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    Response of the human myocardium to ischemic injury and preconditioning: The role of cardiac and comorbid conditions, medical treatment, and basal redox status

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    The diseased human myocardium is highly susceptible to ischemia/reoxygenation (I/R)-induced injury but its response to protective interventions such as ischemic preconditioning (IPreC) is unclear. Cardiac and other pre-existing clinical conditions as well as previous or ongoing medical treatment may influence the myocardial response to I/R injury and protection. This study investigated the effect of both on myocardial susceptibility to I/R-induced injury and the protective effects of IPreC.The response to I/R varied widely. Myocardium from patients with aortic valve disease was the most susceptible to injury whereas myocardium from dyslipidemia patients was the least susceptible. Tissue from females was better protected than tissue from males. Myocardium from patients with mitral valve disease was the least responsive to IPreC. The basal redox status was altered in the myocardium from patients with mitral and aortic valve disease.The response of the myocardium to I/R and IPreC is highly variable and influenced by the underlying cardiac pathology, dyslipidemia, sex, and the basal redox status. These results should be taken into account in the design of future clinical studies on the prevention of I/R injury and protection

    Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models

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    The increased survival in Systemic Lupus Erythematosus (SLE) patients implies the development of chronic damage, occurring in up to 50% of cases. Its prevention is a major goal in the SLE management. We aimed at predicting chronic damage in a large monocentric SLE cohort by using neural networks.We enrolled 413 SLE patients (M/F 30/383; mean age ± SD 46.3±11.9 years; mean disease duration ± SD 174.6 ± 112.1 months). Chronic damage was assessed by the SLICC/ACR Damage Index (SDI). We applied Recurrent Neural Networks (RNNs) as a machine-learning model to predict the risk of chronic damage. The clinical data sequences registered for each patient during the follow-up were used for building and testing the RNNs.At the first visit in the Lupus Clinic, 35.8% of patients had an SDI≥1. For the RNN model, two groups of patients were analyzed: patients with SDI = 0 at the baseline, developing damage during the follow-up (N = 38), and patients without damage (SDI = 0). We created a mathematical model with an AUC value of 0.77, able to predict damage development. A threshold value of 0.35 (sensitivity 0.74, specificity 0.76) seemed able to identify patients at risk to develop damage.We applied RNNs to identify a prediction model for SLE chronic damage. The use of the longitudinal data from the Sapienza Lupus Cohort, including laboratory and clinical items, resulted able to construct a mathematical model, potentially identifying patients at risk to develop damage

    Adherence to Prophylaxis in Adolescents and Young Adults with Severe Haemophilia: A Quantitative Study with Patients

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    haemophilia is an inherited bleeding disorder caused by a deficiency in one of the blood coagulation factors. For people affected by severe haemophilia, the deficiency can cause spontaneous internal bleeding. Most young people with severe haemophilia in the UK follow a preventative treatment regimen (prophylaxis) consisting of several intravenous injections of factor concentrate each week. There is good evidence that prophylaxis reduces bleeds whilst also improving quality of life. However, levels of adherence among young people with haemophilia reported in the existing literature vary widely and are predominately based on estimations made by healthcare professionals and parents. Additionally, drivers of (non)adherence among young people specifically have not been evidenced.to assess self-reported adherence among young people with haemophilia, provide evidence of psychosocial predictors of adherence, and to establish the associations between non-adherence and number of bleeds and hospital visits.91 participants were recruited during outpatient appointments in 13 haemophilia centres across England and Wales, and invited to complete a questionnaire assessing self-reported adherence (VERITAS-Pro), Haemophilia-related pain and impact of pain, Illness Perceptions, Beliefs about Medications, Self-efficacy, Outcome expectations, Positive and Negative Affect, and Social support. Number of hospital visits and bleeds during the previous six months were collected from medical files.Of 78 participants with complete data, just 18% had scores indicating non-adherence. Psychosocial predictors differed between intentional (skipping) and un-intentional (forgetting) non-adherence. Overall, however, better adherence was reported where participants perceived the need for prophylaxis was greater than their concern over taking it as well as having a positive expectancy of its effectiveness, good social support and a stronger emotional reaction to having haemophilia.The findings indicate that adherence is generally good, and that assessing illness and treatment beliefs, social support and outcome expectations may play a valuable role in identifying which individuals are at risk of non-adherence. Interventions aimed at improving adherence should particularly consider improving social support, reducing patients’ concerns about prophylaxis, increasing their belief in the necessity of prophylaxis, and increasing positive outcome expectations

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