The health of mothers of children with a life-limiting condition; a comparative cohort study

ObjectivesThis study aimed to quantify the incidence rates of common mental and physical health conditions in mothers of children with a life-limiting condition.MethodsComparative national longitudinal cohort study using linked primary and secondary care data from the Clinical Practice Research Datalink in England. Maternal-child dyads were identified in these data. Maternal physical and mental health outcomes were identified in the primary and secondary care datasets using previously developed diagnostic coding frameworks. Incidence rates of the outcomes were modelled using Poisson regression adjusting for deprivation, ethnicity and age and accounting for time at risk.ResultsA total of 35,683 mothers, 8,950 had a child with a life-limiting condition, 8,868 had a child with a chronic condition and 17,865 had a child with no long-term condition.The adjusted incidence rates of all of the physical and mental health conditionswere significantly higher in the mothers of children with a life-limiting condition when compared to those mothers with a child with no long-term condition. (e.g. depression IRR 1.21 (95%CI 1.13 to 1.30) cardiovascular disease IRR 1.73 (95%CI 1.27 to 2.36), death in mothers IRR 1.59 (95%CI 1.16 to 2.18).ConclusionsThis study clearly demonstrates the higher incidence rates of common and serious physical and mental health problems and death in mothers of children with a life limiting condition. Further research is required to understand how best to support these mothers, but healthcare providers should consider how they can target this population to provide preventative and treatment services

Assessing spatial and temporal variability of acid-extractable organics in oil sands process-affected waters

The acid-extractable organic compounds (AEOs), including naphthenic acids (NAs), present within oil sands process-affected water (OSPW) receive great attention due to their known toxicity. While recent progress in advanced separation and analytical methodologies for AEOs has improved our understanding of the composition of these mixtures, little is known regarding any variability (i.e., spatial, temporal) inherent within, or between, tailings ponds. In this study, 5 samples were collected from the same location of one tailings pond over a 2-week period. In addition, 5 samples were collected simultaneously from different locations within a tailings pond from a different mine site, as well as its associated recycling pond. In both cases, the AEOs were analyzed using SFS, ESI-MS, HRMS, GC×GC-ToF/MS, and GC- & LC-QToF/MS (GC analyses following conversion to methyl esters). Principal component analysis of HRMS data was able to distinguish the ponds from each other, while data from GC×GC-ToF/MS, and LC- and GC-QToF/MS were used to differentiate samples from within the temporal and spatial sample sets, with the greater variability associated with the latter. Spatial differences could be attributed to pond dynamics, including differences in inputs of tailings and surface run-off. Application of novel chemometric data analyses of unknown compounds detected by LC- and GC-QToF/MS allowed further differentiation of samples both within and between data sets, providing an innovative approach for future fingerprinting studies

Multidimensional sexual perfectionism and female sexual function: A longitudinal investigation

Research on multidimensional sexual perfectionism differentiates four forms of sexual perfectionism: self-oriented, partner-oriented, partner-prescribed, and socially prescribed. Self-oriented sexual perfectionism reflects perfectionistic standards people apply to themselves as sexual partners; partner-oriented sexual perfectionism reflects perfectionistic standards people apply to their sexual partner; partner-prescribed sexual perfectionism reflects people’s beliefs that their sexual partner imposes perfectionistic standards on them; and socially prescribed sexual perfectionism reflects people’s beliefs that society imposes such standards on them. Previous studies found partner-prescribed and socially prescribed sexual perfectionism to be maladaptive forms of sexual perfectionism associated with a negative sexual self-concept and problematic sexual behaviors, but only examined cross-sectional relationships. The present article presents the first longitudinal study examining whether multidimensional sexual perfectionism predicts changes in sexual self-concept and sexual function over time. A total of 366 women aged 17-69 years completed measures of multidimensional sexual perfectionism, sexual esteem, sexual anxiety, sexual problem self-blame, and female sexual function (cross-sectional data). Three to six months later, 164 of the women completed the same measures again (longitudinal data). Across analyses, partner-prescribed sexual perfectionism emerged as the most maladaptive form of sexual perfectionism. In the cross-sectional data, partner-prescribed sexual perfectionism showed positive relationships with sexual anxiety, sexual problem self-blame, and intercourse pain and negative relationships with sexual esteem, desire, arousal, lubrication, and orgasmic function. In the longitudinal data, partner-prescribed sexual perfectionism predicted increases in sexual anxiety and decreases in sexual esteem, arousal, and lubrication over time. The findings suggest that partner-prescribed sexual perfectionism contributes to women’s negative sexual self-concept and female sexual dysfunction

Use of the distributions of adamantane acids to profile short-term temporal and pond-scale spatial variations in the composition of oil sands process-affected waters

© The Royal Society of Chemistry. Oil industry produced waters, such as the oils sands process-affected waters (OSPW) of Alberta, Canada, represent a challenge in terms of risk assessment and reclamation due to their extreme complexity, particularly of the organic chemical constituents, including the naphthenic acids (NA). The identification of numerous NA in single samples has raised promise for the use of NA distributions for profiling OSPW. However, monitoring of the success of containment is still difficult, due to the lack of knowledge of the homogeneity (or otherwise) of OSPW composition within, and between, different industry containments. Here we used GC×GC-MS to compare the NA of five OSPW samples from each of two different industries. Short-term temporal and pond-scale spatial variations in the distributions of known adamantane acids and diacids and other unknown tricyclic acids were examined and a statistical appraisal of the replicate data made. The presence/absence of individual acids easily distinguished the OSPW NA of one industry from those of the other. The proportions of tricyclic acids with different carbon numbers also varied significantly between the OSPW of the two industries. The pond-scale spatial variation in NA in OSPW samples was higher than the short-term (2 weeks) temporal variations. An OSPW sample from an aged pond was exceptionally high in the proportion of C<inf>15,16,17</inf> compounds, possibly due to increased biotransformation. Such techniques could possibly also help to distinguish different sources of NA in the environment

Risk of selection bias in randomised trials

Background: Selection bias occurs when recruiters selectively enrol patients into the trial based on what the next treatment allocation is likely to be. This can occur even if appropriate allocation concealment is used if recruiters can guess the next treatment assignment with some degree of accuracy. This typically occurs in unblinded trials when restricted randomisation is implemented to force the number of patients in each arm or within each centre to be the same. Several methods to reduce the risk of selection bias have been suggested; however, it is unclear how often these techniques are used in practice. Methods: We performed a review of published trials which were not blinded to assess whether they utilised methods for reducing the risk of selection bias. We assessed the following techniques: (a) blinding of recruiters; (b) use of simple randomisation; (c) avoidance of stratification by site when restricted randomisation is used; (d) avoidance of permuted blocks if stratification by site is used; and (e) incorporation of prognostic covariates into the randomisation procedure when restricted randomisation is used. We included parallel group, individually randomised phase III trials published in four general medical journals (BMJ, Journal of the American Medical Association, The Lancet, and New England Journal of Medicine) in 2010. Results: We identified 152 eligible trials. Most trials (98%) provided no information on whether recruiters were blind to previous treatment allocations. Only 3% of trials used simple randomisation; 63% used some form of restricted randomisation, and 35% did not state the method of randomisation. Overall, 44% of trials were stratified by site of recruitment; 27% were not, and 29% did not report this information. Most trials that did stratify by site of recruitment used permuted blocks (58%), and only 15% reported using random block sizes. Many trials that used restricted randomisation also included prognostic covariates in the randomisation procedure (56%). Conclusions: The risk of selection bias could not be ascertained for most trials due to poor reporting. Many trials which did provide details on the randomisation procedure were at risk of selection bias due to a poorly chosen randomisation methods. Techniques to reduce the risk of selection bias should be more widely implemented

Advances in Distinguishing Groundwater Influenced by Oil Sands Process-Affected Water (OSPW) from Natural Bitumen-Influenced Groundwaters.

The objective of this study was to advance analytical methods for detecting oil sands process-affected water (OSPW) seepage from mining containments and discriminating any such seepage from the natural bitumen background in groundwaters influenced by the Alberta McMurray formation. Improved sampling methods and quantitative analyses of two groups of monoaromatic acids were employed to analyze OSPW and bitumen-affected natural background groundwaters for source discrimination. Both groups of monoaromatic acids showed significant enrichment in OSPW, while ratios of O2/O4 containing heteroatomic ion classes of acid extractable organics (AEOs) did not exhibit diagnostic differences. Evaluating the monoaromatic acids to track a known plume of OSPW-affected groundwater confirmed their diagnostic abilities. A secondary objective was to assess anthropogenically derived artificial sweeteners and per- and polyfluoroalkyl substances (PFAS) as potential tracers for OSPW. Despite the discovery of acesulfame and PFAS in most OSPW samples, trace levels in groundwaters influenced by general anthropogenic activities preclude them as individual robust tracers. However, their inclusion with the other metrics employed in this study served to augment the tiered, weight of evidence methodology developed. This methodology was then used to confirm earlier findings of OSPW migrations into groundwater reaching the Athabasca River system adjacent to the reclaimed pond at Tar Island Dyke

Should methodological filters for diagnostic test accuracy studies be used in systematic reviews of psychometric instruments? a case study involving screening for postnatal depression

<p>Abstract</p> <p>Background</p> <p>Challenges exist when searching for diagnostic test accuracy (DTA) studies that include the design of DTA search strategies and selection of appropriate filters. This paper compares the performance of three MEDLINE search strategies for psychometric diagnostic test accuracy (DTA) studies in postnatal depression.</p> <p>Methods</p> <p>A reference set of six relevant studies was derived from a forward citation search via Web of Knowledge. The performance of the 'target condition and index test' method recommended by the Cochrane DTA Group was compared to two alternative strategies which included methodological filters. Outcome measures were total citations retrieved, sensitivity, precision and associated 95% confidence intervals (95%CI).</p> <p>Results</p> <p>The Cochrane recommended strategy and one of the filtered search strategies were equivalent in performance and both retrieved a total of 105 citations, sensitivity was 100% (95% CI 61%, 100%) and precision was 5.2% (2.6%, 11.9%). The second filtered search retrieved a total of 31 citations, sensitivity was 66.6% (30%, 90%) and precision was 12.9% (5.1%, 28.6%). This search missed the DTA study with most relevance to the DTA review.</p> <p>Conclusions</p> <p>The Cochrane recommended search strategy, 'target condition and index test', method was pragmatic and sensitive. It was considered the optimum method for retrieval of relevant studies for a psychometric DTA review (in this case for postnatal depression). Potential limitations of using filtered searches during a psychometric mental health DTA review should be considered.</p

Evaluation of biases present in the cohort multiple randomised controlled trial design: a simulation study

Background The cohort multiple randomised controlled trial (cmRCT) design provides an opportunity to incorporate the benefits of randomisation within clinical practice; thus reducing costs, integrating electronic healthcare records, and improving external validity. This study aims to address a key concern of the cmRCT design: refusal to treatment is only present in the intervention arm, and this may lead to bias and reduce statistical power. Methods We used simulation studies to assess the effect of this refusal, both random and related to event risk, on bias of the effect estimator and statistical power. A series of simulations were undertaken that represent a cmRCT trial with time-to-event endpoint. Intention-to-treat (ITT), per protocol (PP), and instrumental variable (IV) analysis methods, two stage predictor substitution and two stage residual inclusion, were compared for various refusal scenarios. Results We found the IV methods provide a less biased estimator for the causal effect when refusal is present in the intervention arm, with the two stage residual inclusion method performing best with regards to minimum bias and sufficient power. We demonstrate that sample sizes should be adapted based on expected and actual refusal rates in order to be sufficiently powered for IV analysis. Conclusion We recommend running both an IV and ITT analyses in an individually randomised cmRCT as it is expected that the effect size of interest, or the effect we would observe in clinical practice, would lie somewhere between that estimated with ITT and IV analyses. The optimum (in terms of bias and power) instrumental variable method was the two stage residual inclusion method. We recommend using adaptive power calculations, updating them as refusal rates are collected in the trial recruitment phase in order to be sufficiently powered for IV analysis

A multicenter assessment of single-cell models aligned to standard measures of cell health for prediction of acute hepatotoxicity.

Assessing the potential of a new drug to cause drug-induced liver injury (DILI) is a challenge for the pharmaceutical industry. We therefore determined whether cell models currently used in safety assessment (HepG2, HepaRG, Upcyte and primary human hepatocytes in conjunction with basic but commonly used endpoints) are actually able to distinguish between novel chemical entities (NCEs) with respect to their potential to cause DILI. A panel of thirteen compounds (nine DILI implicated and four non-DILI implicated in man) were selected for our study, which was conducted, for the first time, across multiple laboratories. None of the cell models could distinguish faithfully between DILI and non-DILI compounds. Only when nominal in vitro concentrations were adjusted for in vivo exposure levels were primary human hepatocytes (PHH) found to be the most accurate cell model, closely followed by HepG2. From a practical perspective, this study revealed significant inter-laboratory variation in the response of PHH, HepG2 and Upcyte cells, but not HepaRG cells. This variation was also observed to be compound dependent. Interestingly, differences between donors (hepatocytes), clones (HepG2) and the effect of cryopreservation (HepaRG and hepatocytes) were less important than differences between the cell models per se. In summary, these results demonstrate that basic cell health endpoints will not predict hepatotoxic risk in simple hepatic cells in the absence of pharmacokinetic data and that a multicenter assessment of more sophisticated signals of molecular initiating events is required to determine whether these cells can be incorporated in early safety assessment

Simple estimators of the intensity of seasonal occurrence

<p>Abstract</p> <p>Background</p> <p>Edwards's method is a widely used approach for fitting a sine curve to a time-series of monthly frequencies. From this fitted curve, estimates of the seasonal intensity of occurrence (i.e., peak-to-low ratio of the fitted curve) can be generated.</p> <p>Methods</p> <p>We discuss various approaches to the estimation of seasonal intensity assuming Edwards's periodic model, including maximum likelihood estimation (MLE), least squares, weighted least squares, and a new closed-form estimator based on a second-order moment statistic and non-transformed data. Through an extensive Monte Carlo simulation study, we compare the finite sample performance characteristics of the estimators discussed in this paper. Finally, all estimators and confidence interval procedures discussed are compared in a re-analysis of data on the seasonality of monocytic leukemia.</p> <p>Results</p> <p>We find that Edwards's estimator is substantially biased, particularly for small numbers of events and very large or small amounts of seasonality. For the common setting of rare events and moderate seasonality, the new estimator proposed in this paper yields less finite sample bias and better mean squared error than either the MLE or weighted least squares. For large studies and strong seasonality, MLE or weighted least squares appears to be the optimal analytic method among those considered.</p> <p>Conclusion</p> <p>Edwards's estimator of the seasonal relative risk can exhibit substantial finite sample bias. The alternative estimators considered in this paper should be preferred.</p