determine the level of services rather than to ration special services to particular patients, and it would be up to the government to decide the level of services offered to people.Smokers might argue that the revenue generated by their smoking sustains more than just the NHS budget.Secondly, failure rates derived by statistics do not apply to individual people.It is unethical to deny a patient the benefit of any treatment simply to reduce failure rates.Even the authors admit that the success rate of the operation is not spectacular.Probably there is a stronger case to look at the operation itself than at the imperfect people who have it.The third argument is that the damage caused by smoking is self inflicted.If we extend that argu- ment we might be tempted to deny services to people who do not adhere to a "healthy" lifestyle or strict medical advice; we would end up with an NHS treating only saints.
All women delivering for the first time between 1981and 2000 were linked to records of their second pregnancy usingroutinely collected data from the Scottish Morbidity Returns.Women who had an intrauterine death in their first pregnancyformed the exposed cohort, whereas those who had a live birthformed the unexposed cohort.
Background Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. Objectives To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers. Design This was an individual participant data meta-analysis of cohort studies. Setting Source data from secondary and tertiary care. Predictors We identified predictors from systematic reviews, and prioritised for importance in an international survey. Primary outcomes Early-onset (delivery at < 34 weeks’ gestation), late-onset (delivery at ≥ 34 weeks’ gestation) and any-onset pre-eclampsia. Analysis We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration. We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C -statistics of ≥ 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I 2 and τ 2 . A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals. Results The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models could be validated in 11 UK cohorts. Summary C -statistics were between 0.6 and 0.7 for most models, and calibration was generally poor owing to large between-study heterogeneity, suggesting model overfitting. The clinical utility of the models varied between showing net harm to showing minimal or no net benefit. The average discrimination for IPPIC models ranged between 0.68 and 0.83. This was highest for the second-trimester clinical characteristics and biochemical markers model to predict early-onset pre-eclampsia, and lowest for the first-trimester clinical characteristics models to predict any pre-eclampsia. Calibration performance was heterogeneous across studies. Net benefit was observed for International Prediction of Pregnancy Complications first and second-trimester clinical characteristics and clinical characteristics and biochemical markers models predicting any pre-eclampsia, when validated in singleton nulliparous women managed in the UK NHS. History of hypertension, parity, smoking, mode of conception, placental growth factor and uterine artery pulsatility index had the strongest unadjusted associations with pre-eclampsia. Limitations Variations in study population characteristics, type of predictors reported, too few events in some validation cohorts and the type of measurements contributed to heterogeneity in performance of the International Prediction of Pregnancy Complications models. Some published models were not validated because model predictors were unavailable in the individual participant data. Conclusion For models that could be validated, predictive performance was generally poor across data sets. Although the International Prediction of Pregnancy Complications models show good predictive performance on average, and in the singleton nulliparous population, heterogeneity in calibration performance is likely across settings. Future work Recalibration of model parameters within populations may improve calibration performance. Additional strong predictors need to be identified to improve model performance and consistency. Validation, including examination of calibration heterogeneity, is required for the models we could not validate. Study registration This study is registered as PROSPERO CRD42015029349. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment ; Vol. 24, No. 72. See the NIHR Journals Library website for further project information.
Abstract Background In high-income countries, stillbirth is a relatively rare event occurring in < 1% of pregnancies. Recurrent stillbirth is even rarer. Our objective was to explore the prevalence of stillbirth and recurrent stillbirth, factors associated with stillbirth and whether a stillbirth in first pregnancy influences the time to subsequent pregnancy. Methods This population-based study involved routinely-collected administrative data on singleton births in South Australia from 1998 to 2015 (n = 333,785). Stillbirth was defined as pregnancies >20 weeks gestation or weighing >400 grams. Univariable and multivariable logistic regression was used to explore associations between sociodemographic factors and stillbirth. Cox proportional hazard was used to explore time to pregnancy. Results 0.7% of all first pregnancies and 0.6% of all second pregnancies were stillbirths. Of women in their second pregnancy, <10 experienced recurrent stillbirth. In univariable analyses, higher odds of stillbirth in second pregnancies were associated with younger and older maternal age (<20 or ≥ 40 years), being single, unemployed, smoking, shorter inter-pregnancy intervals and numerous medical conditions (e.g. diabetes or hypertension). Multivariable models were unstable due to too few data. The hazard ratio for women who previously experienced a stillbirth compared with livebirth was 1.14 (95%CI 0.39, 3.32). Conclusions Studying recurrent stillbirth is especially difficult due to the rare nature of the problem, limiting progress on developing evidence-based advice for women who experience stillbirth in their first pregnancy. Key messages Recurrent stillbirth is challenging to study due to the rareness of the problem but could be addressed by careful pooling of large administrative datasets.
Abstract Study question Is in utero exposure to five over-the-counter (non-prescription) analgesics (paracetamol, ibuprofen, aspirin, diclofenac, naproxen) associated with offspring health outcomes? Summary answer Consumption of over-the-counter analgesics during pregnancy, either as single compounds or in combinations, is significantly associated with a variety of adverse offspring health outcomes. What is known already A high percentage of pregnant women use over-the-counter analgesics during pregnancy globally. Some of these compounds such as paracetamol are considered safe to use, while contraindications exist for others, such as NSAIDs use beyond gestational week 30. Current evidence regarding the safety of use during pregnancy in humans is largely conflicting. Results from many published human studies on the topic suffer from limitations including use of small cohorts, short study time or failure to adjust for important confounders. These may explain conflicting results that cause significant concern regarding evidence-based prenatal guidance on use during pregnancy. Study design, size, duration Retrospective cohort study using the Aberdeen Maternity and Neonatal Databank. Data from 151,141 singleton pregnancies over 30 years (between 1985 and 2015) were used. Consumption of paracetamol, ibuprofen, aspirin, diclofenac and naproxen during pregnancy was recorded in medical notes of each woman. In our analysis, the control group was pregnancies where no analgesic was consumed, and the exposure groups included pregnancies with over-the-counter analgesic consumption either in combinations or as single compound use. Participants/materials, setting, methods Maternal baseline characteristics were compared using χ2 tests for categorical variables and Mann-Whitney for continuous variables (significance at < 0.05). Premature delivery, stillbirth, neonatal death, baby weight, neonatal unit admission, APGAR score at 1 and 5 minutes, neural tube defects, amniotic band defects, gastroschisis, and, in males only, hypospadias and cryptorchidism, were the outcomes assessed. Crude (cORs) and adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were calculated using logistic regression to control for confounders. Main results and the role of chance The overall prevalence of over-the-counter analgesics use during pregnancy was 29.1%, increasing over the 30-year study period, to over 60% of women in the last seven years of the study. 83.7% of those women reported first trimester use when specifically asked at their first antenatal clinic visit. Pregnancies exposed to at least one of the five analgesics were independently associated with increased risks for premature delivery <37 weeks (aOR=1.50, 95%CI 1.43–1.58), stillbirth (aOR=1.33, 95%CI 1.15–1.54), neonatal death (aOR=1.56, 95%CI 1.27–1.93), birthweight <2,500g (aOR=1.28, 95%CI 1.20–1.37), birthweight >4,000g (aOR=1.09, 95%CI 1.05–1.13), admission to neonatal unit (aOR=1.57, 95%CI 1.51–1.64), APGAR score <7 at 1 minute (aOR=1.18, 95%CI 1.13–1.23) and 5 minutes (aOR=1.48, 95%CI 1.35–1.62), neural tube defects (aOR=1.64, 95%CI 1.08–2.47) and hypospadias (aOR=1.27, 95%CI 1.05–1.54 males only). ). Associations of paracetamol alone with high birth weight, neural tube defects and hypospadias were not significant in the adjusted analysis. Diclofenac consumption was associated with significantly decreased odds of stillbirth (aOR=0.59, 95%CI 0.41–0.87). Limitations, reasons for caution Our data were based on medical notes; however, consumption is self-reported, and details on the timing, dosage, product type (single-ingredient vs combination) and administration type were not available in the database. Our study only considered neonatal health outcomes and longer-term follow-up of the offspring was not available at this time. Wider implications of the findings: This is one of the largest and most comprehensive studies into analgesic use in pregnancy. The increased risks of adverse neonatal outcomes associated with non-prescribed, over-the-counter, analgesics use during pregnancy indicate that healthcare guidance for pregnant women regarding analgesic use should be re-assessed. Trial registration number N/A
Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model’s calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. PROSPERO ID: CRD42015029349
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Teenage pregnancy is a known social problem which has been previously described using a number of deprivation measures. This study aimed to explore the temporal patterns of teenage pregnancy in Aberdeen, Scotland and to assess the discriminating ability of three measures of socioeconomic status.This was a population-based study from 1950 to 2010, using data from the Aberdeen Maternity Neonatal Databank (AMND). The main outcome variable was conceptions occurring in women aged less than 20 years. This study used two area-based measures, the Scottish Index of Multiple Deprivation (SIMD) and the Carstairs index, and one individual-based measure the Social Class based on Occupation (SCO). These measures were compared for their association with teenage conceptions using logistic regression models. The models were used to determine receiver operating characteristic (ROC) curves showing the discriminating ability of the measures.There was an overall decline in teenage conceptions over the 60-year period, but an increase in the rate ratio for deprived areas. All the measures of socioeconomic status were highly associated with teenage pregnancy. The adjusted OR of SIMD and teenage conception was 5.72 (95% CI 4.62 to 7.09), which compared the most deprived decile with the least deprived decile. The use of ROC curves showed that socioeconomic measures performed better than chance at determining teenage conceptions (χ(2)=21.67, p≤0.0001). They further showed that the SIMD had the largest area under the curve (AUC) with a value of 0.81 (95% CI 0.80 to 0.82), followed by the Carstairs index with an AUC of 0.80 (95% CI 0.78 to 0.80), then by SCO with an AUC of 0.79 (95% CI 0.78 to 0.80).Despite a slight decline in teenage pregnancies over the past decades, there is still an evident association between deprivation and teenage pregnancy. This study shows that all the measures of socioeconomic status were highly associated with teenage pregnancy, with the SIMD having the greatest discriminatory effect.
To assess the risk of skin cancer in persons treated with neonatal phototherapy (NNPT) for jaundice.
Design
Retrospective cohort study.
Setting
Grampian Region, Scotland, UK.
Data source
Aberdeen Maternity and Neonatal Databank. NNPT exposure was abstracted from paper records spanning 1976–1990. Follow-up to 31 December 2006 by linkage to cancer registration and mortality records.
Main outcome measures
Incidence ratios, standardised for age, sex, calendar period and socio-economic position.
Results
After excluding neonatal deaths (n=435), the cohort comprised 77 518 persons. 5868 Received NNPT, providing 138 000 person-years at risk (median follow-up, 24 years). Two cases of melanoma occurred in persons exposed to NNPT versus 16 cases in unexposed persons, yielding a standardised incidence ratio of 1.40 (95% CI, 0.17 to 5.04; p=0.834). No cases of squamous cell or basal cell carcinoma of skin were observed in exposed persons.
Conclusions
Although there is no statistically significant evidence of an excess risk of skin cancer following NNPT, limited statistical power and follow-up duration mean it is not possible categorically to rule out an effect. However, taken in conjunction with the results of the only other study to investigate risk of melanoma following NNPT, evidence available so far does not suggest a major cause for concern.
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