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The text describes the effects of the pandemic on the dynamics of migration flows from abroad to Italy in 2020. The composition and demographic structure of the population of foreign origin are described in order to understand which areas of immigration and integration are most affected by the pandemic.It has been observed that, although the downward trend in migration flows predates the spread of COVID-19, the pandemic has led to a drastic decrease in migration flows towards our country, where a stable foreign presence has settled over the years. The transformation of Italy into a country of stable integration is also witnessed by the growing number of foreigners who become Italian through the acquisition of citizenship, a process that not even the pandemic has slowed down. Instead, the possible effects of the pandemic on economic and labour integration and inclusion, particularly of the many children and young people of foreign origin living in our country, are worrying.
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COVID-19 , Emigrantes e Imigrantes , Migrantes , Adolescente , COVID-19/epidemiologia , Criança , Demografia , Países Desenvolvidos , Europa (Continente) , Humanos , Itália/epidemiologia , Pandemias , Dinâmica PopulacionalRESUMO
OBJECTIVES: to evaluate the impact on total mortality of the COVID-19 pandemic in Italy, by country of birth. DESIGN: historic cohort study based on administrative databases. SETTING AND PARTICIPANTS: the study is based on subjects included in the Base Register of Individuals of the Italian National Institute of Statistics on 01.01.2019, aged 35-64 years, and followed-up until 31.07.2021. MAIN OUTCOME MEASURES: age-standardized mortality rates were computed to analyse trends in overall mortality by country of birth grouped in three categories: 1. Italy and other high developed countries; 2. European countries with strong migratory pressure (EU-SMP); 3, non-European countries with strong migratory pressure (non-EU-SMP). Variations in mortality rates during the pandemic (March 2020-July 2021) with respect to the pre-pandemic period (January 2019-February 2020) were measured and compared across groups using mortality rate ratios (MRR) estimated by Poisson regression models, separately for men and women. RESULTS: the cohort includes 26,199,241 individuals, of whom 172,847 died during the follow-up. Over the whole period, mortality was consistently lower in individuals born in non-EU-SMP countries as compared to those born in Italy and other high developed countries. During the first pandemic wave (March-April 2020), individuals born in non-EU-SMP countries had higher excesses as compared to those born in Italy or other high developed countries (MRRs: 1.42 vs 1.28 in men and 1.30 vs 1.11 in women). Similar results were observed during the pandemic period October 2020-April 2021, when the MRRs were 1.37 vs 1.20 in men and 1.30 vs 1.11 in women. In the same period, the excess mortality among individuals born in EU-SMP did not significantly differ from that observed among those born in Italy and other high developed countries. CONCLUSIONS: in Italy, excess mortality during the COVID-19 pandemic was higher among immigrants born in non-EU-SMP countries as compared to the native population and immigrants born in high developed countries.
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COVID-19 , Emigrantes e Imigrantes , Estudos de Coortes , Feminino , Humanos , Itália/epidemiologia , Masculino , Mortalidade , PandemiasRESUMO
BACKGROUND: Accurate medication reconciliation reduces the risk of drug incompatibilities and adverse events that can occur during transitions in care. Community pharmacies (CPs) are a crucial part of the health care system and could be involved in collecting essential information on conventional and supplementary drugs used at home. OBJECTIVE: The aim of this paper was to establish an alliance between our cancer institute, Istituto Romagnolo per lo Studio dei Tumori (IRST), and CPs, the latter entrusted with the completion of a pharmacological recognition survey. We also aimed to integrate the national information technology (IT) platform of CPs with the electronic medical records of IRST. METHODS: Cancer patients undergoing antiblastic treatments were invited to select a CP taking part in the study and to complete the pharmacological recognition step. The information collected by the pharmacist was sent to the electronic medical records of IRST through the new IT platform, after which the oncologist performed the reconciliation process. RESULTS: A total of 66 CPs completed surveys for 134 patients. An average of 5.9 drugs per patient was used at home, with 12 or more used in the most advanced age groups. Moreover, 60% (80/134) of the patients used nonconventional products or critical foods. Some potential interactions between nonconventional medications and cancer treatments were reported. CONCLUSIONS: In the PROF-1 (Progetto di Rete in Oncologia con le Farmacie di comunità della Romagna) study, an alliance was created between our cancer center and CPs to improve medication reconciliation, and a new integrated IT platform was validated. TRIAL REGISTRATION: ClinicalTrials.gov NCT04796142; https://clinicaltrials.gov/ct2/show/NCT04796142.
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Reconciliação de Medicamentos , Farmacêuticos , Registros Eletrônicos de Saúde , Humanos , Estudos ProspectivosRESUMO
BACKGROUND: there is increasing concern that the COVID-19 pandemic has disproportionately affected the most vulnerable individuals. OBJECTIVES: to determine whether education inequalities have widened during the first wave of the COVID-19 pandemic in Italy. DESIGN: historic cohort study based on administrative databases. SETTING AND PARTICIPANTS: the study was based on subjects registered in the Base Register of Individuals on 01.01.2019, aged >=35 years, and followed-up until 30.06.2020. MAIN OUTCOME MEASURES: education inequalities in mortality before, during the first phase (March-April), and during the second phase (May-June) of the first pandemic wave in Italy were measured through the mortality rate ratios (MRRs). MMRs were estimated through negative binomial models. The interaction term between period and education was tested through the likelihood ratio test. RESULTS: the cohort included 37,976,670 individuals, and 719,665 of them died over the follow-up. In high pandemic areas, the MRR among less educated men were: 1.48 (95%CI 1.42-1.55) in the pre-pandemic period, 1.45 (95%CI 1.36-1.55) in the first phase and 1.42 (95%CI 1.30-1.56) in the second phase of the pandemic (p-value: 0.92). Corresponding figures among women were: 1.26 (95%CI 1.21-1.32), 1.39 (95%CI 1.30-1.49), and 1.35 (95%CI 1.23-1.48); p-value: 0.03. The MRRs substantially increased in the first pandemic phase among women aged 35-64 years (from 1.48 to 1.98; p-value; 0.011) and 65-79 years (from 1.22 to 1.51; p-value: 0.017). During the second phase, the MRRs returned to the values observed before the pandemic. CONCLUSIONS: in Italy, education inequality in mortality widened during the COVID-19 pandemic among working-age women and those aged 65-79 years.
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COVID-19 , Pandemias , Idoso , Estudos de Coortes , Feminino , Humanos , Itália/epidemiologia , Masculino , Mortalidade , SARS-CoV-2RESUMO
INTRODUCTION: Excess mortality (EM) is a valid indicator of COVID-19's impact on public health. Several studies regarding the estimation of EM have been conducted in Italy, and some of them have shown conflicting values. We focused on three estimation models and compared their results with respect to the same target population, which allowed us to highlight their strengths and limitations. METHODS: We selected three estimation models: model 1 (Maruotti et al.) is a Negative-Binomial GLMM with seasonal patterns; model 2 (Dorrucci et al.) is a Negative Binomial GLM epidemiological approach; and model 3 (Scortichini et al.) is a quasi-Poisson GLM time-series approach with temperature distributions. We extended the time windows of the original models until December 2021, computing various EM estimates to allow for comparisons. RESULTS: We compared the results with our benchmark, the ISS-ISTAT official estimates. Model 1 was the most consistent, model 2 was almost identical, and model 3 differed from the two. Model 1 was the most stable towards changes in the baseline years, while model 2 had a lower cross-validation RMSE. DISCUSSION: Presently, an unambiguous explanation of EM in Italy is not possible. We provide a range that we consider sound, given the high variability associated with the use of different models. However, all three models accurately represented the spatiotemporal trends of the pandemic waves in Italy.
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COVID-19 , Humanos , COVID-19/epidemiologia , Itália/epidemiologia , Fatores de Tempo , Pandemias , Estações do Ano , MortalidadeRESUMO
AIMS: To assess the impact of the COVID-19 pandemic on all-cause mortality in Italy during the first wave of the epidemic, taking into consideration the geographical heterogeneity of the spread of COVID-19. METHODS: This study is a retrospective, population-based cohort study using national statistics throughout Italy. Survival analysis was applied to data aggregated by day of death, age groups, sex, and Italian administrative units (107 provinces). We applied Cox models to estimate the relative hazards (RH) of excess mortality, comparing all-cause deaths in 2020 with the expected deaths from all causes in the same time period. The RH of excess deaths was estimated in areas with a high, moderate, and low spread of COVID-19. We reported the estimate also restricting the analysis to the period of March-April 2020 (first peak of the epidemic). RESULTS: The study population consisted of 57,204,501 individuals living in Italy as of January 1, 2020. The number of excess deaths was 36,445, which accounts for 13.4% of excess mortalities from all causes during January-May 2020 (i.e., RH = 1.134; 95% confidence interval (CI): 1.129-1.140). In the macro-area with a relatively higher spread of COVID-19 (i.e., incidence rate, IR): 450-1,610 cases per 100,000 residents), the RH of excess deaths was 1.375 (95% CI: 1.364-1.386). In the area with a relatively moderate spread of COVID-19 (i.e., IR: 150-449 cases) it was 1.049 (95% CI: 1.038-1.060). In the area with a relatively lower spread of COVID-19 (i.e., IR: 30-149 cases), it was 0.967 (95% CI: 0.959-0.976). Between March and April (peak months of the first wave of the epidemic in Italy), we estimated an excess mortality from all causes of 43.5%. The RH of all-cause mortality for increments of 500 cases per 100,000 residents was 1.352 (95% CI: 1.346-1.359), corresponding to an increase of about 35%. CONCLUSIONS: Our analysis, making use of a population-based cohort model, estimated all-cause excess mortality in Italy taking account of both time period and of COVID-19 geographical spread. The study highlights the importance of a temporal/geographic framework in analyzing the risk of COVID-19-epidemy related mortality.
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COVID-19 , Estudos de Coortes , Humanos , Itália/epidemiologia , Pandemias , Estudos RetrospectivosRESUMO
. Introducing clinical nurse specialists (CNS) in the ambulatory setting: the experience of a Research Cancer Center in Italy. INTRODUCTION: In 2018 the role of clinical nurse specialist (CNS) was implemented in an ambulatory setting at our cancer institute. OBJECTIVES: To describe the CNS role implementation and the indicators to measure and the impact of the CNS after one year. METHODS: Indicators for the implementation: CNS interface mapping in disease pathways, participation in multidisciplinary team (MDT) meetings, and number of training hours per CNS on specific cancers. Indicators for the impact: patient satisfaction with CNS (survey), compliance with for waiting times for the first visit, number of documented CNS-patient communications and number of improvement projects in which CNSs were involved. RESULTS: One year after CNS introduction, pathway mapping was 100%; MDT meeting participation 95%; training hours 40.5/CNS vs. standard 30 hours; 83.2% of interviewed patients were very satisfied with CNSs. On average 27 face to face and 126 phone interviews per month were performed. The number of first visits increased of 13% componed to the previous year. CONCLUSIONS: CNSs were successfully introduced into disease pathways and played an active role in the MDTs. The positive impact observed suggests that this new role could represent a response to the need to design patient centered services for cancer diseases. Measuring the CNSs activities and their impact on the patient outcomes and on system efficiency is the key for defining nursing staffing standards in the disease pathways, tailored on patients and organization characteristics.
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Neoplasias , Enfermeiros Clínicos , Instituições de Assistência Ambulatorial , Humanos , Neoplasias/terapia , Inquéritos e Questionários , Recursos HumanosRESUMO
INTRODUCTION: Little consideration is given to the referral and uptake of available supportive services after distress screening. However, identifying the reasons for accepting or refusing help is mandatory for implementing a screening policy. The present study explored the practical usefulness of and potential barriers to the application of distress management. METHODS: 406 cancer patients were consecutively selected and asked to complete the Distress Thermometer (DT) and Problem Check List (PL). All patients with a DT score ≥6 were invited for a post-DT telephone interview with a trained psychologist. RESULTS: The 112 patients who refused to take part were more often older, retired, at a more advanced stage of illness, and with no previous experience of psychological intervention with respect to those who accepted. Of the 78 patients with a score ≥6 who were referred to the Psycho-Oncology Service, 65.4% accepted the telephone interview. Twenty-two patients rejected the initial invitation immediately for various reasons including logistic difficulties, physical problems, and feeling embarrassed about opening up to a psychologist. CONCLUSIONS: Our study confirms that screening per sé is insufficient to deal with the problem of distress and that more emphasis should be placed on implementing referral and treatment.
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COVID-19 dramatically influenced mortality worldwide, in Italy as well, the first European country to experience the Sars-Cov2 epidemic. Many countries reported a two-wave pattern of COVID-19 deaths; however, studies comparing the two waves are limited. The objective of the study was to compare all-cause excess mortality between the two waves that occurred during the year 2020 using nationwide data. All-cause excess mortalities were estimated using negative binomial models with time modeled by quadratic splines. The models were also applied to estimate all-cause excess deaths "not directly attributable to COVD-19", i.e., without a previous COVID-19 diagnosis. During the first wave (25th February-31st May), we estimated 52,437 excess deaths (95% CI: 49,213-55,863) and 50,979 (95% CI: 50,333-51,425) during the second phase (10th October-31st December), corresponding to percentage 34.8% (95% CI: 33.8%-35.8%) in the second wave and 31.0% (95%CI: 27.2%-35.4%) in the first. During both waves, all-cause excess deaths percentages were higher in northern regions (59.1% during the first and 42.2% in the second wave), with a significant increase in the rest of Italy (from 6.7% to 27.1%) during the second wave. Males and those aged 80 or over were the most hit groups with an increase in both during the second wave. Excess deaths not directly attributable to COVID-19 decreased during the second phase with respect to the first phase, from 10.8% (95% CI: 9.5%-12.4%) to 7.7% (95% CI: 7.5%-7.9%), respectively. The percentage increase in excess deaths from all causes suggests in Italy a different impact of the SARS-CoV-2 virus during the second wave in 2020. The decrease in excess deaths not directly attributable to COVID-19 may indicate an improvement in the preparedness of the Italian health care services during this second wave, in the detection of COVID-19 diagnoses and/or clinical practice toward the other severe diseases.
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COVID-19 , Teste para COVID-19 , Europa (Continente) , Humanos , Itália/epidemiologia , Masculino , Pandemias , RNA Viral , SARS-CoV-2RESUMO
Testicular cancer is the most common tumor in young males aged 15-40 years. The overall cure rate for men with testicular cancer is >90%, so a huge number of these patients will become testicular cancer survivors. These people may feel some stress in the experience of diagnosis, treatment, and consequences that affects the quality of life, and during follow-up, especially when new issues and emotional distresses appear over time, such as late side-effects of treatments and emotional challenges including fear of tumor relapse, fertility and sexuality concerns, and social and workplace issues. The cancer experience has an impact not only on patients, but also on their relatives (e.g., spouses, parents, or siblings), who often have to assume a caregiving role for the duration of and following treatment for cancer. Moreover, the caregiver plays an important role in supporting a man with a testicular cancer, providing physical and emotional care. This review presents a summary of existing knowledge regarding the impact and the burden of testicular cancer on caregivers.
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OBJECTIVE: To report the distribution and availability of the indicators describing the population of childbearing women in Europe and to assess the impact of the difference in the distribution of two of these indicators (age and multiple births) on some outcome indicators. METHODS: The six PERISTAT indicators of population characteristics were computed using data from a survey of data providers in Europe. For maternal age and multiple births, the impact on health outcome was simulated for the extremes of the distribution using indirect standardised rates. RESULTS: Data availability is good for basic demographic indicators (age, parity, multiple births), but less complete for indicators of social characteristics (education, smoking, country of birth). Further, common definitions are not used for the latter. Simulations of the impact of maternal age on health outcome found that variation in the maternal age distribution may cause trisomy 21 rates to differ by nearly 20% and maternal mortality ratios by nearly 50%. CONCLUSION: Indicators of basic population characteristics are not collected routinely in every country. The crude distribution of these indicators is essential for international comparisons. Interpretation of comparative data would be improved by collection of health outcomes and service use by maternal characteristics.