Fertility and early pregnancy outcomes after conservative treatment for cervical intraepithelial neoplasia

BACKGROUND: Cervical intra-epithelial neoplasia (CIN) typically occurs in young women of reproductive age. Although several studies have reported the impact that cervical conservative treatment may have on obstetric outcomes, there is much less evidence for fertility and early pregnancy outcomes. OBJECTIVES: To assess the effect of cervical treatment for CIN (excisional or ablative) on fertility and early pregnancy outcomes. SEARCH METHODS: We searched in January 2015 the following databases: the Cochrane Gynaecological Cancer Specialised Register, Cochrane Central Register of Controlled Trials (CENTRAL; The Cochrane Library, Issue 12, 2014), MEDLINE (up to November week 3, 2014) and EMBASE (up to week 52, 2014). SELECTION CRITERIA: We included all studies reporting on fertility and early pregnancy outcomes (less than 24 weeks of gestation) in women with a history of CIN treatment (excisional or ablative) as compared to women that had not received treatment. DATA COLLECTION AND ANALYSIS: Studies were classified according to the treatment method used and the fertility or early pregnancy endpoint. Pooled risk ratios (RR) and 95% confidence intervals (CI) were calculated using a random-effects model and inter-study heterogeneity was assessed with I(2). Two review authors (MK, AM) independently assessed the eligibility of retrieved papers and risk of bias. The two review authors then compared their results and any disagreements were resolved by discussion. If still unresolved, a third review author (MA) was involved until consensus was reached. MAIN RESULTS: Fifteen studies (2,223,592 participants - 25,008 treated and 2,198,584 untreated) that fulfilled the inclusion criteria for this review were identified from the literature search. The meta-analysis demonstrated that treatment for CIN did not adversely affect the chances of conception. The overall pregnancy rate was higher for treated (43%) versus untreated women (38%; RR 1.29, 95% CI 1.02 to 1.64; 4 studies, 38,050 participants, very low quality), although the inter-study heterogeneity was considerable (P < 0.01). The pregnancy rates in treated and untreated women with an intention to conceive (88% versus 95%, RR 0.93, 95% CI 0.80 to 1.08; 2 studies, 70 participants, very low quality) and the number of women requiring more than 12 months to conceive (14% versus 9%, RR 1.45, 95% CI 0.89 to 2.37; 3 studies, 1348 participants, very low quality) were no different. Although the total miscarriage rate (4.6% versus 2.8%, RR 1.04, 95% CI 0.90 to 1.21; 10 studies, 39,504 participants, low quality) and first trimester miscarriage rate (9.8% versus 8.4%, RR 1.16, 95% CI 0.80 to 1.69, 4 studies, 1103 participants, low quality) was similar for treated and untreated women, CIN treatment was associated with an increased risk of second trimester miscarriage, (1.6% versus 0.4%, RR 2.60, 95% CI 1.45 to 4.67; 8 studies, 2,182,268 participants, low quality). The number of ectopic pregnancies (1.6% versus 0.8%, RR 1.89, 95% CI 1.50 to 2.39; 6 studies, 38,193 participants, low quality) and terminations (12.2% versus 7.4%, RR 1.71, 95% CI 1.31 to 2.22; 7 studies, 38,208 participants, low quality) were also higher in treated women.The results should be interpreted with caution. The included studies were often small with heterogenous design. Most of these studies were retrospective and of low or very low quality (GRADE assessment) and were therefore prone to bias. Subgroup analyses for the individual treatment methods and comparison groups and analysis to stratify for the cone length was not possible. AUTHORS' CONCLUSIONS: This meta-analysis suggests that treatment for CIN does not adversely affect fertility, although treatment was associated with an increased risk of miscarriage in the second trimester. These results should be interpreted with caution as the included studies were non-randomised and many were of low or very low quality and therefore at high risk of bias. Research should explore mechanisms that may explain the increase in mid-trimester miscarriage risk and stratify this impact of treatment by the length of the cone and the treatment method used

The risk stratification of adverse neonatal outcomes in women with gestational diabetes (STRONG) study

Aims: To assess the risk of adverse neonatal outcomes in women with gestational diabetes (GDM) by identifying subgroups of women at higher risk to recognize the characteristics most associated with an excess of risk. Methods: Observational, retrospective, multicenter study involving consecutive women with GDM. To identify distinct and homogeneous subgroups of women at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used. Overall, 2736 pregnancies complicated by GDM were analyzed. The main outcome measure was the occurrence of adverse neonatal outcomes in pregnancies complicated by GDM. Results: Among study participants (median age 36.8 years, pre-gestational BMI 24.8 kg/m2), six miscarriages, one neonatal death, but no maternal death was recorded. The occurrence of the cumulative adverse outcome (OR 2.48, 95% CI 1.59–3.87), large for gestational age (OR 3.99, 95% CI 2.40–6.63), fetal malformation (OR 2.66, 95% CI 1.00–7.18), and respiratory distress (OR 4.33, 95% CI 1.33–14.12) was associated with previous macrosomia. Large for gestational age was also associated with obesity (OR 1.46, 95% CI 1.00–2.15). Small for gestational age was associated with first trimester glucose levels (OR 1.96, 95% CI 1.04–3.69). Neonatal hypoglycemia was associated with overweight (OR 1.52, 95% CI 1.02–2.27) and obesity (OR 1.62, 95% CI 1.04–2.51). The RECPAM analysis identified high-risk subgroups mainly characterized by high pre-pregnancy BMI (OR 1.68, 95% CI 1.21–2.33 for obese; OR 1.38 95% CI 1.03–1.87 for overweight). Conclusions: A deep investigation on the factors associated with adverse neonatal outcomes requires a risk stratification. In particular, great attention must be paid to the prevention and treatment of obesity

Automated census record linking: a machine learning approach

Thanks to the availability of new historical census sources and advances in record linking technology, economic historians are becoming big data genealogists. Linking individuals over time and between databases has opened up new avenues for research into intergenerational mobility, assimilation, discrimination, and the returns to education. To take advantage of these new research opportunities, scholars need to be able to accurately and efficiently match historical records and produce an unbiased dataset of links for downstream analysis. I detail a standard and transparent census matching technique for constructing linked samples that can be replicated across a variety of cases. The procedure applies insights from machine learning classification and text comparison to the well known problem of record linkage, but with a focus on the sorts of costs and benefits of working with historical data. I begin by extracting a subset of possible matches for each record, and then use training data to tune a matching algorithm that attempts to minimize both false positives and false negatives, taking into account the inherent noise in historical records. To make the procedure precise, I trace its application to an example from my own work, linking children from the 1915 Iowa State Census to their adult-selves in the 1940 Federal Census. In addition, I provide guidance on a number of practical questions, including how large the training data needs to be relative to the sample.This research has been supported by the NSF-IGERT Multidisciplinary Program in Inequality & Social Policy at Harvard University (Grant No. 0333403)

Life Expectancy at Birth in Europe: An Econometric Approach Based on Random Forests Methodology

The objective of this work is to identify and classify the relative importance of several socioeconomic factors which explain life expectancy at birth in the European Union (EU) countries in the period 2008–2017, paying special attention to greenhouse gas emissions and public environmental expenditures. Methods: The Random Forests methodology was employed, which allows classification of the socioeconomic variables considered in the analysis according to their relative importance to explain health outcomes. Results: Per capita income, the educational level of the population, and the variable AREA (which reflects the subdivision of Europe into four relatively homogeneous areas), followed by the public expenditures on environmental and social protection, are the variables with the highest relevance in explaining life expectancy at birth in Europe over the perip.1 he peusto el correo e inciod 2008–2017. Conclusions: We have identified seven sectors as the main sources of greenhouse gas emissions: Electricity, gas, steam, and air conditioning supply; manufacturing; transportation and storage; agriculture, forestry, and fishing; construction; wholesale and retail trade, repair of motor vehicles and motorcycles; and mining and quarrying. Therefore, any public intervention related to environmental policy should be aimed at these economic sectors. Furthermore, it will be more effective to focus on public programs with higher relevance to the health status of the population, such as environmental and social protection expenditures

Socioeconomic Mediators of Racial and Ethnic Disparities in Congenital Heart Disease Outcomes: A Population-Based Study in California.

Background Racial/ethnic and socioeconomic disparities exist in outcomes for children with congenital heart disease. We sought to determine the influence of race/ethnicity and mediating socioeconomic factors on 1-year outcomes for live-born infants with hypoplastic left heart syndrome and dextro-Transposition of the great arteries. Methods and Results The authors performed a population-based cohort study using the California Office of Statewide Health Planning and Development database. Live-born infants without chromosomal anomalies were included. The outcome was a composite measure of mortality or unexpected hospital readmissions within the first year of life defined as &gt;3 (hypoplastic left heart syndrome) or &gt;1 readmissions (dextro-Transposition of the great arteries). Hispanic ethnicity was compared with non-Hispanic white ethnicity. Mediation analyses determined the percent contribution to outcome for each mediator on the pathway between race/ethnicity and outcome. A total of 1796 patients comprised the cohort (n=964 [hypoplastic left heart syndrome], n=832 [dextro-Transposition of the great arteries]) and 1315 were included in the analysis (n=477 non-Hispanic white, n=838 Hispanic). Hispanic ethnicity was associated with a poor outcome (crude odds ratio, 1.72; 95% confidence interval [CI], 1.37-2.17). Higher maternal education (crude odds ratio 0.5; 95% CI , 0.38-0.65) and private insurance (crude odds ratio, 0.65; 95% CI , 0.45-0.71) were protective. In the mediation analysis, maternal education and insurance status explained 33.2% (95% CI , 7-66.4) and 27.6% (95% CI , 6.5-63.1) of the relationship between race/ethnicity and poor outcome, while infant characteristics played a minimal role. Conclusions Socioeconomic factors explain a significant portion of the association between Hispanic ethnicity and poor outcome in neonates with critical congenital heart disease. These findings identify vulnerable populations that would benefit from resources to lessen health disparities

Feeding interventions for growth and development in infants with cleft lip, cleft palate or cleft lip and palate.

BACKGROUND: Cleft lip and cleft palate are common birth defects, affecting about one baby of every 700 born. Feeding these babies is an immediate concern and there is evidence of delay in growth of children with a cleft as compared to those without clefting. In an effort to combat reduced weight for height, a variety of advice and devices are recommended to aid feeding of babies with clefts. OBJECTIVES: This review aims to assess the effects of these feeding interventions in babies with cleft lip and/or palate on growth, development and parental satisfaction. SEARCH STRATEGY: The following electronic databases were searched: the Cochrane Oral Health Group Trials Register (to 27 October 2010), the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2010, Issue 4), MEDLINE via OVID (1950 to 27 October 2010), EMBASE via OVID (1980 to 27 October 2010), PsycINFO via OVID (1950 to 27 October 2010) and CINAHL via EBSCO (1980 to 27 October 2010). Attempts were made to identify both unpublished and ongoing studies. There was no restriction with regard to language of publication. SELECTION CRITERIA: Studies were included if they were randomised controlled trials (RCTs) of feeding interventions for babies born with cleft lip, cleft palate or cleft lip and palate up to the age of 6 months (from term). DATA COLLECTION AND ANALYSIS: Studies were assessed for relevance independently and in duplicate. All studies meeting the inclusion criteria were data extracted and assessed for validity independently by each member of the review team. Authors were contacted for clarification or missing information whenever possible. MAIN RESULTS: Five RCTs with a total of 292 babies, were included in the review. Comparisons made within the RCTs were squeezable versus rigid feeding bottles (two studies), breastfeeding versus spoon-feeding (one study) and maxillary plate versus no plate (two studies). No statistically significant differences were shown for any of the primary outcomes when comparing bottle types, although squeezable bottles were less likely to require modification. No difference was shown for infants fitted with a maxillary plate compared to no plate. However, there was some evidence of an effect on weight at 6 weeks post-surgery in favour of breastfeeding when compared to spoon-feeding (mean difference 0.47; 95% confidence interval 0.20 to 0.74). AUTHORS' CONCLUSIONS: Squeezable bottles appear easier to use than rigid feeding bottles for babies born with clefts of the lip and/or palate, however, there is no evidence of a difference in growth outcomes between the bottle types. There is weak evidence that breastfeeding is better than spoon-feeding following surgery for cleft. There was no evidence to suggest that maxillary plates assist growth in babies with clefts of the palate. No evidence was found to assess the use of any types of maternal advice and/or support for these babies

Feature extraction from electroencephalograms for Bayesian assessment of newborn brain maturity

We explored the feature extraction techniques for Bayesian assessment of EEG maturity of newborns in the context that the continuity of EEG is the most important feature for assessment of the brain development. The continuity is associated with EEG “stationarity” which we propose to evaluate with adaptive segmentation of EEG into pseudo-stationary intervals. The histograms of these intervals are then used as new features for the assessment of EEG maturity. In our experiments, we used Bayesian model averaging over decision trees to differentiate two age groups, each included 110 EEG recordings. The use of the proposed EEG features has shown, on average, a 6% increase in the accuracy of age differentiation

ASSESSMENT OF RISK IN PRETERM INFANTS USING POINT PROCESS AND MACHINE LEARNING APPROACHES

Preemies, infants who are born too soon, have a higher incidence of Life-Threatening Events (LTE’s) such as apnea (cessation of breathing), bradycardia (slowing of heart rate) and hypoxemia (oxygen desaturation) also termed as ABD (Apnea, Bradycardia, and Desaturation) events. Clinicians at Neonatal Intensive Care Units (NICU) are facing the demanding task of assessing the risk of infants based on their physiological signals. The aim of this thesis is to develop a risk stratification algorithm using a machine-learning framework with the features related to pathological fluctuations derived from point process model that will be embedded into the current physiological recording system to assess the risk of life-threatening events well in advance of occurrence in individual infants in the NICU. We initially propose a point process algorithm of heart rate dynamics for risk stratification of preterm infants. Based on this analysis, point process indices were tested to determine whether they were useful as precursors for life-threatening events. Finally, a machine-learning framework using point process indices as precursors were designed and tested to classify the risk of preterm infants. This work helps to predict the number of bradycardia events, N, in the subsequent hours measuring point process indices for the current hour. The model proposed uses Quadratic Support Vector Machine (QSVM), a machine learning classifier, which can solve class optimization problems and execute data at an exponential speed with higher accuracy for risk assessment that might facilitate effective management and treatment for preterm infants in NICU. The findings are relevant to risk assessment by analyzing the fluctuations in physiological signals that can act as precursors for the future life-threatening events