Search for the Radiative Capture d+d->^4He+\gamma Reaction from the dd\mu Muonic Molecule State

A search for the muon catalyzed fusion reaction dd --> ^4He +\gamma in the dd\mu muonic molecule was performed using the experimental \mu CF installation TRITON and NaI(Tl) detectors for \gamma-quanta. The high pressure target filled with deuterium at temperatures from 85 K to 800 K was exposed to the negative muon beam of the JINR phasotron to detect \gamma-quanta with energy 23.8 MeV. The first experimental estimation for the yield of the radiative deuteron capture from the dd\mu state J=1 was obtained at the level n_{\gamma}\leq 2\times 10^{-5} per one fusion.Comment: 9 pages, 3 Postscript figures, submitted to Phys. At. Nuc

Expert Consensus on the Characteristics of Patients with Epstein–Barr Virus-Positive Post-Transplant Lymphoproliferative Disease (EBV+ PTLD) for Whom Standard-Dose Chemotherapy May be Inappropriate: A Modified Delphi Study

Introduction: Following hematopoietic stem cell transplantation or solid organ transplantation, patients are at risk of developing Epstein–Barr virus-positive post-transplant lymphoproliferative disease (EBV+ PTLD), which is an ultra-rare and potentially lethal hematologic malignancy. Common treatments for EBV+ PTLD include rituximab alone or combined with chemotherapy. Given specific considerations for this population, including severity of the underlying condition requiring transplant, the rigors of the transplant procedure, as well as risks to the transplanted organ, there is a group of patients with EBV+ PTLD for whom chemotherapy may be inappropriate; however, there is limited information characterizing these patients. This study aimed to reach expert consensus on the key characteristics of patients for whom chemotherapy may be inappropriate in a real-world setting. Methods: A two-round modified Delphi study was conducted to reach consensus among clinicians with expertise treating EBV+ PTLD. Articles identified in a targeted literature review guided the development of round 1 and 2 topics and related statements. The consensus threshold for round 1 statements was 75.0%. If consensus was achieved in round 1, the statement was not discussed further in round 2. The consensus thresholds for round 2 were moderate (62.5–75.0%), strong (87.5%), or complete (100.0%). Results: The panel was composed of a total of eight clinicians (seven hematologists/hemato-oncologists) from six European countries. The panel generated a final list of 43 consensus recommendations on the following topics: terminology used to describe patients for whom chemotherapy may be inappropriate; demographic characteristics; organ transplant characteristics; comorbidities that preclude the use of chemotherapy; EBV+ PTLD characteristics; and factors related to treatment-related mortality and morbidity. Conclusions: This modified Delphi panel successfully achieved consensus on key topics and statements that characterized patients with EBV+ PTLD for whom chemotherapy may be inappropriate. These recommendations will inform clinicians and aid in the treatment of EBV+ PTLD

Does adding risk-trends to survival models improve in-hospital mortality predictions? A cohort study

<p>Abstract</p> <p>Background</p> <p>Clinicians informally assess changes in patients' status over time to prognosticate their outcomes. The incorporation of trends in patient status into regression models could improve their ability to predict outcomes. In this study, we used a unique approach to measure trends in patient hospital death risk and determined whether the incorporation of these trend measures into a survival model improved the accuracy of its risk predictions.</p> <p>Methods</p> <p>We included all adult inpatient hospitalizations between 1 April 2004 and 31 March 2009 at our institution. We used the daily mortality risk scores from an existing time-dependent survival model to create five trend indicators: absolute and relative percent change in the risk score from the previous day; absolute and relative percent change in the risk score from the start of the trend; and number of days with a trend in the risk score. In the derivation set, we determined which trend indicators were associated with time to death in hospital, independent of the existing covariates. In the validation set, we compared the predictive performance of the existing model with and without the trend indicators.</p> <p>Results</p> <p>Three trend indicators were independently associated with time to hospital mortality: the absolute change in the risk score from the previous day; the absolute change in the risk score from the start of the trend; and the number of consecutive days with a trend in the risk score. However, adding these trend indicators to the existing model resulted in only small improvements in model discrimination and calibration.</p> <p>Conclusions</p> <p>We produced several indicators of trend in patient risk that were significantly associated with time to hospital death independent of the model used to create them. In other survival models, our approach of incorporating risk trends could be explored to improve their performance without the collection of additional data.</p

The example of CaPSURE: lessons learned from a national disease registry

IntroductionAlthough randomized controlled trials (RCTs) remain the gold standard for determining evidence-based clinical practices, large disease registries that enroll large numbers of patients have become paramount as a relatively cost-effective additional tool.MethodsWe highlight the advantages of disease registries focusing on the example of prostate cancer and the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE™) registry.ResultsCaPSURE collects approximately 1,000 clinical and patient-reported variables, in over 13,000 men that are enrolled. Thus far, CaPSURE has yielded over 130 peer-reviewed publications, with several others in press, in key areas of risk migration, practice patterns, outcome prediction, and quality of life outcomes.ConclusionsDisease registries, like CaPSURE complement RCTs and CaPSURE, have provided a means to better understand many aspects of prostate cancer epidemiology, practice patterns, oncologic and HRQOL outcomes, and costs of care across populations. Specialized observational disease registries such as CaPSURE provide insight and have broad implications for disease management and policy