Predicted Event Rates Research Articles

Comparison of Cardiopulmonary Exercise Test Variables to Predict Adverse Events in Patients with Heart Failure.

Given the rising burden of heart failure (HF), stratification of patients at increased risk for adverse events is critical. We aim to compare the predictive value of various maximal and submaximal cardiopulmonary exercise test (CPET) variables for adverse events in patients with HF. 237 patients with HF (66 [58-73] years, 30% women, 70% HF with reduced ejection fraction) completed a CPET and had five years of follow-up. Baseline characteristics and clinical outcomes (all-cause mortality, major adverse cardiovascular events, and cardiovascular-related hospitalization) were extracted from electronic patient files. Receiver operating characteristics curves for maximal (e.g. peak VO2) and submaximal CPET variables (e.g. VE/VCO2 slope, cardiorespiratory optimal point (COP), VO2 at anaerobic threshold) were compared using the Akaike Information Criterion (AIC) method, whereas their calibration was assessed. 103 participants (43%) reached the composite endpoint, and 55 (23%) died. Percent predicted peak VO2 was the best predictor for adverse outcomes (AIC: 302.6) followed by COP (AIC: 304.3), and relative peak VO2 (mL/(kg·min), AIC: 304.4). Relative peak VO2 (AIC: 217.1) and COP (AIC: 224.4) were also among the three best predictors for mortality, together with absolute peak VO2 (ml/min, AIC: 220.5). A good calibration between observed and predicted event rate was observed for these variables. Percent predicated and relative peak VO2 had the best predictive accuracy for adverse events and mortality, but the submaximal COP had a non-inferior predictive accuracy for adverse events in patients with HF. These findings highlight the potential of submaximal exercise testing in patients with HF.

Indirect search of heavy neutral leptons using the DUNE near detector

We evaluate the potential of the DUNE near detector (DUNEND) for establishing bounds for heavy neutral leptons (HNLs). This is achieved by studying how the presence of HNLs affects the production rates of active neutrinos, therefore creating a deficit in the neutrino charged current (CC) events at the LArTPC of the DUNEND. The estimated bounds on HNLs are calculated for masses between 1 eV and 500 MeV. We consider 10 years of operation (five in neutrino and antineutrino modes) and obtain limits of |Uμ4|2 < 9 × 10−3 (4 × 10−2) and |Ue4|2 < 7 × 10−3 (3 × 10−2) for masses below 10 MeV and a 5% (20%) overall normalization uncertainty in the neutrino charged current event rate prediction. These limits, within the region of masses below 2 (10) MeV, are better than those that can be achieved by DUNE direct searches for the case of a 5% (20%) uncertainty. When a conservative 20% uncertainty is present, our limits can only improve current constraints on |Ue4|2 by up to a factor of 3 in a small region of approximately 5 eV and set limits on |Uμ4|2 in a mass region free of constraints (40 eV–1 MeV).

Retrospective validation study of an artificial neural network-based preoperative decision-support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN14341750)

BackgroundSurgical sentinel lymph node biopsy (SLNB) is routinely used to reliably stage axillary lymph nodes in early breast cancer (BC). However, SLNB may be associated with postoperative arm morbidities. For most patients with BC undergoing SLNB, the findings are benign, and the procedure is currently questioned. A decision-support tool for the prediction of benign sentinel lymph nodes based on preoperatively available data has been developed using artificial neural network modelling.MethodsThis was a retrospective geographical and temporal validation study of the noninvasive lymph node staging (NILS) model, based on preoperatively available data from 586 women consecutively diagnosed with primary BC at two sites. Ten preoperative clinicopathological characteristics from each patient were entered into the web-based calculator, and the probability of benign lymph nodes was predicted. The performance of the NILS model was assessed in terms of discrimination with the area under the receiver operating characteristic curve (AUC) and calibration, that is, comparison of the observed and predicted event rates of benign axillary nodal status (N0) using calibration slope and intercept. The primary endpoint was axillary nodal status (discrimination, benign [N0] vs. metastatic axillary nodal status [N+]) determined by the NILS model compared to nodal status by definitive pathology.ResultsThe mean age of the women in the cohort was 65 years, and most of them (93%) had luminal cancers. Approximately three-fourths of the patients had no metastases in SLNB (N0 74% and 73%, respectively). The AUC for the predicted probabilities for the whole cohort was 0.6741 (95% confidence interval: 0.6255–0.7227). More than one in four patients (n = 151, 26%) were identified as candidates for SLNB omission when applying the predefined cut-off for lymph node-negative status from the development cohort. The NILS model showed the best calibration in patients with a predicted high probability of healthy axilla.ConclusionThe performance of the NILS model was satisfactory. In approximately every fourth patient, SLNB could potentially be omitted. Considering the shift from postoperatively to preoperatively available predictors in this validation study, we have demonstrated the robustness of the NILS model. The clinical usability of the web interface will be evaluated before its clinical implementation.Trial registrationRegistered in the ISRCTN registry with study ID ISRCTN14341750.Date of registration 23/11/2018.

Performance of Cardiovascular Risk Prediction Models in Korean Patients With New-Onset Rheumatoid Arthritis: National Cohort Study.

This study aimed to compare the performance of established cardiovascular risk algorithms in Korean patients with new-onset rheumatoid arthritis. This retrospective cohort study identified patients newly diagnosed with rheumatoid arthritis without a history of cardiovascular diseases between 2013 and 2019 using the National Health Insurance Service database. The cohort was followed up until 2020 for the development of the first major adverse cardiovascular event. General cardiovascular risk prediction algorithms, such as the systematic coronary risk evaluation model, the Korean risk prediction model for atherosclerotic cardiovascular diseases, the American College of Cardiology/American Heart Association pooled equations, and the Framingham Risk Score, were used. The discrimination and calibration of cardiovascular risk prediction models were evaluated. Hazard ratios were estimated using Cox proportional hazards regression. A total of 611 patients among 24 889 patients experienced a major adverse cardiovascular event during follow-up. The median 10-year atherosclerotic cardiovascular diseases risk score was significantly higher in patients with major adverse cardiovascular events than those without. The C-statistics of risk algorithms ranged between 0.72 and 0.74. Compared with the low-risk group, the actual risk of developing major adverse cardiovascular events increased significantly in the intermediate- and high-risk groups for all algorithms. However, the risk predictions calculated from all algorithms overestimated the observed cardiovascular risk in the middle to high deciles, and only the systematic coronary risk evaluation algorithm showed comparable observed and predicted event rates in the low-intermediate deciles with the highest sensitivity. The systematic coronary risk evaluation model algorithm and the general risk prediction models discriminated patients with rheumatoid arthritis appropriately. However, overestimation should be considered when applying the cardiovascular risk prediction model in Korean patients.

Lipoprotein(a) and the pooled cohort equations for ASCVD risk prediction: The Multi-Ethnic Study of Atherosclerosis

Background and aimsLipoprotein(a) [Lp(a)] is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD) but is not included in the Pooled Cohort Equations (PCE). We aimed to assess how well the PCE predict 10-year event rates in individuals with elevated Lp(a), and whether the addition of Lp(a) improves risk prediction. MethodsWe compared observed versus PCE-predicted 10-year ASCVD event rates, stratified by Lp(a) level and ASCVD risk category using Poisson regression, and evaluated the association between Lp(a) > 50 mg/dL and ASCVD risk using Cox proportional hazards models in the Multi-Ethnic Study of Atherosclerosis (MESA). We evaluated the C-index and net reclassification improvement (NRI) with addition of Lp(a) to the PCE. ResultsThe study population included 6639 individuals (20%, n = 1325 with elevated Lp(a)). The PCE accurately predicted 10-year event rates for individuals with elevated Lp(a) with observed event rates falling within predicted limits. Elevated Lp(a) was associated with increased risk of CVD events overall (HR 1.27, 95% CI 1.00–1.60), particularly in low (HR 2.45, 95% CI 1.40–4.31), and high-risk (HR 1.41, 95% CI 1.02–1.96) individuals. Continuous NRI (95% CI) with the addition of Lp(a) to the PCE for CVD was 0.0963 (0.0158–0.1953) overall, and 0.2999 (0.0876, 0.5525) among low-risk individuals. ConclusionsThe PCE performs well for event rate prediction in individuals with elevated Lp(a). However, Lp(a) is associated with increased CVD risk, and the addition of Lp(a) to the PCE improves risk prediction, particularly among low-risk individuals. These results lend support for increasing use of Lp(a) testing for risk assessment.

Predicting 1-Year Mortality in Outpatients With Heart Failure With Reduced Left Ventricular Ejection Fraction: Do Empiric Models Outperform Physician Intuitive Estimates? A Multicenter Cohort Study.

Many studies have demonstrated that physicians often err in estimating patient prognosis. No studies have directly compared physician to model predictive performance in heart failure (HF). We aimed to compare the accuracy of physician versus model predictions of 1-year mortality. This multicenter prospective cohort study on 11 HF clinics in 5 provinces in Canada included consecutive consented outpatients with HF with reduced left ventricular ejection fraction (<40%). By collecting clinical data, we calculated predicted 1-year mortality using the Seattle HF Model (SHFM), the Meta-Analysis Global Group in Chronic HF score, and the HF Meta-Score. HF cardiologists and family doctors, blinded to model predictions, estimated patient 1-year mortality. During 1-year follow-up, we recorded the composite end point of mortality, urgent ventricular assist device implant, or heart transplant. We compared physicians and model discrimination (C statistic), calibration (observed versus predicted event rate), and risk reclassification. The study included 1643 patients with ambulatory HF with a mean age of 65 years, 24% female, and mean left ventricular ejection fraction of 28%. Over 1-year follow-up, 9% had an event. The SHFM had the best discrimination (SHFM C statistic 0.76; HF Meta-Score 0.73; Meta-Analysis Global Group in Chronic Heart Failure 0.70) and calibration. Physicians' discrimination differed little (0.75 for HF cardiologists and 0.73 for family doctors) but both physician groups substantially overestimated risk by >10% in both low- and high-risk patients (poor calibration). In risk reclassification analysis, among patients without events, the SHFM better classified 51% in comparison to HF cardiologists and 43% in comparison to family doctors. In patients with events, the SHFM erroneously assigned lower risk to 44% in comparison to HF cardiologists and 34% in comparison to family doctors. Family doctors and HF cardiologists showed adequate risk discrimination, with however substantial overestimation of absolute risk. Predictive models showed higher accuracy. Incorporating models in family and HF cardiology practices may improve patient care and resource use in HF with reduced left ventricular ejection fraction. URL: https://www. gov; Unique identifier: NCT04009798.

Neutrino structure functions from GeV to EeV energies

The interpretation of present and future neutrino experiments requires accurate theoretical predictions for neutrino-nucleus scattering rates. Neutrino structure functions can be reliably evaluated in the deep-inelastic scattering regime within the perturbative QCD (pQCD) framework. At low momentum transfers (Q2 ≲ few GeV2), inelastic structure functions are however affected by large uncertainties which distort event rate predictions for neutrino energies Eν up to the TeV scale. Here we present a determination of neutrino inelastic structure functions valid for the complete range of energies relevant for phenomenology, from the GeV region entering oscillation analyses to the multi-EeV region accessible at neutrino telescopes. Our NNSFν approach combines a machine-learning parametrisation of experimental data with pQCD calculations based on state-of-the-art analyses of proton and nuclear parton distributions (PDFs). We compare our determination to other calculations, in particular to the popular Bodek-Yang model. We provide updated predictions for inclusive cross sections for a range of energies and target nuclei, including those relevant for LHC far-forward neutrino experiments such as FASERν, SND@LHC, and the Forward Physics Facility. The NNSFν determination is made available as fast interpolation LHAPDF grids, and it can be accessed both through an independent driver code and directly interfaced to neutrino event generators such as GENIE.

Long-term outcomes of successful left atrial appendage occlusion with focus on stroke prevention: 10-year follow-up of a single-center registry.

Percutaneous left atrial appendage occlusion (LAAO) is an alternative to anticoagulation in the prevention of stroke in patients with nonvalvular atrial fibrillation, especially in patients with a contraindication for oral anticoagulation therapy (OAT). The study sought to obtain long-term patient outcomes after successful LAAO in everyday clinical practice. In this single-center registry spanning over 10 years, data of all consecutive patients that underwent percutaneous LAAO were collected. Observed thromboembolic and major bleeding event rates after successful LAAO during follow-up were compared with expected event rates based on CHA2DS2-VASc (congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism, vascular disease, age 65-74 years, sex category) and HAS-BLED (hypertension, abnormal renal or liver function, stroke, bleeding, labile international normalized ratio, elderly, drugs or alcohol) scores. Furthermore, anticoagulation and antiplatelet use during follow-up was evaluated. Of 230 patients scheduled for LAAO (38% women, 69.5 ± 8.2 years of age, CHA2DS2-VASc score 3.9 ± 1.6, HAS-BLED score 2.9 ± 1.0), 218 patients had a successful implantation (95%) with a follow-up duration of 5.2 ± 3.1 years. The procedure was combined with catheter ablation in 52% of the patients. Fifty thromboembolic complications (24 ischemic stroke, 26 transient ischemic attack) were observed during follow-up in 40 (18%) of 218 patients. Ischemic strokes occurred with a rate of 2.1 per 100 patient-years, accounting for a 66% relative risk reduction compared with the CHA2DS2-VASc predicted event rate. Device-related thrombus was observed in 5 (2%) patients. Sixty-five nonprocedural major bleeding complications occurred in 24 (11%) of 218 patients with a rate of 5.7 per 100-patient years, which is comparable to estimated HAS-BLED-bleeding rates under OAT use. At end of follow-up 71% of all patients were on single antiplatelet or no antiplatelet or anticoagulation treatment, while 29% were on OAT. Thromboembolic event rates during long-term follow-up after successful LAAO remained consistently lower than expected supporting the efficacy of LAAO.

Mass-Dependent Critical Value Expressions for Particle Finding in Single-Particle ICP-TOFMS.

In time-of-flight mass spectrometry (TOFMS), ion detection is often achieved via electron multiplication followed by fast analog-to-digital conversion (ADC). This detection approach is chosen over time-to-digital conversion because it extends the dynamic range of TOFMS measurements, especially for transient analyses. However, fast ADC detection also introduces measurement noise fundamental to the electron multiplication process. In previous research, we demonstrated that TOFMS signals acquired with fast ADC follow a compound Poisson distribution in which the Poisson-distributed arrival of ions at the detector is compounded with the response profile of the electron multiplier. Here, we consider the influence of mass-to-charge (m/z)-dependent detector responses and their impact on particle-finding accuracy in single-particle inductively coupled plasma TOFMS (spICP-TOFMS). In spICP-TOFMS, highly time-resolved ion signals are recorded and particle signals are distinguished from background signals based on thresholding the data at m/z-specific critical values. Through Monte Carlo modeling with measured m/z-dependent detector responses, we generate compound Poisson model distributions and critical values that accurately account for the dispersion of measured signals. We test the accuracy of critical values through the analysis of dissolved element solutions and comparison of measured versus predicted event rates above critical value thresholds. The use of m/z-dependent compound Poisson critical values reduces false-positive particle identifications by one to two orders of magnitude compared to thresholding criteria based on normal or Poisson statistics. The improved accuracy and robustness of compound Poisson critical values enables automated multi-element particle finding in spICP-TOFMS.

Stroke Prevention With Left Atrial Appendage Closure in Patients With Atrial Fibrillation and Prior Intracranial Hemorrhage

BackgroundOral anticoagulation (OAC) is deemed a relative contraindication after intracranial hemorrhage (ICH) if the cause cannot be eliminated and the risk of recurrence is high. That leaves atrial fibrillation (AF) patients at high risk of thromboembolic events. Endovascular left atrial appendage closure (LAAC) can be an alternative to OAC for patients requiring stroke prevention. MethodsWe performed a retrospective single-centre analysis of 138 consecutive ICH patients with nonvalvular AF and high stroke risk who underwent LAAC between 2010 and 2022 at Vancouver General Hospital. We report the baseline characteristics, procedural results, and follow-up data, comparing the observed stroke/transient ischemic attack (TIA) rate with the predicted event rate based on their CHA2DS2-VASc scores. ResultsThe average age was 76.1 ± 8.5 years; the mean CHA2DS2-VASc score was 4.4 ± 1.5; and the mean HAS-BLED score was 3.7 ± 0.9. The procedural success rate was 98.6%, and the complication rate was 3.6% with no periprocedural death, stroke, or TIA. The antithrombotic regimen post-LAAC consisted of short-term dual antiplatelet therapy (1-6 months) followed by aspirin alone for a minimum of 6 months in 86.2%. At mean follow-up of 14.7 ± 13.7 months, 9 deaths (6.5%, 7 cardiovascular, 2 noncardiovascular), 2 strokes (1.4%), and 1 TIA (0.7%) had occurred. The annualized observed stroke/TIA rate was 1.8%, which was lower than the adjusted predicted stroke rate of 7.0% (95% confidence interval: 4.8%-9.2%). Two patients (1.5%) suffered another ICH (both on aspirin monotherapy). One device-related thrombus (0.7%) was confirmed and treated with OAC without sequelae. ConclusionEndovascular LAAC is a feasible alternative to OAC for stroke prevention in patients with nonvalvular AF and prior ICH.

Risk stratification of perioperative myocardial infarction/injury following noncardiac surgery in high risk patients

Abstract Background Perioperative myocardial infarction/injury (PMI) screening is increasingly recommended by current guidelines. PMI is often caused by type 2 myocardial infarction, and risk stratification tools for these patients are lacking. Purpose To derive and internally validate a risk prognostication model for PMI of likely type 2 infarction (lT2MI) Methods We included consecutive high-risk patients undergoing noncardiac surgery into this prospective multicenter study. Patients received a systematic routine PMI screening with pre- and postoperative measurement of cardiac troponin (cTn). PMI was prospectively defined as an absolute increase of cTn above the preoperative value. PMI etiology was centrally adjudicated and hierarchically classified by 2 independent physicians based on all clinical information obtained during index hospitalization and selected those with lT2MI for further analyses. To identify risk factors and allow risk stratification in lT2MI, we prespecified that only perioperative variables should be included into the model. We constructed a logistic binary regression model for major adverse cardiac events (MACE) within 120 days, including variables available at time of clinical evaluation: additional symptoms or ECG-criteria required according to the Universal Definition of Myocardial Infarction, absolute increase in cTn (categorized according to level of absolute increase 1–&amp;lt;2 times the 99th percentile, ≥2 to &amp;lt;4 times, and ≥4 times), urgency of procedure, perioperative bleeding (drop in haemoglobin &amp;gt;30g/L or deemed relevant for PMI by adjudicator), and ESC/ESA surgery risk (low, medium, high risk of cardiac events). Variables were omitted from the final model if the p-value was &amp;gt;0.05. Variable levels with similar odds ratios were grouped for simplification of the prognostic model. We constructed a calibration plot and calculated the area under the receiver-operating characteristics curve (AUC) and Brier Score. For internal validation we calculated the predicted probabilities and classified patients into low-risk (predicted event rate &amp;lt;10%), intermediate range (10–20%), and high-risk (&amp;gt;20%), and compared the predicted with the observed event rate. Results PMI occurred in 1016/7754 patients (13.1%) of which 750/1016 (73.8%) were adjudicated as lT2MI. MACE within 120 days occurred in 118/750 (15.7%) patients. The initial and final logistic prognostic model for 120-day MACE or death is shown in the table. Internal validation found a good fit of predicted and observed event rate following bootstrapping of 1000 iterations (Figure 1), a good AUC of 0.71 and a Brier score of 0.12. Conclusion The derived risk prognostication model for PMI of lT2MI can aid in the stratification of patients and support clinical decision making following noncardiac surgery. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Swiss National Science FoundationSwiss Heart Foundation

Gusts in the headwind: uncertainties in direct dark matter detection

ABSTRACT We use high-resolution, hydrodynamic, galaxy simulations from the Latte suite of FIRE-2 simulations to investigate the inherent variation of dark matter in sub-sampled regions around the Solar Circle of a Milky Way-type analogue galaxy and its impact on direct dark matter detection. These simulations show that the baryonic back reaction, as well as the assembly history of substructures, has lasting impacts on the dark matter’s spatial and velocity distributions. These are experienced as ‘gusts’ of dark matter wind around the Solar Circle, potentially complicating interpretations of direct detection experiments on Earth. We find that the velocity distribution function in the galactocentric frame shows strong deviations from the Maxwell Boltzmann form typically assumed in the fiducial Standard Halo Model, indicating the presence of high-velocity substructures. By introducing a new numerical integration technique that removes any dependencies on the Standard Halo Model, we generate event-rate predictions for both single-element Germanium and compound Sodium Iodide detectors, and explore how the variability of dark matter around the Solar Circle influences annual modulation signal predictions. We find that these velocity substructures contribute additional astrophysical uncertainty to the interpretation of event rates, although their impact on summary statistics, such as the peak day of annual modulation, is generally low.

The Effect of Metallicity on the Formation of Massive Black Holes through Stellar Collisions in Young Massive Star Clusters

Dynamical interactions facilitated by the high densities in massive star clusters can lead to large numbers of stellar collisions and unique stellar evolution pathways not possible for stars evolving in isolation. Using N-body cluster models, we study the role of stellar collisions in the formation of massive black holes, specifically studying the effect of stellar metallicity on this process. We show that at high metallicity (up to solar), the number of massive black holes formed may be reduced by up to a factor of ten compared to low-metallicity clusters. We also examine the role of collisions in the production of pair-instability supernovae and predict event rates of these transients in the local universe.

The NILS Study Protocol: A Retrospective Validation Study of an Artificial Neural Network Based Preoperative Decision-Making Tool for Noninvasive Lymph Node Staging in Women with Primary Breast Cancer (ISRCTN14341750).

Newly diagnosed breast cancer (BC) patients with clinical T1–T2 N0 disease undergo sentinel-lymph-node (SLN) biopsy, although most of them have a benign SLN. The pilot noninvasive lymph node staging (NILS) artificial neural network (ANN) model to predict nodal status was published in 2019, showing the potential to identify patients with a low risk of SLN metastasis. The aim of this study is to assess the performance measures of the model after a web-based implementation for the prediction of a healthy SLN in clinically N0 BC patients. This retrospective study was designed to validate the NILS prediction model for SLN status using preoperatively available clinicopathological and radiological data. The model results in an estimated probability of a healthy SLN for each study participant. Our primary endpoint is to report on the performance of the NILS prediction model to distinguish between healthy and metastatic SLNs (N0 vs. N+) and compare the observed and predicted event rates of benign SLNs. After validation, the prediction model may assist medical professionals and BC patients in shared decision making on omitting SLN biopsies in patients predicted to be node-negative by the NILS model. This study was prospectively registered in the ISRCTN registry (identification number: 14341750).

Reduced cardiovascular morbidity in patients with hemophilia: results of a 5-year multinational prospective study

AbstractHemophilia is a congenital bleeding disorder caused by low levels of clotting factor VIII or IX. The life expectancy of people with hemophilia (PWH) has increased with the availability of clotting factor concentrates. At the same time, the incidence of cardiovascular disease (CVD) has increased; in retrospective studies, there are conflicting data regarding if, despite this increase, the incidence is still lower than in the general population. We prospectively compared the incidence of CVD in PWH vs the predicted incidence. This prospective, multicenter, observational study included adult PWH (aged >30 years) from The Netherlands and United Kingdom. They were followed up for a 5-year period, and CVD incidence was compared with a predicted event rate based on the QRISK2-2011 CVD risk model. The primary end point was the observed fatal and nonfatal CVD incidence after 5 years compared with the estimated events and in relation to severity of hemophilia. The study included 709 patients, of whom 687 (96.9%) completed 5 years' follow-up or reached an end point. For 108 patients, the QRISK score could not be calculated at inclusion. For the remaining 579, fewer CVD events were observed than predicted: 9 vs 24 (relative risk, 0.38; 95% confidence interval, 0.18-0.80; P = .01), corresponding with an absolute risk reduction of 2.4%. Severe hemophilia treated on demand had the highest risk reduction. There was no statistically significant relation between severity of hemophilia and incidence of CVD. In hemophilia, a lower-than-predicted CVD incidence was found, supporting the theory that hemophilia protects against CVD. The study is registered at www.clinicaltrials.gov as #NCT01303900.

Obscura: A modular C++ tool and library for the direct detection of (sub-GeV) dark matter via nuclear and electron recoils

For the interpretation of past and future direct searches for dark matter (DM) particles, it is important to be able to provide accurate predictions for event rates and spectra under a variety of possible and viable assumptions in a computationally efficient way. While there exists a few tools to compute DM induced nuclear recoil spectra, 'obscura' is not limited to nuclear targets. Instead its main focus lies on sub-GeV DM searches probing electron recoils which typically requires methods from atomic and condensed matter physics. In the context of sub-GeV DM searches, new ideas such as target materials or detection techniques are being proposed regularly, and the theoretical modelling of these are getting improved continuously. At the same time, currently running experiments continue to publish their results and analyses, setting increasingly strict bounds on the DM parameter space. In such a dynamic field, 'obscura' can be an invaluable tool due to its high level of adaptability and facilitate and accelerate the development of new, reliable research software for the preparation of a DM discovery in the hopefully near future.

Event rate predictions of strongly lensed gravitational waves with detector networks and more realistic templates

ABSTRACT Strong lensing of gravitational waves (GWs) is attracting growing attention of the community. The event rates of lensed GWs by galaxies were predicted in numerous papers, which used some approximations to evaluate the GW strains detectable by a single detector. The joint detection of GW signals by a network of instruments will increase the detecting ability of fainter and farther GW signals, which could increase the detection rate of the lensed GWs, especially for the 3rd generation detectors, e.g. Einstein Telescope (ET) and Cosmic Explorer (CE). Moreover, realistic GW templates will improve the accuracy of the prediction. In this work, we consider the detection of galaxy-scale lensed GW events under the 2nd, 2.5th, and 3rd generation detectors with the network scenarios and adopt the realistic templates to simulate GW signals. Our forecast is based on the Monte Carlo technique which enables us to take Earth’s rotation into consideration. We find that the overall detection rate is improved, especially for the 3rd generation detector scenarios. More precisely, it increases by ∼37 per cent adopting realistic templates, and under network detection strategy, further increases by ∼58 per cent comparing with adoption of the realistic templates, and we estimate that the 3rd generation GW detectors will detect hundreds lensed events per year. The effect from the Earth’s rotation is weakened in the detector network strategy.

External Validation of the SYNTAX Score II 2020

BackgroundThe SYNTAX score II 2020 (SSII-2020) was derived from cross correlation and externally validated in randomized trials to predict death and major adverse cardiac and cerebrovascular events (MACE) following percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) in patients with 3-vessel disease (3VD) and/or left main coronary artery disease (LMCAD). ObjectivesThe authors aimed to investigate the SSII-2020’s value in identifying the safest modality of revascularization in a non-randomized setting. MethodsFive-year mortality and MACE were assessed in 7,362 patients with 3VD and/or LMCAD enrolled in a Japanese PCI/CABG registry. The discriminative abilities of the SSII-2020 were assessed using Harrell’s C statistic. Agreement between observed and predicted event rates following PCI or CABG and treatment benefit (absolute risk difference [ARD]) for these outcomes were assessed by calibration plots. ResultsThe SSII-2020 for 5-year mortality well predicted the prognosis after PCI and CABG (C-index = 0.72, intercept = −0.11, slope = 0.92). When patients were grouped according to the predicted 5-year mortality ARD, <4.5% (equipoise of PCI and CABG) and ≥4.5% (CABG better), the observed mortality rates after PCI and CABG were not significantly different in patients with lower predicted ARD (observed ARD: 2.1% [95% CI: −0.4% to 4.4%]), and the significant difference in survival in favor of CABG was observed in patients with higher predicted ARD (observed ARD: 9.7% [95% CI: 6.1%-13.3%]). For MACE, the SSII-2020 could not recommend a specific treatment with sufficient accuracy. ConclusionsThe SSII-2020 for predicting 5-year death has the potential to support decision making on revascularization in patients with 3VD and/or LMCAD.

Estimating risk factor progression equations for the UKPDS Outcomes Model 2 (UKPDS 90).

To estimate 13equations that predict clinically plausible risk factor time paths to inform the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model version 2 (UKPDS-OM2). Data from 5102 UKPDS participants from the 20-year trial, and the 4031survivors with 10years further post-trial follow-up, were used to derive equations for the time paths of 13clinical risk factors: HbA1c , systolic blood pressure, LDL-cholesterol, HDL-cholesterol, BMI, micro- or macro-albuminuria, creatinine, heart rate, white blood cell count, haemoglobin, estimated glomerular filter rate, atrial fibrillation and peripheral vascular disease (PVD). The incidence of events and death predicted by the UKPDS-OM2 when informed by the new risk factor equations was compared with the observed cumulative rates up to 25years. The new equations were based on 24years of follow-up and up to 65,252 person-years of data. Women were associated with higher values of all continuous risk factors except for haemoglobin. Older age and higher BMI at diagnosis were associated with higher rates of PVD (HR 1.06 and 1.02), atrial fibrillation (HR 1.10 and 1.08) and micro- or macro-albuminuria (HR 1.01 and 1.18). Smoking was associated with higher rates of developing PVD (HR 2.38) and micro- and macro-albuminuria (HR 1.39). The UKPDS-OM2, informed by the new risk factor equations, predicted event rates for complications and death consistent with those observed. The new equations allow risk factor time paths beyond observed data, which should improve modelling of long-term health outcomes for people with type 2 diabetes when using the UKPDS-OM2 or other models.

Effects of cognitive-behavioral and psychodynamic-interpersonal treatments for eating disorders: a meta-analytic inquiry into the role of patient characteristics and change in eating disorder-specific and general psychopathology in remission

BackgroundCognitive behavior therapy (CBT) and psychodynamic-interpersonal therapies (PIT) are two widely used and conceptually different outpatient treatments for eating disorders (EDs). To better understand how these treatments works, for whom, and under what circumstances, there is a need for knowledge about how outcomes are affected by diagnosis, comorbidity, changes in psychopathology, and study design.MethodReports on the effects of CBT and PIT for eating disorders were searched. Rates of remission and changes in ED specific- and general psychopathology were computed. Regression models were made to predict event rates by changes in specific- and general psychopathology, as well as ED diagnosis and study design.ResultsThe remission rate of CBT for binge eating disorder was 50%, significantly higher than the effect for other diagnostic groups (anorexia = 33%, bulimia: 28%, mixed samples 30%). The number of studies found for PIT was limited. All effect sizes differed from zero (binge eating disorder = 27%, anorexia = 24%, bulimia = 18%, mixed samples = 15%), but the precision of the estimates was low, with some lower-bound confidence intervals close to zero. For CBT, change in ED specific psychopathology predicted remission only when controlling for ED diagnosis, while change in general psychopathology did not predict remission at all. The predictive value of change in psychopathology for PIT, and the potential impact of comorbid personality disorders could not be analyzed due to a lack of studies. There was no difference in effects between randomized controlled trials and observational studies.ConclusionsCBT showed consistent remission rates for all EDs but left a substantial number of patients not in remission. Extant evidence suggest that PIT is not consistently effective in achieving remission for patients with EDs, although this finding is uncertain due to a small number of eligible studies. A group of patients with eating disorders may, however, require therapy aimed at strengthening deficits in self functions not easily ameliorable by cognitive behavioral techniques alone. Further research should be aimed at identifying treatment interventions that helps patients change behavior, while strengthening self-functions to substitute eating-disordered behavior in the long-term.