Background Several studies have been focusing on the potential role of atmospheric pollutants in the diffusion and impact on health of Covid-19. This study’s objective was to estimate the association between ≤10 μm diameter particulate matter (PM10) exposure and the likelihood of experiencing pneumonia due to Covid-19 using individual-level data in Italy. Methods Information on Covid-19 patients was retrieved from the Italian IQVIA® Longitudinal Patient Database (LPD), a computerized network of general practitioners (GPs) including anonymous data on patients’ consultations and treatments. All patients with a Covid-19 diagnosis during March 18th, 2020 – June 30th, 2020 were included in the study. The date of first Covid-19 registration was the starting point of the 3-month follow-up (Index Date). Patients were classified based on Covid-19-related pneumonia registrations on the Index date and/or during follow-up presence/absence. Each patient was assigned individual exposure by calculating average PM10 during the 30-day period preceding the Index Date, and according to GP’s office province. A multiple generalized linear mixed model, mixed-effects logistic regression, was used to assess the association between PM10 exposure tertiles and the likelihood of experiencing pneumonia. Results Among 6483 Covid-19 patients included, 1079 (16.6%) had a diagnosis of pneumonia. Pneumonia patients were older, more frequently men, more health-impaired, and had a higher individual-level exposure to PM10 during the month preceding Covid-19 diagnosis. The mixed-effects model showed that patients whose PM10 exposure level fell in the second tertile had a 30% higher likelihood of having pneumonia than that of first tertile patients, and the risk for those who were in the third tertile was almost doubled. Conclusion The consistent findings toward a positive association between PM10 levels and the likelihood of experiencing pneumonia due to Covid-19 make the implementation of new strategies to reduce air pollution more and more urgent.

Understand the demographics and clinical features of patients with osteoarthritis (OA), quantify healthcare resource utilization by OA patients, and estimate the annual direct medical costs per OA patient from a National Health Service (NHS) perspective in Italy. Patients and Methods: Retrospective observational cohort analysis using data from electronic medical records captured by the Italian IQVIA Longitudinal Patient Database (LPD). Only direct medical costs reimbursed by the NHS were considered. Patients were included if they received at least one diagnosis of OA during the period from January 1 to December 31, 2018. Each patient was observed for 3 years: a 24-month baseline period preceding the index date, and a 12-month follow-up period starting at the index date. Results: A total of 71,467 patients met inclusion criteria: 43.98% had not been prescribed NSAIDs/opioids, 40.76% had been prescribed NSAIDs, and 15.26% an opioid. Mean age was 71.36 years, and 68.2% of the patients were women. At least one comorbidity was present in 91.34% of the patients; 38.05% were newly diagnosed with OA. During 1-year of follow-up, 173,884 prescriptions with an associated diagnosis of OA were found: 47.36% had been prescribed an NSAID, 9.11% diclofenac, 8.30% codeine+paracetamol, and 7.32% ketoprofen. Nearly 15% of the patients had at least 1 request for a specialist visit and 23.82% had at least 1 request for exams. Orthopedic visits accounted for 60% of all specialist visits. Yearly mean costs per patient were €622, for approximately €2.5 billion per year in direct costs, considering 3.9 million patients with OA in Italy. Protheses were a major driver in annual costs: €143.45 in patients without a prosthesis and €10,090.91 in those with a joint prosthesis. Conclusion:This real-world analysis of direct costs of care of patients with OA in Italy confirms the substantial economic burden. Direct costs dramatically increased when joint replacement was needed.

BACKGROUND: Several studies have been focusing on the potential role of atmospheric pollutants in the diffusion and impact on health of Covid-19. This study’s objective was to estimate the association between ≤10 micrometers diameter particulate matter (PM10) exposure and the likelihood of experiencing pneumonia due to Covid-19 using individual-level data in Italy.METHODS: Information on Covid-19 patients was retrieved from the Italian IQVIA® Longitudinal Patient Database (LPD), a computerized network of general practitioners (GPs) including anonymous data on patients’ consultations and treatments. All patients with a Covid-19 diagnosis during March 18th, 2020 – June 30th, 2020 were included in the study. The date of first Covid-19 registration was the starting point of the 3-month follow-up (Index Date). Patients were classified based on Covid-19-related pneumonia registrations on the Index date and/or during follow-up presence/absence. Each patient was assigned individual exposure by calculating average PM10 during the 30-day period preceding the Index Date, and according to GP’s office province. A multiple generalized linear mixed model, mixed-effects logistic regression, was used to assess the association between PM10 exposure tertiles and the likelihood of experiencing pneumonia.RESULTS: Among 6,483 Covid-19 patients included, 1,079 (16.6%) had a diagnosis of pneumonia. Pneumonia patients were older, more frequently men, more health-impaired, and had a higher individual-level exposure to PM10 during the month preceding Covid-19 diagnosis. The mixed-effects model showed that patients whose PM10 exposure level fell in the second tertile had a 30% higher likelihood of having pneumonia than that of first tertile patients, and the risk for those who were in the third tertile was almost doubled.CONCLUSION: The consistent findings toward a positive association between PM10 levels and the likelihood of experiencing pneumonia due to Covid-19 make the implementation of new strategies to reduce air pollution more and more urgent.

Purpose The primary objectives were to describe weight changes following initiation of lurasidone versus other antipsychotics and estimate the risk of clinically relevant (≥7%) weight changes. Patients and Methods This retrospective, longitudinal comparative cohort study was based on electronic medical records (EMRs) of United States (US) adult patients with schizophrenia who were prescribed lurasidone or other antipsychotics as monotherapy between 1 April 2013 and 30 June 2019. Results Overall, the study included 15,323 patients with a diagnosis of schizophrenia; 6.1% of patients received lurasidone, 60.4% received antipsychotics associated with a medium-high risk of weight gain (clozapine, olanzapine, quetiapine, risperidone, paliperidone) and 33.5% received antipsychotics with a low risk of weight gain (aripiprazole, first-generation antipsychotics, ziprasidone). Lurasidone was associated with the smallest proportion of patients experiencing clinically relevant weight gain and the greatest proportion of patients with clinically relevant weight loss. The risk of clinically relevant weight gain was numerically higher with all antipsychotics versus lurasidone and was statistically significant for olanzapine (hazard ratio [HR]=1.541; 95% confidence interval [CI]=1.121; 2.119; p=0.0078) versus lurasidone. The likelihood of ≥7% weight loss was significantly greater with lurasidone versus all antipsychotics (p<0.05), except ziprasidone. Conclusion This real-world study suggests that lurasidone has a lower risk of clinically relevant weight gain and a higher likelihood of clinically relevant weight loss than other commonly used antipsychotics.

Background: Major depressive disorders represent a significant burden to the society, and it is recommended that antidepressant therapy should last at least 6 months. In Italy, antidepressant use in clinical practice was reported to increase by 1.7% in 2020 compared to 2019, but only 40% of new prescriptions are characterized by a treatment duration longer than 3 months. Objective: Describe adherence and persistence to therapy in a subset of antidepressants (citalopram, duloxetine, escitalopram, paroxetine, sertraline, venlafaxine) vs. vortioxetine in Italy, during a 2-year period from 2017 to 2019. Methods: A retrospective analysis of the longitudinal patient database reporting data from general practitioners on drug prescriptions in Italy, was carried out in a cohort of 8,235 adult patients who were prescribed antidepressants. Results: Overall, 32.4% of the patients adhered to treatment for ≥6 months over a 1-year period. Vortioxetine had a lower risk of low adherence compared to duloxetine, paroxetine and venlafaxine and a higher risk compared to citalopram, escitalopram, and sertraline. 68.7% of patients discontinued treatment during follow-up. The greatest percentage of patients continuing therapy was seen with duloxetine, while citalopram was associated with the highest proportion of patients discontinuing therapy. No significant differences in discontinuation were observed when comparing vortioxetine to the other antidepressants. Conclusion: Adherence results were considerably less than the 6-month recommendation in this real-world analysis of antidepressant therapies. Also, persistence to therapy was low, with most of patients discontinuing treatment. Thus, there is the need for interventions to help patients adhere to their planned therapy.