Description of the Method for Evaluating Digital Endpoints in Alzheimer Disease Study : Protocol for an Exploratory, Cross-sectional Study

©Jelena Curcic, Vanessa Vallejo, Jennifer Sorinas, Oleksandr Sverdlov, Jens Praestgaard, Mateusz Piksa, Mark Deurinck, Gul Erdemli, Maximilian Bügler, Ioannis Tarnanas, Nick Taptiklis, Francesca Cormack, Rebekka Anker, Fabien Massé, William Souillard-Mandar, Nathan Intrator, Lior Molcho, Erica Madero, Nicholas Bott, Mieko Chambers, Josef Tamory, Matias Shulz, Gerardo Fernandez, William Simpson, Jessica Robin, Jón G Snædal, Jang-Ho Cha, Kristin Hannesdottir. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 10.08.2022.BACKGROUND: More sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests. OBJECTIVE: This study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials. METHODS: The Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies' ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments. RESULTS: Participant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic. CONCLUSIONS: This study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35442.Peer reviewe

Isoleren: minder energie of meer comfort

status: publishe

Energy Saving Predictions in the Residential Building Sector # An Assessment based on Stochastic Modeling

Energy Saving Predictions in the Residential Building Sector - An Assessment based on Stochastic Modeling Energy savings in the residential building sector are typically predicted by means of simplified, normative calculation tools, relying on standardized user behaviour. In reality however, actual energy savings prove to be only 20 to 60% of those predicted, seriously questioning the use of these tools in reliable cost efficiency analyses and robust policy making. Additionally, the tools are mostly conceived deterministically, giving no insight in the uncertainties inherent to predicting energy savings. The main aim of this work is to provide a more reliable energy saving prediction method, embedded in a probabilistic framework. To do so, an evidence-based probabilistic behavioural model is developed, reflecting the large variety in dwelling use. Key aspects of the final behavioural model are (i) the use of time-dependent occupancy profiles and (ii) the implementation of space-dependent heating patterns. As the simple thermal building models of the normative tools are no longer suitable to implement this behavioural model, a transient zonal building model is set up as well. By using the well-known Monte-Carlo technique, energy saving predictions can be generated in terms of probability distributions. When applied on an existing case study district, the results show the above methodology is able to predict energy use estimates that are very comparable to measured data (both in average values and statistical spread), confirming its overall reliability. In addition, and in contrast to the simplified calculation tools, the methodology is capable of capturing typical retrofitting effects like the temperature takeback. Finally, the probabilistic setup proves to be worthwhile in assessing energy savings at a large-scale building stock level (district, city, region, ...): as the building parameters can be conceived probabilistic as well, it allows for an incorporation of the global uncertainty of statistical building stock data within the final energy saving estimates.nrpages: 204status: publishe

Isoleren: minder energie of meer comfort

status: publishe

The effect of a reflective underlay on the global thermal behaviour of pitched roofs

The influence of the emissivity of a roof underlay on the global thermal behaviour of sloped roofs is investigated. Five well-insulated pitched roofs have been constructed in a test building. The five roofs have a south-west and north-east-oriented pitch and differ in long wave emissivity of the underlay. All roofs are equipped with thermocouples and heat fluxes sensors to evaluate the thermal response of the roofs to the climatic conditions. Both summer and winter conditions have been measured. In addition to the in situ evaluation, a laboratory experiment was set-up to evaluate the influence of the emissivity of the underlay on the summer behaviour of a sloped roof under fixed boundary conditions. With thermocouples and heat flux sensors at different heights in the roof the effect of the reflective foil on the heat gain to the inside could be evaluated. The measured data are compared with a simple numerical model that accounts for the buoyancy effects in the ventilated cavity between tiles and underlay. Laboratory experiments and simulations revealed that a low emissivity of the underlay decreases the heat gain to the indoor environment, but that due to the thermal stack flow in the air cavity underneath the tiles, the advantage of a reflective foil mainly plays a role in the bottom part of the roof. In the in situ measurements it was found that workmanship, airtightness and wind and thermal stack effects are much more important and disturb the possible benefits of using a reflective underlay.status: publishe

Predicting energy savings at district level: representative vs. individual dwelling approach

When predicting energy savings at aggregated level, a common simplification is the representation of a large group of similar houses by one single representative dwelling, occupied by one specific inhabitant. The calculated energy savings for this representative dwelling are then multiplied with the number of houses to obtain the expected aggregated energy savings. In this paper, this representative dwelling approach is compared with the individual dwelling approach where multiple different dwellings are modelled separately and their energy savings are added. When combined with probabilistic user behaviour, it is found that the representative dwelling approach predicts similar mean aggregated savings, but underestimates the actual spread due to the lack of variety in building characteristics.status: accepte

Energy consumption for heating and rebound effects

When comparing calculated heating consumption in residential buildings assuming standard usage with standardized measured data, then the two typically does not fit. In fact, measured consumption may be a fraction only of what was calculated. The reason is direct rebound behavior by the inhabitants. The paper shows the importance of direct rebound through measured results. First the temperatures, recorded in daytime and sleeping rooms in a sample of dwellings, are commented. Then follows a discussion of the indoor temperatures found when calculated energy consumptions for heating were forced to give the same numbers as measured. Next, two small scale analyses of energy data gained in low-income estates are commented, followed by test results on direct rebound in two dwellings, one non-insulated, the other well insulated. These data prove that the benefits of direct rebound are much larger in non-insulated than in well insulated homes. That fact is used to construct a rebound curve, starting from the normalized consumption data gained in 964 houses. The paper ends by showing the effect of energy price on direct rebound.status: publishe