Cardiac biomarkers and clinical scores for risk stratification in elderly patients with non-high-risk pulmonary embolism.

OBJECTIVE To determine the prognostic accuracy of cardiac biomarkers alone and in combination with clinical scores in elderly patients with non-high-risk pulmonary embolism (PE). DESIGN Ancillary analysis of a Swiss multicentre prospective cohort study. SUBJECTS A total of 230 patients aged ≥65 years with non-high-risk PE. MAIN OUTCOME MEASURES The study end-point was a composite of PE-related complications, defined as PE-related death, recurrent venous thromboembolism or major bleeding during a follow-up of 30 days. The prognostic accuracy of the Pulmonary Embolism Severity Index (PESI), the Geneva Prognostic Score (GPS), the precursor of brain natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) was determined using sensitivity, specificity, predictive values, receiver operating characteristic (ROC) curve analysis, logistic regression and reclassification statistics. RESULTS The overall complication rate during follow-up was 8.7%. hs-cTnT achieved the highest prognostic accuracy [area under the ROC curve: 0.75, 95% confidence interval (CI): 0.63-0.86, P < 0.001). At the predefined cut-off values, the negative predictive values of the biomarkers were above 95%. For levels above the cut-off, the risk of complications increased fivefold for hs-cTnT [odds ratio (OR): 5.22, 95% CI: 1.49-18.25] and 14-fold for NT-proBNP (OR: 14.21, 95% CI: 1.73-116.93) after adjustment for both clinical scores and renal function. Reclassification statistics indicated that adding hs-cTnT to the GPS or the PESI significantly improved the prognostic accuracy of both clinical scores. CONCLUSION In elderly patients with nonmassive PE, NT-proBNP or hs-cTnT could be an adequate alternative to clinical scores for identifying low-risk individuals suitable for outpatient management.

Stratification of high-risk prostate cancer into prognostic categories: a European multi-institutional study

BACKGROUND High-risk prostate cancer (PCa) is an extremely heterogeneous disease. A clear definition of prognostic subgroups is mandatory. OBJECTIVE To develop a pretreatment prognostic model for PCa-specific survival (PCSS) in high-risk PCa based on combinations of unfavorable risk factors. DESIGN, SETTING, AND PARTICIPANTS We conducted a retrospective multicenter cohort study including 1360 consecutive patients with high-risk PCa treated at eight European high-volume centers. INTERVENTION Retropubic radical prostatectomy with pelvic lymphadenectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Two Cox multivariable regression models were constructed to predict PCSS as a function of dichotomization of clinical stage (< cT3 vs cT3-4), Gleason score (GS) (2-7 vs 8-10), and prostate-specific antigen (PSA; ≤ 20 ng/ml vs > 20 ng/ml). The first "extended" model includes all seven possible combinations; the second "simplified" model includes three subgroups: a good prognosis subgroup (one single high-risk factor); an intermediate prognosis subgroup (PSA >20 ng/ml and stage cT3-4); and a poor prognosis subgroup (GS 8-10 in combination with at least one other high-risk factor). The predictive accuracy of the models was summarized and compared. Survival estimates and clinical and pathologic outcomes were compared between the three subgroups. RESULTS AND LIMITATIONS The simplified model yielded an R(2) of 33% with a 5-yr area under the curve (AUC) of 0.70 with no significant loss of predictive accuracy compared with the extended model (R(2): 34%; AUC: 0.71). The 5- and 10-yr PCSS rates were 98.7% and 95.4%, 96.5% and 88.3%, 88.8% and 79.7%, for the good, intermediate, and poor prognosis subgroups, respectively (p = 0.0003). Overall survival, clinical progression-free survival, and histopathologic outcomes significantly worsened in a stepwise fashion from the good to the poor prognosis subgroups. Limitations of the study are the retrospective design and the long study period. CONCLUSIONS This study presents an intuitive and easy-to-use stratification of high-risk PCa into three prognostic subgroups. The model is useful for counseling and decision making in the pretreatment setting.

Measuring depression with a well-being index: Further evidence for the validity of the WHO Well-Being Index (WHO-5) as a measure of the severity of depression

BACKGROUND: In recent years, the WHO Wellbeing Index (WHO-5) has been used as a screening measure for depression. Nevertheless, research on the validity of this measure in the context of clinical depression is sparse. QUESTIONS: The aim of the present study was to investigate the measurement invariance of the WHO-5 across depressed and non-depressed individuals, as well as the shape and specificity of its relationship to measures of depression severity. METHOD: Of the 414 subjects who completed the WHO-5 and the Beck Depression Inventory-II (BDI-II), 207 had a diagnosis of a major depressive episode (MDE). A subsample also completed the Beck Anxiety Inventory (BAI) and was assessed by clinicians using the Hamilton Depression Rating Scale (HAM-D) and the Hamilton Anxiety Rating Scale (HAM-A). RESULTS: The WHO-5 demonstrated strong measurement invariance regarding the presence or absence of a current MDE. The WHO-5 showed a very high negative association with self- and observer-rated measures of depressive symptoms, especially in the range of mild to moderate symptoms. These associations were still substantial after controlling for measures of anxiety symptoms. LIMITATIONS: In addition to a diagnostic interview, only one measure for self- and observer-rated symptoms of depression was used. Furthermore, the observer-rated measure was only assessed in one subsample that exhibited a somewhat restricted range of depression severity. CONCLUSION: Although this index was originally designed as a measure of well-being, the results support the use of the WHO-5 in the context of depression research.

A new measure for party coherence: Applying a physics-based concept to the Swiss party system

The paper revives a theoretical definition of party coherence as being composed of two basic elements, cohesion and factionalism, to propose and apply a novel empirical measure based on spin physics. The simultaneous analysis of both components using a single measurement concept is applied to data representing the political beliefs of candidates in the Swiss general elections of 2003 and 2007, proposing a connection between the coherence of the beliefs party members hold and the assessment of parties being at risk of splitting. We also compare our measure with established polarization measures and demonstrate its advantage with respect to multi-dimensional data that lack clear structure. Furthermore, we outline how our analysis supports the distinction between bottom-up and top-down mechanisms of party splitting. In this way, we are able to turn the intuition of coherence into a defined quantitative concept that, additionally, offers a methodological basis for comparative research of party coherence. Our work serves as an example of how a complex systems approach allows to get a new perspective on a long-standing issue in political science.

Global diversity, population stratification and selection of human copy number variation

In order to explore the diversity and selective signatures of duplication and deletion human copy number variants (CNVs), we sequenced 236 individuals from 125 distinct human populations. We observed that duplications exhibit fundamentally different population genetic and selective signatures than deletions and are more likely to be stratified between human populations. Through reconstruction of the ancestral human genome, we identify megabases of DNA lost in different human lineages and pinpoint large duplications that introgressed from the extinct Denisova lineage now found at high frequency exclusively in Oceanic populations. We find that the proportion of CNV base pairs to single nucleotide variant base pairs is greater among non-Africans than it is among African populations, but we conclude that this difference is likely due to unique aspects of non-African population history as opposed to differences in CNV load.

The capabilities of ROSINA/DFMS to measure argon isotopes at comet 67P/Churyumov–Gerasimenko

Little is known about the noble gas abundances in comets. These highly volatile atoms are possible tracers of the history of cometary matter including the thermal evolution. They can help quantify the contribution of cometary impacts to terrestrial oceans and help elucidate on the formation history of comets and their role in the formation and evolution of planetary atmospheres. This paper focuses on argon and the capabilities to measure this noble gas with in situ mass spectrometry at comet 67P/Churyumov–Gerasimenko, the target of the European Space Agency׳s spacecraft Rosetta. Argon may have been detected by remote sensing in a single Oort cloud comet but to date nothing is known about the isotopic abundances of argon in comets. Furthermore, no detection of argon in a Jupiter-family comet has been reported. Comet 67P/Churyumov–Gerasimenko belongs to the group of Jupiter-family comets and originates most likely in the Kuiper belt. Onboard Rosetta is ROSINA/DFMS (Rosetta Orbiter Spectrometer for Ion and Neutral Analysis/Double Focusing Mass Spectrometer). DFMS has unprecedented mass resolution and high sensitivity and is designed to measure isotopic ratios including argon (Balsiger et al., 2007). Argon measurements using the DFMS lab model (identical to the flight model) demonstrate this capability. At very least, this mass spectrometer has the resolution and sensitivity to reduce the upper limit on the argon outgassing rate relative to water by more than three orders of magnitude (for 38Ar). Most likely, ROSINA/DFMS will provide the first detection of argon in a Jupiter-family comet together with the first determination of the ³⁶Ar/³⁸Ar ratio at a comet.

Validity of SYNTAX score II for risk stratification of percutaneous coronary interventions: A patient-level pooled analysis of 5,433 patients enrolled in contemporary coronary stent trials.

OBJECTIVES To assess the clinical profile and long-term mortality in SYNTAX score II based strata of patients who received percutaneous coronary interventions (PCI) in contemporary randomized trials. BACKGROUND The SYNTAX score II was developed in the randomized, all-comers' SYNTAX trial population and is composed by 2 anatomical and 6 clinical variables. The interaction of these variables with the treatment provides individual long-term mortality predictions if a patient undergoes coronary artery bypass grafting (CABG) or PCI. METHODS Patient-level (n=5433) data from 7 contemporary coronary drug-eluting stent (DES) trials were pooled. The mortality for CABG or PCI was estimated for every patient. The difference in mortality estimates for these two revascularization strategies was used to divide the patients into three groups of theoretical treatment recommendations: PCI, CABG or PCI/CABG (the latter means equipoise between CABG and PCI for long term mortality). RESULTS The three groups had marked differences in their baseline characteristics. According to the predicted risk differences, 5115 patients could be treated either by PCI or CABG, 271 should be treated only by PCI and, rarely, CABG (n=47) was recommended. At 3-year follow-up, according to the SYNTAX score II recommendations, patients recommended for CABG had higher mortality compared to the PCI and PCI/CABG groups (17.4%; 6.1% and 5.3%, respectively; P<0.01). CONCLUSIONS The SYNTAX score II demonstrated capability to help in stratifying PCI procedures.

Three Experimental Approaches to Measure the Social Context Dependence of Prejudice Communication and Discriminatory Behavior

Empirical research on discrimination is faced with crucial problems stemming from the specific character of its object of study. In democratic societies the communication of prejudices and other forms of discriminatory behavior is considered socially undesirable and depends on situational factors such as whether a situation is considered private or whether a discriminatory consensus can be assumed. Regular surveys thus can only offer a blurred picture of the phenomenon. But also survey experiments intended to decrease the social desirability bias (SDB) so far failed in systematically implementing situational variables. This paper introduces three experimental approaches to improve the study of discrimination and other topics of social (un-)desirability. First, we argue in favor of cognitive context framing in surveys in order to operationalize the salience of situational norms. Second, factorial surveys offer a way to take situational contexts and substitute behavior into account. And third, choice experiments – a rather new method in sociology – offer a more valid method of measuring behavioral characteristics compared to simple items in surveys. All three approaches – which may be combined – are easy to implement in large-scale surveys. Results of empirical studies demonstrate the fruitfulness of each of these approaches.