Longitudinal deep learning clustering of Type 2 Diabetes Mellitus trajectories using routinely collected health records.

Type 2 diabetes mellitus (T2DM) is a highly heterogeneous chronic disease with different pathophysiological and genetic characteristics affecting its progression, associated complications and response to therapies. The advances in deep learning (DL) techniques and the availability of a large amount of healthcare data allow us to investigate T2DM characteristics and evolution with a completely new approach, studying common disease trajectories rather than cross sectional values. We used an Kernelized-AutoEncoder algorithm to map 5 years of data of 11,028 subjects diagnosed with T2DM in a latent space that embedded similarities and differences between patients in terms of the evolution of the disease. Once we obtained the latent space, we used classical clustering algorithms to create longitudinal clusters representing different evolutions of the diabetic disease. Our unsupervised DL clustering algorithm suggested seven different longitudinal clusters. Different mean ages were observed among the clusters (ranging from 65.3±11.6 to 72.8±9.4). Subjects in clusters B (Hypercholesteraemic) and E (Hypertensive) had shorter diabetes duration (9.2±3.9 and 9.5±3.9 years respectively). Subjects in Cluster G (Metabolic) had the poorest glycaemic control (mean glycated hemoglobin 7.99±1.42%), while cluster E had the best one (mean glycated hemoglobin 7.04±1.11%). Obesity was observed mainly in clusters A (Neuropathic), C (Multiple Complications), F (Retinopathy) and G. A dashboard is available at dm2.b2slab.upc.edu to visualize the different trajectories corresponding to the 7 clusters.

Measuring the Digital Skills of Catalan Health Care Professionals as a Key Step Toward a Strategic Training Plan: Digital Competence Test Validation Study.

BACKGROUND: Despite Catalonia being an advanced region in terms of digital health adoption, the "Forum for Professional Dialogue" identified the need to improve information and communication technology (ICT) competences as one of the present and future challenges for health care professionals (HPs). OBJECTIVE: We aimed to validate the digital competence test developed ad hoc for this study and to measure the digital competence level of Catalan HPs to establish their current level as the baseline for designing a strategic training plan. METHODS: An exploratory observational study was conducted based on a voluntary survey where sociodemographic, professional and digital tool knowledge, digital tool use, and training needs data were collected and based on the score obtained from a digital competence test developed ad hoc. The digital competence test consisted of 2 "real-life scenarios" with 7 and 11 questions. RESULTS: In total, 803 HPs, of whom 612 (76.2%) were women, completed the survey between June 28 and July 16, 2021. Most participants self-rated their digital competence level as either intermediate (384/803, 47.8%) or basic (357/803, 44.5%). The mean score in the digital competence test was 22.6 (SD 4.3). Therefore, most participants displayed a basic level of digital competence. The internal consistency of the digital competence test was 0.66, and the discrimination index of all questions was ≥0.2 for all items except for 1 question. CONCLUSIONS: This exploratory study highlights the need to improve the digital competence of HPs working in Catalonia, with special effort being made to provide training according to the specific needs of the different HP profiles. The results have informed the Health Plan for Catalonia 2021-2025 and lay the foundations for the development and deployment of a framework program for the digital competences of HPs. The developed digital competence test shows acceptable consistency for the objective pursued, although improvements are needed to fine-tune its accuracy.

Diffusion-weighted MR imaging of upper abdominal organs: field strength and intervendor variability of apparent diffusion coefficients.

PURPOSE: To determine the variability of apparent diffusion coefficient (ADC) values in various anatomic regions in the upper abdomen measured with magnetic resonance (MR) systems from different vendors and with different field strengths. MATERIALS AND METHODS: Ten healthy men (mean age, 36.6 years ± 7.7 [standard deviation]) gave written informed consent to participate in this prospective ethics committee-approved study. Diffusion-weighted (DW) MR imaging was performed in each subject with 1.5- and 3.0-T MR systems from each of three vendors at two institutions. Two readers independently measured ADC values in seven upper abdominal regions (left and right liver lobe, gallbladder, pancreas, spleen, and renal cortex and medulla). ADC values were tested for interobserver differences, as well as for differences related to field strength and vendor, with repeated-measures analysis of variance; coefficients of variation (CVs) and variance components were calculated. RESULTS: Interreader agreement was excellent (intraclass coefficient, 0.876). ADC values were (77.5-88.8) ×10(-5) mm(2)/sec in the spleen and (250.6-278.5) ×10(-5) mm(2)/sec in the gallbladder. There were no significant differences between ADC values measured at 1.5 T and those measured at 3.0 T in any anatomic region (P >.10 for all). In two of seven regions at 1.5 T (left and right liver lobes, P < .023) and in four of seven regions at 3.0 T (left liver lobe, pancreas, and renal cortex and medulla, P < .008), intervendor differences were significant. CVs ranged from 7.0% to 27.1% depending on the anatomic location. CONCLUSION: Despite significant intervendor differences in ADC values of various anatomic regions of the upper abdomen, ADC values of the gallbladder, pancreas, spleen, and kidney may be comparable between MR systems from different vendors and between different field strengths.

Design, Implementation, and Analysis of an Assessment and Accreditation Model to Evaluate a Digital Competence Framework for Health Professionals: Mixed Methods Study.

BACKGROUND: Although digital health is essential for improving health care, its adoption remains slow due to the lack of literacy in this area. Therefore, it is crucial for health professionals to acquire digital skills and for a digital competence assessment and accreditation model to be implemented to make advances in this field. OBJECTIVE: This study had two objectives: (1) to create a specific map of digital competences for health professionals and (2) to define and test a digital competence assessment and accreditation model for health professionals. METHODS: We took an iterative mixed methods approach, which included a review of the gray literature and consultation with local experts. We used the arithmetic mean and SD in descriptive statistics, P values in hypothesis testing and subgroup comparisons, the greatest lower bound in test diagnosis, and the discrimination index in study instrument analysis. RESULTS: The assessment model designed in accordance with the competence content defined in the map of digital competences and based on scenarios had excellent internal consistency overall (greatest lower bound=0.91). Although most study participants (110/122, 90.2%) reported an intermediate self-perceived digital competence level, we found that the vast majority would not attain a level-2 Accreditation of Competence in Information and Communication Technologies. CONCLUSIONS: Knowing the digital competence level of health professionals based on a defined competence framework should enable such professionals to be trained and updated to meet real needs in their specific professional contexts and, consequently, take full advantage of the potential of digital technologies. These results have informed the Health Plan for Catalonia 2021-2025, thus laying the foundations for creating and offering specific training to assess and certify the digital competence of such professionals.

Effect of vitamin D3 on self-perceived fatigue: A double-blind randomized placebo-controlled trial.

BACKGROUND: Vitamin D deficiency is frequent and has been associated with fatigue in uncontrolled trials. METHODS: This is the first double-blind placebo-controlled clinical trial to investigate the efficacy of per os vitamin D3 (cholecalciferol) in treating fatigue among otherwise healthy persons with low serum 25-hydroxyvitamin D (25(OH)D) levels. We enrolled 120 individuals (mean age 29 ±â€Š6 years, 53% women) presenting with fatigue and vitamin D deficiency (serum 25(OH)D < 20 µg/L). Participants were randomized to a single oral dose of 100,000 units of vitamin D or placebo. The primary endpoint was intra-individual change in the fatigue assessment scale (FAS) at 4 weeks after treatment. RESULT: The mean age of the participants was 29 ±â€Š6 years, 53% were women. Mean FAS decreased significantly more in the vitamin D group (-3.3 ±â€Š5.3; 95% confidence interval [CI] for change -14.1 to 4.1) compared with placebo (-0.8 ±â€Š5.3; 95% CI for change -9.0 to 8.7); (P = 0.01). Amelioration of fatigue was reported more frequently in vitamin D than in placebo group (42 [72%] vs. 31 [50%]; P = 0.01; odds ratio [OR] 2.63, 95% CI for OR 1.23-5.62). Among all participants, improvement in fatigue score correlated with the rise in 25(OH)D level (R = -0.22, P = 0.02). CONCLUSION: Vitamin D treatment significantly improved fatigue in otherwise healthy persons with vitamin D deficiency.This study was registered at the www.ClinicalTrials.gov Protocol ID NCT02022475.