Adherence to GLP1-RA and SGLT2-I affects clinical outcomes and costs in patients with type 2 diabetes.

AIMS: To evaluate the impact of adherence to glucagon like peptide-1 receptor agonists (GLP1-RA) and sodium-glucose transporter two inhibitors (SGLT2-I) on clinical outcomes and costs in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: The 121,115 residents of the Lombardy Region (Italy) aged ≥40 years newly treated with metformin during 2007-2015 were followed to identify those who started therapy with GLP1-RA or SGLT2-I. Adherence to drug therapy over the first year was defined as the proportion of days covered >80%. Within each drug class, for each adherent patient, one non-adherent patient was matched for age, sex, duration, adherence to metformin treatment and propensity score. The primary clinical outcome was a composite of insulin initiation, hospitalisation for micro- and macrovascular complications and all-cause mortality after the first year of drug treatment. Costs were evaluated based on reimbursements from the national healthcare system. RESULTS: After matching, 1182 pairs of adherent and non-adherent GLP1-RA users and 1126 pairs of adherent and non-adherent SGLT2-I users were included. In both groups, adherent patients experienced a significantly lower incidence of the primary outcome (HR: 0.85, 95% CI 0.72-0.98 for GLP1-RA and HR: 0.69, 95% CI 0.55-0.87 for SGLT2-I). A significant reduction in hospitalizations was found for adherent patients in the GLP1-RA group but not for the SGLT2-I group. Results were consistent when analyses were stratified by age and sex. While higher drug-related costs in the adherent group were counterbalanced by decreased hospitalisation costs in SGLT2-I treated patients, this was not the case for GLP1-RA. CONCLUSIONS: Higher adherence to drug treatment with GLP1-RA and SGLT2-I during the first year of the drug intake is associated with a lower incidence of adverse clinical outcomes in a real-world setting.

Dose-response association between cigarette smoking and gastric cancer risk: a systematic review and meta-analysis.

This study aims at providing an accurate and up-to-date quantification of the dose-response association between cigarette smoking and gastric cancer (GC) risk, overall and by subsite. We conducted a systematic review and meta-analysis of case-control and cohort studies on the association between cigarette smoking and GC risk published up to January 2023. We estimated pooled relative risks (RR) of GC and its subsites according to smoking status, intensity, duration, and time since quitting. Among 271 eligible articles, 205 original studies were included in this meta-analysis. Compared with never smokers, the pooled RR for GC was 1.53 (95% confidence interval; CI 1.44-1.62; n = 92) for current and 1.30 (95% CI 1.23-1.37; n = 82) for former smokers. The RR for current compared with never smokers was 2.08 (95% CI 1.66-2.61; n = 21) for gastric cardia and 1.48 (95% CI 1.33-1.66; n = 8) for distal stomach cancer. GC risk nonlinearly increased with smoking intensity up to 20 cigarettes/day (RR:1.69; 95% CI 1.55-1.84) and levelled thereafter. GC risk significantly increased linearly with increasing smoking duration (RR: 1.31; 95% CI 1.25-1.37 for 20 years) and significantly decreased linearly with increasing time since quitting (RR: 0.65; 95% CI 0.44-0.95 for 30 years since cessation). The present meta-analysis confirms that cigarette smoking is an independent risk factor for GC, particularly for gastric cardia. GC risk increases with a low number of cigarettes up to 20 cigarettes/day and increases in a dose-dependent manner with smoking duration.

Probability of second live birth after first natural and medically assisted reproduction-mediated live birth: A historical cohort study.

INTRODUCTION: Evidence on the role of medically assisted reproduction (MAR) in achieving the desired number of children is very limited. The aim of the current investigation was to assess the probability and the mode of conception of a second live birth according to the mode of conception of the first one. MATERIAL AND METHODS: This historical cohort study was based on administrative data from regional healthcare databases. Women hospitalized for childbirth in Lombardy between January 1, 2007 and December 31, 2017 were identified. The probability of a second live birth up to 2021 was estimated using the Kaplan-Meier method. We calculated this probability according to the mode of conception of the first birth, and the analysis was also performed in strata of maternal age at first birth. Cox proportional hazards models were fitted to estimate the hazard ratio (HR) and 95% confidence interval (CI) of the association between mode of conception at first live birth and the probability of having a second live birth. Mothers were right-censored if they moved out of the region, died, or did not have a second live birth by the end of follow-up. RESULTS: We identified 431 333 women who had their first live birth after a natural conception and 16 837 who had their first live birth after MAR. The probability of having a second live birth was 58.6% and 32.1%, respectively in the two groups (HR = 0.68, 95% CI: 0.66-0.70). Considering solely women who naturally conceived their first live birth, the probability to have a second child with MAR was 1.1% and to have a second child naturally 59.3%. The corresponding values were 11.5% and 25.2% in the group of women with a first MAR-mediated live birth. CONCLUSIONS: In our cohort, one woman out of 10 having a first MAR-mediated live birth underwent MAR programs again. Considering women who had a first natural live birth, this proportion was drastically reduced. In the field of MAR, more attention should be given to the capacity of a couple to achieve the number of desired children.

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.

Renin-Angiotensin-Aldosterone System Blockers and the Risk of Covid-19.

BACKGROUND: A potential association between the use of angiotensin-receptor blockers (ARBs) and angiotensin-converting-enzyme (ACE) inhibitors and the risk of coronavirus disease 2019 (Covid-19) has not been well studied. METHODS: We carried out a population-based case-control study in the Lombardy region of Italy. A total of 6272 case patients in whom infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was confirmed between February 21 and March 11, 2020, were matched to 30,759 beneficiaries of the Regional Health Service (controls) according to sex, age, and municipality of residence. Information about the use of selected drugs and patients' clinical profiles was obtained from regional databases of health care use. Odds ratios and 95% confidence intervals for associations between drugs and infection, with adjustment for confounders, were estimated by means of logistic regression. RESULTS: Among both case patients and controls, the mean (±SD) age was 68±13 years, and 37% were women. The use of ACE inhibitors and ARBs was more common among case patients than among controls, as was the use of other antihypertensive and non-antihypertensive drugs, and case patients had a worse clinical profile. Use of ARBs or ACE inhibitors did not show any association with Covid-19 among case patients overall (adjusted odds ratio, 0.95 [95% confidence interval {CI}, 0.86 to 1.05] for ARBs and 0.96 [95% CI, 0.87 to 1.07] for ACE inhibitors) or among patients who had a severe or fatal course of the disease (adjusted odds ratio, 0.83 [95% CI, 0.63 to 1.10] for ARBs and 0.91 [95% CI, 0.69 to 1.21] for ACE inhibitors), and no association between these variables was found according to sex. CONCLUSIONS: In this large, population-based study, the use of ACE inhibitors and ARBs was more frequent among patients with Covid-19 than among controls because of their higher prevalence of cardiovascular disease. However, there was no evidence that ACE inhibitors or ARBs affected the risk of COVID-19.

Clinical relevance of clonal hematopoiesis in persons aged ≥80 years.

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with increased risk of cancers and inflammation-related diseases. This phenomenon becomes common in persons aged ≥80 years, in whom the implications of CHIP are not well defined. We performed a mutational screening in 1794 persons aged ≥80 years and investigated the relationships between CHIP and associated pathologies. Mutations were observed in one-third of persons aged ≥80 years and were associated with reduced survival. Mutations in JAK2 and splicing genes, multiple mutations (DNMT3A, TET2, and ASXL1 with additional genetic lesions), and variant allele frequency ≥0.096 had positive predictive value for myeloid neoplasms. Combining mutation profiles with abnormalities in red blood cell indices improved the ability of myeloid neoplasm prediction. On this basis, we defined a predictive model that identifies 3 risk groups with different probabilities of developing myeloid neoplasms. Mutations in DNMT3A, TET2, ASXL1, or JAK2 were associated with coronary heart disease and rheumatoid arthritis. Cytopenia was common in persons aged ≥80 years, with the underlying cause remaining unexplained in 30% of cases. Among individuals with unexplained cytopenia, the presence of highly specific mutation patterns was associated with myelodysplastic-like phenotype and a probability of survival comparable to that of myeloid neoplasms. Accordingly, 7.5% of subjects aged ≥80 years with cytopenia had presumptive evidence of myeloid neoplasm. In summary, specific mutational patterns define different risk of developing myeloid neoplasms vs inflammatory-associated diseases in persons aged ≥80 years. In individuals with unexplained cytopenia, mutational status may identify those subjects with presumptive evidence of myeloid neoplasms.

Adherence to antidiabetic drug therapy and reduction of fatal events in elderly frail patients.

BACKGROUND: To evaluate the protective effect of oral antidiabetic drugs in a large cohort of elderly patients with type 2 diabetes differing for age, clinical status, and life expectancy, including patients with multiple comorbidities and short survival. METHODS: A nested case-control study was carried out by including the cohort of 188,983 patients from Lombardy (Italy), aged ≥ 65 years, who received ≥ 3 consecutive prescriptions of antidiabetic agents (mostly metformin and other older conventional agents) during 2012. Cases were the 49,201 patients who died for any cause during follow-up (up to 2018). A control was randomly selected for each case. Adherence to drug therapy was measured by considering the proportion of days of the follow-up covered by the drug prescriptions. Conditional logistic regression was used to model the risk of outcome associated with adherence to antidiabetic drugs. The analysis was stratified according to four categories of the clinical status (good, intermediate, poor, and very poor) differing for life expectancy. RESULTS: There was a steep increase in comorbidities and a marked reduction of the 6-year survival from the very good to the very poor (or frail) clinical category. Progressive increase in adherence to treatment was associated with a progressive decrease in the risk of all-cause mortality in all clinical categories and at all ages (65-74, 75-84 and ≥ 85 years) except for the frail patient subgroup aged ≥ 85 years. The mortality reduction from lowest to highest adherence level showed a tendency to be lower in frail patients compared to the other categories. Similar although less consistent results were obtained for cardiovascular mortality. CONCLUSIONS: In elderly diabetic patients, increased adherence to antidiabetic drugs is associated with a reduction in the risk of mortality regardless of the patients' clinical status and age, with the exception of very old patients (age ≥ 85 years) in the very poor or frail clinical category. However, in the frail patient category the benefit of treatment appears to be less than in patients in good clinical conditions.

Effectiveness and economic impact of Dupilumab in asthma: a population-based cohort study.

RATIONALE: Severe asthma is burdened by relevant socio-economic and clinical impact. Randomized controlled trials on Dupilumab showed efficacy and a good safety profile, but post-market studies are needed. OBJECTIVES: To evaluate the impact of Dupilumab on (i) the use of anti-asthmatic drugs, including oral corticosteroids (OCS), (ii) the rates of asthma exacerbation-related hospital admissions, and (iii) the healthcare costs in patients with asthma. METHODS: Data were retrieved from Healthcare Utilization database of Lombardy region (Italy). We compared healthcare resources use between the 6 months after Dupilumab initiation ("post-intervention period") and (i) the 6 months before Dupilumab initiation ("wash-out period") and (ii) the corresponding 6 months of the prior year ("pre-intervention period"). MAIN RESULTS: In a cohort of 176 patients, Dupilumab significantly reduced anti-asthmatic drugs use (including OCS and short-acting ß2-agonists, inhaled corticosteroids (ICS)/long-acting ß2-agonists and ICS alone) when comparing the "pre-intervention" to the "post-intervention" period. When considering hospital admissions, we observed a not statistically or marginally significant reduction between both periods before Dupilumab and the post-intervention period. Six-months discontinuation rate was 8%. Overall healthcare costs had a tenfold increase between the "pre-intervention" and "post-intervention" period, which was mainly led by the biologic drug cost. Conversely, expenditures connected to hospital admissions did not change. CONCLUSIONS: Our real-world investigation suggests that Dupilumab reduced anti-asthmatic drugs use, including OCS, in comparison to a corresponding period in the prior year. However, long-term healthcare sustainability remains an open issue.

Coping with COVID: risk and resilience factors for mental health in a German representative panel study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic might affect mental health. Data from population-representative panel surveys with multiple waves including pre-COVID data investigating risk and protective factors are still rare. METHODS: In a stratified random sample of the German household population (n = 6684), we conducted survey-weighted multiple linear regressions to determine the association of various psychological risk and protective factors assessed between 2015 and 2020 with changes in psychological distress [(PD; measured via Patient Health Questionnaire for Depression and Anxiety (PHQ-4)] from pre-pandemic (average of 2016 and 2019) to peri-pandemic (both 2020 and 2021) time points. Control analyses on PD change between two pre-pandemic time points (2016 and 2019) were conducted. Regularized regressions were computed to inform on which factors were statistically most influential in the multicollinear setting. RESULTS: PHQ-4 scores in 2020 (M = 2.45) and 2021 (M = 2.21) were elevated compared to 2019 (M = 1.79). Several risk factors (catastrophizing, neuroticism, and asking for instrumental support) and protective factors (perceived stress recovery, positive reappraisal, and optimism) were identified for the peri-pandemic outcomes. Control analyses revealed that in pre-pandemic times, neuroticism and optimism were predominantly related to PD changes. Regularized regression mostly confirmed the results and highlighted perceived stress recovery as most consistent influential protective factor across peri-pandemic outcomes. CONCLUSIONS: We identified several psychological risk and protective factors related to PD outcomes during the COVID-19 pandemic. A comparison of pre-pandemic data stresses the relevance of longitudinal assessments to potentially reconcile contradictory findings. Implications and suggestions for targeted prevention and intervention programs during highly stressful times such as pandemics are discussed.

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.

Prevalence and Factors Associated With Intertwin Birth Weight Discordance Among Same-Sex Twins in Lombardy, Northern Italy.

This population-based cohort study investigated the prevalence, potential risk factors, and consequences of birth weight discordance (BWD) among same-sex twins. We retrieved data from the automated system of healthcare utilization databases of Lombardy Region, Northern Italy (2007-2021). BWD was defined as 30% or more disparity in birth weights between the larger and the smaller twin. Multivariate logistic regression was used to analyze the risk factors of BWD in deliveries with same-sex twins. In addition, the distribution of several neonatal outcomes was assessed overall and according to BWD level (i.e., ≤20%, 21-29, and ≥30%). Finally, a stratified analysis by BWD was performed to assess the relationship between assisted reproductive technologies (ART) and neonatal outcomes. We identified 11,096 same-sex twin deliveries; 556 (5.0%) pairs of twins were affected by BWD. Multivariate logistic regression analysis showed that maternal age ≥35 years (OR 1.26, 95% CI [1.05,5.51]), low level of education (OR 1.34, 95% CI [1.05, 1.70]), and ART (OR 1.16, 95% CI [0.94, 1.44], almost significant due to the low power) were independent risk factors for BWD in same-sex twins. Conversely, parity (OR 0.73, 95% CI [0.60, 0.89]) was inversely related. All the adverse outcomes observed were more common among BWD pairs than non-BWD ones. Instead, a protective effect of ART was observed for most neonatal outcomes considered among BWD twins. Our results suggest that conception after ART increases the risk of developing a high disparity between the weights of the two twins. However, the presence of BWD may complicate twin pregnancies, compromising neonatal outcomes, regardless of the modality of conception.

Spontaneous and induced abortions in women with a diagnosis of gestational related neoplasm: a population-based linkage study in Lombardy, 2010-2020.

BACKGROUND: A diagnosis of cancer during pregnancy or within one year after the end of pregnancy is a major clinical and public health issue. The current study aimed at estimating the incidence of pregnancy-associated cancer (PAC) and assessing whether the risk of abortion is increased in women diagnosed with cancer. METHODS: This population-based cohort study used the regional healthcare utilization (HCU) databases of Lombardy, the largest region in Italy, to identify the women who delivered between 2010 and 2020. PAC were identified by oncological ICD-9-CM codes reported in the hospital discharge forms. We computed the ratio of PAC cases to the total number of pregnancies. Following a diagnosis of PAC, the prevalence ratio (PR) of abortion and the corresponding 95% confidence interval (CI), was estimated using a log-binomial model adjusted for maternal age. RESULTS: During the study period, 926 women who gave birth (1.29 cases per 1000 births) and 341 women who had an abortion (1.52 cases per 1000 abortions) were diagnosed with PAC. Regardless of the outcome of pregnancy, the risk of PAC increased with increasing age. The rate of PAC was initially lower among births, but it came very close to the rate of PAC among abortions in the last two calendar years. The proportion of abortions among women with PAC gradually decreased from 27.7% in 2010-2012 to 18.5% in 2019-2020 (p-value < 0.001). Overall, a diagnosis of PAC was related to an approximately 10% increased risk of abortion (PR = 1.11, 95%CI:1.01-1.22). However, no association was observed in 2019-2020 (PR = 0.87, 95%CI:0.65-1.17). Considering only diagnoses made during the first trimester of pregnancy, the risk of abortion was about 2.5 times higher (PR = 2.53, 95%CI:2.05-3.11) and the risk of induced abortion was almost 4 times higher (PR = 3.71, 95%CI:2.82-4.90). CONCLUSION: In this population the risk of abortion was about 10% higher in women with PAC than in women without PAC. However, this association tended to decrease in more recent calendar periods. This trend seemed to be influenced more by spontaneous than by induced abortions.

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.

Comparative study showed that children faced a 78% higher risk of new-onset conditions after they had COVID-19.

AIM: Children have largely been unaffected by severe COVID-19 compared to adults, but data suggest that they may have experienced new conditions after developing the disease. We compared outcomes in children who had experienced COVID-19 and healthy controls. METHODS: A retrospective nested cohort study assessed the incidence rate of new-onset conditions after COVID-19 in children aged 0-14 years. Data were retrieved from an Italian paediatric primary care database linked to Veneto Region registries. Exposed children with a positive nasopharyngeal swab were matched 1:1 with unexposed children who had tested negative. Conditional Cox regression was fitted to estimate the adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for the exposure and outcome associations after adjusting for covariates. RESULTS: We compared 1656 exposed and 1656 unexposed children from 1 February 2020 to 30 November 2021. The overall excess risk for new-onset conditions after COVID-19 was 78% higher in the exposed than unexposed children. We found significantly higher risks for some new conditions in exposed children, including mental health issues (aHR 1.8, 95% CI 1.1-3.0) and neurological problems (aHR 2.4, 95% CI 1.4-4.1). CONCLUSION: Exposed children had a 78% higher risk of developing new conditions of interest after COVID-19 than unexposed children.

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.

Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.

BackgroundDuring the COVID-19 pandemic, large-scale diagnostic testing and contact tracing have proven insufficient to promptly monitor the spread of infections.AimTo develop and retrospectively evaluate a system identifying aberrations in the use of selected healthcare services to timely detect COVID-19 outbreaks in small areas.MethodsData were retrieved from the healthcare utilisation (HCU) databases of the Lombardy Region, Italy. We identified eight services suggesting a respiratory infection (syndromic proxies). Count time series reporting the weekly occurrence of each proxy from 2015 to 2020 were generated considering small administrative areas (i.e. census units of Cremona and Mantua provinces). The ability to uncover aberrations during 2020 was tested for two algorithms: the improved Farrington algorithm and the generalised likelihood ratio-based procedure for negative binomial counts. To evaluate these algorithms' performance in detecting outbreaks earlier than the standard surveillance, confirmed outbreaks, defined according to the weekly number of confirmed COVID-19 cases, were used as reference. Performances were assessed separately for the first and second semester of the year. Proxies positively impacting performance were identified.ResultsWe estimated that 70% of outbreaks could be detected early using the proposed approach, with a corresponding false positive rate of ca 20%. Performance did not substantially differ either between algorithms or semesters. The best proxies included emergency calls for respiratory or infectious disease causes and emergency room visits.ConclusionImplementing HCU-based monitoring systems in small areas deserves further investigations as it could facilitate the containment of COVID-19 and other unknown infectious diseases in the future.

Trends in the incidence of major birth defects after assisted reproductive technologies in Lombardy Region, Northern Italy.

PURPOSE: The incidence of birth defects is increased in children born after assisted reproductive technologies (ART). However, changes in ART over time could influence this incidence. To investigate this issue, we present the frequency and trends of birth defects in ART and natural pregnancies in Lombardy, Northern Italy, during the period 2014-2020. METHODS: This is a population-based study using automated system of healthcare utilization (HCU) databases. ART pregnancies included only those obtained with conventional IVF or ICSI. After identifying the total number of deliveries, the rate of newborns with birth defects was compared between natural and ART pregnancies. A logistic regression model was used to calculate the adjusted odd ratio (OR). Analyses were repeated for every calendar year. RESULTS: Overall, 508,421 deliveries were identified, of which 14,067 (2.8%) were achieved after IVF-ICSI. A decreasing trend in birth defects over time was highlighted. The adjusted OR dropped from 1.40 (95%CI: 1.03-1.91) in 2014 to 0.92 (95%CI: 0.69-1.22) in 2020. During the study period, a significant reduction in multiple pregnancy and in the ratio of ICSI to conventional IVF was also observed, explaining at least in part the positive trend observed for birth defects. CONCLUSION: The increased risk of birth defects in children born after IVF-ICSI is not steady over time. A decline of this risk emerged in our region. Policy changes in ART may explain this beneficial effect.

Research strategies in treatment of hypertension: value of retrospective real-life data.

This review will discuss the limitations of data collected by RCTs in relation to their applicability to daily life clinical management. It will then argue that these limitations are only partially overcome by modifications of RCT design and conduction (e.g. 'pragmatic trials') while being substantially attenuated by real-life-derived research, which can fill many gaps left by trial-collected evidence and have thus an important complementary value. The focus will be on the real-life research approach based on the retrospective analysis of the now widely available healthcare utilization databases (formerly known as administrative databases), which will be discussed in detail for their multiple advantages as well as challenges. Emphasis will be given to the potential of these databases to provide low-cost information over long periods on many different healthcare issues, drug therapies in particular, from the general population to clinically important subgroups, including (i) prognostic aspects of treatments implemented at the medical practice level via hospitalization and fatality data and (ii) medical practice-related phenomena such as low treatment adherence and therapeutic inertia (unsatisfactorily evaluated by RCTs). It will also be mentioned that thanks to the current availability of these data in electronic format, results can be obtained quickly, helping timely decisions under emergencies. The potential shortcomings of this approach (confounding by indication, misclassification, and selection bias) will also be discussed along with their possible minimization by suitable analytic means. Finally, examples of the contributions of studies on hypertension and other cardiovascular risk factors will be offered based on retrospective healthcare utilization databases that have provided information on real-life cardiovascular treatments unavailable via RCTs.