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1. A Setup to Study Atomic State Population Dynamics and Optical Polarization at CRYRING@ESR

Author

Mohr, K., Sánchez, R., Nörtershäuser, W., Andelkovic, Z., Hannen, V., Hanu, E. -O., Herfurth, F., Heß, R., Horst, M., Imgram, P., König, K., Krantz, C., Lestinsky, M., Litvinov, Yu. A., Menz, E., Müller, P., Palmes, J., Rausch, S., Ratajczyk, T., Renth, L., Rossbach, J., Sidhu, R. S., Sommer, F., Spahn, J., Stallkamp, N., Ueberholz, K., Vorobjev, G., Weinheimer, C., and Zisis, D.

Subjects
Physics - Atomic Physics, Physics - Accelerator Physics
Abstract

We present a recently established setup for laser spectroscopy at CRYRING@ESR at the GSI Helmholtz Centre for Heavy Ion Research. Here, laser spectroscopy can be performed on stored and cooled ion bunches and coasting beams. First spectra of $^{24,25}$Mg$^+$ ions are presented that were recorded by classical Doppler-limited fluorescence spectroscopy as well as $\Lambda$-spectroscopy using counter- and copropagating laser beams that are Doppler-shifted by several nm., Comment: 10 pages, 8 figures, submitted to conference proceedings of "1st Workshop on Polarized Beam and Target-Physics and Applications"

Published
2024

2. High Voltage Determination and Stabilization for Collinear Laser Spectroscopy Applications

Author

König, Kristian, Köhler, Finn, Palmes, Julian, Badura, Henrik, Dockery, Adam, Minamisono, Kei, Meisner, Johann, Müller, Patrick, Nörtershäuser, Wilfried, and Passon, Stephan

Subjects
Physics - Instrumentation and Detectors, Nuclear Experiment
Abstract

Fast beam collinear laser spectroscopy is the established method to investigate nuclear ground state properties such as the spin, the electromagnetic moments, and the charge radius of exotic nuclei. These are extracted with high precision from atomic observables, i.e., the hyperfine splitting and its the isotope shift, which becomes possible due to a large reduction of the Doppler broadening by compressing the velocity width of the ion beam through electrostatic acceleration. With the advancement of the experimental methods and applied devices, e.g., to measure and stabilize the laser frequency, the acceleration potential became the dominant systematic uncertainty contribution. To overcome this, we present a custom-built high-voltage divider, which was developed and tested at the German metrology institute (PTB), and a feedback loop that enabled collinear laser spectroscopy to be performed at a 100-kHz level. Furthermore, we describe the impact of field penetration into the laser-ion-interaction region. This strongly affects the determined isotope shifts and hyperfine splittings, if Doppler tuning is applied, i.e., the ion beam energy is altered instead of scanning the laser frequency. Using different laser frequencies that were referenced to a frequency comb, the field penetration was extracted laser spectroscopically. This allowed us to define an effective scanning potential to still apply the faster and easier Doppler tuning without introducing systematic deviations.

Published
2024

3. AutoDOViz: Human-Centered Automation for Decision Optimization

Author

Weidele, Daniel Karl I., Afzal, Shazia, Valente, Abel N., Makuch, Cole, Cornec, Owen, Vu, Long, Subramanian, Dharmashankar, Geyer, Werner, Nair, Rahul, Vejsbjerg, Inge, Marinescu, Radu, Palmes, Paulito, Daly, Elizabeth M., Franke, Loraine, and Haehn, Daniel

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

We present AutoDOViz, an interactive user interface for automated decision optimization (AutoDO) using reinforcement learning (RL). Decision optimization (DO) has classically being practiced by dedicated DO researchers where experts need to spend long periods of time fine tuning a solution through trial-and-error. AutoML pipeline search has sought to make it easier for a data scientist to find the best machine learning pipeline by leveraging automation to search and tune the solution. More recently, these advances have been applied to the domain of AutoDO, with a similar goal to find the best reinforcement learning pipeline through algorithm selection and parameter tuning. However, Decision Optimization requires significantly more complex problem specification when compared to an ML problem. AutoDOViz seeks to lower the barrier of entry for data scientists in problem specification for reinforcement learning problems, leverage the benefits of AutoDO algorithms for RL pipeline search and finally, create visualizations and policy insights in order to facilitate the typical interactive nature when communicating problem formulation and solution proposals between DO experts and domain experts. In this paper, we report our findings from semi-structured expert interviews with DO practitioners as well as business consultants, leading to design requirements for human-centered automation for DO with RL. We evaluate a system implementation with data scientists and find that they are significantly more open to engage in DO after using our proposed solution. AutoDOViz further increases trust in RL agent models and makes the automated training and evaluation process more comprehensible. As shown for other automation in ML tasks, we also conclude automation of RL for DO can benefit from user and vice-versa when the interface promotes human-in-the-loop.

Published
2023
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4. Not enough trees – Scaling up koala habitat restoration using seed enhancement technologies

Author

Samantha E. Andres, Cesar Medina, Rachael V. Gallagher, Georgina Hillman, Lachlan Palmes, Paige E. Lieurance, and Charlotte H. Mills

Subjects
extruded pellets, habitat improvement, revegetation, seed coatings, seed enhancements, seed‐based restoration, Ecology, QH540-549.5, General. Including nature conservation, geographical distribution, QH1-199.5
Abstract

Abstract Large‐scale ecological restoration is a crucial tool for improving the quality and extent of habitat for wildlife. In Australia, 25,000 hectares of land is to be restored to support habitat connectivity for the Endangered koala (Phascolarctos cinereus). However, limited funding is a barrier to achieving restoration of this scale without the integration of new technologies and approaches. Seed enhancement technologies (SETs) are commonly used in agriculture to improve plant establishment and growth while reducing seed wastage; yet SETs are rarely used in restoration. Here, we tested the efficacy of SETs with five native tree species favored by koalas. Using a greenhouse trial, we measured emergence, time to emergence, growth rates, and survival up to 7 weeks post planting. At 33 weeks post‐planting, we measured total biomass, root: shoot ratios, and the specific root length. SETs resulted in comparable emergence and survival and promoted a longer time to emergence relative to bare seeds. Importantly, seedlings grown from SETs yielded higher average growth rates (0.3 mm/week higher), total biomass (5.93 mg higher) and root: shoot ratios (0.258 higher) relative to seedlings grown without SETs. These findings underscore the applicability of SETs to native species to support large‐scale koala habitat restoration by increasing the growth rate and size of seedlings at the early life stage.

Published
2024
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5. A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales

Author

Hu, Yihao, O'Donncha, Fearghal, Palmes, Paulito, Burke, Meredith, Filgueira, Ramon, and Grant, Jon

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Physics - Atmospheric and Oceanic Physics
Abstract

This paper presents a novel spatio-temporal LSTM (SPATIAL) architecture for time series forecasting applied to environmental datasets. The framework was evaluated across multiple sensors and for three different oceanic variables: current speed, temperature, and dissolved oxygen. Network implementation proceeded in two directions that are nominally separated but connected as part of a natural environmental system -- across the spatial (between individual sensors) and temporal components of the sensor data. Data from four sensors sampling current speed, and eight measuring both temperature and dissolved oxygen evaluated the framework. Results were compared against RF and XGB baseline models that learned on the temporal signal of each sensor independently by extracting the date-time features together with the past history of data using sliding window matrix. Results demonstrated ability to accurately replicate complex signals and provide comparable performance to state-of-the-art benchmarks. Notably, the novel framework provided a simpler pre-processing and training pipeline that handles missing values via a simple masking layer. Enabling learning across the spatial and temporal directions, this paper addresses two fundamental challenges of ML applications to environmental science: 1) data sparsity and the challenges and costs of collecting measurements of environmental conditions such as ocean dynamics, and 2) environmental datasets are inherently connected in the spatial and temporal directions while classical ML approaches only consider one of these directions. Furthermore, sharing of parameters across all input steps makes SPATIAL a fast, scalable, and easily-parameterized forecasting framework.

Published
2021

6. Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization

Author

Palmes, Paulito P., Kishimoto, Akihiro, Marinescu, Radu, Ram, Parikshit, and Daly, Elizabeth

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

The pipeline optimization problem in machine learning requires simultaneous optimization of pipeline structures and parameter adaptation of their elements. Having an elegant way to express these structures can help lessen the complexity in the management and analysis of their performances together with the different choices of optimization strategies. With these issues in mind, we created the AutoMLPipeline (AMLP) toolkit which facilitates the creation and evaluation of complex machine learning pipeline structures using simple expressions. We use AMLP to find optimal pipeline signatures, datamine them, and use these datamined features to speed-up learning and prediction. We formulated a two-stage pipeline optimization with surrogate modeling in AMLP which outperforms other AutoML approaches with a 4-hour time budget in less than 5 minutes of AMLP computation time.

Published
2021

7. Towards Smart Sustainable Cities: Addressing semantic heterogeneity in building management systems using discriminative models

Author

Iddianozie, Chidubem and Palmes, Paulito

Subjects
Computer Science - Computers and Society
Abstract

Building Management Systems (BMS) are crucial in the drive towards smart sustainable cities. This is due to the fact that they have been effective in significantly reducing the energy consumption of buildings. A typical BMS is composed of smart devices that communicate with one another in order to achieve their purpose. However, the heterogeneity of these devices and their associated meta-data impede the deployment of solutions that depend on the interactions among these devices. Nonetheless, automatically inferring the semantics of these devices using data-driven methods provides an ideal solution to the problems brought about by this heterogeneity. In this paper, we undertake a multi-dimensional study to address the problem of inferring the semantics of IoT devices using machine learning models. Using two datasets with over 67 million data points collected from IoT devices, we developed discriminative models that produced competitive results. Particularly, our study highlights the potential of Image Encoded Time Series (IETS) as a robust alternative to statistical feature-based inference methods. Leveraging just a fraction of the data required by feature-based methods, our evaluations show that this encoding competes with and even outperforms traditional methods in many cases.

Published
2020
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8. TSML (Time Series Machine Learnng)

Author

Palmes, Paulito, Ploennigs, Joern, and Brady, Niall

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Over the past years, the industrial sector has seen many innovations brought about by automation. Inherent in this automation is the installation of sensor networks for status monitoring and data collection. One of the major challenges in these data-rich environments is how to extract and exploit information from these large volume of data to detect anomalies, discover patterns to reduce downtimes and manufacturing errors, reduce energy usage, predict faults/failures, effective maintenance schedules, etc. To address these issues, we developed TSML. Its technology is based on using the pipeline of lightweight filters as building blocks to process huge amount of industrial time series data in parallel.

Published
2020

10. Prognostic Value of Myocardial Blush Grade in ST-elevation MI: A Systematic Review and Meta-analysis

Author

Patrick Vera Cruz, Patricio Palmes, and Nadine Bacalangco

Subjects
Surgery, RD1-811, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background: Ineffective myocardial perfusion despite angiographic success after angioplasty occurs frequently and is associated with an increased risk of mortality. Hence, this study determined whether myocardial perfusion measured by myocardial blush grade (MBG) identifies ST-elevation MI (STEMI) patients at high risk for poor outcomes after successful angioplasty. Methods: The search employed strategies designed for research databases. An article was eligible if it included adults who underwent coronary angioplasty for STEMI, post-angioplasty MBG was assessed, and mortality or major adverse cardiovascular events (MACE) were determined. Risk for bias was assessed using the Quality In Prognosis Studies tool and forest plots in a Mantel-Haenszel fixed effects model were created using RevMan5.4. Results/discussion: Eight observational studies with an overall low risk of bias were included, involving 8,044 patients. MBG 0/1 with no to poor myocardial perfusion had a negative prognostic value for mortality (OR 2.68; 95% CI [2.22–3.23]) and MACE (OR 1.20; 95% CI [1.01–1.41]). Furthermore, MBG 2 with moderate myocardial perfusion and MBG 3 with normal myocardial perfusion were associated with increased survival with a logHR of 0.47 (95% CI [0.43–0.52]) and 0.20 percutaneous coronary intervention (95% CI [0.18–0.23]). These results imply MBG is a useful prognostic marker for STEMI patients. Conclusion: MBG 0/1 after primary angioplasty is a strong negative prognostic marker for long-term all-cause mortality and MACE among STEMI patients, and a post-primary angioplasty MBG of 2 or 3 is a robust prognostic marker for long-term survival.

Published
2022
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11. Microsurgical training course for clinicians and scientists: a 10-year experience at the Münster University Hospital

Author

Mazen A. Juratli, Felix Becker, Daniel Palmes, Sandra Stöppeler, Ralf Bahde, Linus Kebschull, Hans-Ullrich Spiegel, and Jens P. Hölzen

Subjects
Microsurgical training, Anastomosis, Microsurgery, Vascular anastomosis, Training, Curricular training, Special aspects of education, LC8-6691, Medicine
Abstract

Abstract Background Microsurgical techniques are an important part of clinical and experimental research. Here we present our step-by-step microsurgery training course developed at the Münster University Hospital. The goal of this course was to create a short, modular curriculum with clearly described and easy to follow working steps in accordance with the Guidelines for Training in Surgical Research in Animals by the Academy of Surgical Research. Methods Over the course of 10 years, we conducted an annual 2.5 day (20 h) microsurgical training course with a total of 120 participants. Results Prior to the course, 90% of the participants reported to have never performed a microanastomosis before. During the 10 years a total of 84.2% of the participants performed microanastomoses without assistance, 15% required assistance and only 0.8% failed. Conclusions Our step-by-step microsurgery training course gives a brief overview of the didactic basics and the organization of a microsurgical training course and could serve as a guide for teaching microsurgical skills. During the 2.5-day curriculum, it was possible to teach, and for participants to subsequently perform a microsurgical anastomosis. The independent reproducibility of the learned material after the course is not yet known, therefore further investigations are necessary. With this step-by-step curriculum, we were able to conduct a successful training program, shown by the fact that each participant is able to perform microvascular anastomoses on a reproducible basis.

Published
2021
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12. Low Frequency L\'evy Copula Estimation

Author

Palmes, Christian

Subjects
Mathematics - Statistics Theory, 60G51, 62G20, 62H12
Abstract

Let $X$ be a $d$-dimensional L\'evy process with L\'evy triplet $(\Sigma,\nu,\alpha)$ and $d\geq 2$. Given the low frequency observations $(X_t)_{t=1,\ldots,n}$, the dependence structure of the jumps of $X$ is estimated. The L\'evy measure $\nu$ describes the average jump behavior in a time unit. Thus, the aim is to estimate the dependence structure of $\nu$ by estimating the L\'evy copula $\mathfrak{C}$ of $\nu$, cf. Kallsen and Tankov \cite{KalTan}. We use the low frequency techniques presented in a one dimensional setting in Neumann and Rei{\ss} \cite{NeuRei} and Nickl and Rei{\ss} \cite{NicRei} to construct a L\'evy copula estimator $\widehat{\mathfrak{C}}_n$ based on the above $n$ observations. In doing so we prove $$\widehat{\mathfrak{C}}_n\to \mathfrak{C},\quad n\to\infty$$ uniformly on compact sets bounded away from zero with the convergence rate $\sqrt{\log n}$. This convergence holds under quite general assumptions, which also include L\'evy triplets with $\Sigma\neq 0$ and $\nu$ of arbitrary Blumenthal-Getoor index $0\leq\beta\leq 2$. Note that in a low frequency observation scheme, it is statistically difficult to distinguish between infinitely many small jumps and a Brownian motion part. Hence, the rather slow convergence rate $\sqrt{\log n}$ is not surprising. In the complementary case of a compound Poisson process (CPP), an estimator $\widehat{C}_n$ for the copula $C$ of the jump distribution of the CPP is constructed under the same observation scheme. This copula $C$ is the analogue to the L\'evy copula $\mathfrak{C}$ in the finite jump activity case, i.e. the CPP case. Here we establish $$\widehat{C}_n \to C,\quad n\to\infty$$ with the convergence rate $\sqrt{n}$ uniformly on compact sets bounded away from zero. Both convergence rates are optimal in the sense of Neumann and Rei{\ss}.

Published
2014

13. Copula Relations in Compound Poisson Processes

Author

Palmes, Christian

Subjects
Mathematics - Statistics Theory, 60G51, 60F99, 62H20
Abstract

We investigate in multidimensional compound Poisson processes (CPP) the relation between the dependence structure of the jump distribution and the dependence structure of the respective components of the CPP itself. For this purpose the asymptotic $\lambda t\to \infty$ is considered, where $\lambda$ denotes the intensity and $t$ the time point of the CPP. For modeling the dependence structures we are using the concept of copulas. We prove that the copula of a CPP converges under quite general assumptions to a specific Gaussian copula, depending on the underlying jump distribution. Let $F$ be a $d$-dimensional jump distribution $(d\geq 2)$, $\lambda>0$ and let $\Psi(\lambda,F)$ be the distribution of the corresponding CPP with intensity $\lambda$ at the time point $1$. Further, denote the operator which maps a $d$-dimensional distribution on its copula as $\mathcal{T}$. The starting point of our investigation was the validity of the equation \begin{equation} \label{marFreeEq} \mathcal{T}(\Psi(\lambda,F))=\mathcal{T}(\Psi(\lambda,\mathcal{T}F)). \end{equation} Our asymptotic theory implies that this equation is, in general, not true. A simulation study that confirms our theoretical results is given in the last section.

Published
2014

14. Comparison of WIFi, University of Texas and Wagner Classification Systems as Major Amputation Predictors for Admitted Diabetic Foot Patients: A Prospective Cohort Study

Author

Vera-Cruz PN, Palmes PP, Tonogan LJM, and Troncillo AH

Subjects
diabetic foot, wifi, wagner, university of texas classification, major amputation, Orthopedic surgery, RD701-811
Abstract

INTRODUCTION: Classifications systems are powerful tools that could reduce the length of hospital stay and economic burden. The Would, Ischemia, and Foot Infection (WIFi) classification system was created as a comprehensive system for predicting major amputation but is yet to be compared with other systems. Thus, the objective of this study is to compare the predictive abilities for major lower limb amputation of WIFi, Wagner and the University of Texas Classification Systems among diabetic foot patients admitted in a tertiary hospital through a prospective cohort design. MATERIALS AND METHODS: Sixty-three diabetic foot patients admitted from June 15, 2019 to February 15, 2020. Methods included one-on-one interview for clinico-demographic data, physical examination to determine the classification. Patients were followed-up and outcomes were determined. Pearson Chi-square or Fisher’s Exact determined association between clinico-demographic data, the classifications, and outcomes. The receiver operating characteristic (ROC) curve determined predictive abilities of classification systems and paired analysis compared the curves. Area Under the Receiver Operating Characteristic Curve (AUC) values used to compare the prediction accuracy. Analysis was set at 95% CI. RESULTS: Results showed hypertension, duration of diabetes, and ambulation status were significantly associated with major amputation. WIFi showed the highest AUC of 0.899 (p = 0.000). However, paired analysis showed AUC differences between WIFi, Wagner, and University of Texas classifications by grade were not significantly different from each other. CONCLUSION: The WIFi, Wagner, and University of Texas classification systems are good predictors of major amputation with WIFi as the most predictive.

Published
2020
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15. Impact of preoperative risk factors on outcome after gastrectomy

Author

Ann-Kathrin Eichelmann, Meltem Saidi, Kirsten Lindner, Christina Lenschow, Daniel Palmes, Andreas Pascher, and Richard Hummel

Subjects
Gastric cancer, Gastrectomy, Risk factors, P-/O-POSSUM, National Surgical Quality Improvement Program Surgical Risk Calculator, Surgery, RD1-811, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Gastrectomy is associated with relevant postoperative morbidity. However, outcome of surgery can be improved by careful selection of patients. The objective of the current study was therefore to identify preoperative risk factors that might impact on patients’ further outcome after surgical resection. Methods Preoperative risk factors having respectively different surgical risk scores for major complex surgery (including Cologne Risk Score, p-/o-POSSUM, and NSQIP risk score) of patients that underwent gastrectomy for AEG II/III tumors and gastric cancer were correlated with complications according to Clavien-Dindo and outcome. Patients who underwent surgery in palliative intention were excluded from further analysis. Results Subtotal gastrectomy was performed in 23%, gastrectomy in 59%, and extended gastrectomy in 18% in a total of 139 patients (mean age: 64 years old). Thirty six percent experienced a minor complication (Dindo I-II) and 24% a major complication (Dindo III-V), which resulted in a prolonged hospital stay (p < 0.001). In-hospital mortality (=Dindo V) was 2.5%. Besides age, type of surgical procedure impacted on complications with extended gastrectomy showing the highest risk (p = 0.005). The o-POSSUM score failed to predict mortality accurately. We observed a highly positive correlation between predicted morbidity respectively mortality and occurrence of complications estimated by p-POSSUM (p = 0.005), Cologne Risk (p = 0.007), and NSQIP scores (p < 0.001). Conclusion The results demonstrate a significant association between different risk scores and occurrence of complications following gastrectomy. The p-POSSUM, Cologne Risk, and NSQIP score exhibited superior performance than the o-POSSUM score. Therefore, these scores might allow identification and selection of high-risk patients and thus might be highly useful for clinical decision making.

Published
2020
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17. Data Driven Insight Into Fish Behaviour and Their Use for Precision Aquaculture

Author

Fearghal O'Donncha, Caitlin L. Stockwell, Sonia Rey Planellas, Giulia Micallef, Paulito Palmes, Chris Webb, Ramon Filgueira, and Jon Grant

Subjects
machine learning, hydroacoustic, aquaculture, AutoML, IoT, Veterinary medicine, SF600-1100
Abstract

Aquaculture, or the farmed production of fish and shellfish, has grown rapidly, from supplying just 7% of fish for human consumption in 1974 to more than half in 2016. This rapid expansion has led to the growth of Precision Aquaculture concept that aims to exploit data-driven management of fish production, thereby improving the farmer's ability to monitor, control, and document biological processes in farms. Fundamental to this paradigm is monitoring of environmental and animal processes within a cage, and processing those data toward farm insight using models and analytics. This paper presents an analysis of environmental and fish behaviour datasets collected at three salmon farms in Norway, Scotland, and Canada. Information on fish behaviour were collected using hydroacoustic sensors that sampled the vertical distribution of fish in a cage at high spatial and temporal resolution, while a network of environmental sensors characterised local site conditions. We present an analysis of the hydroacoustic datasets using AutoML (or automatic machine learning) tools that enables developers with limited data science expertise to train high-quality models specific to the data at hand. We demonstrate how AutoML pipelines can be readily applied to aquaculture datasets to interrogate the data and quantify the primary features that explains data variance. Results demonstrate that variables such as temperature, wind conditions, and hour-of-day were important drivers of fish motion at all sites. Further, there were distinct differences in factors that influenced in-cage variations driven by local variables such as water depth and ambient environmental conditions (particularly dissolved oxygen). The framework offers a transferable approach to interrogate fish behaviour within farm systems, and quantify differences between sites.

Published
2021
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19. Non-additive effects of ACVR2A in preeclampsia in a Philippine population

Author

Melissa D. Amosco, Gloria R. Tavera, Van Anthony M. Villar, Justin Michael A. Naniong, Lara Marie G. David-Bustamante, Scott M. Williams, Pedro A. Jose, and Cynthia P. Palmes-Saloma

Subjects
Association study, Multifactor dimensionality reduction, Philippines, Preeclampsia, Single nucleotide polymorphism, Gynecology and obstetrics, RG1-991
Abstract

Abstract Background Multiple interrelated pathways contribute to the pathogenesis of preeclampsia, and variants in susceptibility genes may play a role among Filipinos, an ethnically distinct group with high prevalence of the disease. The objective of this study was to examine the association between variants in maternal candidate genes and the development of preeclampsia in a Philippine population. Methods A case-control study involving 29 single nucleotide polymorphisms (SNPs) in 21 candidate genes was conducted in 150 patients with preeclampsia (cases) and 175 women with uncomplicated normal pregnancies (controls). Genotyping for the GRK4 and DRD1 gene variants was carried out using the TaqMan Assay, and all other variants were assayed using the Sequenom MassARRAY Iplex Platform. PLINK was used for SNP association testing. Multilocus association analysis was performed using multifactor dimensionality reduction (MDR) analysis. Results Among the clinical factors, older age (P

Published
2019
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21. Comparison of kidney allograft survival in the Eurotransplant senior program after changing the allocation criteria in 2010-A single center experience.

Author

Anne-Sophie Mehdorn, Stefan Reuter, Barbara Suwelack, Katharina Schütte-Nütgen, Felix Becker, Norbert Senninger, Daniel Palmes, Thomas Vogel, and Ralf Bahde

Subjects
Medicine, Science
Abstract

AimsThe European Senior Program (ESP) aims to avoid waiting list competition between younger and elderly patients applying for renal transplantation. By listing patients ≥65 years on a separate waiting list and locally allocating of grafts ≥65 years exclusively to this cohort, waiting and cold ischemia times are predicted to be shortened, potentially resulting in improved kidney transplantation outcomes. This study compared a historic cohort of renal transplant recipients being simultaneously listed on the general and the ESP waiting lists with a collective exclusively listed on the ESP list in terms of surrogates of the transplantation outcome.MethodsTotal 151 eligible patients ≥ 65 years from Münster transplant Center, Germany, between 1999 and 2014 were included. Graft function, graft and patient survival were compared using surrogate markers of short- and long-term graft function. Patients were grouped according to their time of transplantation.ResultsRecipients and donors in the newESP (nESP) cohort were significantly older (69.6 ± 3.5 years vs 67.1 ± 2 years, pConclusionnESP recipients received significantly older grafts, but experienced significantly shorter time on dialysis. Cold ischemia times were comparable, but graft function in the nESP cohort was significantly better in the long term.

Published
2020
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25. Impact of nighttime procedures on outcomes after liver transplantation.

Author

Felix Becker, Thekla Voß, Annika Mohr, Anne-Sophie Mehdorn, Katharina Schütte-Nütgen, Stefan Reuter, Iyad Kabar, Eike Bormann, Thorsten Vowinkel, Daniel Palmes, Jens G Brockmann, Andreas Pascher, Ralf Bahde, Linus Kebschull, and Thomas Vogel

Subjects
Medicine, Science
Abstract

BackgroundSleep deprivation is a well-known risk factor for the performance of medical professionals. Solid organ transplantation (especially orthotopic liver transplantation (oLT)) appears to be vulnerable since it combines technically challenging operative procedures with an often unpredictable start time, frequently during the night. Aim of this study was to analyze whether night time oLT has an impact on one-year graft and patient survival.Material and methodsDeceased donor oLTs between 2006 and 2017 were retrospectively analyzed and stratified for recipients with a start time at day (8 a.m. and 6 p.m.) or at night (6 p.m. to 8 a.m.). We examined donor as well as recipient demographics and primary outcome measure was one-year patient and graft survival.Results350 oLTs were conducted in the study period, 154 (44%) during daytime and 196 (56%) during nighttime. Donor and recipient variables were comparable. One-year patient survival (daytime 75.3% vs nighttime 76.5%, p = 0.85) as well as graft survival (daytime 69.5% vs nighttime 73.5%, p = 0.46) were similar between the two groups. Frequencies of reoperation (daytime 53.2% vs nighttime 55.1%, p = 0.74) were also not significantly different.ConclusionOur retrospective single center data derived from a German transplant center within the Eurotransplant region provides evidence that oLT is a safe procedure irrespective of the starting time. Our data demonstrate that compared to daytime surgery nighttime liver transplantation is not associated with a greater risk of surgical complications. In addition, one-year graft and patient survival do not display inferior results in patients undergoing nighttime transplantation.

Published
2019
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26. Expanding the donor pool in kidney transplantation: Should organs with acute kidney injury be accepted?-A retrospective study.

Author

Katharina Schütte-Nütgen, Markus Finke, Sabrina Ehlert, Gerold Thölking, Hermann Pavenstädt, Barbara Suwelack, Daniel Palmes, Ralf Bahde, Raphael Koch, and Stefan Reuter

Subjects
Medicine, Science
Abstract

BackgroundGiven the gap between patients in need of a renal transplantation (RTx) and organs available, transplantation centers increasingly accept organs of suboptimal quality, e.g. from donors with acute kidney injury (AKI).MethodsTo determine the outcome of kidney transplants from deceased donors with AKI (defined as ≥ AKIN stage 1), all 107 patients who received a RTx from donors with AKI between August 2004 and July 2014 at our center were compared to their respective consecutively transplanted patients receiving kidneys from donors without AKI. 5-year patient and graft survival, frequencies of delayed graft function (DGF), acute rejections and glomerular filtration rate (eGFR, CKD-EPI) were assessed.ResultsPatient survival was similar in both groups, whereas death-censored and overall graft survival were decreased in AKI kidney recipients. AKI kidney recipients showed higher frequencies of DGF and had a reduced eGFR at 7 days, three months and one and three years after RTx. However, mortality was noticeably lower compared to waiting list candidates. Rejection-free survival was similar between groups.ConclusionsIn our cohort, both short-term and long-term renal function was inferior in recipients of AKI kidneys, while patient survival was similar. Our data indicates that recipients of donor AKI kidneys should be carefully selected and additional factors impairing short- and long-term outcome should be minimized to prevent further deterioration of graft function.

Published
2019
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29. The weekend effect in liver transplantation.

Author

Felix Becker, Thomas Vogel, Thekla Voß, Anne-Sophie Mehdorn, Katharina Schütte-Nütgen, Stefan Reuter, Annika Mohr, Iyad Kabar, Eike Bormann, Thorsten Vowinkel, Daniel Palmes, Norbert Senninger, Ralf Bahde, and Linus Kebschull

Subjects
Medicine, Science
Abstract

BACKGROUND:The weekend effect describes a phenomenon whereby patients admitted to hospitals on weekends are at higher risk of complications compared to those admitted during weekdays. However, if a weekend effect exists in orthotopic liver transplantation (oLT). METHODS:We analyzed oLT between 2006 and 2016 and stratified patients into weekday (Monday to Friday) and weekend (Saturday, Sunday) groups. Primary outcome measures were one-year patient and graft survival. RESULTS:364 deceased donor livers were transplanted into 329 patients with 246 weekday (74.77%) and 83 weekend (25.23%) patients. Potential confounders (e.g. age, ischemia time, MELD score) were comparable. One-year patient and graft survival were similar. Frequencies of rejections, primary-non function or re-transplantation were not different. The day of transplantation was not associated with one-year patient and graft survival in multivariate analysis. CONCLUSIONS:We provide the first data for the Eurotransplant region on oLT stratified for weekend and weekday procedures and our findings suggest there was no weekend effect on oLT. While we hypothesize that the absent weekend effect is due to standardized transplant procedures and specialized multidisciplinary transplant teams, our results are encouraging showing oLT is a safe and successful procedure, independent from the day of the week.

Published
2018
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30. Kohlbergian Analysis of the Moral Reasoning in Lino Brocka’s Leading Films

Author

Diana F. Palmes and F.P.A. Demeterio III

Subjects
Lino Brocka, Tinimbang Ka Ngunit Kulang, Maynila sa mga Kuko ng Liwanag, Insiang, Jaguar, Bayan Ko: Kapit sa Patalim, Orapronobis, moral reasoning, moral criticism, Lawrence Kohlberg, and theory of moral development, General Works, History of scholarship and learning. The humanities, AZ20-999
Abstract

The year 2014 marks the 75th birth anniversary of the Filipino film maker and National Artist for Film Lino Brocka. By using the moral development theory of the American psychologist Lawrence Kohlberg, this paper examines sixteen cases of moral dilemmas and their resolutions, as found in Brocka’s iconic films Tinimbang Ka Ngunit Kulang (You’ve Been Weighed and Found Wanting), Maynila sa mga Kuko ng Liwanag (Manila, In the Claws of Light), Insiang, Jaguar (Guard), Bayan Ko: Kapit sa Patalim (My Country: Gripping the Knife’s Edge), and Orapronobis (Fight for Us). This paper established that one of the techniques that Brocka used in his moral discourses is to contrast the moral reasoning of his f ictive agents with his own moral reasoning. This results in an infusion of his moral narratives with the potentiality for multiple interpretation by the audience: in some cases, this contrapuntal technique was used to propose a third higher moral narrative; while in others, the moral narratives of Brocka had the tendency to challenge the Philippine traditional norms and rules, as well as the hypocrisies of the Philippine society; and finally, that Brocka tended to intertwine his moral and political discourses, particularly his argument for class solidarity as the remedy of the injustices brought about by the power inequality among Philippine social classes. Thus, Brocka’s masterpieces should not only be used as materials in the study of Philippine films, or in the study of political and social criticism; but more so as materials for the study of ethics and morality that are relevant to Philippine social conditions.

Published
2015

32. Cross-Cultural Psychiatry in the Field: Collaborating with Anthropology

Author

Folmar, Steven and Palmes, Guy K.

Abstract

Psychiatric and anthropological collaborations have produced robust literatures on varied topics but there are challenges in the working relation between these two fields. A research into how cultures deal with attention-deficit hyperactivity disorders in Afghanistan is discussed to highlight the challenges in the working relations between psychiatrists and anthropologists.

Published
2009

36. Implementation of Strengthened Technical Vocational Education Program - Competency Based Curriculum, Northern Mindanao, Philippines

Author

Reynilda C. Alferez and Nenita D. Palmes

Subjects
strengthened technical vocational education, program-competency based curriculum stvep-cbc activities, Social Sciences, Education
Abstract

This study attempted to assess the implementation of the Strengthened Technical and Vocational Education Program - Competency Based Curriculum (STVEP-CBC) in Region x. The study involved nine (9) DepED Technical Vocational High Schools in Region X - Northern Mindanao. The respondents included twenty one (21) administrators and ninety one (91) teachers. Descriptive statistics were used to describe and to analyze the data. The study also utilized T - test for paired values to evaluate the difference between administrators and teachers assessments in the status of implementation of STVEP - CBC. The school administrators and teachers assessed the status of the implementation of STVEP-CBC along the aspects of its program. Findings show that both administrators and teacher respondents were assessed very satisfactory on items of Competency Assessment and Certification, Instructional and Teacher Support Material, Curriculum Instruction, Program and Project Management and Monitoring and Evaluation. On one hand, both respondents register as only satisfactory on the aspect of facilities and services. This can be due to the fact that a budgetary allocation in this area is insufficient. On the other hand, assessments of administrators and teachers vary on the following: excellent by the administrators while very satisfactory by the teachers respectively the items on Human Resource Development, Property Supply Management, Fiscal Management and Physical Plant Facility. Such high assessments of the two groups are attributed to their satisfaction level with the implementation of the different programs.

Published
2012
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38. Perioperative chemotherapy in gastroesophageal cancer. A retrospective monocenter evaluation of 42 cases.

Author

Ann-Christin E Brehler, Wolfgang Hartmann, Stefanie Wiebe, Andrea Kerkhoff, Christoph Schliemann, Daniel Palmes, Norbert Senninger, Frank Lenze, Hansjoerg Ullerich, Wolfgang E Berdel, and Torsten Kessler

Subjects
Medicine, Science
Abstract

BACKGROUND:Perioperative chemotherapy increases the overall and progression-free survival of patients suffering from resectable adenocarcinomas of the lower esophagus, gastroesophageal junction and stomach (GEC). Comparing different chemotherapy regimens platin-based protocols with 5-fluorouracil (5-FU)/calcium folinate (CF) or oral fluoropyrimidines were favorable in terms of efficacy and side-effects. However, there is no consensus which regimen is the most efficacious. METHODS:42 consecutive patients with resectable GEC (UICC II and III) were treated with 3 pre- and postoperative chemotherapy cycles each consisting of epirubicin, oxaliplatin and capecitabine (EOX). We analyzed the overall survival, progression-free survival and toxicity retrospectively in comparison to published data. RESULTS:The median overall survival in our cohort was 29 months and the progression-free survival was 17 months. The most frequent grade 3 and 4 toxicities during preoperative chemotherapy were diarrhea (16.7%), leukocytopenia (9.5%) and nausea (9.5%); overall 38.1% of our patients suffered from grade 3 or 4 toxicity. Surgery was carried out in 83% of our patients, 69% of those achieved R0 resection. CONCLUSION:Comparing our data with the results of previously published randomized trials EOX is at least non-inferior with regard to overall survival, progression-free survival and toxicity. In conclusion, EOX is an appropriate perioperative therapy for patients with resectable GEC.

Published
2015
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39. Prior individual training and self-organized queuing during group emergency escape of mice from water pool.

Author

Caesar Saloma, Gay Jane Perez, Catherine Ann Gavile, Jacqueline Judith Ick-Joson, and Cynthia Palmes-Saloma

Subjects
Medicine, Science
Abstract

We study the impact of prior individual training during group emergency evacuation using mice that escape from an enclosed water pool to a dry platform via any of two possible exits. Experimenting with mice avoids serious ethical and legal issues that arise when dealing with unwitting human participants while minimizing concerns regarding the reliability of results obtained from simulated experiments using 'actors'. First, mice were trained separately and their individual escape times measured over several trials. Mice learned quickly to swim towards an exit-they achieved their fastest escape times within the first four trials. The trained mice were then placed together in the pool and allowed to escape. No two mice were permitted in the pool beforehand and only one could pass through an exit opening at any given time. At first trial, groups of trained mice escaped seven and five times faster than their corresponding control groups of untrained mice at pool occupancy rate ρ of 11.9% and 4%, respectively. Faster evacuation happened because trained mice: (a) had better recognition of the available pool space and took shorter escape routes to an exit, (b) were less likely to form arches that blocked an exit opening, and (c) utilized the two exits efficiently without preference. Trained groups achieved continuous egress without an apparent leader-coordinator (self-organized queuing)-a collective behavior not experienced during individual training. Queuing was unobserved in untrained groups where mice were prone to wall seeking, aimless swimming and/or blind copying that produced circuitous escape routes, biased exit use and clogging. The experiments also reveal that faster and less costly group training at ρ = 4%, yielded an average individual escape time that is comparable with individualized training. However, group training in a more crowded pool (ρ = 11.9%) produced a longer average individual escape time.

Published
2015
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40. Dapagliflozin and cardiovascular outcomes in type 2 diabetes

Author

Wiviott, S, Raz, I, Bonaca, M, Mosenzon, O, Kato, E, Cahn, A, Silverman, M, Zelniker, T, Kuder, J, Murphy, S, Bhatt, D, Leiter, L, Mcguire, D, Wilding, J, Ruff, C, Nilsson, G, Fredriksson, M, Johansson, P, Langkilde, A, Sabatine, M, Bansilal, S, Furtado, R, Fish, M, Gabovitch, D, Jevne, A, Ahern, S, Im, K, Goodrich, E, Lowe, C, Fisher, N, Gannon, J, Trindade, S, Towarowski, A, Fox, Y, Johnsson, E, Ranft, S, Faber, B, Wallander, M, Weiss, A, Buskila, A, Abola, M, Ardissino, D, Averkov, O, Aylward, P, Bode, C, Bonnici, F, Bonora, E, Budaj, A, Cernea, S, Chiang, C, Cooper, M, Dalby, A, Deerochanawong, C, Dellborg, M, Diaz, R, Dimulescu, D, Eliaschewitz, F, Goudev, A, Hadjadj, S, Herrera, M, Huo, Y, Jermendy, G, Ji, L, Kadowaki, T, Kiss, R, Kooy, A, Kumar, K, Lewis, B, Litwak, L, Lopez-Sendon, J, Ma, R, Merlini, P, Nauck, M, Nguyen, T, Nicolau, J, Ostgren, C, Ophuis, T, Padilla, F, Pais, P, Park, K, Parkhomenko, A, Ray, K, Rosenstock, J, Ruda, M, Satman, I, Shestakova, M, Smahelova, A, Spinar, J, Strojek, K, Sy, R, Tankova, T, Theroux, P, Tkac, I, Van Gaal, L, Wainstein, J, Harrington, R, Droller, M, Lee, K, Nesto, R, Tuomilehto, J, Hedlin, H, Desai, M, Sayfer, I, Alexanian, S, Awtry, E, Bentley-Lewis, R, Berger, C, Croce, K, Desai, A, Garg, R, Gelfand, E, Gignac, G, Goessling, W, Ho, C, Hochberg, E, Lane, A, Larrey, D, Leeman, D, Lewis, J, Link, M, Mcdonnell, M, Norden, A, Pande, A, Rosenberg, C, Rost, N, Ruberg, F, Schiff, E, Silverman, S, Singhal, A, Wagner, A, Wolpin, B, Aizenberg, D, Fernandez, M, Sala, J, Maffei, L, Luquez, C, Waitman, J, Rista, L, Nardone, L, Sposetti, G, Cantero, M, Alvarisqueta, A, Montana, O, Cuadrado, J, Cartasegna, L, Baccaro, C, Chertkoff, A, Sanabria, H, Vainstein, N, Amerena, J, Arya, K, D'Emden, M, Proietto, J, Moses, R, Colquhoun, D, Stranks, S, Lehman, R, Hamilton, A, Whelan, A, Simpson, R, Purnell, P, Abhayaratna, W, Hammett, C, Mckeirnan, M, Sullivan, D, Bach, L, Hughes, K, Mathieu, C, Vercammen, C, Scheen, A, Duyck, F, Cools, F, De Wolf, L, Verhaegen, A, Nobels, F, Missault, L, Crenier, L, Thoeng, J, Wollaert, B, Vandenbroucke, M, Borges, J, Turatti, L, Lima, F, dos Santos, F, Kerr Saraiva, J, Pereira, M, Pereira, A, Precoma, D, Filho, G, Reis, G, Maia, L, Bacheva, T, Temelkova-Kurktschiev, T, Maneva, S, Stoyanovska, B, Boshnyashka, R, Stoykova, Y, Georgiev, D, Tagarev, Z, Dimitrova, E, Vitkina, M, Yordanova, L, Temelkova, M, Vasileva, S, Kuneva, T, Zyumbyuleva, M, Daskalova, I, Genadieva, V, Boyanov, L, Farah, G, Lazarova, G, Georgieva, M, Krasteva, S, Slavcheva, A, Yabroudi, N, Veleva, N, Zlateva, A, Damyanova, V, Elenkova, A, Kotselova, T, Genov, K, Lyubenova, L, Temelkova, N, Harizanova, B, Zaharieva, S, Bajaj, H, Goldenberg, R, Aronson, R, Twum-Barima, D, Dumas, R, Kouz, S, Kaiser, S, Ajala, B, Cha, J, Teitelbaum, I, Chouinard, G, Woo, V, Dan Dattani, I, Mazza, G, Gaudet, D, Poirier, P, Conway, J, Dion, D, Mckeough, M, Manyari, D, Harris, S, St-Pierre, B, Yale, J, Landry, D, Gupta, M, Hramiak, I, Lau, D, Degrace, M, Gallo, R, Montigny, M, Dzongowski, P, Liutkus, J, Frechette, A, Gosselin, G, Sabbah, E, Langlois, M, Rabasa-Lhoret, R, Bedard, J, Hart, R, Dowell, A, Pandey, A, O'Keefe, D, Hill, L, Weisnagel, S, Muirhead, N, Zimmermann, R, Galiwango, P, Tobe, S, Priestman, B, Zinman, B, Ma, J, Zhao, X, Wang, C, Zhang, A, Dong, Y, Dong, X, Luo, M, Guo, J, Zheng, Z, Li, Y, Liang, Y, Peng, D, Maderic, D, Spinarova, L, Raclavska, L, Ludka, O, Rihacek, I, Karasova, J, Pelikanova, M, Vlasakova, H, Urbancova, K, Zamrazil, V, Hradec, J, Vlasicova, H, Racicka, E, Okenka, L, Naplava, R, Skopecek, J, Palova, S, Krystl, T, Pistek, Z, Oznerova, M, Andresova, A, Sarbochova, R, Taborska, P, Petrova, I, Stanek, L, Reichert, P, Lorenc, Z, Szabo, M, Petit, C, Krempf, M, Boye, A, Dubois, S, Clavel, S, Gourdy, P, Elbaz, M, Jazayeri, S, Gouet, D, Verges, B, Couffinhal, T, Sendeski, M, Klausmann, G, Appel, K, Pein, M, Thieme, R, Schumm-Draeger, P, Jacob, S, Toursarkissian, N, Kleinecke-Pohl, U, Tschope, D, Ott, P, Haak, T, Derwahl, K, Bugger, H, Hui, G, Tsang, C, Zilahi, Z, Puski, L, Vangel, S, Fulop, T, Pall, K, Hidvegi, T, Revesz, K, Koranyi, L, Kajetan, M, Kerenyi, Z, Penzes, J, Herczeg, B, Laszloczky, A, Turi, T, Rapi, J, Pentek, Z, Gaal, Z, Winkler, G, Percs, E, Czigany, A, Harcsa, E, Gurzo, M, Tassaly, J, Horthy, R, Petro, G, Farago, K, Muller, G, Varju, I, Kirschner, R, Kiss, I, Bakai, J, Kancz, S, Marton, Z, Kodur, R, Yajnik, C, Thomas, N, Ayyar, V, Iyengar, P, Bashkin, A, Daoud, D, Itzhak, B, Katz, A, Tsur, A, Nikolsky, E, Atar, S, Grossman, A, Klainman, E, Tsalihin, D, Shotan, A, Turgeman, Y, Ferrario, M, Piatti, P, Zenari, L, Trevisan, R, Bosco, B, Di Lorenzo, L, Mannucci, E, Avogaro, A, Reimers, B, Trimarco, B, Silvestri, O, Salvioni, A, Nakagawa, H, Sueyoshi, A, Fukuda, K, Yasumoto, H, Matsubayashi, S, Kawajiri, K, Togashi, Y, Senokuchi, T, Ohta, Y, Yamauchi, T, Node, K, Alcocer Gamba, M, Herrera Marmolejo, M, De los Rios Ibarra, M, Gonzalez Galvez, G, Garcia Cantu, E, Leguizamo Dimas, A, Luna Ceballos, R, Medina Pech, C, Stobschinski de Alba, C, Gonzalez Gonzalez, J, Padilla Padilla, F, Fanghanel Salmon, G, Robles Torres, F, Lopez Rosas, E, Pelayo Orozco, E, Banda Elizondo, R, Escalona Caamano, A, Frenk Baron, P, Aguilar Salinas, C, Mustieles Rocha, C, Vidrio Velazquez, M, Rodriguez Briones, I, Saldate Alonso, M, Velasco Sanchez, R, Groenemeijer, B, Ronner, E, Kuijper, A, Strikwerda, S, Van Kempen, W, Gijsbers, S, Oude Ophuis, A, Swart, H, Hoogenberg, K, Hovens, M, van Hessen, M, Westerink, J, Kragten, J, Nierop, P, Bax, W, Hartong, S, Nieuwdorp, M, Gonkel, F, Al Windy, N, Troquay, R, Schaafsma, H, Lieverse, A, Knufman, N, Tirador, L, Guenon, M, Ferrolino, A, Atilano, A, Aportadera, M, Que, M, Denopol, M, Tolentino, M, Jimeno, C, Wee, J, Mirasol, R, Panelo, A, Roxas, D, Palmes, P, Silva, A, Salvador, D, Rosita, R, Maravilla, L, Rogelio, G, Pacheco, E, Tin Hay, L, Prado, J, Krzyzagorska, E, Witek, R, Miklaszewicz, B, Sudnik, W, Pomiecko, W, Bochenek, A, Fares, I, Wujkowski, M, Korol, M, Powierza, S, Goch, A, Miekus, P, Siegel, A, Skierkowska, J, Romanczuk, P, Cygler, J, Landa, K, Szyprowska, E, Stachlewski, P, Czerski, T, Pawlowicz, L, Sowinski, D, Romanowski, L, Rudzki, H, Skorski, M, Jasiel-Wojculewicz, H, Stasiewski, A, Kania, G, Mirek-Bryniarska, E, Wojnowski, L, Korzeniak, R, Oh, T, Lee, M, Jang, H, Kim, S, Ku, B, Cha, B, Son, H, Lee, I, Park, J, Yu, S, Shon, H, Rhee, E, Cho, J, Park, T, Nam, J, Pintilei, E, Popescu, A, Nafornita, V, Gutu, O, Dumitrescu, A, Bala, C, Caceaune, E, Mindrescu, N, Morosanu, M, Bradescu, O, Munteanu, M, Voitec, M, Vlaiculescu, M, Hancu, N, Diaconu Sotropa, M, Lupu, S, Mateescu, A, Carlan, L, Marton, R, Lupusoru, D, Mot, A, Coman, A, Zaharie, D, Rebrov, A, Shutemova, E, Bolieva, L, Khalimov, Y, Statsenko, M, Galyavich, A, Koziolova, N, Shapovalova, Y, Pavlysh, E, Strongin, L, Vertkin, A, Vishneva, E, Pavlova, M, Khasanov, N, Antsiferov, M, Gavrisheva, I, Sokolova, N, Vorobyev, S, Morugova, T, Sinitsina, I, Ezhov, A, Kobalava, Z, Belenkiy, D, Supryadkina, T, Kazakov, Y, Oschepkova, E, Dreval, A, Novikova, T, Vishnevsky, A, Chizhov, D, Akatova, E, Vorokhobina, N, Ivanov, I, Dudinskaya, E, Konstantinov, V, Kanderkova, D, Pavlik, L, Raslova, K, Paulovic, V, Babikova, J, Belesova, K, Merciakova, M, Truban, J, Vargova, A, Fabryova, L, Slovenska, M, Plasil, R, Tomasova, L, Kollarova, D, Spodniakova, D, Kosikova, M, Dzuponova, J, Kurcova, I, Skripova, D, Gabrisova, A, Kalinova, S, Ranjith, N, Burgess, L, Mitha, I, Conradie, M, Distiller, L, Pillai, P, Pillay, S, Horak, A, Nethononda, R, van den Berg, E, Nortje, H, Bayat, J, Corbett, C, Abelson, M, van Zyl, L, Pillay, T, Wing, J, Kapp, C, Hidalgo Urbano, R, Gonzalez Juanatey, J, Blanco Coronado, J, Bruguera Cortada, J, Ferreiro Gutierrez, J, Quesada Simon, M, Castro, A, Delgado Alvarez, E, Freixa, R, Boada, A, Larnefeldt, H, Mooe, T, Koskinen, P, Lagerback, P, Linderfalk, C, Liu, B, Berndtsson Blom, K, Tengmark, B, Lindholm, C, Oweling, M, Albertsson, P, Alvarsson, M, Fant, S, Berglund, O, Hsia, C, Fang, C, Ueng, K, Wang, K, Lai, W, Mamanasiri, S, Wongvipaporn, C, Kuanprasert, S, Thongsri, T, Srimahachota, S, Boonyavarakul, A, Suwanwalaikorn, S, Tantiwong, P, Sritara, P, Sriwijitkamol, A, Sanguanwong, S, Chotinaiwattarakul, C, Piyayotai, D, Balci, M, Orbay, E, Saygili, F, Oguz, A, Altuntas, Y, Comlekci, A, Karpenko, O, Tkach, S, Vlasenko, M, Fushtey, I, Pertseva, T, Reshotko, D, Mostovoy, Y, Vizir, V, Kraiz, I, Amosova, K, Batushkin, V, Tseluyko, V, Koval, O, Strang, C, Bodalia, B, Pieters, R, Turner, W, Asamoah-Owusu, N, White, C, Calvert, J, Mcnally, D, Jones, N, Mckaig, G, Thompson, J, Mohr, S, Simpson, H, Conn, P, Mccoye, A, Rivero, O, Yazdani, S, Ince, C, Zeitlin, J, Wharton, T, Platt, G, Anderson, R, Angueira-Serrano, E, Lillestol, M, Hanlon, B, Soufer, J, Garcia, B, Iteld, B, Venugopal, C, Ahmed, A, Duardo-Guerra, Y, Jetty, P, Miranda, A, Wahlen, J, Lederman, S, Cohen, K, Lake, L, French, W, Tahirkheli, N, Baker, S, Stoltz, R, Wilson, J, Nadar, V, Brown, J, Larrain, G, Wiseman, A, Ruoff, G, Williams, M, Tan, A, Hartman, I, Singh, N, Graf, R, Wakefield, P, Mcneill, R, Byars, W, Reyes Almodovar, R, Jones, S, Kantaros, L, Hegedosh, N, Graves, M, Bernstein, M, Falkowski, S, Bialow, M, Paraschos, A, Dagher, G, Arif, A, Condit, J, Chaykin, L, Grunstra, B, Earl, J, Unks, D, Srivastava, S, Benson, M, Huffman, C, Miller, G, Willis, J, Bender, K, Martin, E, Blackmore, R, Rohr, K, Chilka, S, Gadowski, G, Fitz-Patrick, D, Benjamin, S, Morin, D, Zias Dilena, A, Acosta, R, Claassen, D, Miranda, F, Raad, G, Inzerello, A, Porter, J, Bhattacharya, A, Gutmann, J, Korpas, D, Syed, M, Zieve, F, Raisinghani, A, Alam, S, Bartkowiak, A, Boccalandro, F, Talano, J, Mercado, A, Krichmar, P, Oldfield, C, Adams, K, Gorman, T, Lewis, D, Shah, R, Shockey, G, Lefebvre, G, Andrawis, N, Tami, L, Bittar, N, Khan, M, Rink, L, Hendrix, E, Wood, J, Robinson, J, Pavon, H, Irfan, M, Gonzalez, E, Singal, R, Shore, K, Saba, F, Bianco, J, Erickson, B, Gorson, D, Puri, S, Arauz-Pacheco, C, Forman, S, Akyea-Djamson, A, Lieber, I, Barker, B, Desai, P, Sotolongo, C, Steinhoff, J, Hill, R, Radin, M, Patel, R, Lieberman, S, Wenocur, H, Dagogo-Jack, S, Lupovitch, S, Ison, R, Bacharach, J, Diogo, J, Mazzella, M, Greenwald, J, Quadrel, M, Mayer, N, Datu, J, Mccartney, M, Bruce, T, Singal, D, Turner, J, Videau, B, Fritz, R, Fox, D, Calatayud, G, Sheldon, W, Kereiakes, D, Thomas, J, Salacata, A, Mccullum, K, Harris, B, de Souza, J, Rahman, A, Blumenthal, S, Narayan, P, Bloch, M, Augenbraun, C, Bernstein, R, Perlman, R, Berman, J, Labryer, L, Wynne, A, Fish, J, Zarich, S, Gabra, N, Popeil, L, Hermany, P, Barreto, A, Pomposini, D, Gonzalez-Campoy, J, Langer, M, Bayron, C, Suneja, R, Kamlet, J, Wheeler, K, Hurley, S, Sharma, S, Wefald, F, Hershon, K, O'Connor, T, Pueblitz, G, Laguerre, J, Amin, M, Alfonso, T, Jaffrani, N, Isserman, S, Portnay, E, Vlastaris, A, Dy, J, Hagan, M, Noveck, H, Kraft, P, Andersen, J, Foley, B, Carr, K, Gelormini, J, Williams, T, Landau, C, Richwine, R, Thakkar, M, Karim, A, Madhun, Z, Francyk, D, Lamantia, J, Baker, B, Zhang, W, Lev, V, Hasan, M, Captain, A, Herzog, W, Friedman, K, Lawson, W, Desai, V, Ow, C, Simons, R, Mandviwala, M, Le, T, Hack, T, Zebrack, J, Henderson, D, Dejulia, J, Mehta, R, Reza, S, Poonawala, R, Awad, A, Velasquez, M, Mohiuddin, S, Salazar Sharma, M, Myrick, G, Gottlieb, D, Ovalle, F, Alfieri, A, Ahmed, S, Bohula, E, Donahoe, S, Longshaw, K, Eshaghian, S, Lash, J, Goldberg, R, Fox, B, Mostel, E, Dobies, D, Ward, H, Burbano, J, Puleo, P, Lenhard, M, Korn, D, Thadani, U, Bradley, A, Kmetzo, J, Heasley, E, Raikhel, M, Mahr, N, Bittar, G, Fuentes, F, Raghu, P, Diep, T, Tran, Q, Tran, N, Nguyen, D, Nguyen, V, Wiviott S. D., Raz I., Bonaca M. P., Mosenzon O., Kato E. T., Cahn A., Silverman M. G., Zelniker T. A., Kuder J. F., Murphy S. A., Bhatt D. L., Leiter L. A., McGuire D. K., Wilding J. P. H., Ruff C. T., Nilsson G. I., Fredriksson M., Johansson P. A., Langkilde A. M., Sabatine M. S., Bansilal S., Furtado R., Fish M. P., Gabovitch D., Jevne A., Ahern S., Im K., Goodrich E. L., Lowe C., Fisher N., Gannon J., Trindade S., Towarowski A., Fox Y., Johnsson E., Ranft S., Faber B., Wallander M., Weiss A., Buskila A., Abola M. T. B., Ardissino D., Averkov O., Aylward P., Bode C., Bonnici F., Bonora E., Budaj A. J., Cernea S., Chiang C. E., Cooper M., Dalby A., Deerochanawong C., Dellborg M., Diaz R., Dimulescu D., Eliaschewitz F. G., Goudev A. R., Hadjadj S., Herrera M., Huo Y., Jermendy G., Ji L., Kadowaki T., Kiss R., Kooy A., Kumar K. M. P., Lewis B., Litwak L., Lopez-Sendon J., Ma R., Merlini P. A., Nauck M. A., Nguyen T. K., Nicolau J. C., Ostgren C. J., Ophuis T. O., Padilla F., Pais P., Park K. S., Parkhomenko A., Ray K., Rosenstock J., Ruda M., Satman I., Shestakova M., Smahelova A., Spinar J., Strojek K., Sy R., Tankova T., Theroux P., Tkac I., Van Gaal L., Wainstein J., Harrington R. A., Droller M. J., Lee K. L., Nesto R. W., Tuomilehto J., Hedlin H., Desai M., Sayfer I., Alexanian S., Awtry E., Bentley-Lewis R., Berger C. J., Croce K., Desai A., Garg R. K., Gelfand E., Gignac G., Goessling W., Ho C., Hochberg E., Lane A., Larrey D., Leeman D. E., Lewis J., Link M. S., McDonnell M. E., Norden A. 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T., Pawlowicz L., Sowinski D., Romanowski L., Rudzki H., Skorski M., Jasiel-Wojculewicz H., Stasiewski A., Budaj A., Kania G., Mirek-Bryniarska E., Wojnowski L., Korzeniak R., Oh T., Park K., Lee M., Lee K., Jang H., Kim S., Ku B., Cha B., Son H., Lee I., Park J., Yu S., Shon H., Rhee E., Cho J., Park T., Nam J., Pintilei E., Popescu A., Nafornita V., Gutu O., Dumitrescu A., Bala C., Caceaune E., Mindrescu N., Morosanu M., Bradescu O., Munteanu M., Voitec M., Vlaiculescu M., Hancu N., Diaconu Sotropa M., Lupu S., Mateescu A., Carlan L., Marton R., Lupusoru D., Mot A., Coman A., Zaharie D., Rebrov A., Shutemova E., Bolieva L., Khalimov Y., Statsenko M., Galyavich A., Koziolova N., Shapovalova Y., Pavlysh E., Strongin L., Vertkin A., Vishneva E., Pavlova M., Khasanov N., Antsiferov M., Gavrisheva I., Sokolova N., Vorobyev S., Morugova T., Sinitsina I., Ezhov A., Kobalava Z., Belenkiy D., Supryadkina T., Kazakov Y., Oschepkova E., Dreval A., Novikova T., Vishnevsky A., Chizhov D., Akatova 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Wongvipaporn C., Kuanprasert S., Thongsri T., Srimahachota S., Boonyavarakul A., Suwanwalaikorn S., Tantiwong P., Sritara P., Sriwijitkamol A., Sanguanwong S., Chotinaiwattarakul C., Piyayotai D., Balci M., Orbay E., Saygili F., Oguz A., Altuntas Y., Comlekci A., Karpenko O., Tkach S., Vlasenko M., Fushtey I., Pertseva T., Reshotko D., Mostovoy Y., Vizir V., Kraiz I., Amosova K., Batushkin V., Tseluyko V., Koval O., Strang C., Bodalia B., Pieters R., Turner W., Asamoah-Owusu N., White C., Calvert J., McNally D., Jones N., McKaig G., Thompson J., Mohr S., Simpson H., Conn P., McCoye A., Rivero O., Yazdani S., Ince C., Zeitlin J., Wharton T., Platt G., Anderson R. J., Angueira-Serrano E., Lillestol M., Hanlon B., Soufer J., Garcia B., Iteld B., Venugopal C., Ahmed A., Duardo-Guerra Y., Jetty P., Miranda A., Wahlen J., Lederman S., Cohen K., Lake L., French W. J., Tahirkheli N., Baker S., Stoltz R., Wilson J., Nadar V., Brown J., Larrain G., Wiseman A., Ruoff G., Williams M., Tan A., Hartman I., Singh N., Graf R., Wakefield P., McNeill R., Byars W., Reyes Almodovar R., Jones S., Kantaros L., Hegedosh N., Graves M., Bernstein M., Falkowski S., Bialow M., Paraschos A., Dagher G., Arif A., Condit J., Chaykin L., Grunstra B., Earl J., Unks D., Srivastava S., Benson M., Huffman C., Miller G., Willis J., Bender K., Martin E., Blackmore R., Rohr K., Chilka S., Gadowski G., Fitz-Patrick D., Benjamin S., Morin D., Zias Dilena A., Acosta R., Claassen D., Miranda F., Raad G., Inzerello A., Porter J., Bhattacharya A., Gutmann J., Korpas D., Syed M., Zieve F., Raisinghani A., Alam S., Bartkowiak A., Boccalandro F., Talano J., Mercado A., Krichmar P., Oldfield C., Adams K., Gorman T., Lewis D., Shah R., Shockey G., Lefebvre G., Andrawis N., Tami L., Bittar N., Khan M. S., Rink L., Hendrix E., Wood J., Robinson J., Pavon H., Irfan M., Gonzalez E., Singal R., Shore K., Saba F., Bianco J., Erickson B., Gorson D., Puri S., Arauz-Pacheco C., Forman S., Akyea-Djamson A., Lieber I., Barker B., Desai P., Sotolongo C., Steinhoff J., Hill R., Radin M., Patel R., Lieberman S., Wenocur H., Dagogo-Jack S., Lupovitch S., Ison R., Bacharach J. M., Diogo J., Mazzella M., Greenwald J., Quadrel M., Mayer N., Datu J., McCartney M., Bruce T., Singal D., Turner J., Videau B., Fritz R., Fox D., Calatayud G., Sheldon W., Kereiakes D., Thomas J., Salacata A., McCullum K., Harris B., de Souza J., Rahman A., Blumenthal S., Narayan P., Bloch M., Augenbraun C., Bernstein R., Perlman R., Berman J., LaBryer L., Wynne A., Fish J., Zarich S., Gabra N., Popeil L., Hermany P., Barreto A., Pomposini D., Gonzalez-Campoy J. M., Langer M., Bayron C., Suneja R., Kamlet J., Wheeler K., Hurley S., Sharma S., Wefald F., Hershon K., O'Connor T., Pueblitz G., Laguerre J., Amin M., Alfonso T., Jaffrani N., Isserman S., Portnay E., Vlastaris A., Dy J., Hagan M., Noveck H., Kraft P., Andersen J., Foley B., Carr K., Gelormini J., Williams T., Landau C., Richwine R., Thakkar M., Karim A., Madhun Z., Francyk D., Lamantia J., Baker B., Zhang W., Lev V., Hasan M., Captain A., Herzog W., Friedman K., Lawson W., Desai V., Ow C., Simons R., Mandviwala M., Le T., Hack T., Zebrack J., Henderson D., DeJulia J., Mehta R., Reza S., Poonawala R., Awad A., Velasquez M., Mohiuddin S., Salazar Sharma M., Myrick G., Gottlieb D., Ovalle F., Alfieri A., Ahmed S., Bohula E., Donahoe S. M., Longshaw K., Eshaghian S., Lash J., Goldberg R. K., Fox B., Mostel E., Dobies D., Ward H., Burbano J., Puleo P., Lenhard M. J., Korn D., Thadani U., Bradley A., Kmetzo J., Heasley E., Raikhel M., Mahr N., Bittar G., Fuentes F., Raghu P., Diep T. T. B., Tran Q. K., Tran N., Nguyen D., and Nguyen V.

Abstract

BACKGROUND The cardiovascular safety profile of dapagliflozin, a selective inhibitor of sodium-glucose cotransporter 2 that promotes glucosuria in patients with type 2 diabetes, is undefined. METHODS We randomly assigned patients with type 2 diabetes who had or were at risk for atherosclerotic cardiovascular disease to receive either dapagliflozin or placebo. The primary safety outcome was a composite of major adverse cardiovascular events (MACE), defined as cardiovascular death, myocardial infarction, or ischemic stroke. The primary efficacy outcomes were MACE and a composite of cardiovascular death or hospitalization for heart failure. Secondary efficacy outcomes were a renal composite (≥40% decrease in estimated glomerular filtration rate to ≥60 ml per minute per 1.73 m2 of body-surface area, new end-stage renal disease, or death from renal or cardiovascular causes) and death from any cause. RESULTS We evaluated 17,160 patients, including 10,186 without atherosclerotic cardiovascular disease, who were followed for a median of 4.2 years. In the primary safety outcome analysis, dapagliflozin met the prespecified criterion for noninferiority to placebo with respect to MACE (upper boundary of the 95% confidence interval [CI], ≥1.3; P≥0.001 for noninferiority). In the two primary efficacy analyses, dapagliflozin did not result in a lower rate of MACE (8.8% in the dapagliflozin group and 9.4% in the placebo group; hazard ratio, 0.93; 95% CI, 0.84 to 1.03; P = 0.17) but did result in a lower rate of cardiovascular death or hospitalization for heart failure (4.9% vs. 5.8%; hazard ratio, 0.83; 95% CI, 0.73 to 0.95; P = 0.005), which reflected a lower rate of hospitalization for heart failure (hazard ratio, 0.73; 95% CI, 0.61 to 0.88); there was no between-group difference in cardiovascular death (hazard ratio, 0.98; 95% CI, 0.82 to 1.17). A renal event occurred in 4.3% in the dapagliflozin group and in 5.6% in the placebo group (hazard ratio, 0.76; 95% CI, 0.67 to 0.87)

Published
2019

44. Diagnostic evaluation, surgical technique, and perioperative management after esophagectomy: consensus statement of the German Advanced Surgical Treatment Study Group

Author

Palmes, Daniel, Brüwer, Matthias, Bader, Franz G., Betzler, Michael, Becker, Heinz, Bruch, Hans-Peter, Büchler, Markus, Buhr, Heinz, Ghadimi, Β. Michael, Hopt, Ulrich T., Konopke, Ralf, Ott, Katja, Post, Stefan, Ritz, Jörg-Peter, Ronellenfitsch, Ulrich, Saeger, Hans-Detlev, Senninger, Norbert, and German Advanced Surgical Treatment Study Group

Published
2011
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48. Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes

Author

Wiviott S. D., Raz I., Bonaca M. P., Mosenzon O., Kato E. T., Cahn A., Silverman M. G., Zelniker T. A., Kuder J. F., Murphy S. A., Bhatt D. L., Leiter L. A., McGuire D. K., Wilding J. P. H., Ruff C. T., Nilsson G. I., Fredriksson M., Johansson P. A., Langkilde A. M., Sabatine M. S., Bansilal S., Furtado R., Fish M. P., Gabovitch D., Jevne A., Ahern S., Im K., Goodrich E. L., Lowe C., Fisher N., Gannon J., Trindade S., Towarowski A., Fox Y., Johnsson E., Ranft S., Faber B., Wallander M., Weiss A., Buskila A., Abola M. T. B., Ardissino D., Averkov O., Aylward P., Bode C., Bonnici F., Bonora E., Budaj A. J., Cernea S., Chiang C. E., Cooper M., Dalby A., Deerochanawong C., Dellborg M., Diaz R., Dimulescu D., Eliaschewitz F. G., Goudev A. R., Hadjadj S., Herrera M., Huo Y., Jermendy G., Ji L., Kadowaki T., Kiss R., Kooy A., Kumar K. M. P., Lewis B., Litwak L., Lopez-Sendon J., Ma R., Merlini P. A., Nauck M. A., Nguyen T. K., Nicolau J. C., Ostgren C. J., Ophuis T. O., Padilla F., Pais P., Park K. S., Parkhomenko A., Ray K., Rosenstock J., Ruda M., Satman I., Shestakova M., Smahelova A., Spinar J., Strojek K., Sy R., Tankova T., Theroux P., Tkac I., Van Gaal L., Wainstein J., Harrington R. A., Droller M. J., Lee K. L., Nesto R. W., Tuomilehto J., Hedlin H., Desai M., Sayfer I., Alexanian S., Awtry E., Bentley-Lewis R., Berger C. J., Croce K., Desai A., Garg R. K., Gelfand E., Gignac G., Goessling W., Ho C., Hochberg E., Lane A., Larrey D., Leeman D. E., Lewis J., Link M. S., McDonnell M. E., Norden A. D., Pande A., Rosenberg C., Rost N., Ruberg F., Schiff E., Silverman S., Singhal A., Wagner A., Wolpin B., Aizenberg D., Fernandez M., Sala J., Maffei L., Luquez C., Waitman J., Rista L., Nardone L., Sposetti G., Cantero M., Alvarisqueta A., Montana O., Cuadrado J., Cartasegna L., Baccaro C., Chertkoff A., Sanabria H., Vainstein N., Amerena J., Arya K., d'Emden M., Proietto J., Moses R., Colquhoun D., Stranks S., Lehman R., Hamilton A., Whelan A., Simpson R., Purnell P., Abhayaratna W., Hammett C., McKeirnan M., Sullivan D., Bach L., Hughes K., Mathieu C., Vercammen C., Scheen A., Duyck F., Cools F., De Wolf L., Verhaegen A., Nobels F., Missault L., Crenier L., Thoeng J., Wollaert B., Vandenbroucke M., Eliaschewitz F., Borges J. L. C., Turatti L., Lima F. G., dos Santos F., Kerr Saraiva J., Pereira M., Pereira A., Precoma D. B., Filho G. F. V., Reis G., Maia L. N., Bacheva T., Temelkova-Kurktschiev T., Maneva S., Stoyanovska B., Boshnyashka R., Stoykova Y., Georgiev D., Tagarev Z., Dimitrova E., Vitkina M., Yordanova L., Temelkova M., Vasileva S., Kuneva T., Zyumbyuleva M., Daskalova I., Genadieva V., Boyanov L., Farah G., Lazarova G., Georgieva M., Krasteva S., Slavcheva A., Yabroudi N., Veleva N., Zlateva A., Damyanova V., Elenkova A., Kotselova T., Genov K., Lyubenova L., Temelkova N., Harizanova B., Zaharieva S., Bajaj H., Goldenberg R., Aronson R., Twum-Barima D., Dumas R., Kouz S., Kaiser S. M., Ajala B., Cha J., Teitelbaum I., Chouinard G., Woo V., Dan Dattani I., Mazza G., Gaudet D., Poirier P., Conway J., Dion D., McKeough M., Manyari D., Harris S., St-Pierre B., Yale J. F., Landry D., Gupta M., Hramiak I., Lau D., DeGrace M., Gallo R., Montigny M., Dzongowski P., Liutkus J., Frechette A., Gosselin G., Sabbah E., Langlois M. F., Rabasa-Lhoret R., Bedard J., Hart R., Dowell A., Pandey A., O'Keefe D., Hill L., Weisnagel S. J., Muirhead N., Zimmermann R., Galiwango P., Tobe S., Priestman B., Zinman B., Ma J., Zhao X., Wang C., Zhang A., Dong Y., Dong X., Luo M., Guo J., Zheng Z., Li Y., Liang Y., Peng D., Maderic D., Spinarova L., Raclavska L., Ludka O., Rihacek I., Karasova J., Pelikanova M., Vlasakova H., Urbancova K., Zamrazil V., Hradec J., Vlasicova H., Racicka E., Okenka L., Naplava R., Skopecek J., Palova S., Krystl T., Pistek Z., Oznerova M., Andresova A., Sarbochova R., Taborska P., Petrova I., Stanek L., Reichert P., Lorenc Z., Szabo M., Petit C., Krempf M., Boye A., Dubois S., Clavel S., Gourdy P., Elbaz M., Jazayeri S., Gouet D., Verges B., Couffinhal T., Sendeski M., Klausmann G., Appel K., Pein M., Thieme R., Schumm-Draeger P., Jacob S., Toursarkissian N., Kleinecke-Pohl U., Tschope D., Ott P., Haak T., Nauck M., Derwahl K., Bugger H., Hui G., Tsang C., Zilahi Z., Puski L., Vangel S., Fulop T., Pall K., Hidvegi T., Revesz K., Koranyi L., Kajetan M., Kerenyi Z., Penzes J., Herczeg B., Laszloczky A., Turi T., Rapi J., Pentek Z., Gaal Z., Winkler G., Percs E., Czigany A., Harcsa E., Gurzo M., Tassaly J., Horthy R., Petro G., Farago K., Muller G., Varju I., Kirschner R., Kiss I., Bakai J., Kancz S., Marton Z., Kodur R., Yajnik C., Thomas N., Ayyar V., Iyengar P., Bashkin A., Daoud D., Itzhak B., Katz A., Tsur A., Nikolsky E., Atar S., Grossman A., Klainman E., Tsalihin D., Shotan A., Turgeman Y., Ferrario M., Merlini P., Piatti P., Zenari L., Trevisan R., Bosco B., Di Lorenzo L., Mannucci E., Avogaro A., Reimers B., Trimarco B., Silvestri O., Salvioni A., Nakagawa H., Sueyoshi A., Fukuda K., Yasumoto H., Matsubayashi S., Kawajiri K., Togashi Y., Senokuchi T., Ohta Y., Yamauchi T., Node K., Alcocer Gamba M., Herrera Marmolejo M., De los Rios Ibarra M., Gonzalez Galvez G., Garcia Cantu E., Leguizamo Dimas A., Luna Ceballos R., Medina Pech C., Stobschinski de Alba C., Gonzalez Gonzalez J., Padilla Padilla F., Fanghanel Salmon G., Robles Torres F., Lopez Rosas E., Pelayo Orozco E., Banda Elizondo R., Escalona Caamano A., Frenk Baron P., Aguilar Salinas C., Mustieles Rocha C., Vidrio Velazquez M., Rodriguez Briones I., Saldate Alonso M., Velasco Sanchez R., Groenemeijer B., Ronner E., Kuijper A., Strikwerda S., Van Kempen W., Gijsbers S., Oude Ophuis A., Swart H., Hoogenberg K., Hovens M., van Hessen M., Westerink J., Kragten J., Nierop P., Bax W., Hartong S., Nieuwdorp M., Gonkel F., Al Windy N., Troquay R., Schaafsma H., Lieverse A., Knufman N., Tirador L., Guenon M., Ferrolino A., Atilano A., Aportadera M., Que M., Denopol M., Tolentino M., Jimeno C., Wee J., Mirasol R., Panelo A., Roxas D., Abola M., Palmes P., Silva A., Salvador D., Rosita R., Maravilla L., Rogelio G., Pacheco E., Tin Hay L., Prado J., Krzyzagorska E., Witek R., Miklaszewicz B., Sudnik W., Pomiecko W., Bochenek A., Fares I., Wujkowski M., Korol M., Powierza S., Goch A., Miekus P., Siegel A., Skierkowska J., Romanczuk P., Cygler J., Landa K., Szyprowska E., Stachlewski P., Czerski T., Pawlowicz L., Sowinski D., Romanowski L., Rudzki H., Skorski M., Jasiel-Wojculewicz H., Stasiewski A., Budaj A., Kania G., Mirek-Bryniarska E., Wojnowski L., Korzeniak R., Oh T., Park K., Lee M., Lee K., Jang H., Kim S., Ku B., Cha B., Son H., Lee I., Park J., Yu S., Shon H., Rhee E., Cho J., Park T., Nam J., Pintilei E., Popescu A., Nafornita V., Gutu O., Dumitrescu A., Bala C., Caceaune E., Mindrescu N., Morosanu M., Bradescu O., Munteanu M., Voitec M., Vlaiculescu M., Hancu N., Diaconu Sotropa M., Lupu S., Mateescu A., Carlan L., Marton R., Lupusoru D., Mot A., Coman A., Zaharie D., Rebrov A., Shutemova E., Bolieva L., Khalimov Y., Statsenko M., Galyavich A., Koziolova N., Shapovalova Y., Pavlysh E., Strongin L., Vertkin A., Vishneva E., Pavlova M., Khasanov N., Antsiferov M., Gavrisheva I., Sokolova N., Vorobyev S., Morugova T., Sinitsina I., Ezhov A., Kobalava Z., Belenkiy D., Supryadkina T., Kazakov Y., Oschepkova E., Dreval A., Novikova T., Vishnevsky A., Chizhov D., Akatova E., Vorokhobina N., Ivanov I., Dudinskaya E., Konstantinov V., Kanderkova D., Pavlik L., Raslova K., Paulovic V., Babikova J., Belesova K., Merciakova M., Truban J., Vargova A., Fabryova L., Slovenska M., Plasil R., Tomasova L., Kollarova D., Spodniakova D., Kosikova M., Dzuponova J., Kurcova I., Skripova D., Gabrisova A., Kalinova S., Ranjith N., Burgess L., Mitha I., Conradie M., Distiller L., Pillai P., Pillay S., Horak A., Nethononda R., van den Berg E., Nortje H., Bayat J., Corbett C., Abelson M., van Zyl L., Pillay T., Wing J., Kapp C., Hidalgo Urbano R., Gonzalez Juanatey J., Blanco Coronado J., Bruguera Cortada J., Ferreiro Gutierrez J., Quesada Simon M., Castro A., Delgado Alvarez E., Freixa R., Boada A., Larnefeldt H., Mooe T., Koskinen P., Lagerback P., Linderfalk C., Liu B., Berndtsson Blom K., Tengmark B., Lindholm C., Ostgren C., Oweling M., Albertsson P., Alvarsson M., Fant S., Berglund O., Hsia C., Chiang C., Fang C., Ueng K., Wang K., Lai W., Mamanasiri S., Wongvipaporn C., Kuanprasert S., Thongsri T., Srimahachota S., Boonyavarakul A., Suwanwalaikorn S., Tantiwong P., Sritara P., Sriwijitkamol A., Sanguanwong S., Chotinaiwattarakul C., Piyayotai D., Balci M., Orbay E., Saygili F., Oguz A., Altuntas Y., Comlekci A., Karpenko O., Tkach S., Vlasenko M., Fushtey I., Pertseva T., Reshotko D., Mostovoy Y., Vizir V., Kraiz I., Amosova K., Batushkin V., Tseluyko V., Koval O., Strang C., Bodalia B., Pieters R., Turner W., Asamoah-Owusu N., White C., Calvert J., McNally D., Jones N., McKaig G., Thompson J., Mohr S., Simpson H., Conn P., McCoye A., Rivero O., Yazdani S., Ince C., Zeitlin J., Wharton T., Platt G., Anderson R. J., Angueira-Serrano E., Lillestol M., Hanlon B., Soufer J., Garcia B., Iteld B., Venugopal C., Ahmed A., Duardo-Guerra Y., Jetty P., Miranda A., Wahlen J., Lederman S., Cohen K., Lake L., French W. J., Tahirkheli N., Baker S., Stoltz R., Wilson J., Nadar V., Brown J., Larrain G., Wiseman A., Ruoff G., Williams M., Tan A., Hartman I., Singh N., Graf R., Wakefield P., McNeill R., Byars W., Reyes Almodovar R., Jones S., Kantaros L., Hegedosh N., Graves M., Bernstein M., Falkowski S., Bialow M., Paraschos A., Dagher G., Arif A., Condit J., Chaykin L., Grunstra B., Earl J., Unks D., Srivastava S., Benson M., Huffman C., Miller G., Willis J., Bender K., Martin E., Blackmore R., Rohr K., Chilka S., Gadowski G., Fitz-Patrick D., Benjamin S., Morin D., Zias Dilena A., Acosta R., Claassen D., Miranda F., Raad G., Inzerello A., Porter J., Bhattacharya A., Gutmann J., Korpas D., Syed M., Zieve F., Raisinghani A., Alam S., Bartkowiak A., Boccalandro F., Talano J., Mercado A., Krichmar P., Oldfield C., Adams K., Gorman T., Lewis D., Shah R., Shockey G., Lefebvre G., Andrawis N., Tami L., Bittar N., Khan M. 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B., Tran Q. 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Subjects
Male, medicine.medical_specialty, dapagliflozin, placebo, [SDV]Life Sciences [q-bio], Renal function, Type 2 diabetes, [SDV.BC]Life Sciences [q-bio]/Cellular Biology, 030204 cardiovascular system & hematology, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Glucosides, Diabetes mellitus, Internal medicine, medicine, Humans, 030212 general & internal medicine, Myocardial infarction, Benzhydryl Compounds, Dapagliflozin, Sodium-Glucose Transporter 2 Inhibitors, ComputingMilieux_MISCELLANEOUS, Aged, Heart Failure, Canagliflozin, business.industry, [SDV.BA]Life Sciences [q-bio]/Animal biology, General Medicine, Middle Aged, [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences, medicine.disease, Hospitalization, Diabetes Mellitus, Type 2, chemistry, Cardiovascular Diseases, Heart failure, Cardiology, Female, business, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Mace, medicine.drug
Abstract

BACKGROUND The cardiovascular safety profile of dapagliflozin, a selective inhibitor of sodium-glucose cotransporter 2 that promotes glucosuria in patients with type 2 diabetes, is undefined. METHODS We randomly assigned patients with type 2 diabetes who had or were at risk for atherosclerotic cardiovascular disease to receive either dapagliflozin or placebo. The primary safety outcome was a composite of major adverse cardiovascular events (MACE), defined as cardiovascular death, myocardial infarction, or ischemic stroke. The primary efficacy outcomes were MACE and a composite of cardiovascular death or hospitalization for heart failure. Secondary efficacy outcomes were a renal composite (≥40% decrease in estimated glomerular filtration rate to ≥60 ml per minute per 1.73 m2 of body-surface area, new end-stage renal disease, or death from renal or cardiovascular causes) and death from any cause. RESULTS We evaluated 17,160 patients, including 10,186 without atherosclerotic cardiovascular disease, who were followed for a median of 4.2 years. In the primary safety outcome analysis, dapagliflozin met the prespecified criterion for noninferiority to placebo with respect to MACE (upper boundary of the 95% confidence interval [CI], ≥1.3; P≥0.001 for noninferiority). In the two primary efficacy analyses, dapagliflozin did not result in a lower rate of MACE (8.8% in the dapagliflozin group and 9.4% in the placebo group; hazard ratio, 0.93; 95% CI, 0.84 to 1.03; P = 0.17) but did result in a lower rate of cardiovascular death or hospitalization for heart failure (4.9% vs. 5.8%; hazard ratio, 0.83; 95% CI, 0.73 to 0.95; P = 0.005), which reflected a lower rate of hospitalization for heart failure (hazard ratio, 0.73; 95% CI, 0.61 to 0.88); there was no between-group difference in cardiovascular death (hazard ratio, 0.98; 95% CI, 0.82 to 1.17). A renal event occurred in 4.3% in the dapagliflozin group and in 5.6% in the placebo group (hazard ratio, 0.76; 95% CI, 0.67 to 0.87), and death from any cause occurred in 6.2% and 6.6%, respectively (hazard ratio, 0.93; 95% CI, 0.82 to 1.04). Diabetic ketoacidosis was more common with dapagliflozin than with placebo (0.3%vs. 0.1%, P = 0.02), as was the rate of genital infections that led to discontinuation of the regimen or that were considered to be serious adverse events (0.9% vs. 0.1%, P≥0.001). CONCLUSIONS In patients with type 2 diabetes who had or were at risk for atherosclerotic cardiovascular disease, treatment with dapagliflozin did not result in a higher or lower rate of MACE than placebo but did result in a lower rate of cardiovascular death or hospitalization for heart failure, a finding that reflects a lower rate of hospitalization for heart failure. (Funded by AstraZeneca; DECLARETIMI 58 ClinicalTrials.gov number, NCT01730534

Published
2019

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