Approximations of the Fisher information for the construction of efficient experimental designs in nonlinear mixed effects models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2012

Experimental design for mixed models with application to population pharmacokinetic studies

experimental design, mixed model, random coefficient regression model, population pharmacokinetics, approximate design

New Exercise-Dipyridamole Combined Test for Nuclear Cardiology in Insufficient Effort: Appropriate Diagnostic Sensitivity Keeping Exercise Prognosis

AbstractBackground:Myocardial perfusion scintigraphy (MPS) in patients not reaching 85% of the maximum predicted heart rate (MPHR) has reduced sensitivity.Objectives:In an attempt to maintain diagnostic sensitivity without losing functional exercise data, a new exercise and dipyridamole combined protocol (EDCP) was developed. Our aim was to evaluate the feasibility and safety of this protocol and to compare its diagnostic sensitivity against standard exercise and dipyridamole protocols.Methods:In patients not reaching a sufficient exercise (SE) test and with no contraindications, 0.56 mg/kg of dipyridamole were IV administered over 1 minute simultaneously with exercise, followed by 99mTc-MIBI injection.Results:Of 155 patients, 41 had MPS with EDCP, 47 had a SE test (≥ 85% MPHR) and 67 underwent the dipyridamole alone test (DIP). They all underwent coronary angiography within 3 months. The three stress methods for diagnosis of coronary lesions had their sensitivity compared. For stenosis ≥ 70%, EDCP yielded 97% sensitivity, SE 90% and DIP 95% (p = 0.43). For lesions ≥ 50%, the sensitivities were 94%, 88% and 95%, respectively (p = 0.35). Side effects of EDCP were present in only 12% of the patients, significantly less than with DIP (p < 0.001).Conclusions:The proposed combined protocol is a valid and safe method that yields adequate diagnostic sensitivity, keeping exercise prognostic information in patients unable to reach target heart rate, with fewer side effects than the DIP.

Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

AbstractBackground:30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes.Objective:This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx) at different stages of cardiac resynchronization therapy (CRT).Methods:Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC) III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves.Results:The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD), ejection fraction < 25% and use of high doses of diuretics (HDD) increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping.Conclusion:We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.

Optimal designs for mixed effects poisson regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2010

Molecular determinants for the subcellular distribution of the synapto-nuclear protein messenger Jacob

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2010

Simulation of interacting populations in inhomogeneous flows using reduced models

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2010

Conversive Hidden non-Markovian models

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Analysis and numerical investigation of dynamic models for liquid chromatography

Magdeburg, Univ., Fak. für Mathematik, Diss., 2013

Regulation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-[kappa]B) by protein Kinase C theta (PKC-[theta]) and cylindromatosis (CYLD) in murine listeriosis and toxoplasmosis

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2013

Optimal designs for multivariate linear models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2013

Mathematical models of influenza A virus infection : from intracellular replication to virus growth in cell populations

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2015

Optimal designs for the prediction in hierarchical random coefficient regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

Analysis of animal models of neurodegenerative diseases with protein deposits

Otto-von-Guericke-Universität Magdeburg, Fakultät für Naturwissenschaften, Univ., Dissertation, 2016