Severe early onset preeclampsia: short and long term clinical, psychosocial and biochemical aspects

Preeclampsia is a pregnancy specific disorder commonly defined as de novo hypertension and proteinuria after 20 weeks gestational age. It occurs in approximately 3-5% of pregnancies and it is still a major cause of both foetal and maternal morbidity and mortality worldwide1. As extensive research has not yet elucidated the aetiology of preeclampsia, there are no rational preventive or therapeutic interventions available. The only rational treatment is delivery, which benefits the mother but is not in the interest of the foetus, if remote from term. Early onset preeclampsia (<32 weeks’ gestational age) occurs in less than 1% of pregnancies. It is, however often associated with maternal morbidity as the risk of progression to severe maternal disease is inversely related with gestational age at onset2. Resulting prematurity is therefore the main cause of neonatal mortality and morbidity in patients with severe preeclampsia3. Although the discussion is ongoing, perinatal survival is suggested to be increased in patients with preterm preeclampsia by expectant, non-interventional management. This temporising treatment option to lengthen pregnancy includes the use of antihypertensive medication to control hypertension, magnesium sulphate to prevent eclampsia and corticosteroids to enhance foetal lung maturity4. With optimal maternal haemodynamic status and reassuring foetal condition this results on average in an extension of 2 weeks. Prolongation of these pregnancies is a great challenge for clinicians to balance between potential maternal risks on one the eve hand and possible foetal benefits on the other. Clinical controversies regarding prolongation of preterm preeclamptic pregnancies still exist – also taking into account that preeclampsia is the leading cause of maternal mortality in the Netherlands5 - a debate which is even more pronounced in very preterm pregnancies with questionable foetal viability6-9. Do maternal risks of prolongation of these very early pregnancies outweigh the chances of neonatal survival? Counselling of women with very early onset preeclampsia not only comprises of knowledge of the outcome of those particular pregnancies, but also knowledge of outcomes of future pregnancies of these women is of major clinical importance. This thesis opens with a review of the literature on identifiable risk factors of preeclampsia

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Health care utilization and outcomes in older adults after Traumatic Brain Injury: A CENTER-TBI study

Introduction The incidence of Traumatic Brain Injury (TBI) is increasingly common in older adults aged ≥65 years, forming a growing public health problem. However, older adults are underrepresented in TBI research. Therefore, we aimed to provide an overview of health-care utilization, and of six-month outcomes after TBI and their determinants in older adults who sustained a TBI. Methods We used data from the prospective multi-center Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. In-hospital and post-hospital health care utilization and outcomes were described for patients aged ≥65 years. Ordinal and linear regression analyses were performed to identify determinants of the Glasgow Outcome Scale Extended (GOSE), health-related quality of life (HRQoL), and mental health symptoms six-months post-injury. Results Of 1254 older patients, 45% were admitted to an ICU with a mean length of stay of 9 days. Nearly 30% of the patients received inpatient rehabilitation. In total, 554/1254 older patients completed the six-month follow-up questionnaires. The mortality rate was 9% after mild and 60% after moderate/severe TBI, and full recovery based on GOSE was reported for 44% of patients after mild and 6% after moderate/severe TBI. Higher age and increased injury severity were primarily associated with functional impairment, while pre-injury systemic disease, psychiatric conditions and lower educational level were associated with functional impairment, lower generic and disease-specific HRQoL and mental health symptoms. Conclusion The rate of impairment and disability following TBI in older adults is substantial, and poorer outcomes across domains are associated with worse preinjury health. Nonetheless, a considerable number of patients fully or partially returns to their preinjury functioning. There should not be pessimism about outcomes in older adults who survive.publishedVersio

Measurement invariance of six language versions of the post-traumatic stress disorder checklist for DSM-5 in civilians after traumatic brain injury

Traumatic brain injury (TBI) is frequently associated with neuropsychiatric impairments such as symptoms of post-traumatic stress disorder (PTSD), which can be screened using self-report instruments such as the Post-Traumatic Stress Disorder Checklist for DSM-5 (PCL-5). The current study aims to inspect the factorial validity and cross-linguistic equivalence of the PCL-5 in individuals after TBI with differential severity. Data for six language groups (n ≥ 200; Dutch, English, Finnish, Italian, Norwegian, Spanish) were extracted from the CENTER-TBI study database. Factorial validity of PTSD was evaluated using confirmatory factor analyses (CFA), and compared between four concurrent structural models. A multi-group CFA approach was utilized to investigate the measurement invariance (MI) of the PCL-5 across languages. All structural models showed satisfactory goodness-of-fit with small between-model variation. The original DSM-5 model for PTSD provided solid evidence of MI across the language groups. The current study underlines the validity of the clinical DSM-5 conceptualization of PTSD and demonstrates the comparability of PCL-5 symptom scores between language versions in individuals after TBI. Future studies should apply MI methods to other sociodemographic (e.g., age, gender) and injury-related (e.g., TBI severity) characteristics to improve the monitoring and clinical care of individuals suffering from PTSD symptoms after TBI.publishedVersio

Prognostic Models for Global Functional Outcome and Post-Concussion Symptoms Following Mild Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study

After mild traumatic brain injury (mTBI), a substantial proportion of individuals do not fully recover on the Glasgow Outcome Scale Extended (GOSE) or experience persistent post-concussion symptoms (PPCS). We aimed to develop prognostic models for the GOSE and PPCS at 6 months after mTBI and to assess the prognostic value of different categories of predictors (clinical variables; questionnaires; computed tomography [CT]; blood biomarkers). From the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we included participants aged 16 or older with Glasgow Coma Score (GCS) 13-15. We used ordinal logistic regression to model the relationship between predictors and the GOSE, and linear regression to model the relationship between predictors and the Rivermead Post-concussion Symptoms Questionnaire (RPQ) total score. First, we studied a pre-specified Core model. Next, we extended the Core model with other clinical and sociodemographic variables available at presentation (Clinical model). The Clinical model was then extended with variables assessed before discharge from hospital: early post-concussion symptoms, CT variables, biomarkers, or all three categories (extended models). In a subset of patients mostly discharged home from the emergency department, the Clinical model was extended with 2-3–week post-concussion and mental health symptoms. Predictors were selected based on Akaike's Information Criterion. Performance of ordinal models was expressed as a concordance index (C) and performance of linear models as proportion of variance explained (R2). Bootstrap validation was used to correct for optimism. We included 2376 mTBI patients with 6-month GOSE and 1605 patients with 6-month RPQ. The Core and Clinical models for GOSE showed moderate discrimination (C = 0.68 95% confidence interval 0.68 to 0.70 and C = 0.70[0.69 to 0.71], respectively) and injury severity was the strongest predictor. The extended models had better discriminative ability (C = 0.71[0.69 to 0.72] with early symptoms; 0.71[0.70 to 0.72] with CT variables or with blood biomarkers; 0.72[0.71 to 0.73] with all three categories). The performance of models for RPQ was modest (R2 = 4% Core; R2 = 9% Clinical), and extensions with early symptoms increased the R2 to 12%. The 2-3-week models had better performance for both outcomes in the subset of participants with these symptoms measured (C = 0.74 [0.71 to 0.78] vs. C = 0.63[0.61 to 0.67] for GOSE; R2 = 37% vs. 6% for RPQ). In conclusion, the models based on variables available before discharge have moderate performance for the prediction of GOSE and poor performance for the prediction of PPCS. Symptoms assessed at 2-3 weeks are required for better predictive ability of both outcomes. The performance of the proposed models should be examined in independent cohorts.publishedVersio

Imaging Findings in Acute Traumatic Brain Injury: a National Institute of Neurological Disorders and Stroke Common Data Element-Based Pictorial Review and Analysis of Over 4000 Admission Brain Computed Tomography Scans from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study

publishedVersio

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

Search for anomalous production of events with three or more leptons in pp collisions at √s = 8TeV

Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published articles title, journal citation, and DOI.A search for physics beyond the standard model in events with at least three leptons is presented. The data sample, corresponding to an integrated luminosity of 19.5fb-1 of proton-proton collisions with center-of-mass energy s=8TeV, was collected by the CMS experiment at the LHC during 2012. The data are divided into exclusive categories based on the number of leptons and their flavor, the presence or absence of an opposite-sign, same-flavor lepton pair (OSSF), the invariant mass of the OSSF pair, the presence or absence of a tagged bottom-quark jet, the number of identified hadronically decaying τ leptons, and the magnitude of the missing transverse energy and of the scalar sum of jet transverse momenta. The numbers of observed events are found to be consistent with the expected numbers from standard model processes, and limits are placed on new-physics scenarios that yield multilepton final states. In particular, scenarios that predict Higgs boson production in the context of supersymmetric decay chains are examined. We also place a 95% confidence level upper limit of 1.3% on the branching fraction for the decay of a top quark to a charm quark and a Higgs boson (t→cH), which translates to a bound on the left- and right-handed top-charm flavor-violating Higgs Yukawa couplings, λtcH and λctH, respectively, of |λtcH|2+|λctH|2<0.21

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe