Long-term monitoring data of hygrothermal conditions of a retrofitted historic building in Settequerce, South Tyrol (Italy)

This data collection presents a comprehensive five-year monitoring record from a historic building located in Settequerce, South Tyrol (Italy). The 17th-century building, characterized by a stone masonry, was subject to a retrofit in 2017 that introduced a wood fiber insulation panel to the inner side of the building's walls. As part of the renovation process, a monitoring system was installed. This system incorporated internal, external, and in-wall sensors, which were strategically placed at three different points within the wall to evaluate the effects of the insulation on the stratigraphy. This setup ensured the continuous collection of climatic data, both from the exterior and interior environments, as well as from within the renovated wall's stratigraphy. This comprehensive dataset delivers new insights into the long-term performance of retrofit interventions. The significant potential for reuse of this dataset makes it a substantial foundation for future studies on energy-efficient retrofitting and the preservation of historical structures in comparable climate (Climate E Köppen). It is expected to inform data-driven decisions in future renovation and preservation projects of comparable historic buildings.

A rapid review of current engagement strategies with people who use drugs in monitoring and reporting on substance use-related harms

BACKGROUND

The Canadian drug supply has significantly increased in toxicity over the past few years, resulting in the worsening of the overdose crisis. A key initiative implemented during this crisis has been data monitoring and reporting of substance use-related harms (SRH). This literature review aims to: (1) identify strategies used for the meaningful engagement of people who use drugs (PWUD) in local, provincial, and national SRH data system planning, reporting, and action and (2) describe data monitoring and reporting strategies and common indicators of SRH within those systems.

METHODS

We searched three academic and five gray literature databases for relevant literature published between 2012 and 2022. Team members who identify as PWUD and a librarian at Public Health Ontario developed search strings collaboratively. Two reviewers screened all search results and applied the eligibility criteria. We used Microsoft Excel for data management.

RESULTS

Twenty-two articles met our eligibility criteria (peer-reviewed n = 10 and gray literature reports n = 12); most used qualitative methods and focused on the Canadian context (n = 20). There were few examples of PWUD engaged as authors of reports on SRH monitoring. Among information systems involving PWUD, we found two main strategies: (1) community-based strategies (e.g., word of mouth, through drug sellers, and through satellite workers) and (2) public health-based data monitoring and communication strategies (e.g., communicating drug quality and alerts to PWUD). Substance use-related mortality, hospitalizations, and emergency department visits were the indicators most commonly used in systems of SRH reporting that engaged PWUD.

CONCLUSION

This review demonstrates limited engagement of PWUD and silos of activity in existing SRH data monitoring and reporting strategies. Future work is needed to better engage PWUD in these processes in an equitable manner. Building SRH monitoring systems in partnership with PWUD may increase the potential impact of these systems to reduce harms in the community.

Monitoring of electricity generation from exhaust waste heat and wireless data recording from a mobile phone in real driving conditions of a vehicle

In this study, a system is designed to generate electrical energy from the exhaust waste heat of vehicles using a thermoelectric generator. Electronic hardware that can communicate wirelessly, firmware, and mobile software specific to the system have been developed to control and monitor this system. The system comprises hexagonal aluminum components, thermoelectric generators, a cooler, sensors, software, and electronic hardware. The easily removable hexagonal modular aluminum component is designed to transmit heat from the exhaust pipe to thermoelectric generators. It used a thermoelectric generator (TEG-SP1848) on each edge of this hexagonal component and a heatsink to cool the generator. The voltage and current values of the electrical energy produced in the observations made under real driving conditions are recorded on the SD card on the system. In addition, system-specific mobile software has been developed by the work team. With this software, the system can be controlled, as well as visualizing the instantaneous parameters of the system. According to the results obtained from the test drives, electrical energy was obtained at a maximum voltage of 9.8 V and a current of 0.32 A. This electrical energy from the exhaust waste heat can be stored in the vehicle's existing battery. In this way, since the alternator used for the vehicle's electricity generation will be activated less, fuel savings will be achieved in the engine, and harmful exhaust emissions will be reduced. In addition, the electrical energy obtained by this method can be stored in an external battery independent of the vehicle battery and used for various purposes. In contrast, the vehicle is stationary or has a portable battery.

The preventive effect of PNF stretching exercise on sports injuries in physical education based on IoT data monitoring

In physical education, in order to prevent sports injuries of students, it is necessary to study and build a set of physical education Internet of Things data monitoring training system to prevent sports injuries of students. This system is mainly composed of sensors, smart phones and cloud servers. Wearable devices equipped with sensors are used to complete data acquisition and transmission by means of the Internet of Things system, and relevant parameters are sorted and monitored by combining data analysis technology. The system makes a more in-depth, comprehensive and accurate analysis and processing of the collected data, so as to better evaluate the status and quality of students' sports, find out the existing problems in time, and put forward the corresponding solutions. By analyzing students' sports data and health data, the system generates personalized training programs, including training intensity, training time, training frequency and other parameters, so as to meet the needs and actual conditions of different students and avoid sports injuries caused by overtraining. This system can better analyze and process the collected data, provide teachers with more comprehensive and in-depth assessment and monitoring of students' sports status, and provide students with more personalized and scientific training programs, so as to effectively prevent the occurrence of students' sports injuries.

Pandemetrics: systematically assessing, monitoring, and controlling the evolution of a pandemic

The still ongoing pandemic of SARS-CoV-2 virus and COVID-19 disease, affecting the population worldwide, has demonstrated the need of more accurate methodologies for assessing, monitoring, and controlling an outbreak of such devastating proportions. Authoritative attempts have been made in traditional fields of medicine (epidemiology, virology, infectiology) to address these shortcomings, mainly by relying on mathematical and statistical modeling. However, here, we propose approaching the methodological work from a different, and to some extent alternative, standpoint. Applied systematically, the concepts and tools of statistical engineering and quality management, developed not only in healthcare settings, but also in other scientific contexts, can be very useful in assessing, monitoring, and controlling pandemic events. We propose a methodology based on a set of tools and techniques, formulas, graphs, and tables to support the decision-making concerning the management of a pandemic like COVID-19. This methodological body is hereby named Pandemetrics. This name intends to emphasize the peculiarity of our approach to measuring, and graphically presenting the unique context of the COVID-19 pandemic.

Use of mobile data collection systems within large-scale epidemiological field trials: findings and lessons-learned from a vector control trial in Iquitos, Peru

Vector-borne diseases are among the most burdensome infectious diseases worldwide with high burden to health systems in developing regions in the tropics. For many of these diseases, vector control to reduce human biting rates or arthropod populations remains the primary strategy for prevention. New vector control interventions intended to be marketed through public health channels must be assessed by the World Health Organization for public health value using data generated from large-scale trials integrating epidemiological endpoints of human health impact. Such phase III trials typically follow large numbers of study subjects to meet necessary power requirements for detecting significant differences between treatment arms, thereby generating substantive and complex datasets. Data is often gathered directly in the field, in resource-poor settings, leading to challenges in efficient data reporting and/or quality assurance. With advancing technology, mobile data collection (MDC) systems have been implemented in many studies to overcome these challenges. Here we describe the development and implementation of a MDC system during a randomized-cluster, placebo-controlled clinical trial evaluating the protective efficacy of a spatial repellent intervention in reducing human infection with Aedes-borne viruses (ABV) in the urban setting of Iquitos, Peru, as well as the data management system that supported it. We discuss the benefits, remaining capacity gaps and the key lessons learned from using a MDC system in this context in detail.

Interim data monitoring in cluster randomised trials: Practical issues and a case study

BACKGROUND

There is an abundance of guidance for the interim monitoring of individually randomised trials. While methodological literature exists on how to extend these methods to cluster randomised trials, there is little guidance on practical implementation. Cluster trials have many features which make their monitoring needs different. We outline the methodological and practical challenges of interim monitoring of cluster trials; and apply these considerations to a case study.

CASE STUDY

The E-MOTIVE study is an 80-cluster randomised trial of a bundle of interventions to treat postpartum haemorrhage. The proposed data monitoring plan includes (1) monitor sample size assumptions, (2) monitor for evidence of selection bias, and (3) an interim assessment of the primary outcome, as well as monitoring data completeness. The timing of the sample size monitoring is chosen with both consideration of statistical precision and to allow time to recruit more clusters. Monitoring for selection bias involves comparing individual-level characteristics and numbers recruited between study arms to identify any post-randomisation participant identification bias. An interim analysis of outcomes presented with 99.9% confidence intervals using the Haybittle-Peto approach should mitigate any concern regarding the inflation of type-I error. The pragmatic nature of the trial means monitoring for adherence is not relevant, as it is built into a process evaluation.

CONCLUSIONS

The interim analyses of cluster trials have a number of important differences to monitoring individually randomised trials. In cluster trials, there will often be a greater need to monitor nuisance parameters, yet there will often be considerable uncertainty in their estimation. This means the utility of sample size re-estimation can be questionable particularly when there are practical or funding difficulties associated with making any changes to planned sample sizes. Perhaps most importantly interim monitoring has the potential to identify selection bias, particularly in trials with post-randomisation identification or recruitment. Finally, the pragmatic nature of cluster trials might mean that the utility of methods to allow for interim monitoring of outcomes based on statistical testing, or monitoring for adherence to study interventions, are less relevant. Our intention is to facilitate the planning of future cluster randomised trials and to promote discussion and debate to improve monitoring of these studies.

Clinical researchers' lived experiences with data quality monitoring in clinical trials: a qualitative study

BACKGROUND

Fundamental to the success of clinical research that involves human participants is the quality of the data that is generated. To ensure data quality, clinical trials must comply with the Good Clinical Practice guideline which recommends data monitoring. To date, the guideline is broad, requires technology for enforcement, follows strict industry standards, mostly designed for drug-registration trials and based on informal consensus. It is also unknown what challenges clinical trials and researchers face in implementing data monitoring procedures. Thus, this study aimed to describe researcher experiences with data quality monitoring in clinical trials.

METHODS

We conducted semi-structured telephone interviews following a guided-phenomenological approach. Participants were recruited from the Australian and New Zealand Clinical Trials Registry and were researchers affiliated with a listed clinical study. Each transcript was analysed with inductive thematic analysis before thematic categorisation of themes from all transcripts. Primary, secondary and subthemes were categorised according to the emerging relationships.

RESULTS

Data saturation were reached after interviewing seven participants. Five primary themes, two secondary themes and 21 subthemes in relation to data quality monitoring emerged from the data. The five primary themes included: education and training, ways of working, working with technology, working with data, and working within regulatory requirements. The primary theme 'education and training' influenced the other four primary themes. While 'working with technology' influenced the 'way of working'. All other themes had reciprocal relationships. There was no relationship reported between 'working within regulatory requirements' and 'working with technology'. The researchers experienced challenges in meeting regulatory requirements, using technology and fostering working relationships for data quality monitoring.

CONCLUSION

Clinical trials implemented a variety of data quality monitoring procedures tailored to their situation and study context. Standardised frameworks that are accessible to all types of clinical trials are needed with an emphasis on education and training.

Implementing an automated monitoring process in a digital, longitudinal observational cohort study

Background

Clinical data collection requires correct and complete data sets in order to perform correct statistical analysis and draw valid conclusions. While in randomized clinical trials much effort concentrates on data monitoring, this is rarely the case in observational studies- due to high numbers of cases and often-restricted resources. We have developed a valid and cost-effective monitoring tool, which can substantially contribute to an increased data quality in observational research.

Methods

An automated digital monitoring system for cohort studies developed by the German Rheumatism Research Centre (DRFZ) was tested within the disease register RABBIT-SpA, a longitudinal observational study including patients with axial spondyloarthritis and psoriatic arthritis. Physicians and patients complete electronic case report forms (eCRF) twice a year for up to 10 years. Automatic plausibility checks were implemented to verify all data after entry into the eCRF. To identify conflicts that cannot be found by this approach, all possible conflicts were compiled into a catalog. This “conflict catalog” was used to create queries, which are displayed as part of the eCRF. The proportion of queried eCRFs and responses were analyzed by descriptive methods. For the analysis of responses, the type of conflict was assigned to either a single conflict only (affecting individual items) or a conflict that required the entire eCRF to be queried.

Results

Data from 1883 patients was analyzed. A total of n = 3145 eCRFs submitted between baseline (T0) and T3 (12 months) had conflicts (40–64%). Fifty-six to 100% of the queries regarding eCRFs that were completely missing were answered. A mean of 1.4 to 2.4 single conflicts occurred per eCRF, of which 59–69% were answered. The most common missing values were CRP, ESR, Schober’s test, data on systemic glucocorticoid therapy, and presence of enthesitis.

Conclusion

Providing high data quality in large observational cohort studies is a major challenge, which requires careful monitoring. An automated monitoring process was successfully implemented and well accepted by the study centers. Two thirds of the queries were answered with new data. While conventional manual monitoring is resource-intensive and may itself create new sources of errors, automated processes are a convenient way to augment data quality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02563-2.

[The new retainers in Dento-Facial Orthopedics]

Digital technologies are gradually integrating our orthodontic practices and retainers, often less considered compared to active devices, are also benefiting. The author will give in this article a brief presentation of the various current possibilities offered by the use of digital tools for carrying out and monitoring fixed or removable retention methods. The digital workflow is perfectly suited to the production of modern and durable retainers, whether for fixed or removable devices, as well as their long-term monitoring. The objective is not to decide on the superiority of one system over another, but to expose all the possibilities for adapting the digital tool to the orthodontist's method of retention. The benefit of using digital technology is saving time and improving performance, minimizing unnecessary manipulation and improving device precision. Digital technology provides all the elements necessary to achieve new generation retainers both more simply, and for them to be more precise and more durable. These technologies are in constant progress and we can still consider improvements in the near future as software and hardware developments progress.

Decision on performing interim analysis for comparative clinical trials

In randomized-controlled trials, interim analyses are often planned for possible early trial termination to claim superiority or futility of a new therapy. While unblinding is necessary to conduct the formal interim analysis in blinded studies, blinded data also have information about the potential treatment difference between the groups. We developed a blinded data monitoring tool that enables investigators to predict whether they observe such an unblinded interim analysis results that supports early termination of the trial. Investigators may skip some of the planned interim analyses if an early termination is unlikely. We specifically focused on blinded, randomized-controlled studies to compare binary endpoints of a new treatment with a control. Assuming one interim analysis is planned for early termination for superiority or futility, we conducted extensive simulation studies to assess the impact of the implementation of our tool on the size, power, expected number of interim analyses, and bias in the treatment effect. The numerical study showed the proposed monitoring tool does not affect size or power, but dramatically reduces the expected number of interim analyses when the effect of the treatment difference is small. The tool serves as a useful reference when interpreting the summary of the blinded data throughout the course of the trial, without losing integrity of the study. This tool could potentially save the study resources and budget by avoiding unnecessary interim analyses.

Minimal sufficient balance randomization for sequential randomized controlled trial designs: results from the ESCAPE trial

Background

We describe the implementation of minimal sufficient balance randomization, a covariate-adaptive randomization technique, used for the “Endovascular treatment for Small Core and Anterior circulation Proximal occlusion with Emphasis on minimizing CT to recanalization times” (ESCAPE) trial.

Methods

The ESCAPE trial is a prospective, multicenter, randomized clinical trial that enrolled subjects with the following main inclusion criteria: less than 12 h from symptom onset, age 18 years or older, baseline NIHSS score > 5, ASPECTS score > 5 and computed tomography angiography (CTA) evidence of carotid T/L or M1-segment middle cerebral artery (MCA) occlusion, and at least moderate collaterals by CTA. Patients were randomized using a real-time, dynamic, Internet-based, minimal sufficient balance randomization method that balanced the study arms with respect to baseline covariates including age, sex, baseline NIHSS score, site of arterial occlusion, baseline ASPECTS score and treatment with intravenously administered alteplase.

Results

Permutation-based tests of group differences confirmed group balance across several baseline covariates including sex (p = 1.00), baseline NIHSS score (p = 0.95), site of arterial occlusion (p = 1.00), baseline ASPECTS score (p = 0.28), treatment with intravenously administered alteplase (p = 0.31), and age (p = 0.67).

Conclusion

Results from the ESCAPE trial demonstrate the feasibility and the benefit of this covariate adaptive randomization scheme in small-sample trials and for data monitoring endeavors.

Trial registration

ESCAPE trial – NCT01778335 – at www.clinicaltrials.gov. Registered on 29 January 2013.

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-017-2264-1) contains supplementary material, which is available to authorized users.

INVESTIGATING THE EFFICACY OF CLINICAL TRIAL MONITORING STRATEGIES: Design and Implementation of the Cluster Randomized START Monitoring Substudy

BACKGROUND

Trial monitoring protects participant safety and study integrity. While monitors commonly go on-site to verify source data, there is little evidence that this practice is efficient or effective. An ongoing international HIV treatment trial (START) provides an opportunity to explore the usefulness of different monitoring approaches.

METHODS

All START sites are centrally monitored and required to follow a local monitoring plan requiring specific quality assurance activities. Additionally, sites were randomized (1:1) to receive, or not receive, annual on-site monitoring. The study will determine if on-site monitoring increases the identification of major protocol deviations (eligibility or consent violations, improper study drug use, primary or serious event underreporting, data alteration or fraud).

RESULTS

The START study completed enrollment in December 2013, with planned follow-up through December 2016. The monitoring study is ongoing at 196 sites in 34 countries. Results are expected when the START study concludes in December 2016.