BACKGROUND:Severe asthma affects a minority of patients with asthma; however, it substantially impacts morbidity, health-care use, and systemic corticosteroid-related harm. Despite the increasing use of biological treatments, achievement of severe asthma remission remains elusive. Notably, real-world data on the disease burden and remission potential of severe asthma in Europe remain limited. We aimed to close this knowledge gap, offering insights with global relevance. METHODS:Using data from 13 455 adults with severe asthma enrolled in the European Severe Heterogeneous Asthma Registry, Patient-centred Clinical Research Collaboration (SHARP CRC), this cross-sectional observational study evaluated the burden of severe asthma and remission-related clinical domains (exacerbations, asthma control, airflow limitation, and maintenance oral corticosteroid use) across Europe and examined their relationship with disease duration, biological therapy, and type 2 biomarkers (blood eosinophils, fractional exhaled nitric oxide [FeNO], and total IgE). Patients with severe asthma had been enrolled in national registries according to local principles and guidelines and in accordance with the European Respiratory Society/American Thoracic Society guidelines; 3% (430 of 13 885) of patients were excluded due to no consent for the international study and/or missing medication data. FINDINGS:Patients were predominantly female (59%; 7999 of 13 453), with adult-onset asthma (82%; 8751 of 10 711), and a median disease duration of 23 years (95% CI 20-26 years). 59% (4148 of 7006) of patients had FEV1/FVC of 0·7 or less, 62% (4680 of 7568) had FEV1 lower than 80% predicted, and 89% (3519 of 3968) had at least one active disease domain. Despite 79% (10 632 of 13 453) receiving biological therapy, more than 66% (2621 of 3968) still had at least two active domains. Elevation of type 2 biomarkers persisted (89% [2806 of 3153] with at least one elevated biomarker) despite widespread biological and maintenance oral corticosteroid treatment. A subset of biologic-naive patients (35%; 1069 of 3018) exhibited a rapid accumulation of disease burden within less than 10 years, suggesting a potentially accelerated progression trajectory. INTERPRETATION:This pan-European analysis of severe asthma revealed significant clinical heterogeneity and a substantial disease burden despite advanced therapies, highlighting the enduring nature of type 2 inflammation, the potential inadequacy of current remission strategies with available therapeutic approaches, and the necessity for early identification of high-risk patients. FUNDING:SHARP Clinical Research Collaboration and consortium partners: European Respiratory Society, GlaxoSmithKline Research and Development, Chiesi Farmaceutici Società per Azioni, Novartis Pharma Aktiengesellschaft, Sanofi-Genzyme Corporation, and Teva Branded Pharmaceutical Products R&D.

Introduction The World Health Organization global standard for representing drug data is the Anatomical Therapeutic Chemical (ATC) classification. However, it does not represent ingredients and other drug properties required by clinical decision support systems. A mapping to a terminology system that contains this information, like RxNorm, may help fill this gap. This work evaluates and compares the completeness of mappings from the chemical substance level (5th-level) ATC classes to RxNorm ingredient concepts in the OHDSI Standardized Vocabularies (OSV) and the Unified Medical Language System (UMLS) Metathesaurus. Methods To check the concordance between OSV and UMLS we compared the included contents of ATC and RxNorm not only in OSV and UMLS but also in BioPortal and the National Library of Medicine (NLM) repository. For each repository, we determined the number of 5th-level ATC concepts, RxNorm ingredient concepts, missing classes and concepts, and the ATC categories with the most missing concepts. The mappings from ATC to RxNorm in OSV and UMLS were compared, and we determined the number of mappings in common, and the mapping differences, which we categorized. We applied the mappings from OSV and UMLS on a sample of Electronic Health Record (EHR) data. Results NLM contained the most ATC and RxNorm concepts. UMLS contained more missing mappings (null mappings) than OSV, 1949 versus 916. Most mapping differences were in the “unknown ingredient in the ATC label” category, for which UMLS provided no mappings. UMLS had a higher coverage of mappings in the sample EHR data than OSV, 96.5% versus 91%. Discussion In conclusion, opting for OSV rather than UMLS is generally preferable for an ATC to RxNorm mapping since OSV provides more mappings. However, the results of the sample data show that UMLS can have fewer null mappings in concrete applications.

Real-world evidence from multinational disease registries is becoming increasingly important not only for confirming the results of randomised controlled trials, but also for identifying phenotypes, monitoring disease progression, predicting response to new drugs and early detection of rare side-effects. With new open-access technologies, it has become feasible to harmonise patient data from different disease registries and use it for data analysis without compromising privacy rules. Here, we provide a blueprint for how a clinical research collaboration can successfully use real-world data from existing disease registries to perform federated analyses. We describe how the European severe asthma clinical research collaboration SHARP (Severe Heterogeneous Asthma Research collaboration, Patient-centred) fulfilled the harmonisation process from nonstandardised clinical registry data to the Observational Medical Outcomes Partnership Common Data Model and built a strong network of collaborators from multiple disciplines and countries. The blueprint covers organisational, financial, conceptual, technical, analytical and research aspects, and discusses both the challenges and the lessons learned. All in all, setting up a federated data network is a complex process that requires thorough preparation, but above all, it is a worthwhile investment for all clinical research collaborations, especially in view of the emerging applications of artificial intelligence and federated learning.

Clinical research is currently limited by the need to manually enter data related to clinical trials through EDC (Electronic Data Capture) or eCRF (electronic Case Report Form). This implies replication of data between Electronic Health Record systems (EHR) and eCRF, the employment of a considerable amount of time and resources and easily leads to errors. Thus, the systematic reuse of Real World Data (mainly EHR data) to automatically fill in eCRF may represent a turning point in clinical trials [1]. OMOP/OHDSI (Observational Medical Outcomes Partnership Observational Health Data Sciences and Informatics) is an ideal middleware to be interposed between EHR and eCRF, in order to decouple the complexity of the clinical sources from the target eCRF [2]. Its use of both a standardized data model and the main standardized terminologies, makes it a particularly suitable candidate. REDCap (Research Electronic Data CAPture) is a widely adopted web-based eCRF system for non-profit studies [3]. There are different solutions to automatically import data into a REDCap study (direct ETL through REDCap API, Dynamic Data Pull (DDP), Clinical Data Pull (CDP)), but to the best of our knowledge no specific project is focusing on automatic data transfer from OMOP Common Data Model (CDM) to REDCap. The aim of this work is proposing a semantically-enriched framework to support automatic data transfer from OMOP CDM to REDCap eCRF.

[This corrects the article DOI: 10.2196/31400.].

The CAPABLE (CAncer PAtient Better Life Experience) project [1], funded in the H2020 program, is developing a novel system to improve the quality of life of cancer patients managed at home. CAPABLE system is based on a distributed software architecture where different components cooperate with the aim of “early detecting and managing cancer-related issues and at satisfying the needs of patients and their home caregivers”. One of the core CAPABLE components is the “CAPABLE Data Platform” (DP); the main objective of the DP is to provide a persistent layer where to store and fetch all project’s patient-related data. To guarantee a state-of-the art level component, OMOP [2] Common Data Model (CDM) and HL7-FHIR [3] have been chosen for persistency and exchange format respectively. The main reason for choosing OMOP is due to its “Standardized clinical data” tables, which are designed to hold disparate patient-related data, and to the “Standardized vocabularies”, a set of international standard terminologies which are consolidated into the same code system. Alongside with the need of having a standard model to represent persisted data, the project also needed a reliable format for exchanging those data in a web-service safe mode: FHIR was chosen for this purpose because it is based on a “composition approach”, representing standard clinical entities as resources that can be combined with each other. The omoponfhir open-source project [4] constituted the starting point for the development of the DP (which in fact can be considered a fork of this project); in this article we highlight the main changes/additions and customization of omoponfhir to make it fit the aims and requirements of the CAPABLE project.

BACKGROUND Many countries have experienced two predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and healthcare dynamics of the COVID-19 pandemic. OBJECTIVE In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating healthcare systems representing 315 hospitals across six countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic. METHODS Using a federated approach, each participating healthcare system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were performed at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual healthcare system effect sizes and synthesizing these using random effects meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19. RESULTS Data were available for 79,487 patients, of which 32,452 were hospitalized in the first wave and 47,035 in the second wave. The prevalence of male patients and patients aged 50–69 decreased significantly between the first and second wave. Patients hospitalized in the second wave had a 9.6% reduction in risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI: 8.2–11.1%). Demographic subgroup analyses indicated that patients aged 26–49; male and female patients; and Black patients had significantly lower risk for severe disease in the second wave compared to the first wave. At admission, the mean values of CRP were significantly lower in the second wave compared to the first. On the seventh hospital day, mean values of CRP, ferritin, fibrinogen, procalcitonin, and creatinine were significantly lower in the second wave compared to the first. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain. CONCLUSIONS Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international healthcare systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.

The aim of this work is the evaluation of a relatively new intervention for chronic patients in Italy, namely the PAI, i.e., "Piano Assistenziale Individuale" (Individual Care Plan). It is a service based on the paradigm of the personalised medicine, which should optimize several aspects of the individual care, such as patients' compliance to therapy, ease of access to care delivery, and a tighter monitoring of the patient's status on the long run. The expected outcomes from the PAI introduction are both the improvement of the patients' status and reduction of costs for the care provider. A case-control study has been performed, involving more than 20000 patients, and preliminary results seem to confirm the effectiveness of the new service, in particular by reducing patients' access to hospital and emergency room.

BACKGROUND:There is no successful pharmacological treatment for cognitive impairment in Parkinson's Disease, therefore treatments capable of slowing down the progression of cognitive dysfunction are needed. OBJECTIVE:To evaluate the effectiveness of a cognitive training, supported by the CoRe computerized tool, in patients with Parkinson's Disease Mild Cognitive Impairment. METHODS:This is a prospective, open-unblinded, randomized, controlled study. After baseline cognitive assessment (T0), enrolled patients were randomized to receive motor rehabilitation plus cognitive intervention (G1) or motor rehabilitation only (G2). Follow-up assessments were scheduled 4 weeks (T1) and 6 months after (T2). Global cognitive functioning scores (MOCA and MMSE) were considered as primary outcome. Outcome measures at T0, T1 and T2 were compared within- and between-groups. A percentage change score between T0 and next assessments was calculated to identify patients who improved, remain stable or worsened. RESULTS:Differently from G2, G1 showed a medium/large effect size improvement in primary (MoCA) and secondary outcome, both between T0 and T1 and T0 and T2. Moreover, within G1, most patients improved their cognitive state compared to the baseline. CONCLUSIONS:Patients trained with CoRe showed a better evolution of cognitive decline, while untreated patients tended to get worse over time.

CoRe is a system for cognitive rehabilitation that has been successfully used for several years in hospital settings. Leveraging on the positive survey results from the potential final users (patients and their home caregivers), we developed HomeCoRe. This new version of the system will allow discharged patients to continue the rehabilitation treatment at home.

BACKGROUND AND OBJECTIVE:We illustrate a low-cost platform easing the estimation of spatio-temporal parameters (GA-STP) ready for large-scale deployment in fall prevention.METHODS:We used a commercial sensorized carpet with a limited cost and a very coarse resolution. An instrument validation test was accomplished: the Wilcoxon test for paired samples and the correlation test with Spearman method were used to compare the values computed by the platform with reference ones. Hierarchical clustering using Ward's method and ROC curves have been used to assess the performance in a pilot study enrolling patients.RESULTS:Validation shows no significant difference between computed and reference values of gait speed (ρ-value:0.99; p-value:2.2E-16), step number (ρ-value:0.91; p-value:5.8E-16) and stride-length (ρ-value:0.92; p-value:7.5E-9). The clinical pilot study confirms that the platform may also be used to track the improvements occurring during a rehabilitation program.CONCLUSIONS:We believe that the use of a commercial carpet makes the solution proposed ready to be deployed on a large scale for effectively bringing GA into the clinical practice.

Objectives: This paper describes the results of a randomized clinical trial about the effectiveness of a computerized rehabilitation treatment on a sample of 31 patients affected by Parkinson disease. Methods: Computerized exercises were administered by the therapists to the intervention group (n= 17) through the CoRe tool, which automatically generates a big variety of exercises leveraging on a stimuli set (words, sounds and images) organized into a dedicated ontology. A battery of standard neuropsychological tests was performed for patients' assessment at baseline, after the treatment (that lasted 1 month), and after 6 months from the treatment stop. The control group underwent a sham intervention. Results: Results show a statistically significant clinical benefit from computerized rehabilitation with respect to sham treatment. For the intervention group, response time and response accuracy were integrated into a weighted score that accounts also for the specific cognitive burden of each exercise. Differently from the control group, the majority of patients in the intervention group showed an improvement in that score, more marked in the first week of treatment, and which lasts for the entire treatment period, which could account both for a quick learning effect and for an improvement of cognitive conditions. Good usability of CoRe, already observed in previous studies, was confirmed by the present trial, where the percentage of protocol completion in the intervention group is very high (all but one patient are above 90%). Conclusions: The CoRe system showed to be effective to improve some cognitive abilities in patients with Parkinson disease. However, after the end of the training, the benefit is hardly maintained over time. These findings support the implementation of CoRe in the clinical routine and the continuation of the treatment after discharge through the use of a homecare version of the system.

In this work we describe an experiment involving aphasic patients, where the same speech rehabilitation exercise was administered in three different modalities, two of which are computer-based. In particular, one modality exploits the "Makey Makey", an electronic board which allows interacting with the computer using physical objects.

The Colibri project is introduced, whose aim is setting up a shared database of Magnetic Resonance images concerning pediatric patients affected by neurological rare disorders. The project involves 19 Italian centers of excellence in pediatric neuro-radiology and is supported by the nationwide coordinating center for the Information and Communication Technology research infrastructure. After the first year devoted to the design and the implementation, in November 2014 the system finally went into service at the centers involved in the project. This paper illustrates the initial assessment of the user perception and provides some preliminary statistics about its use.

Purpose: This work aims at providing a tool for supporting cognitive rehabilitation. This is a wide field, that includes a variety of diseases and related clinical pictures; for this reason the need arises to have a tool available that overcomes the difficulties entailed by what currently is the most common approach, that is, the so-called pen and paper rehabilitation. Methods: We first organized a big number of stimuli in an ontology that represents concepts, attributes and a set of relationships among concepts. Stimuli may be words, sounds, 2D and 3D images. Then, we developed an engine that automatically generates exercises by exploiting that ontology. The design of exercises has been carried on in synergy with neuropsychologists and speech therapists. Solutions have been devised aimed at personalizing the exercises according to both patients' preferences and performance. Results: Exercises addressed to rehabilitation of executive functions and aphasia-related diseases have been implemented. The system has been tested on both healthy volunteers (n = 38) and patients (n = 9), obtaining a favourable rating and suggestions for improvements. Conclusions: We created a tool able to automate the execution of cognitive rehabilitation tasks. We hope the variety and personalization of exercises will allow to increase compliance, particularly from elderly people, usually neither familiar with technology nor particularly willing to rely on it. The next step involves the creation of a telerehabilitation tool, to allow therapy sessions to be undergone from home, thus guaranteeing continuity of care and advantages in terms of time and costs for the patients and the National Healthcare System (NHS).

Cognitive rehabilitation is usually administered in form of paper-based exercises the patient is required to solve. With the availability of new and advanced technologies, computer science is gaining more and more importance in the treatment routine. In this paper a software system for the rehabilitation of cognitively impaired subjects will be presented. Its features guarantee many advantages, both for patients and therapists, but to prevent the risk of reduced compliance, which, considering the intended target of the system-typically elderly people with low computer skills-cannot be ignored, 3D technology has been introduced. The project choices made and implementation strategies applied to increase immersion and entertainment and prevent boredom and drops in compliance will be described. Open issues and future works will also be illustrated.

In recent years, cognitive rehabilitation is shifting from paper-based to computer-based practice. Computerization entails several advantages, among which the availability of a great amount of stimuli to be used within a wide range of easily customizable exercise types and the possibility to monitor the evolution of a patient's skills through the storage of his performance data into a database. Furthermore, a computerized system can automatically assess the patient and adjust each exercise's difficulty accordingly. Patients undergoing exercises which fail to entertain them and stimulate their curiosity, are very likely to develop fatigue and boredom; besides, perceiving computerized rehabilitation as stressful and uncomfortable could very likely reduce the subject's compliance. For this reason great efforts are to be made in order to avoid the onset of stress states: this is why we chose to differentiate the exercises as much as possible before testing the tool on volunteers and patients. The results led us to improve the system, focusing mainly on the visual aspect of the exercises and to introduce 3D technology into our system.