribution were calculated using three proposed interpolation methods and the probability calculated of an 'in-control' provider falling outside of the limits. Examples using published data were shown to demonstrate the potential differences in the identification of outliers. The first interpolation method ensured that the probability of an observation of an 'in control' provider falling outside either limit was always less than a specified nominal probability (p). The second method resulted in such an observation falling outside either limit with a probability that could be either greater or less than p, depending on the expected number of events. The third method led to a probability that was always greater than, or equal to, p. The use of different interpolation methods can lead to differences in the identification of outliers. This is particularly important when the expected number of events is small. We recommend that users of these methods be aware of the differences, and specify which interpolation method is to be used prior to any analysis.

Objectives To evaluate the implementation of four high evidence practices for the care of very preterm infants to assess their use and impact in routine clinical practice and whether they constitute a driver for reducing mortality and neonatal morbidity.Design Prospective multinational population based observational study.Setting 19 regions from 11 European countries covering 850 000 annual births participating in the EPICE (Effective Perinatal Intensive Care in Europe for very preterm births) project.Participants 7336 infants born between 24+0 and 31+6 weeks’ gestation in 2011/12 without serious congenital anomalies and surviving to neonatal admission.Main outcome measures Combined use of four evidence based practices for infants born before 28 weeks’ gestation using an “all or none” approach: delivery in a maternity unit with appropriate level of neonatal care; administration of antenatal corticosteroids; prevention of hypothermia (temperature on admission to neonatal unit ≥36°C); surfactant used within two hours of birth or early nasal continuous positive airway pressure. Infant outcomes were in-hospital mortality, severe neonatal morbidity at discharge, and a composite measure of death or severe morbidity, or both. We modelled associations using risk ratios, with propensity score weighting to account for potential confounding bias. Analyses were adjusted for clustering within delivery hospital.Results Only 58.3% (n=4275) of infants received all evidence based practices for which they were eligible. Infants with low gestational age, growth restriction, low Apgar scores, and who were born on the day of maternal admission to hospital were less likely to receive evidence based care. After adjustment, evidence based care was associated with lower in-hospital mortality (risk ratio 0.72, 95% confidence interval 0.60 to 0.87) and in-hospital mortality or severe morbidity, or both (0.82, 0.73 to 0.92), corresponding to an estimated 18% decrease in all deaths without an increase in severe morbidity if these interventions had been provided to all infants.Conclusions More comprehensive use of evidence based practices in perinatal medicine could result in considerable gains for very preterm infants, in terms of increased survival without severe morbidity.

Objective To investigate temporal trends in multiple birth rates and associated stillbirth and neonatal mortality by socioeconomic deprivation and maternal age in England. Design Population cohort study. Setting England. Participants All live births and stillbirths (1 January 1997 to 31 December 2008). Main outcome measures Multiple maternity rate, stillbirth and neonatal death rate by year of birth, decile of socioeconomic deprivation and maternal age. Results The overall rate of multiple maternities increased over time (+0.64% per annum 95% CI (0.47% to 0.81%)) with an increase in twin maternities (+0.85% per annum 95% CI (0.67% to 1.0%)) but a large decrease in triplet and higher order maternities (−8.32% per annum 95% CI (−9.39% to −7.25%)). Multiple maternities were significantly lower in the most deprived areas, and this was most evident in the older age groups. Women over 40 years of age from the most deprived areas had a 34% lower rate of multiple births compared with similar aged women from the most deprived areas (rate ratio (RR) 0.66 95% CI (0.61 to 0.73)). Multiple births remain at substantially higher risk of neonatal mortality (RR 6.30 95% CI (6.07 to 6.53)). However, for stillbirths, while twins remain at higher risk, this has decreased over time (1997–2000: RR 2.89 (2.69 to 3.10); 2005–2008: RR 2.22 95% CI (2.06 to 2.40)). Socioeconomic inequalities existed in mortality for singletons and multiple births. Conclusions This period has seen increasing rates of twin pregnancies and decreasing rates of higher order births which have coincided with changes in recommendations regarding assisted reproductive techniques. Socioeconomic differences in multiple births may reflect differential access to these treatments. Improved monitoring of multiple pregnancies is likely to have led to the reductions in stillbirths over this time.

Modelling length of stay in neonatal care is vital to inform service planning and the counselling of parents. Preterm babies, at the highest risk of mortality, can have long stays in neonatal care and require high resource use. Previous work has incorporated babies that die into length of stay estimates, but this still overlooks the levels of care required during their stay. This work incorporates all babies, and the levels of care they require, into length of stay estimates. Data were obtained from the National Neonatal Research Database for singleton babies born at 24-31 weeks gestational age discharged from a neonatal unit in England from 2011 to 2014. A Cox multistate model, adjusted for gestational age, was used to consider a baby's two competing outcomes: death or discharge from neonatal care, whilst also considering the different levels of care required: intensive care; high dependency care and special care. The probabilities of receiving each of the levels of care, or having died or been discharged from neonatal care are presented graphically overall and adjusted for gestational age. Stacked predicted probabilities produced for each week of gestational age provide a useful tool for clinicians when counselling parents about length of stay and for commissioners when considering allocation of resources. Multistate modelling provides a useful method for describing the entire neonatal care pathway, where rates of in-unit mortality can be high. For a healthcare service focussed on costs, it is important to consider all babies that contribute towards workload, and the levels of care they require.