Hospital discharge data is not accurate enough to monitor the incidence of postpartum hemorrhage.

Postpartum hemorrhage remains a leading cause of maternal morbidity and mortality worldwide. Therefore, cumulative incidence of postpartum hemorrhage and severe postpartum hemorrhage are commonly monitored within and compared across maternity hospitals or countries for obstetrical safety improvement. These indicators are usually based on hospital discharge data though their accuracy is seldom assessed. We aimed to measure postpartum hemorrhage and severe postpartum hemorrhage using electronic health records and hospital discharge data separately and compare the detection accuracy of these methods to manual chart review, and to examine the temporal trends in cumulative incidence of these potentially avoidable adverse outcomes. We analyzed routinely collected data of 7904 singleton deliveries from a large Swiss university hospital for a three year period (2014-2016). We identified postpartum hemorrhage and severe postpartum hemorrhage in electronic health records by text mining discharge letters and operative reports and calculating drop in hemoglobin from laboratory tests. Diagnostic and procedure codes were used to identify cases in hospital discharge data. A sample of 334 charts was reviewed manually to provide a reference-standard and evaluate the accuracy of the other detection methods. Sensitivities of detection algorithms based on electronic health records and hospital discharge data were 95.2% (95% CI: 92.6% 97.8%) and 38.2% (33.3% to 43.0%), respectively for postpartum hemorrhage, and 87.5% (85.2% to 89.8%) and 36.2% (26.3% to 46.1%) for severe postpartum hemorrhage. Postpartum hemorrhage cumulative incidence based on electronic health records decreased from 15.6% (13.1% to 18.2%) to 8.5% (6.7% to 10.5%) from the beginning of 2014 to the end of 2016, with an average of 12.5% (11.8% to 13.3%). The cumulative incidence of severe postpartum hemorrhage remained at approximately 4% (3.5% to 4.4%). Hospital discharge data-based algorithms provided significantly underestimated incidences. Hospital discharge data is not accurate enough to assess the incidence of postpartum hemorrhage at hospital or national level. Instead, automated algorithms based on structured and textual data from electronic health records should be considered, as they provide accurate and timely estimates for monitoring and improvement in obstetrical safety. Furthermore, they have the potential to better code for postpartum hemorrhage thus improving hospital reimbursement

Development and validation of a self-report measure of epistemic trust

Epistemic trust (ET) refers to trust in communicated knowledge. This paper describes the development and validation of a new self-report questionnaire, the Epistemic Trust, Mistrust and Credulity Questionnaire (ETMCQ). We report on two studies (Study 1, n = 500; Study 2, n = 705) examining the psychometric properties of the ETMCQ and the relationship between EMTCQ scores (i.e., an individual’s epistemic stance) and exposure to adverse childhood experiences, mental health symptoms, attachment, mentalizing and general self-efficacy. The factor structure of the ETMCQ was examined using Exploratory and Confirmatory Factor Analyses, and its reliability and test-retest reliability were tested. Both studies yielded three correlated yet distinct factors – Trust, Mistrust and Credulity – and confirmed the reliability and validity of the ETMCQ. Preregistered hypotheses were confirmed and replicated across both studies. Main findings suggest intriguing links between the ETMCQ and developmental psychopathology constructs and are consistent with thinking on the role of epistemic stance in undermining adaptation and increasing the developmental risk of mental health problems. Mistrust and Credulity scores were associated with childhood adversity and higher scores on the global psychopathology severity index and both factors partially mediated the link between early adversity and mental health symptoms. Mistrust and Credulity were positively associated with difficulties in understanding mental states and insecure attachment styles. Post-hoc analysis identified that different attachment styles were associated with differences in epistemic stance. In addition, Trust was not associated with reduced levels of mental health symptoms and did not moderate the impact of childhood adversity – findings are congruent with the suggestion that the reduction of mistrust and credulity may be crucial common factors in promoting resilience and the effectiveness of psychotherapeutic interventions. This investigation and the ETMCQ provide an empirical measure of what until now has been largely a theoretical concept and open new avenues for future research

Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring

Assessing the intracity spatial distribution and temporal variability in air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if traditional high-quality, expensive monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) monitor has been developed, which can measure up to five gases including the criteria pollutant gases carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3), along with temperature and relative humidity. This study compares various algorithms to calibrate the RAMP measurements including linear and quadratic regression, clustering, neural networks, Gaussian processes, and hybrid random forest–linear regression models. Using data collected by almost 70 RAMP monitors over periods ranging up to 18 months, we recommend the use of limited quadratic regression calibration models for CO, neural network models for NO, and hybrid models for NO2 and O3 for any low-cost monitor using electrochemical sensors similar to those of the RAMP. Furthermore, generalized calibration models may be used instead of individual models with only a small reduction in overall performance. Generalized models also transfer better when the RAMP is deployed to other locations. For long-term deployments, it is recommended that model performance be re-evaluated and new models developed periodically, due to the noticeable change in performance over periods of a year or more. This makes generalized calibration models even more useful since only a subset of deployed monitors are needed to build these new models. These results will help guide future efforts in the calibration and use of low-cost sensor systems worldwide.</p

Effect on falls of providing single lens distance vision glasses to multifocal glasses wearers: VISIBLE randomised controlled trial

Objective To determine whether the provision of single lens distance glasses to older wearers of multifocal glasses reduces falls

A Comprehensive Case Study of Macrosegregation in a Steel Ingot

This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s11663-015-0386-yA case study is presented that examines the macrosegregation and grain structure present in a 12-tonne steel ingot, which was cast for experimental purposes. Details of the casting procedure were well documented and the resulting ingot was characterized using a number of techniques that measured chemical segregation, shrinkage, and porosity. The formation of the porosity and segregation patterns is discussed in reference to the particular grain structure observed in the ingot. It is hoped that this case study can be used as a tool for the validation of future macromodels.This work was undertaken as part of a Project sponsored by Rolls-Royce Power Nuclear plc in collaboration with Sheffield Forgemasters International

The Classic: Bone Morphogenetic Protein

This Classic Article is a reprint of the original work by Marshall R. Urist and Basil S. Strates, Bone Morphogenetic Protein. An accompanying biographical sketch of Marshall R. Urist, MD is available at DOI 10.1007/s11999-009-1067-4; a second Classic Article is available at DOI 10.1007/s11999-009-1069-2; and a third Classic Article is available at DOI 10.1007/s11999-009-1070-9. The Classic Article is © 1971 by Sage Publications Inc. Journals and is reprinted with permission from Urist MR, Strates BS. Bone morphogenetic protein. J Dent Res. 1971;50:1392–1406

MicroRNAs in pulmonary arterial remodeling

Pulmonary arterial remodeling is a presently irreversible pathologic hallmark of pulmonary arterial hypertension (PAH). This complex disease involves pathogenic dysregulation of all cell types within the small pulmonary arteries contributing to vascular remodeling leading to intimal lesions, resulting in elevated pulmonary vascular resistance and right heart dysfunction. Mutations within the bone morphogenetic protein receptor 2 gene, leading to dysregulated proliferation of pulmonary artery smooth muscle cells, have been identified as being responsible for heritable PAH. Indeed, the disease is characterized by excessive cellular proliferation and resistance to apoptosis of smooth muscle and endothelial cells. Significant gene dysregulation at the transcriptional and signaling level has been identified. MicroRNAs are small non-coding RNA molecules that negatively regulate gene expression and have the ability to target numerous genes, therefore potentially controlling a host of gene regulatory and signaling pathways. The major role of miRNAs in pulmonary arterial remodeling is still relatively unknown although research data is emerging apace. Modulation of miRNAs represents a possible therapeutic target for altering the remodeling phenotype in the pulmonary vasculature. This review will focus on the role of miRNAs in regulating smooth muscle and endothelial cell phenotypes and their influence on pulmonary remodeling in the setting of PAH