Temporal changes in key maternal and fetal factors affecting birth outcomes: A 32-year population-based study in an industrial city

<p>Abstract</p> <p>Background</p> <p>The link between maternal factors and birth outcomes is well established. Substantial changes in society and medical care over time have influenced women's reproductive choices and health, subsequently affecting birth outcomes. The objective of this study was to describe temporal changes in key maternal and fetal factors affecting birth outcomes in Newcastle upon Tyne over three decades, 1961–1992.</p> <p>Methods</p> <p>For these descriptive analyses we used data from a population-based birth record database constructed for the historical cohort <b>Pa</b>rticulate <b>M</b>atter and <b>P</b>erinatal <b>E</b>vents <b>R</b>esearch (PAMPER) study. The PAMPER database was created using details from paper-based hospital delivery and neonatal records for all births during 1961–1992 to mothers resident in Newcastle (out of a total of 109,086 singleton births, 97,809 hospital births with relevant information). In addition to hospital records, we used other sources for data collection on births not included in the delivery and neonatal records, for death and stillbirth registrations and for validation.</p> <p>Results</p> <p>The average family size decreased mainly due to a decline in the proportion of families with 3 or more children. The distribution of mean maternal ages in all and in primiparous women was lowest in the mid 1970s, corresponding to a peak in the proportion of teenage mothers. The proportion of older mothers declined until the late 1970s (from 16.5% to 3.4%) followed by a steady increase. Mean birthweight in all and term babies gradually increased from the mid 1970s. The increase in the percentage of preterm birth paralleled a two-fold increase in the percentage of caesarean section among preterm births during the last two decades. The gap between the most affluent and the most deprived groups of the population widened over the three decades.</p> <p>Conclusion</p> <p>Key maternal and fetal factors affecting birth outcomes, such as maternal age, parity, socioeconomic status, birthweight and gestational age, changed substantially during the 32-year period, from 1961 to 1992. The availability of accurate gestational age is extremely important for correct interpretation of trends in birthweight.</p

Paternal age in relation to offspring intelligence in the West of Scotland Twenty-07 prospective cohort study.

Background The adverse effects of advancing maternal age on offspring's health and development are well understood. Much less is known about the impact of paternal age. Methods We explored paternal age-offspring cognition associations in 772 participants from the West of Scotland Twenty-07 study. Offspring cognitive ability was assessed using Part 1 of the Alice Heim 4 (AH4) test of General Intelligence and by reaction time (RT). Results There was no evidence of a parental age association with offspring RT. However, we observed an inverse U-shaped association between paternal age and offspring AH4 score with the lowest scores observed for the youngest and oldest fathers. Adjustment for parental education and socioeconomic status somewhat attenuated this association. Adjustment for number of, particularly older, siblings further reduced the scores of children of younger fathers and appeared to account for the lower offspring scores in the oldest paternal age group. Conclusion We observed a paternal age association with AH4 but not RT, a measure of cognition largely independent of social and educational experiences. Factors such as parental education, socioeconomic status and number of, particularly older, siblings may play an important role in accounting for paternal age-AH4 associations. Future studies should include parental intelligence

URLs in print: To cite or not to cite

A letter published in Computer magazine expressed concern over the validity of citing uniform resource locators (URLs) in journals. The letter elicited varying response from readers of the magazine. Some readers cite instances of URLs that do not contain sufficient information, making them unreliable. There are those, however, who believe that URL use will have a positive impact in publishing and information acquisition

Prediction of Coronary Artery Calcium Using Deep Learning of Echocardiograms

BackgroundCoronary artery calcification (CAC), often assessed by computed tomography (CT), is a powerful marker of coronary artery disease that can guide preventive therapies. Computed tomographies, however, are not always accessible or serially obtainable. It remains unclear whether other widespread tests such as transthoracic echocardiograms (TTEs) can be used to predict CAC.MethodsUsing a data set of 2,881 TTE videos paired with coronary calcium CTs, we trained a video-based artificial intelligence convolutional neural network to predict CAC scores from parasternal long-axis views. We evaluated the model's ability to classify patients from a held-out sample as well as an external site sample into zero CAC and high CAC (CAC ≥ 400 Agatston units) groups by receiver operating characteristic and precision-recall curves. We also investigated whether such classifications prognosticated significant differences in 1-year mortality rates by the log-rank test of Kaplan-Meier curves.ResultsTransthoracic echocardiogram artificial intelligence models had high discriminatory abilities in predicting zero CAC (receiver operating characteristic area under the curve [AUC]&nbsp;=&nbsp;0.81 [95% CI, 0.74-0.88], F1 score&nbsp;=&nbsp;0.95) and high CAC (AUC&nbsp;=&nbsp;0.74 [0.68-0.8], F1 score&nbsp;=&nbsp;0.74). This performance was confirmed in an external test data set of 92 TTEs (AUC&nbsp;=&nbsp;0.75 [0.65-0.85], F1 score&nbsp;=&nbsp;0.77; and AUC&nbsp;=&nbsp;0.85 [0.76-0.93], F1 score&nbsp;=&nbsp;0.59, respectively). Risk stratification by TTE-predicted CAC performed similarly to CT CAC scores in prognosticating significant differences in 1-year survival in high-CAC patients (CT CAC ≥&nbsp;400 vs CT CAC &lt; 400, P&nbsp;=&nbsp;.03; TTE-predicted CAC ≥ 400 vs TTE-predicted CAC &lt; 400, P&nbsp;=&nbsp;.02).ConclusionsA video-based deep learning model successfully used TTE videos to predict zero CAC and high CAC with high accuracy. Transthoracic echocardiography-predicted CAC prognosticated differences in 1-year survival similar to CT CAC. Deep learning of TTEs holds promise for future adjunctive coronary artery disease risk stratification to guide preventive therapies

Cardiovascular and hepatic disease associations by magnetic resonance imaging: A retrospective cohort study

BackgroundHepatic disease is linked to cardiovascular events but the independent association between hepatic and cardiovascular disease remains unclear, given shared risk factors.MethodsThis was a retrospective study of consecutive patients with a clinical cardiac MRI (CMR) and a serological marker of hepatic fibrosis, the FIB-4 score, within one year of clinical imaging. We assessed the relations between FIB-4 scores grouped based on prior literature: low (&lt; 1.3), moderate (1.3-3.25), and high (&gt;3.25), and abnormalities detected by comprehensive CMR grouped into 4 domains: cardiac structure (end diastolic volumes, atrial dimensions, wall thickness); cardiac function (ejection fractions, wall motion abnormalities, cardiac output); vascular structure (ascending aortic and pulmonary arterial sizes); and cardiac composition (late gadolinium enhancement, T1 and T2 times). We used Poisson regression to examine the association between the conventionally defined FIB-4 category (low &lt;1.3, moderate 1.3-3.25, and high &gt;3.25) and any CMR abnormality while adjusting for demographics and traditional cardiovascular risk factors.ResultsOf the 1668 patients studied (mean age: 55.971 ± 7.28, 901 [54%] male), 85.9% had ≥1 cardiac abnormality with increasing prevalence seen within the low (82.0%) to moderate (88.8%) to high (92.3%) FIB-4 categories. Multivariable analyses demonstrated the presence of any cardiac abnormality was significantly associated with having a high-range FIB-4 (prevalence ratio 1.07, 95% CI: 1.01-1.13); notably, the presence of functional cardiac abnormalities were associated with being in the high FIB-4 range (1.41, 1.21-1.65) and any vascular abnormalities with being in the moderate FIB-4 range (1.22, 1.01-1.47).ConclusionsElevated FIB-4 was associated with cardiac functional and vascular abnormalities even after adjustment for shared risk factors in a cohort of patients with clinically referred CMR. These CMR findings indicate that cardiovascular abnormalities exist in the presence of subclinical hepatic fibrosis, irrespective of shared risk factors, underscoring the need for further studies of the heart-liver axis

Survival of Burgess Shale-type animals in a Middle Ordovician deep-water setting

Appendix 1: Assemblage Compositio

The mechanism of patellamide macrocyclization revealed by the characterization of the PatG macrocyclase domain

Peptide macrocycles are found in many biologically active natural products. Their versatility, resistance to proteolysis and ability to traverse membranes has made them desirable molecules. Although technologies exist to synthesize such compounds, the full extent of diversity found among natural macrocycles has yet to be achieved synthetically. Cyanobactins are ribosomal peptide macrocycles encompassing an extraordinarily diverse range of ring sizes, amino acids and chemical modifications. We report the structure, biochemical characterization and initial engineering of the PatG macrocyclase domain of Prochloron sp. from the patellamide pathway that catalyzes the macrocyclization of linear peptides. The enzyme contains insertions in the subtilisin fold to allow it to recognize a three-residue signature, bind substrate in a preorganized and unusual conformation, shield an acyl-enzyme intermediate from water and catalyze peptide bond formation. The ability to macrocyclize a broad range of nonactivated substrates has wide biotechnology applications