Matteo Monzio Compagnoni

Background: Despite the societal impact of the COVID‐19 pandemic, research assessing changes in symptoms of anxiety and depression following the sanitary crisis has reported heterogeneous evidence, especially among individuals with pre‐existing mental health conditions. Most earlier studies used summary scores of depression or anxiety assessment surveys, which does not provide insights into changes in individual symptoms and symptom structure during the pandemic. Objective: This study used a network analysis to investigate the symptom structure of anxiety and depressive symptoms and temporal changes in symptoms across three timepoints before and during the COVID‐19 pandemic in a sample primarily of persons with anxiety and depressive disorders. Methods: Data are retrieved from 675 participants of the Netherlands Study of Depression and Anxiety (NESDA) and Netherlands Study of Depression in Older Persons (NESDO) cohorts who completed all three timepoints. Anxiety and depressive symptoms were assessed using the Beck anxiety inventory (BAI) and the Quick Inventory of Depressive Symptomatology–Self‐Rated (QIDS–SR). Symptom networks were estimated for three timepoints: pre‐COVID, first COVID‐peak (April 2020), second COVID‐peak (January/February 2021), and compared. Symptom importance was quantified using centrality indices (strength, betweenness, and closeness), and temporal stability was assessed using the network comparison test (NCT). Results: The symptom networks were largely consistent between the two COVID‐19 peak timepoints but differed significantly from the pre‐COVID network in terms of global strength. Fear‐related anxiety symptoms, sleep‐related symptoms, and thoughts of death or suicide demonstrated greater strength centrality at the pre‐COVID timepoint compared to both COVID‐19 peak timepoints. Conclusion: Our findings illustrate that a stressful situation, such as the COVID‐19 pandemic, can result in changes in the complex associations of anxiety and depressive symptoms. Unexpectedly, anxiety symptom networks shifted from being driven by somatic fear responses before the pandemic, toward greater prominence of cognitive appraisal symptoms during the pandemic. Network insights could help focus intervention planning by targeting the key symptoms of anxiety and depression.

Introduction: The care provided to patients with severe mental disorders remains a major challenge for the organization of healthcare systems. Data on recent treatment patterns within mental health services are essential to estimate the unmet needs for care and to guide service planning and resource allocation. Aim: To identify individual patient and organizational-level predictors of the provision of minimally adequate care for patients with severe mental illness. Methods: A population-based study was designed, retrieving data from Healthcare Utilization databases of Lombardy region (Italy). 72,115 patients from Departments of Mental Health (DMHs) in care for schizophrenic, bipolar or major depressive disorder, were identified. Minimally Adequate Treatment (MAT) was calculated as either minimum psychiatric visits (≥4) with pharmacological treatment (≥2 months) or psychotherapy sessions (≥8, for major depressive disorder only). Patients meeting these criteria were considered as having received MAT; others were classified as having received less than adequate treatment. Multilevel analyses were performed to estimate the association between patients' individual (e.g., age, sex, education, marital status) and DMHs' aggregate (i.e., organizational features, activity volume, staff employed in facilities providing MHC) characteristics and provision of MAT. Results: Overall, 45% of patients received MAT. Patients with increased probability of receiving MAT included married individuals (8%, 95% CI: 4%–12%), those with schizophrenia (11%, 95% CI: 9%–13%) or bipolar disorder (23%, 20%–25%), younger patients (22%, 20%–25%), and those with previous continuity of care (48%, 46%–51%). Differences in DMHs' structural features (e.g., number of day-treatment facilities, presence of multidisciplinary teams) contributed to heterogeneous MAT coverage. Moreover, the composition of psychiatric teams (in terms of hours worked by each category of healthcare professionals) and the number of affiliated facilities were associated with MAT delivery. Conclusions: This study ascertained that the quality of care offered to psychiatric patients is still low and not adequate. Administrative data can usefully contribute to identify both individual and organizational-level predictors of MAT provision, offering a valuable benchmark for managing organizational features of DMHs and for optimally allocating the working hours in multidisciplinary professional teams, with the goal of maximizing the provision of adequate mental healthcare.

Background: There is limited evidence on the association between psychiatric morbidity and COVID-19 mortality. Methods: We used deidentified electronic health records from the Catalan public health system to evaluate the association between number of mental disorders and COVID-19 mortality. Adults diagnosed with a mental disorder in Catalonia’s mental health services (from to 2017–2019) were compared to a matched (1:1) control group by sex, age, and area of residence. COVID-19 mortality risk was evaluated from February to December 2020. Odds ratios (OR) with 95% confidence intervals (CI) were estimated for the association between the number of mental disorders and COVID-19 mortality. To examine if different patterns of psychiatric comorbidity were related to COVID-19 death, we performed K-means cluster analysis on individuals with ≥2 disorders, stratified by COVID-19 death. Results: The final sample included 785,378 adults (392,689 with ≥1 mental disorder). Mortality risk increased with the number of mental disorders: OR 1.23 (95% CI: 1.11–1.35) for one mental disorder, up to 5.21 (95% CI: 1.34–20.27) for four or more. Cluster analysis (n=84,207) identified seven psychiatric comorbidity profiles among those who did not die of COVID-19, and six profiles among those who died, with substantial comparability between cohorts. Conclusion: An increasing number of psychiatric diagnoses was associated with greater COVID-19 mortality, while specific comorbidity patterns showed limited differential influence. This suggests that it is not the specific combination of mental disorders that influences COVID-19 death outcomes, but rather the overall burden of multiple diagnoses.

Few studies have examined the implications of the Covid-19 pandemic on mental health across different employment branches. This study investigated the impact of the pandemic on long-term sickness absence (SA) with common mental disorders (CMDs) and antidepressant prescriptions in different employment branches and age groups in Sweden. Using national registers, we observed the Swedish population (18–65 years) with gainful employment quarterly from 2018 to 2021. An interrupted time-series design was employed to examine changes in trends of incidence rates (IRs) for (i) long-term (>90 days) SA with CMDs and for (ii) antidepressant prescriptions across eight employment branches during versus pre-pandemic. Analyses were stratified by age group. There was no evidence of outcome changes in the entire working age population. However, compared to pre-pandemic levels, the IRs of long-term SA with CMD increased by 5.9% per quarter for those working in the cultural sector [95% confidence interval (CI): 2.2%–9.8%], 3.4% in trade and transportation (95% CI: 0.4%–6.4%), and 5.5% in manufacturing and services (95% CI: 1.5%–9.7%) as well as among individuals aged 56–64. Incident antidepressant prescription rates were marginally higher for workers in construction (1.1% annual increase; 95% CI: 0.1%–2.1%), culture (1.4%; 0.7%–2.0%), and trade and transportation (0.9%; 0.1%–1.7%). While the risk of CMD-related long-term SA or incident antidepressant prescription in Swedish workers did not appear to be impacted by the pandemic, certain employment branches and older individuals were negatively affected in terms of both outcomes. Targeted countermeasures and initiatives to improve well-being are necessary for vulnerable groups.

Background: This study aims to understand the relationship between the experience of psychological distress and compliance with COVID-19 sanitary measures. We testeed whether this relationship was modified by individuals’ gender and socioeconomic status (i.e., educational level and employment). Methods: Data from four European cohort studies (n = 13,635), were analysed using an Individual Participant Data (IPD) meta-analytic approach. Mixed effect models were employed to examine associations between mental health difficulties and compliance with sanitary measures, as well as effect modification by socioeconomic status. Statistical models were stratified by gender. Results: We found a statistically significant association between mental health difficulties and increased compliance with sanitary measures in women, while amongst men the statistically significant association observed was opposite. Moreover, there was a statistically significant interaction between participants’ educational level and mental health difficulties amongst men only, indicating especially low compliance levels with COVID-19 sanitary measures amongst individuals with only primary schooling and who reported psychological distress. Conclusion: The association between psychological distress and compliance with sanitary measures is complex–positive in women, negative in men. Men experiencing mental health difficulties, especially those with lower educational attainment, exhibit low levels of compliance with sanitary measures. These results suggest that psychological distress and its possible consequences should be considered when designing measures addressing infectious disease spread.

Background: Differences in survival between patients treated with antipsychotic monotherapy vs. polytherapy are debated. This study aimed to examine the association of antipsychotic polytherapy with 2-year all-cause mortality in a population-based cohort. Methods: Data were retrieved from healthcare databases of four local health units of Lombardy, Italy. Subjects aged 18–79 years who received continuous antipsychotic prescriptions in 2018 were identified. Overall survival among patients with antipsychotic monotherapy vs. polytherapy was compared. A multivariate Cox PH model was used to estimate the association between antipsychotic therapy, or antipsychotic use (continuous vs. non-continuous), and all-cause mortality. Adjustments were made for the presence of metabolic disturbances, total antipsychotic dosage amount (olanzapine equivalent doses), age, and sex. Results: A total of 49,875 subjects receiving at least one prescription of antipsychotics during 2018 were identified. Among the 33,221 patients receiving continuative antipsychotic prescriptions, 1958 (5.9%) experienced death from any cause at two years. Patients with continuous antipsychotic use had a 1.13-point increased mortality risk compared with non-continuous users. Patients treated with antipsychotic polytherapy showed an adjusted mortality risk increased by 17% (95% CI: 2%, 33%) compared to monotherapy. Conclusions: The study highlights the potential risks associated with antipsychotic polypharmacy, emphasizing the importance of optimizing drug prescriptions to improve patient safety and reduce mortality rates in individuals receiving antipsychotic therapy.

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.

Introduction: Asthma is one of the most common diseases in children, with a variable range of severity. In recent years, treatment for severe asthma has been largely improved by the availability of targeted biologic therapies. Nevertheless, studies reporting real‐world data and cost‐effectiveness analyses are lacking. The aim of this study was to evaluate, on a population‐based cohort of children with asthma, the impact of the treatment with biologics on healthcare service utilization and associated costs.Methods: Data were retrieved from Healthcare Utilization database of Lombardy region (Italy). A cohort of 46 asthmatic children aged 6–11 in treatment with dupilumab, mepolizumab or omalizumab was identified during 2017–2021. We compared healthcare resources use between the year before (“baseline period”) and the year after the treatment initiation (“follow‐up period”). Average 1‐year healthcare costs were also calculated.Results: Comparing the baseline with the follow‐up period, the number of patients with at least one exacerbation‐related hospitalization and ER access decreased by 75.0% and 85.7%, respectively. The use of biologic agents, namely omalizumab, mepolizumab and dupilumab, significantly reduced oral corticosteroids (OCS), short‐acting β2‐agonists and the association inhaled corticosteroids/long‐acting β2‐agonists use. ER admissions for non‐respiratory causes were also significantly reduced, while discontinuation rate was low (6.5%). The overall costs increased, due to the costs of the biologic agents, but the hospital admission‐related costs due to respiratory causes reduced significantly.Conclusions: Our real‐world investigation suggests that biologic agents reduced hospital admissions for respiratory causes and use of anti‐asthmatic drugs, including OCS. However, long‐term healthcare sustainability still needs more in‐depth assessments.

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.