Cost of healthcare utilization associated with incident cardiovascular and renal disease in individuals with type 2 diabetes: A multinational, observational study across 12 countries.

AIM: To examine how the development of cardiovascular and renal disease (CVRD) translates to hospital healthcare costs in individuals with type 2 diabetes (T2D) initially free from CVRD. METHODS: Data were obtained from the digital healthcare systems of 12 nations using a prespecified protocol. A fixed country-specific index date of 1 January was chosen to secure sufficient cohort disease history and maximal follow-up, varying between each nation from 2006 to 2017. At index, all individuals were free from any diagnoses of CVRD (including heart failure [HF], chronic kidney disease [CKD], coronary ischaemic disease, stroke, myocardial infarction [MI], or peripheral artery disease [PAD]). Outcomes during follow-up were hospital visits for CKD, HF, MI, stroke, and PAD. Hospital healthcare costs obtained from six countries, representing 68% of the total study population, were cumulatively summarized for CVRD events occurring during follow-up. RESULTS: In total, 1.2 million CVRD-free individuals with T2D were identified and followed for 4.5 years (mean), that is, 4.9 million patient-years. The proportion of individuals indexed before 2010 was 18% (n = 207 137); 2010-2015, 31% (361 175); and after 2015, 52% (609 095). Overall, 184 420 (15.7%) developed CVRD, of which cardiorenal disease was most frequently the first disease to develop (59.7%), consisting of 23.0% HF and 36.7% CKD, and more common than stroke (16.9%), MI (13.7%), and PAD (9.7%). The total cumulative cost for CVRD was US$1 billion, of which 59.0% was attributed to cardiorenal disease, 3-, 5-, and 6-fold times greater than the costs for stroke, MI, and PAD, respectively. CONCLUSION: Across all nations, HF or CKD was the most frequent CVRD manifestation to develop in a low-risk population with T2D, accounting for the highest proportion of hospital healthcare costs. These novel findings highlight the importance of cardiorenal awareness when planning healthcare.

Determinants of the Use of Health and Fitness Mobile Apps by Patients With Asthma: Secondary Analysis of Observational Studies.

BACKGROUND: Health and fitness apps have potential benefits to improve self-management and disease control among patients with asthma. However, inconsistent use rates have been reported across studies, regions, and health systems. A better understanding of the characteristics of users and nonusers is critical to design solutions that are effectively integrated in patients' daily lives, and to ensure that these equitably reach out to different groups of patients, thus improving rather than entrenching health inequities. OBJECTIVE: This study aimed to evaluate the use of general health and fitness apps by patients with asthma and to identify determinants of usage. METHODS: A secondary analysis of the INSPIRERS observational studies was conducted using data from face-to-face visits. Patients with a diagnosis of asthma were included between November 2017 and August 2020. Individual-level data were collected, including age, gender, marital status, educational level, health status, presence of anxiety and depression, postcode, socioeconomic level, digital literacy, use of health services, and use of health and fitness apps. Multivariate logistic regression was used to model the probability of being a health and fitness app user. Statistical analysis was performed in R. RESULTS: A total of 526 patients attended a face-to-face visit in the 49 recruiting centers and 514 had complete data. Most participants were ≤40 years old (66.4%), had at least 10 years of education (57.4%), and were in the 3 higher quintiles of the socioeconomic deprivation index (70.1%). The majority reported an overall good health status (visual analogue scale [VAS] score>70 in 93.1%) and the prevalence of anxiety and depression was 34.3% and 11.9%, respectively. The proportion of participants who reported using health and fitness mobile apps was 41.1% (n=211). Multivariate models revealed that single individuals and those with more than 10 years of education are more likely to use health and fitness mobile apps (adjusted odds ratio [aOR] 2.22, 95%CI 1.05-4.75 and aOR 1.95, 95%CI 1.12-3.45, respectively). Higher digital literacy scores were also associated with higher odds of being a user of health and fitness apps, with participants in the second, third, and fourth quartiles reporting aORs of 6.74 (95%CI 2.90-17.40), 10.30 (95%CI 4.28-27.56), and 11.52 (95%CI 4.78-30.87), respectively. Participants with depression symptoms had lower odds of using health and fitness apps (aOR 0.32, 95%CI 0.12-0.83). CONCLUSIONS: A better understanding of the barriers and enhancers of app use among patients with lower education, lower digital literacy, or depressive symptoms is key to design tailored interventions to ensure a sustained and equitable use of these technologies. Future studies should also assess users' general health-seeking behavior and their interest and concerns specifically about digital tools. These factors may impact both initial engagement and sustained use.

What Are We Looking for in Computer-Based Learning Interventions in Medical Education? A Systematic Review.

BACKGROUND: Computer-based learning (CBL) has been widely used in medical education, and reports regarding its usage and effectiveness have ranged broadly. Most work has been done on the effectiveness of CBL approaches versus traditional methods, and little has been done on the comparative effects of CBL versus CBL methodologies. These findings urged other authors to recommend such studies in hopes of improving knowledge about which CBL methods work best in which settings. OBJECTIVE: In this systematic review, we aimed to characterize recent studies of the development of software platforms and interventions in medical education, search for common points among studies, and assess whether recommendations for CBL research are being taken into consideration. METHODS: We conducted a systematic review of the literature published from 2003 through 2013. We included studies written in English, specifically in medical education, regarding either the development of instructional software or interventions using instructional software, during training or practice, that reported learner attitudes, satisfaction, knowledge, skills, or software usage. We conducted 2 latent class analyses to group articles according to platform features and intervention characteristics. In addition, we analyzed references and citations for abstracted articles. RESULTS: We analyzed 251 articles. The number of publications rose over time, and they encompassed most medical disciplines, learning settings, and training levels, totaling 25 different platforms specifically for medical education. We uncovered 4 latent classes for educational software, characteristically making use of multimedia (115/251, 45.8%), text (64/251, 25.5%), Web conferencing (54/251, 21.5%), and instructional design principles (18/251, 7.2%). We found 3 classes for intervention outcomes: knowledge and attitudes (175/212, 82.6%), knowledge, attitudes, and skills (11.8%), and online activity (12/212, 5.7%). About a quarter of the articles (58/227, 25.6%) did not hold references or citations in common with other articles. The number of common references and citations increased in articles reporting instructional design principles (P=.03), articles measuring online activities (P=.01), and articles citing a review by Cook and colleagues on CBL (P=.04). There was an association between number of citations and studies comparing CBL versus CBL, independent of publication date (P=.02). CONCLUSIONS: Studies in this field vary highly, and a high number of software systems are being developed. It seems that past recommendations regarding CBL interventions are being taken into consideration. A move into a more student-centered model, a focus on implementing reusable software platforms for specific learning contexts, and the analysis of online activity to track and predict outcomes are relevant areas for future research in this field.

Characterization of medical students recall of factual knowledge using learning objects and repeated testing in a novel e-learning system.

BACKGROUND: Spaced-repetition and test-enhanced learning are two methodologies that boost knowledge retention. ALERT STUDENT is a platform that allows creation and distribution of Learning Objects named flashcards, and provides insight into student judgments-of-learning through a metric called 'recall accuracy'. This study aims to understand how the spaced-repetition and test-enhanced learning features provided by the platform affect recall accuracy, and to characterize the effect that students, flashcards and repetitions exert on this measurement. METHODS: Three spaced laboratory sessions (s0, s1 and s2), were conducted with n=96 medical students. The intervention employed a study task, and a quiz task that consisted in mentally answering open-ended questions about each flashcard and grading recall accuracy. Students were randomized into study-quiz and quiz groups. On s0 both groups performed the quiz task. On s1 and s2, the study-quiz group performed the study task followed by the quiz task, whereas the quiz group only performed the quiz task. We measured differences in recall accuracy between groups/sessions, its variance components, and the G-coefficients for the flashcard component. RESULTS: At s0 there were no differences in recall accuracy between groups. The experiment group achieved a significant increase in recall accuracy that was superior to the quiz group in s1 and s2. In the study-quiz group, increases in recall accuracy were mainly due to the session, followed by flashcard factors and student factors. In the quiz group, increases in recall accuracy were mainly accounted by flashcard factors, followed by student and session factors. The flashcard G-coefficient indicated an agreement on recall accuracy of 91% in the quiz group, and of 47% in the study-quiz group. CONCLUSIONS: Recall accuracy is an easily collectible measurement that increases the educational value of Learning Objects and open-ended questions. This metric seems to vary in a way consistent with knowledge retention, but further investigation is necessary to ascertain the nature of such relationship. Recall accuracy has educational implications to students and educators, and may contribute to deliver tailored learning experiences, assess the effectiveness of instruction, and facilitate research comparing blended-learning interventions.

A novel collaborative e-learning platform for medical students - ALERT STUDENT.

BACKGROUND: The increasing complexity of medical curricula would benefit from adaptive computer supported collaborative learning systems that support study management using instructional design and learning object principles. However, to our knowledge, there are scarce reports regarding applications developed to meet this goal and encompass the complete medical curriculum. The aim of ths study was to develop and assess the usability of an adaptive computer supported collaborative learning system for medical students to manage study sessions. RESULTS: A study platform named ALERT STUDENT was built as a free web application. Content chunks are represented as Flashcards that hold knowledge and open ended questions. These can be created in a collaborative fashion. Multiple Flashcards can be combined into custom stacks called Notebooks that can be accessed in study Groups that belong to the user institution. The system provides a Study Mode that features text markers, text notes, timers and color-coded content prioritization based on self-assessment of open ended questions presented in a Quiz Mode. Time spent studying and Perception of knowledge are displayed for each student and peers using charts. Computer supported collaborative learning is achieved by allowing for simultaneous creation of Notebooks and self-assessment questions by many users in a pre-defined Group. Past personal performance data is retrieved when studying new Notebooks containing previously studied Flashcards. Self-report surveys showed that students highly agreed that the system was useful and were willing to use it as a reference tool. CONCLUSIONS: The platform employs various instructional design and learning object principles in a computer supported collaborative learning platform for medical students that allows for study management. The application broadens student insight over learning results and supports informed decisions based on past learning performance. It serves as a potential educational model for the medical education setting that has gathered strong positive feedback from students at our school.This platform provides a case study on how effective blending of instructional design and learning object principles can be brought together to manage study, and takes an important step towards bringing information management tools to support study decisions and improving learning outcomes.

Implementation of a Pilot Study to Analyze Circulating Tumor DNA in Early-Stage Lung Cancer.

INTRODUCTION: Liquid biopsies based on plasma circulating tumour deoxyribonucleic acid (ctDNA) have shown promise in monitoring lung cancer evolution. The expression of ctDNA across time, its relationship with clinicopathological parameters and its association with lung cancer progression through imaging allow us to weigh how useful ctDNA could be in monitoring surgically resectable lung cancer. The aim of this study was to assess the impact of ctDNA analysis implementation in early-stage lung cancer. METHODS: A cohort of 47 patients was sequentially recruited. Only 34 patients with early-stage lung cancer were included. All patients had a tissue specimen and five blood samples drawn: at the preoperative stage, from the pulmonary vein, at surgical discharge, at the first follow-up and at the last follow-up. All blood samples were evaluated for ctDNA expression. RESULTS: On average, the maximum yield of ctDNA was obtained in liquid biopsies at the surgical discharge of patients when compared with PO, PV, and F1 (p < 0.0001, p < 0.0001, p < 0.0001 respectively). No statistically significant differences were found when comparing the last follow-up to surgical discharge ctDNA expression (p = 0.851). The correlation between ctDNA concentration according to five-time points and the four clinicopathological characteristics showed that patients younger than 70 years had a statistically significant reduction of the concentration of ctDNA at the preoperative and surgical discharge time point [ß = -16 734 (-27 707; - 5760); p = 0.003; ß = -21 785 (-38 447; -5123); p = 0.010], as opposed to an increase of the concentration of ctDNA at the pulmonary vein and last follow-up time points [ß = 8369 (0.359; 16 378); p = 0.041; ß = 34 402 (12 549; 56 254); p = 0.002] all with a confidence level of 95%. In the cases where actionable mutations were identified in tissue biopsies, the expected mutation was found in five out of six patients plasma samples at the pre-operatory time point and in two out of six patients plasma samples at the pulmonary vein time point. Two out of six patients with actionable mutations had disease progression. CONCLUSION: The results of this pilot study suggest that the maximum yield of ctDNA is obtained at the surgical discharge of the patients and that the pre-operatory timepoint is the one offering the highest sensitivity for the detection of actionable mutations in ctDNA in early-stage lung cancer.

Predicting Quality of Life in Parkinson's Disease: A Machine Learning Approach Employing Common Clinical Variables.

Background: Parkinson's Disease significantly impacts health-related quality of life, with the Parkinson's Disease Questionnaire-39 extensively used for its assessment. However, predicting such outcomes remains a challenge due to the subjective nature and variability in patient experiences. This study develops a machine learning model using accessible clinical data to enable predictions of life-quality outcomes in Parkinson's Disease and utilizes explainable machine learning techniques to identify key influencing factors, offering actionable insights for clinicians. Methods: Data from the Parkinson's Real-world Impact Assessment study (PRISM), involving 861 patients across six European countries, were analyzed. After excluding incomplete data, 627 complete observations were used for the analysis. An ensemble machine learning model was developed with a 90% training and 10% validation split. Results: The model demonstrated a Mean Absolute Error of 4.82, a Root Mean Squared Error of 8.09, and an R2 of 0.75 in the training set, indicating a strong model fit. In the validation set, the model achieved a Mean Absolute Error of 11.22, a Root Mean Squared Error of 13.99, and an R2 of 0.36, showcasing moderate variation. Key predictors such as age at diagnosis, patient's country, dementia, and patient's age were identified, providing insights into the model's decision-making process. Conclusions: This study presents a robust model capable of predicting the impact of Parkinson's Disease on patients' quality of life using common clinical variables. These results demonstrate the potential of machine learning to enhance clinical decision-making and patient care, suggesting directions for future research to improve model generalizability and applicability.

Can Breastfeeding Prevent Long-Term Overweight and Obesity in Children? A Population-Based Cohort Study.

The aims of this study were to assess the impact of exclusive breastfeeding up to 6 months of age on reducing the incidence of overweight and obesity in children up to 10 years of age and to estimate the annual incidence of obesity and overweight in the study population. Our retrospective cohort analysis using electronic health records included children from zero to ten years old, born between 1 January 2006 and 31 December 2022, followed up at the Unidade Local de Saúde de Matosinhos (ULSM). Information on their comorbidity history was collected, and positive or negative control results were defined. In the first year of life, around 29% of the children on exclusive breastfeeding were obese and 20% were overweight. This trend was reversed by the age of 9. Asthma and allergic rhinitis were used as positive control outcomes and allergic dermatitis as a negative control outcome. There seems to be no relationship between exclusive and non-exclusive breastfeeding and the development of overweight or obesity at the age of 10. The results showed that breastfeeding is associated with a lower risk of asthma in the future.

Patients' health care resources utilization and costs estimation across cardiovascular risk categories: insights from the LATINO study.

BACKGROUND: Atherosclerotic Cardiovascular Disease (ASCVD) is a global public health concern. This study aimed to estimate the healthcare resource utilization (HRU) and costs stratified by cardiovascular disease (CVD) risk categories using real-world evidence, in a regional population in Portugal. METHODS: This is a retrospective observational study, using data from Electronic Health Records between 2017 and 2021. Patients aged ≥ 40 years, and with at least one general practitioner (GP) appointment in the 3 years before 31st of December 2019, were included. CVD risk categories were determined based on 2021 ESC prevention guidelines. HRU encompassed hospital data (hospitalizations, outpatient and emergency room visits) and GP appointments. Total direct costs per patient were calculated based on the reference cost of the Portuguese legislation for payment methodology on Diagnosis-Related Groups (DRGs). RESULTS: Analysis of 3 122 695 episodes, revealed consistent HRU and costs across the five years. Very high-risk patients, showed higher HRU, particularly in hospital admissions. Costs tended to rise with higher CVD risk level. Very high-risk patients with ASCVD had higher costs for hospital admissions, while low-to-moderate risk patients had higher costs for GP visits. Despite a smaller proportion, very high-risk patients with prior ASCVD represent the highest costs per patient across healthcare settings (from 115€ in emergency visits to 2 673€ in hospitalizations), followed by very high-risk patients without prior ASCVD (ASCVD-risk equivalents). CONCLUSION: This study revealed a substantial HRU and costs by patients with very high CVD risk, particularly those with prior ASCVD. Moreover, ASCVD-risk equivalents emerge as notable consumers, emphasizing the importance of risk assessment and preventive measures in cost-effective management of these patients.

Long-term cardiovascular outcomes in a population-based multicentric cohort of northern Portugal: Validation of the ESC/EAS prognostic risk classification.

BACKGROUND: Cardiovascular (CV) risk scores identify individuals at higher long-term risk of CV events that may benefit from more aggressive preventive interventions. OBJECTIVE: To assess the association of CV-risk categories and criteria with long-term CV events. METHODS: Observational cohort study between 2000-2019 on patients aged 40-80 years, followed by 14 primary care centers assisted by 1 hospital in Portugal. Follow-up began when electronic health records data allowed for CV-risk classification and dynamic reassessment per 2019 ESC/EAS Guidelines. Inclusion criteria required at least one appointment with a primary care physician within three years before follow-up initiation. We assessed the 10-year adjusted hazard-ratio of combined CV death and non-fatal atherosclerotic cardiovascular disease (ASCVD) hospitalization, across SCORE risk categories and criteria, using Cox proportional hazards models adjusted for sex, age, competing comorbidities, and medication. RESULTS: The study included 161 681 observations from 87 035 unique patients. During the observation period, 71 787 patients were classified as low/moderate, 51 476 as high and 38 418 as very-high CV-risk categories. In the very-high group, prevalent comorbidities were hypertension (69%), hypercholesterolemia (69%) and type 2 diabetes (61%), and 13% were hospitalized for ASCVD. The adjusted 10-year hazard ratio of the composite of CV death or ASCVD hospitalization was 2.10 (95% CI: 1.91-2.32) for high-risk and 3.56 (95% CI: 3.21-3.96) for very-high-risk patients (low-risk as reference). CONCLUSION: Our study reinforces the prognostic relevance of CV-risk stratification for long-term prediction of CV death and ASCVD hospitalization in an unselected cohort, independently of sex, age, competing comorbidities and medication.

MedGAN: optimized generative adversarial network with graph convolutional networks for novel molecule design.

Generative Artificial Intelligence can be an important asset in the drug discovery process to meet the demand for novel medicines. This work outlines the optimization and fine-tuning steps of MedGAN, a deep learning model based on Wasserstein Generative Adversarial Networks and Graph Convolutional Networks, developed to generate new quinoline-scaffold molecules from complex molecular graphs, including hyperparameter adjustments and evaluations of drug-likeness attributes such as pharmacokinetics, toxicity, and synthetic accessibility. The best model was capable of generating 25% valid molecules, 62% fully connected, from which 92% were quinolines, 93% were novel, and 95% unique, preserving chirality, atom charge, and favorable drug-like properties while generating 4831 novel quinolines. These results provide valuable insights into how activation functions, optimizers, learning rates, neuron units, molecule size and constitution, and scaffold structure affect the performance of generative models and their potential to create new molecular structures, enhancing deep learning applications in computational drug design.

Characterization and LDL-C management in a cohort of high and very high cardiovascular risk patients: The PORTRAIT-DYS study.

AIM: This study aims to characterize sociodemographic and clinical characteristics, use of lipid-lowering therapies (LLTs), and low-density lipoprotein cholesterol (LDL-C) control in a population with increased cardiovascular (CV) risk. METHODS: A cross-sectional observational study that uses electronic health records of patients from one hospital and across 14 primary care health centers in the North of Portugal, spanning from 2000 to 2020 (index date). Patients presented at least (i) 1 year of clinical data before inclusion, (ii) one primary care appointment 3 years before the index date, and (iii) sufficient data for CV risk classification. Patients were divided into three cohorts: high CV risk; atherosclerotic cardiovascular disease (ASCVD) risk equivalents without established ASCVD; evidence of ASCVD. CV risk and LDL-C control were defined by the 2019 and 2016 European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) dyslipidemia guidelines. RESULTS: A total of 51 609 patients were included, with 23 457 patients classified as high CV risk, 19 864 with ASCVD equivalents, and 8288 with evidence of ASCVD. LDL-C control with 2016 ESC/EAS guidelines was 32%, 10%, and 18% for each group, respectively. Considering the ESC/EAS 2019 guidelines control level was even lower: 7%, 3%, and 7% for the same cohorts, respectively. Patients without any LLT prescribed ranged from 37% in the high CV risk group to 15% in patients with evidence of ASCVD. CONCLUSION: We found that LDL-C control was very low in patients at higher risk of CV events. An alarming gap between guidelines on dyslipidemia management and clinical implementation persists, even in those at very high risk or with established ASCVD.

Gamification and Oral Health in Children and Adolescents: Scoping Review.

BACKGROUND: Oral health is a determinant of overall well-being and quality of life. Individual behaviors, such as oral hygiene and dietary habits, play a central role in oral health. Motivation is a crucial factor in promoting behavior change, and gamification offers a means to boost health-related knowledge and encourage positive health behaviors. OBJECTIVE: This study aims to evaluate the impact of gamification and its mechanisms on oral health care of children and adolescents. METHODS: A systematic search covered multiple databases: PubMed/MEDLINE, PsycINFO, the Cochrane Library, ScienceDirect, and LILACS. Gray literature, conference proceedings, and WHOQOL internet resources were considered. Studies from January 2013 to December 2022 were included, except for PubMed/MEDLINE, which was searched until January 2023. A total of 15 studies were selected following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The eligibility criteria were peer-reviewed, full-text, and empirical research related to gamification in oral health care, reports of impact, and oral health care outcomes. The exclusion criteria encompassed duplicate articles; unavailable full texts; nonoriginal articles; and non-digital game-related, non-oral health-related, and protocol studies. Selected studies were scrutinized for gamification mechanisms and outcomes. Two main questions were raised: "Does gamification in oral health care impact oral health?" and "Does oral health care gamification enhance health promotion and literacy?" The PICO (Patient, Intervention, Comparison, Outcome) framework guided the scoping review. RESULTS: Initially, 617 records were obtained from 5 databases and gray literature sources. After applying exclusion criteria, 15 records were selected. Sample size in the selected studies ranged from 34 to 190 children and adolescents. A substantial portion (11/15, 73%) of the studies discussed oral self-care apps supported by evidence-based oral health. The most clearly defined data in the apps were "brushing time" (11/11, 100%) and "daily amount brushing" (10/11, 91%). Most studies (11/15, 73%) mentioned oral health care behavior change techniques and included "prompt intention formation" (11/26, 42%), "providing instructions" (11/26, 42%), "providing information on the behavior-health link" (10/26, 38%), "providing information on consequences" (9/26, 35%), "modeling or demonstrating behavior" (9/26, 35%), "providing feedback on performance" (8/26, 31%), and "providing contingent rewards" (8/26, 31%). Furthermore, 80% (12/15) of the studies identified game design elements incorporating gamification features in oral hygiene applications. The most prevalent gamification features were "ideological incentives" (10/12, 83%) and "goals" (9/16, 56%), which were found in user-specific and challenge categories, respectively. CONCLUSIONS: Gamification in oral health care shows potential as an innovative approach to promote positive health behaviors. Most studies reported evidence-based oral health and incorporated oral health care behavior change techniques.

Children's outcomes in road traffic accidents: challenges for personal injury assessment.

Children represent a specific group of road traffic accident (RTA) victims. Performing a personal injury assessment (PIA) on a child presents a significant challenge, especially when assessing permanent disabilities and needs. However, medico-legal recommendations for PIA in such cases are lacking. The main objective of this study was to analyse the differences between children and a young- and middle-aged adult population of RTA victims to contribute to the development of relevant guidelines. Secondary objectives were to identify and characterize specifics of children's posttraumatic damages regarding: (i) temporary and permanent outcomes; and (ii) medico-legal damage parameters in the Portuguese context. We performed a retrospective study of RTA victims by comparing two groups (n = 114 each) matched for acute injury severity (SD = 0.01): G1 (children) and G2 (young- and middle-aged adults). Logistic regression was used to estimate the odds ratios. G1 presented a greater chance of evolving without or with less severe body, functional and situational outcomes (three-dimensional assessment methodology), and with lower permanent functional disability values than G2. Our findings suggest that childhood trauma generally has a better prognosis than trauma in young- and middle-aged adults. This study generated evidence on the subject and highlighted the most significant difficulties encountered by medico-legal experts when performing PIA in children. Key points: This retrospective study of PIA in child victims of RTA in Portugal considered outcomes in victims' real-life situations.Several significant differences between children and young- and middle-aged adults were observed.Children's cases presented better results in terms of the severity of body, functional and situational outcomes, and permanent damage parameters.The average time between the RTA and final PIA date and the consolidation time were longer for children because of the need to wait for the Children's next growth phase or final pubertal period (as applicable), which increased the time for PIA conclusion.There were several difficulties in the medical-legal evaluation of children's cases, which was a complex process because the trauma affected them in their growth phase.

Are There Any Differences in Road Traffic Injury Outcomes between Older and Younger Adults? Setting the Grounds for Posttraumatic Senior Personal Injury Assessment Guidelines.

Injury outcomes seem to be more severe in older than younger persons. This may make personal injury assessment (PIA) particularly difficult, mainly because of seniors' previous health frailties. To set the grounds for seniors' PIA guidelines, we compared an older with a younger adult population of trauma victims and, secondarily, identified differences between the groups regarding three-dimensional and medico-legal damage parameters assessment. Using a retrospective study of victims of road traffic accidents, we compared the groups (n = 239 each), assuring similar acute injury severity (ISS standardised difference = 0.01): G1 (older adults); G2 (younger adults). Logistic regression was used to estimate the odds ratio. G1 revealed higher negative consequences when considering the three-dimensional damage assessment, with more frequent and severe outcomes, being a cause of further difficulties in daily living activities, with a loss of independence and autonomy. Nevertheless, regarding the medico-legal damage parameters, permanent functional disability did not show significant differences. This study generates evidence that reveals the need to rethink the traditional methodology of PIA in older persons, giving more relevance to the real-life contexts of each person. It is essential to: obtain complete information about previous physiologic and health states, begin the medico-legal assessment as early as possible, make regular follow-ups, and perform a multidisciplinary evaluation.

Health Conditions in Older Adults Suspected of Being Maltreated: A 20-Year Real-World Study.

Older adult maltreatment (OAM) is a global problem that has attracted increasing attention due to the ageing population and its severe impact on victim health. Thus, this study aims to analyse the prevalence of certain health conditions in people ≥ 60 years old whom physicians from a local healthcare unit suspected to be victims of maltreatment. The specific objectives are to determine the prevalence rates of health-related risk factors, traumatic injuries and intoxications, mental disorders, and physical disorders. We conducted a real-world, retrospective, observational, and cross-sectional study based on secondary data analyses of electronic health records and healthcare registers of patients at the Local Healthcare Unit of Matosinhos (2001-2021). Information was obtained based on codes from the International Classification of Diseases, codes from the International Classification of Primary Care, and clinical notes (according to previously defined keywords). We identified 3092 suspected victims of OAM, representing 4.5% of the total population analysed. This prevalence is lower than the known rates. We also found that some health risk factors, traumatic injuries and intoxications, mental health disorders, and physical disorders presented higher rates in the suspected victims than among the total population. In this age group, we cannot assume that these health problems are only related to a possible current victimisation process; they could also be associated with adverse childhood experiences or intimate partner violence, among other forms of violence, all of which can lead to cumulative effects on the victim's health. This evidence increases healthcare providers' responsibility in detecting and reporting all cases of suspected maltreatment.

Secur-e-Health Project: Towards Federated Learning for Smart Pediatric Care.

The application of machine learning (ML) algorithms to electronic health records (EHR) data allows the achievement of data-driven insights on various clinical problems and the development of clinical decision support (CDS) systems to improve patient care. However, data governance and privacy barriers hinder the use of data from multiple sources, especially in the medical field due to the sensitivity of data. Federated learning (FL) is an attractive data privacy-preserving solution in this context by enabling the training of ML models with data from multiple sources without any data sharing, using distributed remotely hosted datasets. The Secur-e-Health project aims at developing a solution in terms of CDS tools encompassing FL predictive models and recommendation systems. This tool may be especially useful in Pediatrics due to the increasing demands on Pediatric services, and the current scarcity of ML applications in this field compared to adult care. Herein we provide a description of the technical solution proposed in this project for three specific pediatric clinical problems: childhood obesity management, pilonidal cyst post-surgical care and retinography imaging analysis.

Missed opportunities in the diagnosis of heart failure: a real-world assessment.

AIMS: Heart failure (HF) is a leading cause of hospitalization worldwide. An early HF diagnosis is key to reducing hospitalizations. We used electronic health records (EHRs) to characterize HF pathways at the primary care physician (PCP) level prior to a first HF hospitalization (hHF). This study aimed to identify missed opportunities for HF diagnosis and management at the PCP level before a first hHF. METHODS AND RESULTS: This cohort study used EHRs of a large health care organization in Portugal. Patients with incident hHF between 2017 and 2020 were identified. Missed opportunities were defined by the absence of any of the following work-up in the 6 months after signs or symptoms had been recorded: lab results and electrocardiogram, natriuretic peptides, echocardiogram, referral to HF specialist, or HF medication initiation. A total of 2436 patients with a first hHF were identified. The median (interquartile range) age at the time of hospitalization was 81 (14) years, and 1361 (56%) were women. Most patients were treated with cardiovascular drugs prior or at index event. A total of 720 (30%) patients had records of HF signs or symptoms, 94% (n = 674) within 6 months prior to hHF. Among patients with recorded HF signs or symptoms, 410 (57%) had clinical management considered adequate before signs and symptoms were recorded. Of the 310 remaining patients, 155 (50%) had a follow-up that was considered inadequate. CONCLUSIONS: Relatively few patients with a first hHF had primary care records of signs or symptoms prior to admission. Of these, nearly half had inadequate management considering diagnosis and treatment. These data suggest the need to improve PCP HF awareness.

Sex differences in LDL-C control in a primary care population: The PORTRAIT-DYS study.

BACKGROUND AND AIMS: Cardiovascular (CV) diseases show clear differences in clinical manifestation and treatment outcomes between men and women. To reduce sex disparities in achieving lipid-lowering therapy (LLT) goals, a sex-focused assessment is essential and more studies are needed to bring new evidence to clinicians. This study aims to assess the role of sex in attaining low-density lipoprotein cholesterol (LDL-C) goals, after correction for age, CV risk category, LLT intensity, and presence of mental health disorder and social deprivation. METHODS: A retrospective cohort analysis of patients aged 40-85, followed in 1 hospital and 14 primary care centers in Portugal, using electronic health records from 1/1/2012 to 31/12/2020, was performed. The analysis considered an episode-based design, where exposure consists of any time when LLT was started or intensity changed. The likelihood of reaching the LDL-C goal according to contemporary ESC/EAS guidelines was modeled using multivariate Cox regression. LDL-C goal achievement at 180 days was defined as the outcome. The analysis was repeated at 30-day follow-up intervals up to 360 days, and also stratified by CV risk category. RESULTS: We identified 40,032 exposure episodes (LLT initiation or intensity change) in 30,323 distinct patients. Male sex, older age, lower CV risk and increasing LLT intensity were associated with improved LDL-C control. Women were 22% less likely to reach the LDL-C goal than men (HR = 0.78, 95% CI:0.73, 0.82) independently of covariates. CONCLUSIONS: Women have a lower likelihood of attaining LDL-C goals than men after adjustment for LLT intensity, age, CV risk category, presence of mental health disorder and social deprivation. This finding underscores the need for further investigation and tailoring of LLT management strategies in women.

Twenty years of real-world data to estimate chronic kidney disease prevalence and staging in an unselected population.

Chronic kidney disease (CKD) represents a global public health burden, but its true prevalence is not fully characterized in the majority of countries. We studied the CKD prevalence in adult users of the primary, secondary and tertiary healthcare units of an integrated health region in northern Portugal (n = 136 993; representing ∼90% of the region's adult population). Of these, 45 983 (33.6%) had at least two estimated glomerular filtration rate (eGFR) assessments and 30 534 (22.2%) had at least two urinary albumin:creatinine ratio (UACR) assessments separated by at least 3 months. CKD was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines as a persistent decrease in eGFR (<60 ml/min/1.73 m2) and/or an increase in UACR (≥30 mg/g). The estimated overall prevalence of CKD was 9.8% and was higher in females (5.5%) than males (4.2%). From these, it was possible to stratify 4.7% according to KDIGO guidelines. The prevalence of CKD was higher in older patients (especially in patients >70 years old) and in patients with comorbidities. This is the first real-world-based study to characterize CKD prevalence in a large, unselected Portuguese population. It probably provides the nearest estimate of the true CKD prevalence and may help healthcare providers to guide CKD-related policies and strategies focused on prevention and on the improvement of cardiovascular disease and other outcomes.