Analysis and clinical determinants of post-COVID-19 syndrome in the Lombardy region: evidence from a longitudinal cohort study.

OBJECTIVE: To define macro symptoms of long COVID and to identify predictive factors, with the aim of preventing the development of the long COVID syndrome. DESIGN: A single-centre longitudinal prospective cohort study conducted from May 2020 to October 2022. SETTING: The study was conducted at Luigi Sacco University Hospital in Milan (Italy). In May 2020, we activated the ARCOVID (Ambulatorio Rivalutazione COVID) outpatient service for the follow-up of long COVID. PARTICIPANTS: Hospitalised and non-hospitalised patients previously affected by COVID-19 were either referred by specialists or general practitioners or self-referred. INTERVENTION: During the first visit, a set of questions investigated the presence and the duration of 11 symptoms (palpitations, amnesia, headache, anxiety/panic, insomnia, loss of smell, loss of taste, dyspnoea, asthenia, myalgia and telogen effluvium). The follow-up has continued until the present time, by sending email questionnaires every 3 months to monitor symptoms and health-related quality of life. PRIMARY AND SECONDARY OUTCOME MEASURES: Measurement of synthetic scores (aggregation of symptoms based on occurrence and duration) that may reveal the presence of long COVID in different clinical macro symptoms. To this end, a mixed supervised and empirical strategy was adopted. Moreover, we aimed to identify predictive factors for post-COVID-19 macro symptoms. RESULTS: In the first and second waves of COVID-19, 575 and 793 patients (respectively) were enrolled. Three different post-COVID-19 macro symptoms (neurological, sensorial and physical) were identified. We found significant associations between post-COVID-19 symptoms and (1) the patients' comorbidities, and (2) the medications used during the COVID-19 acute phase. ACE inhibitors (OR=2.039, 95% CI: 1.095 to 3.892), inhaled steroids (OR=4.08, 95% CI: 1.17 to 19.19) and COVID therapies were associated with increased incidence of the neurological macro symptoms. Age (OR=1.02, 95% CI: 1.01 to 1.04), COVID-19 severity (OR=0.42, 95% CI: 0.21 to 0.82), number of comorbidities (OR=1.22, 95% CI: 1.01 to 1.5), metabolic (OR=2.52, 95% CI: 1.25 to 5.27), pulmonary (OR=1.87, 95% CI: 1.10 to 3.32) and autoimmune diseases (OR=4.57, 95% CI: 1.57 to 19.41) increased the risk of the physical macro symptoms. CONCLUSIONS: Being male was the unique protective factor in both waves. Other factors reflected different medical behaviours and the impact of comorbidities. Evidence of the effect of therapies adds valuable information that may drive future medical choices.

The effect of differently modulated communications on the covid-19 pandemic in the young population.

BACKGROUND: Media communication during the covid-19 pandemic has been relevant for the population to receive information about the ongoing number of cases, deaths, and social restriction measures. Notably, the effects of the communication methods on young adults during the covid-19 pandemic have not been studied. Therefore the present study aimed to investigate the influence of communication modality about covid-19 on the perception of risk and judgment among young adults. METHODS: A double-blind cross-sectional study was designed. Three hundred four subjects (age range19-25 years old) saw a 4-minute video concerning data communication on the covid-19 pandemic and compiled an online questionnaire about their perceptions. Two videos were randomized, one presenting the covid-19 data negatively (HARD video) while the other showed a positive ongoing resolution of the pandemic (SOFT video). Association tests and nominal logistic regression were used to evaluate differences in responses among the two groups. RESULTS: The two videos lead to different reactions. Participants showed higher disagreement concerning the video content in the "SOFT" group compared to the "HARD" group. The responses of the "SOFT" group were more to be optimistic (OR=2.87, 95% CI 1.311-6.27) than those who had seen the "HARD" video. The sense of helplessness was lower in the "SOFT" compared "HARD" group (OR=3.02, 95% CI 1.311-6.96). The perception of fear was higher for the "HARD" group (OR=2.91, 95% CI 1.21-7-02). DISCUSSION: The modality of data presentation influenced the perception and feelings about the covid-19 pandemic. Likely, pre-existing perception of a pessimistic perspective was present in both groups; thus, the video did not lead to any change in the behavior. CONCLUSIONS: The phobic or counter-phobic reactions shown in the study participants highlighted the importance of the reliability of the information received and how previous feelings may influence the perception of the information.

Surfactant protein D (SP-D) as a biomarker of SARS-CoV-2 infection.

BACKGROUND: Surfactant protein-D (SP-D) is a lung-resident protein that has emerged as a potential biomarker for COVID-19. Previous investigations on acute respiratory distress syndrome patients demonstrated a significant increment of SP-D serum levels in pathological conditions. Since SP-D is not physiologically permeable to alveoli-capillary membrane and poorly expressed by other tissues, this enhancement is likely due to an impairment of the pulmonary barrier caused by prolonged inflammation. METHODS: A retrospective study on a relatively large cohort of patients of Hospital Pio XI of Desio was conducted to assess differences of the hematic SP-D concentrations among COVID-19 patients and healthy donors and if SP-D levels resulted a risk factor for disease severity and mortality. RESULTS: The first analysis, using an ANOVA-model, showed a significant difference in the mean of log SP-D levels between COVID-19 patients and healthy donors. Significant variations were also found between dead vs survived patients. Results confirm that SP-D concentrations were significantly higher for both hospitalized COVID-19 and dead patients, with threshold values of 150 and 250 ng/mL, respectively. Further analysis conducted with Logistic Mixed models, highlighted that higher SP-D levels at admission and increasing differences among follow-up and admission values resulted the strongest significant risk factors of mortality (model predictive accuracy, AUC = 0.844). CONCLUSIONS: The results indicate that SP-D can be a predictive marker of COVID-19 disease and its outcome. Considering its prognostic value in terms of mortality, the early detection of SP-D levels and its follow-up in hospitalized patients should be considered to direct the therapeutic intervention.

The impact of COVID-19 pandemic on AMI and stroke mortality in Lombardy: Evidence from the epicenter of the pandemic.

BACKGROUND: The first Covid-19 epidemic outbreak has enormously impacted the delivery of clinical healthcare and hospital management practices in most of the hospitals around the world. In this context, it is important to assess whether the clinical management of non-Covid patients has not been compromised. Among non-Covid cases, patients with Acute Myocardial Infarction (AMI) and stroke need non-deferrable emergency care and are the natural candidates to be studied. Preliminary evidence suggests that the time from onset of symptoms to emergency department (ED) presentation has significantly increased in Covid-19 times as well as the 30-day mortality and in-hospital mortality. METHODS: We check, in a causal inference framework, the causal effect of the hospital's stress generated by Covid-19 pandemic on in-hospital mortality rates (primary end-point of the study) of AMI and stroke over several time-windows of 15-days around the implementation date of the State of Emergency restrictions for COVID-19 (March, 9th 2020) using two quasi-experimental approaches, regression-discontinuity design (RDD) and difference-in-regression-discontinuity (DRD) designs. Data are drawn from Spedali Civili of Brescia, one of the most hit provinces in Italy by Covid-19 during March and May 2020. FINDINGS: Despite the potential adverse effects on expected mortality due to a longer time to hospitalization and staff extra-burden generated by the first wave of Covid-19, the AMI and stroke mortality rates are overall not statistically different during the first wave of Covid-19 than before the first peak. The obtained results provided by RDD models are robust also when we account for seasonality and unobserved factors with DRD models. INTERPRETATION: The non-statistically significant impact on mortality rates for AMI and stroke patients provides evidence of the hospital ability to manage -with the implementation of a dual track organization- the simultaneous delivery of high-quality cares to both Covid and non-Covid patients.

Determinants of transient and persistent hospital efficiency: The case of Italy.

In this paper, we extend the 4-random-component closed skew-normal stochastic frontier model by including exogenous determinants of hospital persistent (long-run) and transient (short-run) inefficiency, separated from unobserved heterogeneity. We apply this new model to a dataset composed by 133 Italian hospitals during the period 2008-2013. We show that average total inefficiency is about 23%, higher than previous estimates; hence, a model where the different types of inefficiency and hospital unobserved characteristics are not confounded allows us to get less biased estimates of hospital inefficiency. Moreover, we find that transient efficiency is more important than persistent efficiency, as it accounts for 60% of the total one. Last, we find that ownership (for-profit hospitals are more transiently inefficient and less persistently inefficient than not-for-profit ones, whereas public hospitals are less transiently inefficient than not-for-profit ones), specialization (specialized hospitals are more transiently inefficient than general ones; i.e., there is evidence of scope economies in short-run efficiency), and size (large-sized hospitals are better than medium and small ones in terms of transient inefficiency) are determinants of both types of inefficiency, although we do not find any statistically significant effect of multihospital systems and teaching hospitals.

Psychotropic Drug Consumption and Employment Status in Time of Economic Crisis (2007-2011).

Psychiatric disorders and in particular depression have increased during the "Great Recession". The aim of this study was to investigate the consumption of psychotropic drugs in people who lost their permanent employment, using administrative data. The study considered all of the subjects domiciled in Lombardy, Northern Italy, who lost a permanent employment between 2008 and 2010, not assuming psychotropic drugs and who did not find a new job within the following 12 months. The control group included people who did not lose permanent job in the study period, matched to the cases for gender, age, nationality, skill level, education and economic sector, using propensity score matching. The subjects who lost their permanent employment were 17 % more likely to receive one or more drug prescriptions than the controls, but the difference was significant only for males. Females, subjects aged >50 years, low skill level workers and Italians were more likely to have received a prescription for psychotropic drugs than respectively males, subjects aged 20-29 years or aged 30-39 years, low skill level workers and non-Italians. The average number of drugs prescribed for those who lost their job and those who continued working was respectively 2.9 and 3.1. In conclusion, losing a permanent job increases significantly psychotropic drugs consumption in males but not in females.

EPMA position paper in cancer: current overview and future perspectives.

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision.

Use of psychotropic drugs in Lombardy in time of economic crisis (2007-2011): a population-based study of adult employees.

Over years, there has been an increase in the prescription of psychotropic drugs (PDs), particularly antidepressants (ADs). The aim of the study was to evaluate the consumption of PDs in adult employees in a productive area of Italy and the possible changes induced by the "economic crisis". The study is a retrospective survey in all adult employees in Lombardy, Northern Italy, aged >18 years in the period 2007-2011, classified by gender, age class, nationality, education and province. During the 5-year period, there were 3,554,860 employed adults in Lombardy, of whom 277,865 (7.8%) used PDs. The use of PDs (particularly ADs) was associated with being an Italian woman aged >55 years with a basic education, a blue collar job, and an unstable working position. In 39% of cases, the use of PDs was limited to one trimester. The increase in the number of prescriptions of PDs after the economic crisis was the same as before it. The increase in PD use can be attributed more to ADs and anti-epileptic drugs with anxiolytic properties. Although continuously increasing, the use of AD fluctuated and was greater during the fall and winter. The increase involved all the provinces in Lombardy in a similar manner.

Structural Equation Models in a Redundancy Analysis Framework With Covariates.

A recent method to specify and fit structural equation modeling in the Redundancy Analysis framework based on so-called Extended Redundancy Analysis (ERA) has been proposed in the literature. In this approach, the relationships between the observed exogenous variables and the observed endogenous variables are moderated by the presence of unobservable composites, estimated as linear combinations of exogenous variables. However, in the presence of direct effects linking exogenous and endogenous variables, or concomitant indicators, the composite scores are estimated by ignoring the presence of the specified direct effects. To fit structural equation models, we propose a new specification and estimation method, called Generalized Redundancy Analysis (GRA), allowing us to specify and fit a variety of relationships among composites, endogenous variables, and external covariates. The proposed methodology extends the ERA method, using a more suitable specification and estimation algorithm, by allowing for covariates that affect endogenous indicators indirectly through the composites and/or directly. To illustrate the advantages of GRA over ERA we propose a simulation study of small samples. Moreover, we propose an application aimed at estimating the impact of formal human capital on the initial earnings of graduates of an Italian university, utilizing a structural model consistent with well-established economic theory.

The effectiveness-efficiency trade-off in health care: The case of hospitals in Lombardy, Italy.

We study the presence and the magnitudes of trade-offs between health outcomes and hospitals' efficiency using a data set from Lombardy, Italy, for the period 2008-2011. Our goal is to analyze whether the pressures for cost containment may affect hospital performance in terms of population health status. Unlike previous work in this area, we analyze hospitals at the ward level so comparisons can be made across more homogeneous treatments. We focus on two different health outcomes: mortality and readmission rates. We find that there is a trade-off between mortality rates and efficiency, as more efficient hospitals have higher mortality rates. We also find, however, that more efficient hospitals have lower readmission rates. Moreover, we show that focusing the analysis at the ward level is essential, since there is evidence of higher mortality rates in general medicine and surgery, while in oncology mortality is lower in more efficient hospitals. Furthermore, we find that consideration of spatial processes is important since mortality rates are higher for hospitals subject to high degree of horizontal competition, but lower for those hospitals having strong competition but high efficiency. This implies that the interplay of efficient resource allocation and hospital competition is important for the sustainability and effectiveness of regional health care systems.

Comparing health outcomes among hospitals: the experience of the Lombardy Region.

In recent years, governments and other stakeholders have increasingly used administrative data for measuring healthcare outcomes and building rankings of health care providers. However, the accuracy of such data sources has often been questioned. Starting in 2002, the Lombardy (Italy) regional administration began monitoring hospital care effectiveness on administrative databases using seven outcome measures related to mortality and readmissions. The present study describes the use of benchmarking results of risk-standardized mortality from Lombardy regional hospitals. The data usage is part of a general program of continuous improvement directed to health care service and organizational learning, rather than at penalizing or rewarding hospitals. In particular, hierarchical regression analyses - taking into account mortality variation across hospitals - were conducted separately for each of the most relevant clinical disciplines. Overall mortality was used as the outcome variable and the mix of the hospitals' output was taken into account by means of Diagnosis Related Group data, while also adjusting for both patient and hospital characteristics. Yearly adjusted mortality rates for each hospital were translated into a reporting tool that indicates to healthcare managers at a glance, in a user-friendly and non-threatening format, underachieving and over-performing hospitals. Even considering that benchmarking on risk-adjusted outcomes tend to elicit contrasting public opinions and diverging policymaking, we show that repeated outcome measurements and the development and dissemination of organizational best practices have promoted in Lombardy region implementation of outcome measures in healthcare management and stimulated interest and involvement of healthcare stakeholders.

New evidence in health economics.

The 2nd Health Econometrics Workshop took place at the Catholic University of Rome in Italy on 15-17 July 2010. The purpose of this meeting was to provide a forum where policy makers, economists and econometricians could discuss the use of statistical and econometric methods to address issues in the field of health economics. There were seven keynote speakers - leading scholars in the subject - invited to give their contributions: Alberto Holly, Stephen Hall, Badi Baltagi, William Greene, Andrew Jones, John Mullahy and Edward Norton. The meeting was attended by 50 participants from around the world, and 17 scientific papers were presented. Some of these works will be published in the forthcoming special issue of Empirical Economics.

Does community care work? A model to evaluate the effectiveness of mental health services.

The aim of this paper is to evaluate the effectiveness of community Mental Health Departments in Lombardy (Italy), and analyse the eventual differences in outcome produced by different packages of care. The survey was conducted in 2000 on 4,712 patients treated in ten Mental Health Departments. Patients were assessed at least twice in a year with HoNOS (Health of the Nation Outcome Scales). Data on treatment packages were drawn from the regional mental health information system, which includes all outpatient and day-care contacts, as well as general hospital and inpatient admissions provided by Mental Health Departments. Multilevel growth models were used for outcomes statistical analysis, expressed in terms of change of the total HoNOS score. On the whole, Mental Health Departments were effective in reducing HoNOS scores. The main predictor of improvement was treatment, while length of care, gender and diagnosis were weaker predictors. After severity adjustment, some packages of care proved more effective than others. Appropriate statistical methods, comprehensive treatment descriptions and routine outcome assessment tools are needed to evaluate the effectiveness of community mental health services in clinical settings.