VBAC In Women Undergoing IOL With Dinoprostone Versus Spontaneous Labor

Sem PDFOBJECTIVE: To compare the rate of vaginal birth in women attempting vaginal birth after caesarean delivery (VBAC) through labour induction with dinoprostone versus a trial of spontaneous labour. METHODS: A 10-year retrospective cohort study in a tertiary care hospital of women with one prior caesarean delivery. Women who attempted VBAC with labour induction with dinoprostone were compared with women undergoing spontaneous labour. Logistic regression analyses were performed to assess the relationship between VBAC success and labour induction taking into account confounding variables. Both maternal and neonatal safety were studied to find a difference between the group with spontaneous labour versus the group labour induction. RESULTS: A total of 1076 women in the cohort attempted VBAC (649 with spontaneous labour and 427 with induced labour). Women who were given a trial of spontaneous labour were more likely to have a successful VBAC (70.3% compared with 48.7%, odds ratio (OR) 2.49, 95% confidence interval (CI) 1.93–3.21). If women have had a previous vaginal delivery they were more likely to have a successful VBAC, OR of 2.98, 95% CI 2.08-4.27. The risk of uterine rupture (0.5% for induced labour compared with 0.6% for spontaneous labour) or overall morbidity (2.7% compared with 2.1%) was not significantly increased in the women with labour induction. CONCLUSION: Women with a previous caesarean section have a lower VBAC rate with labour induction versus spontaneous labour. If they have a previous vaginal delivery, the chance of a vaginal delivery increases. Overall, vaginal birth is safe and effective in women with one caesarean section with labour induction with dinoprostone.publishersversionpublishe

Faster identification of faster Formula 1 drivers via time-rank duality

Two natural ways of modelling Formula 1 race outcomes are a probabilistic approach, based on the exponential distribution, and econometric modelling of the ranks. Both approaches lead to exactly soluble race-winning probabilities. Equating race-winning probabilities leads to a set of equivalent parametrisations. This time-rank duality is attractive theoretically and leads to quicker ways of disentangling driver and car level effects

Plasma lipid profiles change with increasing numbers of mild traumatic brain injuries in rats

Mild traumatic brain injury (mTBI) causes structural, cellular and biochemical alterations which are difficult to detect in the brain and may persist chronically following single or repeated injury. Lipids are abundant in the brain and readily cross the blood-brain barrier, suggesting that lipidomic analysis of blood samples may provide valuable insight into the neuropathological state. This study used liquid chromatography-mass spectrometry (LC-MS) to examine plasma lipid concentrations at 11 days following sham (no injury), one (1×) or two (2×) mTBI in rats. Eighteen lipid species were identified that distinguished between sham, 1× and 2× mTBI. Three distinct patterns were found: (1) lipids that were altered significantly in concentration after either 1× or 2× F mTBI: cholesterol ester CE (14:0) (increased), phosphoserine PS (14:0/18:2) and hexosylceramide HCER (d18:0/26:0) (decreased), phosphoinositol PI(16:0/18:2) (increased with 1×, decreased with 2× mTBI); (2) lipids that were altered in response to 1× mTBI only: free fatty acid FFA (18:3 and 20:3) (increased); (3) lipids that were altered in response to 2× mTBI only: HCER (22:0), phosphoethanolamine PE (P-18:1/20:4 and P-18:0/20:1) (increased), lysophosphatidylethanolamine LPE (20:1), phosphocholine PC (20:0/22:4), PI (18:1/18:2 and 20:0/18:2) (decreased). These findings suggest that increasing numbers of mTBI induce a range of changes dependent upon the lipid species, which likely reflect a balance of damage and reparative responses

Skeletal pathology and variable anatomy in elephant feet assessed using computed tomography

Foot problems are a major cause of morbidity and mortality in elephants, but are underreported due to difficulties in diagnosis, particularly of conditions affecting the bones and internal structures. Here we evaluate post-mortem computer tomographic (CT) scans of 52 feet from 21 elephants (seven African Loxodonta africana and 14 Asian Elephas maximus), describing both pathology and variant anatomy (including the appearance of phalangeal and sesamoid bones) that could be mistaken for disease. We found all the elephants in our study to have pathology of some type in at least one foot. The most common pathological changes observed were bone remodelling, enthesopathy, osseous cyst-like lesions, and osteoarthritis, with soft tissue mineralisation, osteitis, infectious osteoarthriti, subluxation, fracture and enostoses observed less frequently. Most feet had multiple categories of pathological change (81% with two or more diagnoses, versus 10% with a single diagnosis, and 9% without significant pathology). Much of the pathological change was focused over the middle/lateral digits, which bear most weight and experience high peak pressures during walking. We found remodelling and osteoarthritis to be correlated with increasing age, more enthesopathy in Asian elephants, and more cyst-like lesions in females. We also observed multipartite, missing and misshapen phalanges as common and apparently incidental findings. The proximal (paired) sesamoids can appear fused or absent, and the predigits (radial/tibial sesamoids) can be variably ossified, though are significantly more ossified in Asian elephants. Our study reinforces the need for regular examination and radiography of elephant feet to monitor for pathology and as a tool for improving welfare

The clinical characteristics of familial cluster headache

BACKGROUND: A positive family history predisposes to the development of cluster headache. The distinct characteristics of familial cluster headache have yet to be confirmed, however, evidence suggests a younger age of onset and higher proportion of females in this subgroup. OBJECTIVES: To assess the rate and mode of inheritance of familial cluster headache in a tertiary referral centre for headache. To describe the clinical features of familial cluster headache. METHODS: A retrospective study conducted between 2007 and 2017. Cluster headache was confirmed in probands and affected relatives. Differences in demographics, clinical characteristics, and response-to-treatment in familial cluster headache were delineated through multivariate analysis using a control cohort of 597 patients with sporadic cluster headache. RESULTS: Familial cluster headache was confirmed in 48 (7.44%) patients and predominantly reflected an autosomal dominant mode of inheritance with reduced penetrance. Familial cases were more likely to report nasal blockage (OR 4.06, 95% CI; 2.600-6.494, p < 0.001) during an attack and a higher rate of concurrent short-lasting unilateral neuralgiform headache with conjunctival injection and tearing (OR 3.76, 95% CI; 1.572-9.953, p = 0.004). CONCLUSION: These findings add to evidence suggesting a genetic component to cluster headache. Here, we demonstrated prominent nasal blockage, and a higher occurrence of concomitant short-lasting unilateral neuralgiform headache with conjunctival injection and tearing in this subgroup, further delineating the phenotype

Exploratory analysis of multivariate drill core time series measurements

Demand for mineral resources is increasing, necessitating exploitation of lower grade and more heterogeneous orebodies. The high variability inherent in such orebodies leads to an increase in the cost, complexity and environmental footprint associated with mining and mineral processing. Enhanced knowledge of orebody characteristics is thus vital for mining companies to optimize profitability. We present a pilot study to investigate prediction of geometallurgical variables from drill sensor data. A comparison is made of the performance of multilayer perceptron (MLP) and multiple linear regression models (MLR) for predicting a geometallurgical variable. This comparison is based on simulated data that are physically realistic, having been derived from models fitted to the one available drill core. The comparison is made in terms of the mean and standard deviation (over repeated samples from the population) of the mean absolute error, root mean square error, and coefficient of determination. The best performing model depends on the form of the response variable and the sample size. The standard deviation of performance measures tends to be higher for the MLP, and MLR appears to offer a more consistent performance for the test cases considered. References R. M. Balabin and S. V. Smirnov. Interpolation and extrapolation problems of multivariate regression in analytical chemistry: Benchmarking the robustness on near-infrared (NIR) spectroscopy data”. Analyst 137.7 (2012), pp. 1604–1610. doi: 10.1039/c2an15972d C. M. Bishop. Pattern recognition and machine learning. Springer, 2006. url: https://link.springer.com/book/9780387310732 J. B. Boisvert, M. E. Rossi, K. Ehrig, and C. V. Deutsch. Geometallurgical modeling at Olympic dam mine, South Australia”. Math. Geosci. 45 (2013), pp. 901–925. doi: 10.1007/s11004-013-9462-5 T. Bollerslev. Generalized autoregressive conditional heteroskedasticity”. J. Economet. 31.3 (1986), pp. 307–327. doi: 10.1016/0304-4076(86)90063-1 C. Both and R. Dimitrakopoulos. Applied machine learning for geometallurgical throughput prediction—A case study using production data at the Tropicana Gold Mining Complex”. Minerals 11.11 (2021), p. 1257. doi: 10.3390/min11111257 J. Chen and G. Li. Tsallis wavelet entropy and its application in power signal analysis”. Entropy 16.6 (2014), pp. 3009–3025. doi: 10.3390/e16063009 S. Coward, J. Vann, S. Dunham, and M. Stewart. The primary-response framework for geometallurgical variables”. Seventh international mining geology conference. 2009, pp. 109–113. https://www.ausimm.com/publications/conference-&gt;url: https://www.ausimm.com/publications/conference- proceedings/seventh-international-mining-geology- conference-2009/the-primary-response-framework-for- geometallurgical-variables/ A. C. Davis and N. B. Christensen. Derivative analysis for layer selection of geophysical borehole logs”. Comput. Geosci. 60 (2013), pp. 34–40. doi: 10.1016/j.cageo.2013.06.015 C. Dritsaki. An empirical evaluation in GARCH volatility modeling: Evidence from the Stockholm stock exchange”. J. Math. Fin. 7.2 (2017), pp. 366–390. doi: 10.4236/jmf.2017.72020 R. F. Engle and T. Bollerslev. Modelling the persistence of conditional variances”. Econ. Rev. 5.1 (1986), pp. 1–50. doi: 10.1080/07474938608800095 A. S. Hadi and R. F. Ling. Some cautionary notes on the use of principal components regression”. Am. Statistician 52.4 (1998), pp. 15–19. doi: 10.2307/2685559 J. Hunt, T. Kojovic, and R. Berry. Estimating comminution indices from ore mineralogy, chemistry and drill core logging”. The Second AusIMM International Geometallurgy Conference (GeoMet) 2013. 2013, pp. 173–176. http://ecite.utas.edu.au/89773&gt;url: http://ecite.utas.edu.au/89773 on p. C210). R. Hyndman, Y. Kang, P. Montero-Manso, T. Talagala, E. Wang, Y. Yang, M. O’Hara-Wild, S. Ben Taieb, H. Cao, D. K. Lake, N. Laptev, and J. R. Moorman. tsfeatures: Time series feature extraction. R package version 1.0.2. 2020. https://CRAN.R-project.org/package=tsfeatures&gt;url: https://CRAN.R-project.org/package=tsfeatures on p. C222). C. L. Johnson, D. A. Browning, and N. E. Pendock. Hyperspectral imaging applications to geometallurgy: Utilizing blast hole mineralogy to predict Au-Cu recovery and throughput at the Phoenix mine, Nevada”. Econ. Geol. 114.8 (2019), pp. 1481–1494. doi: 10.5382/econgeo.4684 E. B. Martin and A. J. Morris. An overview of multivariate statistical process control in continuous and batch process performance monitoring”. Trans. Inst. Meas. Control 18.1 (1996), pp. 51–60. doi: 10.1177/014233129601800107 E. Sepulveda, P. A. Dowd, C. Xu, and E. Addo. Multivariate modelling of geometallurgical variables by projection pursuit”. Math. Geosci. 49.1 (2017), pp. 121–143. doi: 10.1007/s11004-016-9660-z S. J. Webb, G. R. J. Cooper, and L. D. Ashwal. Wavelet and statistical investigation of density and susceptibility data from the Bellevue drill core and Moordkopje borehole, Bushveld Complex, South Africa”. SEG Technical Program Expanded Abstracts 2008. Society of Exploration Geophysicists, 2008, pp. 1167–1171. doi: 10.1190/1.3059129 R. Zuo. Identifying geochemical anomalies associated with Cu and Pb–Zn skarn mineralization using principal component analysis and spectrum–area fractal modeling in the Gangdese Belt, Tibet (China)”. J. Geochem. 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Semi-parametric multivariate modelling when the marginals are the same

A model is developed for multivariate distributions which have nearly the same marginals, up to shift and scale. This model, based on "interpolation" of characteristic functions, gives a new notion of "correlation". It allows straightforward nonparametric estimation of the common marginal distribution, which avoids the "curse of dimensionality" present when nonparametically estimating the full multivariate distribution. The method is illustrated with environmental monitoring network data, where multivariate modelling with common marginals is often appropriate

Correlation between volatile composition and sensory properties in Spanish Albariño wines

To characterize the flavour of Albariño wines, a total of 35 samples representing five geographic areas from Denomination of Origin Rías Baixas were analyzed by sensory descriptive analysis and instrumental analysis (GC-FID). The objective of this work was to study the correlation between instrumental analysis and sensory perception of wine constituents. The results of the investigation were presented by means of multivariate modelling methods such as Principal Component Analysis (PCA) and partial least squares regression (PLSR). Principal Component Analysis showed the distribution of the wines based on chemical and sensory characteristics. The relationships between sensory descriptors and volatile compounds of Albariño wines were studied by Pearson correlation and partial least squares regression (PLSR). The compounds that mostly contributed to the flavour of Albariño wines in instrumental analysis were those related to fruity (ethyl esters and acetates) and floral aromas (monoterpenes). Similar results were found in sensory analysis where the descriptors with the highest Geometric Mean were fruity and floral aromas too (citric, flowers, fruit, ripe fruit, apple and tropical). Therefore, this work demonstrates that some relationships between sensory data and volatile compounds exist to asses sensory properties in Albariño wines.Xunta de Galicia (Spain)

What are the current and projected future cost and health-related quality of life implications of scaling up cognitive stimulation therapy?

Objectives: Cognitive stimulation therapy (CST) is one of the few non-pharmacological interventions for people living with dementia shown to be effective and cost-effective. What are the current and future cost and health-related quality of life implications of scaling-up CST to eligible new cases of dementia in England? // Methods/design: Data from trials were combined with microsimulation and macrosimulation modelling to project future prevalence, needs and costs. Health and social costs, unpaid care costs and quality-adjusted life years (QALYs) were compared with and without scaling-up of CST and follow-on maintenance CST (MCST). // Results: Scaling-up group CST requires year-on-year increases in expenditure (mainly on staff), but these would be partially offset by reductions in health and care costs. Unpaid care costs would increase. Scaling-up MCST would also require additional expenditure, but without generating savings elsewhere. There would be improvements in general cognitive functioning and health-related quality of life, summarised in terms of QALY gains. Cost per QALY for CST alone would increase from £12,596 in 2015 to £19,573 by 2040, which is below the threshold for cost-effectiveness used by the National Institute for Health and Care Excellence (NICE). Cost per QALY for CST and MCST combined would grow from £19,883 in 2015 to £30,906 by 2040, making it less likely to be recommended by NICE on cost-effectiveness grounds. // Conclusions: Scaling-up CST England for people with incident dementia can improve lives in an affordable, cost-effective manner. Adding MCST also improves health-related quality of life, but the economic evidence is less compelling