Is the long-term poor prognosis of acute myocardial infarction in patients with mental illness mediated through their poor adherence with recommended healthcare?

BACKGROUND: Compared with patients without evidence of psychiatric symptoms, those with mental disorders experience reduced adherence with recommended healthcare and poorer clinical outcomes. This study aimed to evaluate whether the worse prognosis of patients with mental disorders after experiencing acute myocardial infarction could be fully or partially mediated by their reduced adherence to recommended healthcare. METHODS: In this retrospective cohort population-based study, 103 389 residents in the Italian Lombardy Region who experienced acute myocardial infarction in 2007-19 were identified. Among them, 1549 patients with severe mental illness (SMI) were matched with five cohort members without evidence of mental disorders (references). Recommended healthcare (cardiac medicaments and selected outpatient services) was evaluated in the year after the date of index hospital discharge. The first occurrences of cardiovascular (CV) hospital admissions and any-cause-death were considered as endpoints. Mediation analysis was performed to investigate whether post-discharge use of recommended healthcare may be considered a mediator of the relationship between healthcare exposure and endpoints occurrence. RESULTS: Compared with references, patients with SMI had lower adherence with recommended healthcare and adjusted risk excesses of 39% and 73% for CV hospitalizations and all-cause mortality. Mediation analysis showed that 4.1% and 11.3% of, respectively, CV hospitalizations and deaths occurred among psychiatric patients was mediated by their worse adherence to specific healthcare. CONCLUSION: The reduced use of recommended outpatient healthcare by patients with SMI had only a marginal effect on their worse prognosis. Other key factors mediating the prognostic gap between patients with and without mental disorders should be investigated.

Allocation of Users of Mental Health Services to Needs-Based Care Clusters: An Italian Pilot Study.

In Italy, despite strong community-based mental health services, needs assessment is unsatisfactory. Using the Mental Health Clustering Tool (MHCT) we adopted a multidimensional and non-diagnosis dependent approach to assign mental health services users with similar needs to groups corresponding to resources required for effective care. We tested the MHCT in nine Departments of Mental Health in four Italian regions. After a brief training, 318 professionals assessed 12,938 cases with a diagnosis of schizophrenia, depression, bipolar disorder and personality disorder through the MHCT. 53% of cases were 40-59 years, half were females, 51% had a diagnosis of schizophrenia, 48% of cases were clinically severe. Clusters included different levels of clinical severity and diagnostic groups. The largest cluster was 11 (ongoing recurrent psychosis), with 18.9% of the sample, followed by cluster 3 (non-psychotic disorders of moderate severity). The MHCT could capture a variety of problems of people with mental disorders beyond the traditional psychiatric assessment, therefore depicting service population from a different standpoint. Following a brief training, MHCT assessment proved to be feasible. The automatic allocation of cases made the attribution to clusters easy and acceptable by professionals. To what extent clustering provide a sound base for care planning will be the matter of further research.

Assessing the quality of the care offer for people with personality disorders in Italy: the QUADIM project. A multicentre research based on the database of use of Mental Health services.

BACKGROUND: Italy can be viewed as a laboratory to assess the quality of mental healthcare delivered in a community-oriented system, especially for severe mental disorders, such as personality disorders. Although initiatives based on clinical indicators for assessing the quality of mental healthcare have been developed by transnational-organisations, there is still no widespread practice of measuring the quality of care pathways delivered to patients with severe mental disorders in a community-oriented system, especially using administrative healthcare databases. The aim of the study is to evaluate the quality of care delivered to patients with personality disorders taken-in-care by mental health services of four Italian regions (Lombardy, Emilia-Romagna, Lazio, Sicily). METHODS: A set of thirty-three clinical indicators, concerning accessibility, appropriateness, continuity, and safety of care, was implemented using regional healthcare utilization databases, containing data on mental health treatments and diagnosis, hospital admissions, outpatient interventions and exams and drug prescriptions. RESULTS: 31,688 prevalent patients with personality disorders treated in 2015 were identified, of whom 2,331 newly taken-in-care. One-in-10 patients received a standardized assessment, the treatment discontinuity affected half of the cases. 12.7% of prevalent patients received at least one hospitalization, 10.6% in the newly taken-in-care cohort. 6-out-of-10 patients had contact with community-services within 14 days from hospital discharge. Access to psychotherapy and psychoeducational treatments was low and delivered with a low intensity. The median of psychosocial interventions per person-year was 19.1 and 9.4, respectively, in prevalent and newly taken-in-care cases. Nearly 50% of patients received pharmacological treatments. CONCLUSIONS: Healthcare utilization databases were used to systematically evaluate and assess service delivery across regional mental health systems; suggesting that in Italy the public mental health services provide to individuals with personality disorders suboptimal treatment paths.

Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system.

BACKGROUND: Mental health (MH) care often exhibits uneven quality and poor coordination of physical and MH needs, especially for patients with severe mental disorders. This study tests a Population Health Management (PHM) approach to identify patients with severe mental disorders using administrative health databases in Italy and evaluate, manage and monitor care pathways and costs. A second objective explores the feasibility of changing the payment system from fee-for-service to a value-based system (e.g., increased care integration, bundled payments) to introduce performance measures and guide improvement in outcomes. METHODS: Since diagnosis alone may poorly predict condition severity and needs, we conducted a retrospective observational study on a 9,019-patient cohort assessed in 2018 (30.5% of 29,570 patients with SMDs from three Italian regions) using the Mental Health Clustering Tool (MHCT), developed in the United Kingdom, to stratify patients according to severity and needs, providing a basis for payment for episode of care. Patients were linked (blinded) with retrospective (2014-2017) physical and MH databases to map resource use, care pathways, and assess costs globally and by cluster. Two regions (3,525 patients) provided data for generalized linear model regression to explore determinants of cost variation among clusters and regions. RESULTS: Substantial heterogeneity was observed in care organization, resource use and costs across and within 3 Italian regions and 20 clusters. Annual mean costs per patient across regions was €3,925, ranging from €3,101 to €6,501 in the three regions. Some 70% of total costs were for MH services and medications, 37% incurred in dedicated mental health facilities, 33% for MH services and medications noted in physical healthcare databases, and 30% for other conditions. Regression analysis showed comorbidities, resident psychiatric services, and consumption noted in physical health databases have considerable impact on total costs. CONCLUSIONS: The current MH care system in Italy lacks evidence of coordination of physical and mental health and matching services to patient needs, with high variation between regions. Using available assessment tools and administrative data, implementation of an episodic approach to funding MH could account for differences in disease phase and physical health for patients with SMDs and introduce performance measurement to improve outcomes and provide oversight.

Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy.

Objective: The aim of this study was to improve the performance of the Chronic Related Score (CReSc) in predicting mortality and healthcare needs in the general population. Methods: A population-based study was conducted, including all beneficiaries of the Regional Health Service of Lombardy, Italy, aged 18 years or older in January 2015. Each individual was classified as exposed or unexposed to 69 candidate predictors measured before baseline, updated to include four mental health disorders. Conditions independently associated with 5-year mortality were selected using the Cox regression model on a random sample including 5.4 million citizens. The predictive performance of the obtained CReSc-2.0 was assessed on the remaining 2.7 million citizens through discrimination and calibration. Results: A total of 35 conditions significantly contributed to the CReSc-2.0, among which Alzheimer's and Parkinson's diseases, dementia, heart failure, active neoplasm, and kidney dialysis contributed the most to the score. Approximately 36% of citizens suffered from at least one condition. CReSc-2.0 discrimination performance was remarkable, with an area under the receiver operating characteristic curve of 0.83. Trends toward increasing short-term (1-year) and long-term (5-year) rates of mortality, hospital admission, hospital stay, and healthcare costs were observed as CReSc-2.0 increased. Conclusion: CReSC-2.0 represents an improved tool for stratifying populations according to healthcare needs.

Capturing the variety of clinical pathways in patients with schizophrenic disorders through state sequences analysis.

BACKGROUND: Care pathways are increasingly being used to enhance the quality of care and optimize the use of resources for health care. Nevertheless, recommendations regarding the sequence of care are mostly based on consensus-based decisions as there is a lack of evidence on effective treatment sequences. In a real-world setting, classical statistical tools were insufficient to consider a phenomenon with such high variability adequately and have to be integrated with novel data mining techniques suitable for identifying patterns in complex data structures. Data-driven techniques can potentially support empirically identifying effective care sequences by extracting them from data collected routinely. The purpose of this study is to perform a state sequence analysis (SSA) to identify different patterns of treatment and to asses whether sequence analysis may be a useful tool for profiling patients according to the treatment pattern. METHODS: The clinical application that motivated the study of this method concerns the mental health field. In fact, the care pathways of patients affected by severe mental disorders often do not correspond to the standards required by the guidelines in this field. In particular, we analyzed patients with schizophrenic disorders (i.e., schizophrenia, schizotypal or delusional disorders) using administrative data from 2015 to 2018 from Lombardy Region. This methodology considers the patient's therapeutic path as a conceptual unit, composed of a succession of different states, and we show how SSA can be used to describe longitudinal patient status. RESULTS: We define the states to be the weekly coverage of different treatments (psychiatric visits, psychosocial interventions, and anti-psychotic drugs), and we use the longest common subsequences (dis)similarity measure to compare and cluster the sequences. We obtained three different clusters with very different patterns of treatments. CONCLUSIONS: This kind of information, such as common patterns of care that allowed us to risk profile patients, can provide health policymakers an opportunity to plan optimum and individualized patient care by allocating appropriate resources, analyzing trends in the health status of a population, and finding the risk factors that can be leveraged to prevent the decline of mental health status at the population level.

The quality of mental health care for people with bipolar disorders in the Italian mental health system: the QUADIM project.

BACKGROUND: The assessment of the quality of care pathways delivered to people with severe mental disorders in a community-based system remains uncommon, especially using healthcare utilization databases. The aim of the study was to evaluate the quality of care provided to people with bipolar disorders taken-in-care by mental health services of four Italian areas (Lombardy, Emilia-Romagna, Lazio, province of Palermo). METHODS: Thirty-six quality indicators were implemented to assess quality of mental health care for patients with bipolar disorders, according to three dimensions (accessibility and appropriateness, continuity, and safety). Data were retrieved from healthcare utilization (HCU) databases, which contain data on mental health treatments, hospital admissions, outpatient interventions, laboratory tests and drug prescriptions. RESULTS: 29,242 prevalent and 752 incident cases taken-in-care by regional mental health services with a diagnosis of bipolar disorder in 2015 were identified. Age-standardized treated prevalence rate was 16.2 (per 10,000 adult residents) and treated incidence rate 1.3. In the year of evaluation, 97% of prevalent cases had ≥ 1 outpatient/day-care contacts and 88% had ≥ 1 psychiatric visits. The median of outpatient/day-care contacts was 9.3 interventions per-year. Psychoeducation was provided to 3.5% of patients and psychotherapy to 11.5%, with low intensity. 63% prevalent cases were treated with antipsychotics, 71.5% with mood stabilizers, 46.6% with antidepressants. Appropriate laboratory tests were conducted in less than one-third of prevalent patients with a prescription of antipsychotics; three quarters of those with a prescription of lithium. Lower proportions were observed for incident patients. In prevalent patients, the Standardized Mortality Ratio was 1.35 (95% CI: 1.26-1.44): 1.18 (1.07-1.29) in females, 1.60 (1.45-1.77) in males. Heterogeneity across areas was considerable in both cohorts. CONCLUSIONS: We found a meaningful treatment gap in bipolar disorders in Italian mental health services, suggesting that the fact they are entirely community-based does not assure sufficient coverage by itself. Continuity of contacts was sufficient, but intensity of care was low, suggesting the risk of suboptimal treatment and low effectiveness. Care pathways were monitored and evaluated using administrative healthcare databases, adding evidence that such data may contribute to assess the quality of clinical pathways in mental health.

Assessment and Monitoring of the Quality of Clinical Pathways in Patients with Depressive Disorders: Results from a Multiregional Italian Investigation on Mental Health Care Quality (the QUADIM Project).

Ensuring adequate quality of care to patients with severe mental disorders remains a challenge. The implementation of clinical indicators aimed at assessing the quality of health care pathways delivered is crucial for the improvement of mental health services (MHS). This study aims to evaluate the quality of care delivered to patients who are taken-into-care with depressive disorders by MHS. Thirty-four clinical indicators concerning accessibility, appropriateness, continuity, and safety were estimated using health care utilization databases from four Italian regions (Lombardy, Emilia-Romagna, Lazio, Sicily). A total of 78,924 prevalent patients treated for depressive disorders in 2015 were identified, of whom 15,234 were newly engaged by MHS. During the year of follow-up, access to psychotherapeutic interventions was low, while the intensity was adequate; 5.1% of prevalent patients received at least one hospitalization in a psychiatric ward (GHPW), and 3.3% in the cohort of newly engaged in services. Five-out-of-10 patients had contact with community services within 14 days after GHPW discharge, but less than half of patients were persistent to antidepressant drug therapy. Furthermore, prevalent patients showed an excess of mortality compared to the general population (SMR = 1.35; IC 95%: 1.26-1.44). In conclusion, the quality of health care is not delivered in accordance with evidence-based mental health standards. Evaluation of health interventions are fundamental strategies for improving the quality and equity of health care.

Are we equally at risk of changing smoking behavior during a public health crisis? Impact of educational level on smoking from the TEMPO cohort.

BACKGROUND: The COVID-19 pandemic as a public health crisis has led to a significant increase in mental health difficulties. Smoking is strongly associated with mental health conditions, which is why the pandemic might have influenced the otherwise decline in smoking rates. Persons belonging to socioeconomically disadvantaged groups may be particularly affected, both because the pandemic has exacerbated existing social inequalities and because this group was more likely to smoke before the pandemic. We examined smoking prevalence in a French cohort study, focusing on differences between educational attainment. In addition, we examined the association between interpersonal changes in tobacco consumption and educational level from 2018 to 2021. METHODS: Using four assessments of smoking status available from 2009 to 2021, we estimated smoking prevalence over time, stratified by highest educational level in the TEMPO cohort and the difference was tested using chi2 test. We studied the association between interpersonal change in smoking status between 2018 and 2021 and educational attainment among 148 smokers, using multinomial logistic regression. RESULTS: Smoking prevalence was higher among those with low education. The difference between the two groups increased from 2020 to 2021 (4.8-9.4%, p < 0.001). Smokers with high educational level were more likely to decrease their tobacco consumption from 2018 to 2021 compared to low educated smokers (aOR = 2.72 [1.26;5.89]). CONCLUSION: Current findings showed a widening of the social inequality gap in relation to smoking rates, underscoring the increased vulnerability of persons with low educational level to smoking and the likely inadequate focus on social inequalities in relation to tobacco control policies during the pandemic.

From contact coverage to effective coverage of community care for patients with severe mental disorders: A real-world investigation from Italy.

Objectives: To measure the gap between contact and effective coverage of mental healthcare (MHC). Materials and methods: 45,761 newly referred cases of depression, schizophrenia, bipolar disorder, and personality disorder from four Italian regions were included. A variant of the self-controlled case series method was adopted to estimate the incidence rate ratio (IRR) for the relationship between exposure (i.e., use of different types of MHC such as pharmacotherapy, generic contact with the outpatient services, psychosocial intervention, and psychotherapy) and relapse (emergency hospital admissions for mental illness). Results: 11,500 relapses occurred. Relapse risk was reduced during periods covered by (i) psychotherapy for patients with depression (IRR 0.67; 95% CI: 0.49 to 0.91) and bipolar disorder (0.64; 0.29 to 0.99); (ii) psychosocial interventions for those with depression (0.74; 0.56 to 0.98), schizophrenia (0.83; 0.68 to 0.99), and bipolar disorder (0.55; 0.36 to 0.84), (iii) pharmacotherapy for patients with schizophrenia (0.58; 0.49 to 0.69), and bipolar disorder (0.59; 0.44 to 0.78). Coverage with generic care, in absence of psychosocial/psychotherapeutic interventions, did not affect risk of relapse. Conclusion: This study ascertained the gap between contact and effective coverage of MHC and showed that administrative data can usefully contribute to assess the effectiveness of a mental health system.

Monitoring the Emotional Response to the COVID-19 Pandemic Using Sentiment Analysis: A Case Study in Mexico.

The world is facing the COVID-19 pandemic, leading to an unprecedented change in the lifestyle routines of millions. Beyond the general physical health, financial, and social repercussions of the pandemic, the adopted mitigation measures also present significant challenges in the population's mental health and health programs. It is complex for public organizations to measure the population's mental health in order to incorporate it into their own decision-making process. Traditional survey methods are time-consuming, expensive, and fail to provide the continuous information needed to respond to the rapidly evolving effects of governmental policies on the population's mental health. A significant portion of the population has turned to social media to express the details of their daily life, rendering this public data a rich field for understanding emotional and mental well-being. This study aims to track and measure the sentiment changes of the Mexican population in response to the COVID-19 pandemic. To this end, we analyzed 760,064,879 public domain tweets collected from a public access repository to examine the collective shifts in the general mood about the pandemic evolution, news cycles, and governmental policies using open sentiment analysis tools. Sentiment analysis polarity scores, which oscillate around -0.15, show a weekly seasonality according to Twitter's usage and a consistently negative outlook from the population. It also remarks on the increased controversy after the governmental decision to terminate the lockdown and the celebrated holidays, which encouraged the people to incur social gatherings. These findings expose the adverse emotional effects of the ongoing pandemic while showing an increase in social media usage rates of 2.38 times, which users employ as a coping mechanism to mitigate the feelings of isolation related to long-term social distancing. The findings have important implications in the mental health infrastructure for ongoing mitigation efforts and feedback on the perception of policies and other measures. The overall trend of the sentiment polarity is 0.0001110643.

Cognitive insight in individuals at ultra-high risk for psychosis compared to patients with first-episode psychosis and non-psychotic help-seeking youths.

BACKGROUND: Defective insight is a hallmark of schizophrenia. Less is known about insight in emerging psychosis. In this study a widely used measure of cognitive insight, the Beck Cognitive Insight Scale (BCIS), has been applied to a sample including patients with first-episode psychosis (FEP), at ultra-high risk (UHR) for psychosis, and help-seeking youths without psychotic symptoms. METHODS: The Comprehensive Assessment of At-Risk Mental State (CAARMS) interview was used to classify patients. Enrolled patients were assessed with the General Health Questionnaire-12 (GHQ-12), the Prodromal Questionnaire-16 (PQ-16), the Social and Occupational Functioning Assessment Scale (SOFAS), and the BCIS. RESULTS: The sample included 212 participants (58%) with non-psychotic mental distress, 131 participants (36%) were UHR, and 22 (6%) were with FEP. Males and females were in equal proportion, mean age was 19.2 ± 2.6 years old (range: 15-25 years). Reliability (Cronbach's alpha) was good for clinical scales (>0.7) and acceptable (around 0.6) for the two BCIS subscales. The self-certainty subscale of the BCIS was more reproducible in factor analysis than the self-reflectiveness scale. Youths devoid of psychotic symptoms scored lower than UHR and FEP participants on the GHQ-12 and the PQ-16 and had better psychosocial functioning as measured by the SOFAS. Levels of cognitive insight did not differ between groups. CONCLUSION: People in the early stages of psychosis may be still accessible to self-reflectiveness and more hesitant about the certainty of their beliefs than patients at more advanced stages of the illness, as those with fully displayed schizophrenia.

The quality of mental health care delivered to patients with schizophrenia and related disorders in the Italian mental health system. The QUADIM project: a multi-regional Italian investigation based on healthcare utilisation databases.

AIMS: To evaluate the quality of mental health care delivered to patients with schizophrenia and related disorders taken-in-care by mental health services in four Italian regions (Lombardy, Emilia-Romagna, Lazio, Sicily). METHODS: Thirty-one clinical indicators concerning accessibility, appropriateness, continuity and safety were defined and estimated using healthcare utilisation (HCU) databases, containing data on mental health treatments, hospital admissions, outpatient interventions, lab tests and drug prescriptions. RESULTS: A total of 70 586 prevalent patients with schizophrenia and related disorders treated in 2015 were identified, of whom 1752 were newly taken-in-care by the facilities of regional mental health services. For most patients community care was accessible and moderately intensive. However, care pathways were not implemented based on a structured assessment and only half of the patients received psychosocial treatments. One patient out of ten had access to psychological interventions and psychoeducation. Activities specifically addressed to families involved a third of prevalent patients and less than half of new patients. One patient out of six was admitted to a community residential facility, and one out of ten to a General Hospital Psychiatric Ward (GHPW); higher values were identified in new cases. In general hospitals, few patients had a length of stay (LoS) of more than 30 days, while one-fifth of the admissions were followed by readmission within 30 days of discharge. For two-thirds of patients, continuity of community care was met, and six times out of ten a discharge from a GHPW was followed by an outpatient contact within 2 weeks. For cases newly taken-in-care, the continuity of community care was uncommon, while the readiness of outpatient contacts after discharge was slightly more frequent. Most of the patients received antipsychotic medication, but their adherence to long-term treatment was low. Antipsychotic polytherapy was frequent and the control of metabolic side effects was poor. The variability between regions was high and consistent in all the quality domains. CONCLUSIONS: The Italian mental health system could be improved by increasing the accessibility to psychosocial interventions, improving the quality of care for newly taken-in-care patients, focusing on somatic health and mortality, and reducing regional variability. Clinical indicators demonstrate the strengths and weaknesses of the mental health system in these regions, and, as HCU databases, they could be useful tools in the routine assessment of mental healthcare quality at regional and national levels.

Does the mental health system provide effective coverage to people with schizophrenic disorder? A self-controlled case series study in Italy.

PURPOSE: To measure indicators of timeliness and continuity of treatments on patients with schizophrenic disorder in 'real-life' practice, and to validate them through their relationship with relapse occurrences. METHODS: The target population was from four Italian regions overall covering 22 million beneficiaries of the NHS (37% of the entire Italian population). The cohort included 12,054 patients newly taken into care for schizophrenic disorder between January 2015 and June 2016. The self-controlled case series (SCCS) design was used to estimate the incidence rate ratio of relapse occurrences according to mental healthcare coverage. RESULTS: Poor timeliness (82% and 33% of cohort members had not yet started treatment with psychosocial interventions and antipsychotic drug therapy within the first year after they were taken into care) and continuity (27% and 23% of patients were persistent with psychosocial interventions, and antipsychotic drug therapy within the first 2 years after starting the specific treatment) were observed. According to SCCS design, 4794 relapses occurred during 9430 PY (with incidence rate of 50.8 every 100 PY). Compared with periods not covered by mental healthcare, those covered by psychosocial intervention alone, antipsychotic drugs alone and by psychosocial intervention and antipsychotic drugs together were, respectively, associated with relapse rate reductions of 28% (95% CI 4-46%), 24% (17-30%) and 44% (32-53%). CONCLUSION: Healthcare administrative data may contribute to monitor and to assess the effectiveness of a mental health system. Persistent use of both psychosocial intervention and antipsychotic drugs reduces risk of severe relapse.

A Monte Carlo dose calculation system for ophthalmic brachytherapy based on a realistic eye model.

PURPOSE: There is a growing trend towards the adoption of model-based calculation algorithms (MBDCAs) for brachytherapy dose calculations which can properly handle media and source/applicator heterogeneities. However, most of dose calculations in ocular plaque therapy are based on homogeneous water media and standard in-silico ocular phantoms, ignoring non-water equivalency of the anatomic tissues and heterogeneities in applicators and patient anatomy. In this work, we introduce EyeMC, a Monte Carlo (MC) model-based calculation algorithm for ophthalmic plaque brachytherapy using realistic and adaptable patient-specific eye geometries and materials. METHODS: We used the MC code PENELOPE in EyeMC to model Bebig IsoSeed I25.S16 seeds in COMS plaques and 106 Ru/106 Rh applicators that are coupled onto a customizable eye model with realistic geometry and composition. To significantly reduce calculation times, we integrated EyeMC with CloudMC, a cloud computing platform for radiation therapy calculations. EyeMC is equipped with an evaluation module that allows the generation of isodose distributions, dose-volume histograms, and comparisons with Plaque Simulator three-dimensional dose distribution. We selected a sample of patients treated with 125 I and 106 Ru isotopes in our institution, covering a variety of different type of plaques, tumor sizes, and locations. Results from EyeMC were compared to the original plan calculated by the TPS Plaque Simulation, studying the influence of heterogeneous media composition as well. RESULTS: EyeMC calculations for Ru plaques agreed well with manufacturer's reference data and data of MC simulations from Hermida et al. (2013). Significant deviations, up to 20%, were only found in lateral profiles for notched plaques. As expected, media composition significantly affected estimated doses to different eye structures, especially in the 125 I cases evaluated. Dose to sclera and lens were found to be about 12% lower when considering real media, while average dose to tumor was 9% higher. 106 Ru cases presented a 1%-3% dose reduction in all structures using real media for calculation, except for the lens, which showed an average dose 7.6% lower than water-based calculations. Comparisons with Plaque Simulator calculations showed large differences in dose to critical structures for 106 Ru notched plaques. 125 I cases presented significant and systematic dose deviations when using the default calculation parameters from Plaque Simulator version 5.3.8., which were corrected when using calculation parameters from a custom physics model for carrier-attenuation and air-interface correction functions. CONCLUSIONS: EyeMC is a MC calculation system for ophthalmic brachytherapy based on a realistic and customizable eye-tumor model which includes the main eye structures with their real composition. Integrating this tool into a cloud computing environment allows to perform high-precision MC calculations of ocular plaque treatments in short times. The observed variability in eye anatomy among the selected cases justifies the use of patient-specific models.

Proteomic profile of the effects of low-dose bisphenol A on zebrafish ovaries.

Human exposure to bisphenol-A (BPA) is largely unavoidable because BPA is an environmental contaminant found in soil, water, food and indoor dust. The safety of authorized BPA amounts in consumer products is under question because new studies have reported adverse effects of BPA at doses far below that previously established by the NOAEL (50 µg/kg per day). To protect public health, the consequences of low-dose BPA exposure in different organs and organismal functions must be further studied to generate relevant data. This study attempted to investigate the effects and potential molecular mechanisms of short-term exposure to 1 µg/L BPA on zebrafish ovarian follicular development. We observed only minor changes at the histopathological level with a small (3 %) increase in follicular atresia. However, a shotgun proteomics approach indicated deep alterations in BPA-exposed ovarian cells, including induction of the oxidative stress response, metabolic shifts and degradome perturbations, which could drive oocytes towards premature maturation. Based on these results, it could be suggested that inadvertent exposure to small concentrations of BPA on a continuous basis causes alteration in biological processes that are essential for healthy reproduction.

Immunohistochemical expression of aromatase cyp19a1a and cyp19a1b in the ovary and brain of zebrafish (Danio rerio) exposed to different concentrations of bisphenol A.

Bisphenol A (BPA) is used to produce plastic and plastic derived products in multitude of daily utensils, being one of the industrial compounds most widely used. This endocrine disrupting chemical (EDCs) is a well-known environmental pollutant released into the aquatic environment from industrial wastewater, sewage sludge or landfill leachate. Aromatases are considered potential targets of EDCs with characteristics that make them suitable biomarkers of exposure to their effects. The main objective of our study was to evaluate the expression of cyp19a aromatase as a toxicological endpoint after BPA exposure through the identification and assessment of alterations of the main cells responsible for cyp19a1a and cyp19a1b expression in the zebrafish ovary and brain using different concentrations of BPA in water. Immunohistochemistry was used to analyze the expression of these enzymes in female zebrafish exposed and not exposed to different concentrations of BPA (1, 10, 100 and 1000 µg / L) in water (n = 6/group) for 14 days. The results obtained in this study showed that the cyp19a aromatase system, involved in the synthesis of steroid compounds, is specially located in distinct oocyte stages in the ovary (cyp19a1a) and in radial glial cells of the brain (cyp19a1b). An overexpression of these aromatases was observed after BPA exposure in zebrafish, peaking from a concentration of 10 µg/L and showing to be good biomarkers of exposure to identify the early effects of low BPA concentrations. To our knowledge, this study is the first to localize and quantify the expression of cyp19a1a and cyp19a1b in the cells of brain and ovary after fish exposure to different BPA concentrations in water.

Promoting Mental Health in Healthcare Workers in Hospitals Through Psychological Group Support With Eye Movement Desensitization and Reprocessing During COVID-19 Pandemic: An Observational Study.

BACKGROUND: Psychological support was provided by the Eye Movement Desensitization and Reprocessing Integrative Group Treatment Protocol (EMDR-IGTP) within the hospitals in the Northern Italy in favor of healthcare workers during the COVID-19 pandemic. This study aimed at evaluating the effectiveness of treatment in terms of (a) symptomatology reduction related to peri- and post-traumatic stress; (b) clinical improvement over time; and (c) the maintenance of the achieved outcome over time. METHODS: The population was composed of healthcare workers who spontaneously requested psychological intervention in both the first and the second emergency waves. Statistical analyses were carried out to highlight the differences in Impact of Event-Revised (IES-R) and Post-Traumatic Growth Inventory (PTGI) before and after the group intervention. RESULTS: In both the first and the second waves, pre-treatment values are higher than post-treatment values for all dimensions of the IES-R. The results show that there are no significant differences between the first and the second wave with regard to the treatment effect. Healthcare workers maintained positive changes over time despite their prolonged exposure to an emergency and the possibility of retraumatization at the onset of a new emergency phase, irrespective of their working place. Healthcare workers who were treated in the first wave showed at the beginning of the second emergency wave less vulnerability and more resilience than those who were treated only in the second wave.Pre-treatment scores of healthcare workers affected by COVID-19 are discussed. CONCLUSION: COVID-19 had a significant impact on the well-being of healthcare workers who were working in hospitals. Psychological support in case of emergency is needed.

Integrated Programs for Early Recognition of Severe Mental Disorders: Recommendations From an Italian Multicenter Project.

The onset of mental disorders often occurs in adolescence or young adulthood, but the process of early diagnosis and access to timely effective and appropriate services can still be a challenge. The goal of this paper is to describe a pilot case of implementation of the ultra-high-risk (UHR) paradigm in six Italian departments of mental health employing an integrated approach to address clinical practice and service organization for youth in a broader preventive perspective. This approach entailed the integration of the UHR paradigm with a service provision model which prioritizes prevention and the promotion of local community coalitions to improve youth service accessibility. The multicenter Italian project "Integrated programs for recognition and early treatment of severe mental disorders in youths" funded by the National Centre for Disease Prevention and Control (CCM2013 Project) implemented in three Italian regions will be described. As a result of synergic actions targeting accessibility of young individuals to innovative youth mental health teams, a total of 376 subjects aged 15-24 years were recruited by integrated youth services within 12 months. Subjects have been screened by integrated multidisciplinary mental health youth teams employing standardized procedure and evidence-based clinical assessment instruments for at-risk mental states in young subjects [e.g., Comprehensive Assessment of At-Risk Mental States (CAARMS)]. Considering the three UHR categories included in CAARMS, the percentage of UHR subjects was 35% (n = 127) of the sample. In conclusion, future strategies to improve the organization of youth mental health services from a wider preventive perspective will be proposed.