Obtaining EQ-5D-5L utilities from the disease specific quality of life Alzheimer’s disease scale: development and results from a mapping study

Purpose The Quality of Life Alzheimer’s Disease Scale (QoL-AD) is commonly used to assess disease specific health-related quality of life (HRQoL) as rated by patients and their carers. For cost-effectiveness analyses, utilities based on the EQ-5D are often required. We report a new mapping algorithm to obtain EQ-5D indices when only QoL-AD data are available. Methods Different statistical models to estimate utility directly, or responses to individual EQ-5D questions (response mapping) from QoL-AD, were trialled for patient-rated and proxy-rated questionnaires. Model performance was assessed by root mean square error and mean absolute error. Results The response model using multinomial regression including age and sex, performed best in both the estimation dataset and an independent dataset. Conclusions The recommended mapping algorithm allows researchers for the first time to estimate EQ-5D values from QoL-AD data, enabling cost-utility analyses using datasets where the QoL-AD but no utility measures were collected

Influence of low-flow time on survival after extracorporeal cardiopulmonary resuscitation (eCPR)

Abstract Background Venoarterial extracorporeal membrane oxygenation (VA-ECMO) support under extracorporeal cardiopulmonary resuscitation (eCPR) is the last option and may be offered to selected patients. Several factors predict outcome in these patients, including initial heart rhythm, comorbidities, and bystander cardiopulmonary resuscitation (CPR). We evaluated outcomes of all VA-ECMO patients treated within the last 5 years at our center in respect to low-flow duration during CPR. Methods We report retrospective registry data on all patients with eCPR treated at a university hospital between October 2010 and May 2016. Results A total of 133 patients (mean age 58.7 ± 2.6 years, Simplified Acute Physiology Score II score at admission 48.1 ± 3.4) were included in the analysis. The indication for eCPR was either in-hospital or out-of-hospital cardiac arrest without return of spontaneous circulation (n = 74 and 59, respectively). There was a significant difference in survival rates between groups (eCPR in-hospital cardiac arrest [IHCA] 18.9%, eCPR out-of-hospital cardiac arrest [OHCA] 8.5%; p < 0.042). Mean low-flow duration (i.e., duration of mechanical CPR until VA-ECMO support) was 59.6 ± 5.0 minutes in all patients and significantly shorter in IHCA patients than in OHCA patients (49.6 ± 5.9 vs. 72.2 ± 7.4 minutes, p = 0.001). Low-flow time strongly correlated with survival (p < 0.001) and was an independent predictor of mortality. Conclusions Time to full support is an important and alterable predictor of patient survival in eCPR, suggesting that VA-ECMO therapy should be established as fast as possible in the selected patients destined for eCPR

Bayesian estimation of synaptic physiology from the spectral responses of neural masses

We describe a Bayesian inference scheme for quantifying the active physiology of neuronal ensembles using local field recordings of synaptic potentials. This entails the inversion of a generative neural mass model of steady-state spectral activity. The inversion uses Expectation Maximization (EM) to furnish the posterior probability of key synaptic parameter and the marginal likelihood of the model itself. The neural mass model embeds prior knowledge pertaining to both the anatomical [synaptic, circuitry and plausible trajectories of neuronal dynamics. This model comprises a population of excitatory pyramidal cells, under local interneuron inhibition and driving excitation from layer IV stellate cells. Under quasi-stationary assumptions, the model can predict the spectral profile of local field potentials (LFP). This means model parameters can be optimised given real electrophysiological observations. The validity of inferences about synaptic parameters is demonstrated using simulated data and experimental recordings from the medial prefrontal cortex of control and isolation-reared Wistar rats. Specifically, we examined the maximum a posteriori estimates of parameters describing synaptic function in the two groups and tested predictions derived from concomitant microdialysis measures. The modelling of the LFP recordings revealed (i) a sensitization of post-synaptic excitatory responses, particularly marked in pyramidal cells, in the medial prefrontal cortex of socially isolated rats and (ii) increased neuronal adaptation. These inferences were consistent with predictions derived from experimental microdialysis measures of extracellular glutamate levels. (c) 2008 Elsevier Inc. All rights reserved

Aggregation of Human Recombinant Monoclonal Antibodies Influences the Capacity of Dendritic Cells to Stimulate Adaptive T-cell Responses In Vitro

Subvisible proteinaceous particles which are present in all therapeutic protein formulations are in the focus of intense discussions between health authorities, academics and biopharmaceutical companies in the context of concerns that such particles could promote unwanted immunogenicity via anti-drug antibody formation. In order to provide further understanding of the subject, this study closely examines the specific biological effects proteinaceous particles may exert on dendritic cells (DCs) as the most efficient antigen-presenting cell population crucial for the initiation of the adaptive immune response. Two different model IgG antibodies were subjected to three different types of exaggerated physical stress to generate subvisible particles in far greater concentrations than the ones typical for the currently marketed biotherapeutical antibodies. The aggregated samples were used in in vitro biological assays in order to interrogate the early DC-driven events that initiate CD4 T-cell dependent humoral adaptive immune responses – peptide presentation capacity and co-stimulatory activity of DCs. Most importantly, antigen presentation was addressed with a unique approach called MHC-associated peptide proteomics (MAPPs), which allows for identifying the sequences of HLA-DR associated peptides directly from human dendritic cells [1]. The experiments demonstrated that highly aggregated solutions of two model mAbs generated under controlled conditions can induce activation of human monocyte-derived DCs as indicated by upregulation of typical maturation markers including co-stimulatory molecules necessary for CD4 T-cell activation. Additional data suggest that highly aggregated proteins could induce in vitro T-cell responses. Intriguingly, strong aggregation-mediated changes in the pattern and quantity of antigen-derived HLA-DR associated peptides presented on DCs were observed, indicating a change in protein processing and presentation. Increasing the amounts of subvisible proteinaceous particles correlated very well with the pronounced increase in the peptide number and clusters presented in the context of class II HLA-DR molecules, suggesting a major involvement of a mass-action mechanism of altering the presentation

Physicochemical characterization of stressed mAb materials.

<p>Representative MFI screenshots after freeze/thaw (FT) stress of mAb1 (A) unstressed, un; (B) stress level 1, sl1; (C) stress level 2, sl2 and mAb2 un, (E) sl1 and (F) sl2. (G) Particle Size distribution obtained by MFI of mAb1 (left) and mAb2 (right). For visualization the size binning 2–2.5, 2.5–5, 5–10 10–25, 25–50 and 50–400 µm was used. Representative images of individual particles formed by (H) heat/shake, HS; (I) freeze/thaw, FT and (J) shear stress, S. Polydispersity in % (PD%) revealed by DLS for (K) mAb1 and (L) mAb2.</p

MAPPs heat map of identified HLA-DR associated peptides in the HS study.

<p>Heat map visualization of mAb-derived HLA-DR associated peptides for both model antibodies in the HS study. Each sequence position is colored according to the presence and number of different mAb-derived peptides identified. In black colored sequence regions, no peptides were identified, in colored regions, peptides were identified, with the color coding for the number of different peptides identified per position. HS: aggregates generated by heat and shake stress; mAb1: monoclonal antibody 1, mAb2: monoclonal antibody 2, un: unstressed, sl1: stress level 1, sl2: stress level 2.</p

Correlation of HLA-DR associated peptides and peptide clusters measured by MAPPs to the amount of protein present in subvisible particles.

<p>Linear regression analyses of the increase of the HLA-DR associated peptides and clusters as functions of the calculated amount of protein present in the subvisible particles. Left up: HLA-DR associated peptides of mAb1 vs protein amount in subvisible particles (r² = 0.994), left down: HLA-DR associated peptide clusters of mAb1 vs protein amount in subvisible particles (r² = 0.993), right up: HLA-DR associated peptides of mAb2 vs protein amount in subvisible particles (r² = 0.86), right down: HLA-DR associated peptide clusters of mAb2 vs protein amount in subvisible particles (r² = 0.943). HS: aggregates generated by heat and shake stress; FT: aggregates generated by freeze and thaw stress, S: aggregates generated by shear stress mAb1: monoclonal antibody 1, mAb2: monoclonal antibody 2, 1: stress level 1, 2: stress level 2. For further details, please, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086322#s4" target="_blank">Materials and Methods</a>.</p