A NLP-based semi-automatic identification system for delays in follow-up examinations: an Italian case study on clinical referrals

Background: This study aims to propose a semi-automatic method for monitoring the waiting times of follow-up examinations within the National Health System (NHS) in Italy, which is currently not possible to due the absence of the necessary structured information in the official databases. Methods: A Natural Language Processing (NLP) based pipeline has been developed to extract the waiting time information from the text of referrals for follow-up examinations in the Lombardy Region. A manually annotated dataset of 10 000 referrals has been used to develop the pipeline and another manually annotated dataset of 10 000 referrals has been used to test its performance. Subsequently, the pipeline has been used to analyze all 12 million referrals prescribed in 2021 and performed by May 2022 in the Lombardy Region. Results: The NLP-based pipeline exhibited high precision (0.999) and recall (0.973) in identifying waiting time information from referrals' texts, with high accuracy in normalization (0.948-0.998). The overall reporting of timing indications in referrals' texts for follow-up examinations was low (2%), showing notable variations across medical disciplines and types of prescribing physicians. Among the referrals reporting waiting times, 16% experienced delays (average delay = 19 days, standard deviation = 34 days), with significant differences observed across medical disciplines and geographical areas. Conclusions: The use of NLP proved to be a valuable tool for assessing waiting times in follow-up examinations, which are particularly critical for the NHS due to the significant impact of chronic diseases, where follow-up exams are pivotal. Health authorities can exploit this tool to monitor the quality of NHS services and optimize resource allocation

SARS-CoV-2 Vaccine Uptake during Pregnancy in Regione Lombardia, Italy: A Population-Based Study of 122,942 Pregnant Women

Italy has been one of the hardest hit countries in the European Union since the beginning of the SARS-CoV-2 pandemic, and Regione Lombardia (RL) has reported the largest number of cases in the country. This population-based retrospective study analyzed RL records of 122,942 pregnant women to describe SARS-CoV-2 vaccination uptake in the pregnant population, to compare pregnant women vaccine uptake vs. women of childbearing age and to evaluate the impact of vaccination status in pregnant women on admissions to intensive care units during 2021. Vaccination uptake according to citizenship and educational level and the comparison between pregnant and non-pregnant women was performed by Z test. A logistic regression was performed to compare age groups. Out of 122,942 pregnant women, 79.9% were vaccinated at the end of 2021. The vaccine uptake rate was significantly lower in pregnant versus non-pregnant women but increased after the issuing of official recommendations. Vaccine administration was significantly higher among pregnant women with Italian citizenship and with a high level of education in all trimesters. In conclusion, the role of official recommendations with explicit communication about the importance and safety of vaccination in pregnancy is critical to obtain trust and acceptance among pregnant women

Additional file 1 of A NLP-based semi-automatic identification system for delays in follow-up examinations: an Italian case study on clinical referrals

Additional file 1: Supplementary Material. Contains more details about the pipeline, the dataset and the error analysis

Factors influencing adherence to adjuvant endocrine therapy in breastcancer‑treated women: using real‑world data to inform a switch from acute to chronic disease management

We tested determinants of Adjuvant endocrine therapy (AET) adherence using patient characteristics, treatment pathways, AET initiation timing, and multiple healthcare facility use. An underlying objective was to explore how oncological pathways mirror chronic disease management to monitor adherence and target improvement interventions using administrative datasets

Vulnerability Predictors of Post-Vaccine SARS-CoV-2 Infection and Disease—Empirical Evidence from a Large Population-Based Italian Platform

We aimed to identify individual features associated with increased risk of post-vaccine SARS-CoV-2 infection and severe COVID-19 illness. We performed a nested case–control study based on 5,350,295 citizens from Lombardy, Italy, aged ≥ 12 years who received a complete anti-COVID-19 vaccination from 17 January 2021 to 31 July 2021, and followed from 14 days after vaccine completion to 11 November 2021. Overall, 17,996 infections and 3023 severe illness cases occurred. For each case, controls were 1:1 (infection cases) or 1:10 (severe illness cases) matched for municipality of residence and date of vaccination completion. The association between selected predictors (sex, age, previous occurrence of SARS-CoV-2 infection, type of vaccine received, number of previous contacts with the Regional Health Service (RHS), and the presence of 59 diseases) and outcomes was assessed by using multivariable conditional logistic regression models. Sex, age, previous SARS-CoV-2 infection, type of vaccine and number of contacts with the RHS were associated with the risk of infection and severe illness. Moreover, higher odds of infection and severe illness were significantly associated with 14 and 34 diseases, respectively, among those investigated. These results can be helpful to clinicians and policy makers for prioritizing interventions

Association of Influenza Vaccination and Prognosis in Patients Testing Positive to SARS-CoV-2 Swab Test: A Large-Scale Italian Multi-Database Cohort Study

To investigate the association of the 2019-2020 influenza vaccine with prognosis of patients positive for SARS-CoV-2A, a large multi-database cohort study was conducted in four Italian regions (i.e., Lazio, Lombardy, Veneto, and Tuscany) and the Reggio Emilia province (Emilia-Romagna). More than 21 million adults were residing in the study area (42% of the population). We included 115,945 COVID-19 cases diagnosed during the first wave of the pandemic (February-May, 2020); 34.6% of these had been vaccinated against influenza. Three outcomes were considered: hospitalization, death, and intensive care unit (ICU) admission/death. The adjusted relative risk (RR) of being hospitalized in the vaccinated group when compared with the non-vaccinated group was 0.87 (95% CI: 0.86-0.88). This reduction in risk was not confirmed for death (RR = 1.04; 95% CI: 1.01-1.06), or for the combined outcome of ICU admission or death. In conclusion, our study, conducted on the vast majority of the population during the first wave of the pandemic in Italy, showed a 13% statistically significant reduction in the risk of hospitalization in some geographical areas and in the younger population. No impact of seasonal influenza vaccination on COVID-19 prognosis in terms of death and death or ICU admission was estimated

Balancing Benefits and Harms of COVID-19 Vaccines: Lessons from the Ongoing Mass Vaccination Campaign in Lombardy, Italy

Background. Limited evidence exists on the balance between the benefits and harms of the COVID-19 vaccines. The aim of this study is to compare the benefits and safety of mRNA-based (Pfizer-BioNTech and Moderna) and adenovirus-vectored (Oxford-AstraZeneca) vaccines in subpopulations defined by age and sex. Methods. All citizens who are newly vaccinated from 27 December 2020 to 3 May 2021 are matched to unvaccinated controls according to age, sex, and vaccination date. Study outcomes include the events that are expected to be avoided by vaccination (i.e., hospitalization and death from COVID-19) and those that might be increased after vaccine inoculation (i.e., venous thromboembolism). The incidence rate ratios (IRR) of vaccinated and unvaccinated citizens are separately estimated within strata of sex, age category and vaccine type. When suitable, number needed to treat (NNT) and number needed to harm (NNH) are calculated to evaluate the balance between the benefits and harm of vaccines within each sex and age category. Results. In total, 2,351,883 citizens are included because they received at least one dose of vaccine (755,557 Oxford-AstraZeneca and 1,596,326 Pfizer/Moderna). A reduced incidence of COVID-19-related outcomes is observed with a lowered incidence rate ranging from 55% to 89% and NNT values ranging from 296 to 3977. Evidence of an augmented incidence of harm-related outcomes is observed only for women aged <50 years within 28 days after Oxford-AstraZeneca (being the corresponding adjusted IRR of 2.4, 95% CI 1.1–5.6, and NNH value of 23,207, 95% CI 10,274–89,707). Conclusions. A favourable balance between benefits and harms is observed in the current study, even among younger women who received Oxford-AstraZeneca

Balancing Benefits and Harms of COVID-19 Vaccines: Lessons from the Ongoing Mass Vaccination Campaign in Lombardy, Italy

Background. Limited evidence exists on the balance between the benefits and harms of the COVID-19 vaccines. The aim of this study is to compare the benefits and safety of mRNA-based (Pfizer-BioNTech and Moderna) and adenovirus-vectored (Oxford-AstraZeneca) vaccines in subpopulations defined by age and sex. Methods. All citizens who are newly vaccinated from 27 December 2020 to 3 May 2021 are matched to unvaccinated controls according to age, sex, and vaccination date. Study outcomes include the events that are expected to be avoided by vaccination (i.e., hospitalization and death from COVID-19) and those that might be increased after vaccine inoculation (i.e., venous thromboembolism). The incidence rate ratios (IRR) of vaccinated and unvaccinated citizens are separately estimated within strata of sex, age category and vaccine type. When suitable, number needed to treat (NNT) and number needed to harm (NNH) are calculated to evaluate the balance between the benefits and harm of vaccines within each sex and age category. Results. In total, 2,351,883 citizens are included because they received at least one dose of vaccine (755,557 Oxford-AstraZeneca and 1,596,326 Pfizer/Moderna). A reduced incidence of COVID-19-related outcomes is observed with a lowered incidence rate ranging from 55% to 89% and NNT values ranging from 296 to 3977. Evidence of an augmented incidence of harm-related outcomes is observed only for women aged Conclusions. A favourable balance between benefits and harms is observed in the current study, even among younger women who received Oxford-AstraZeneca

Postmarketing active surveillance of myocarditis and pericarditis following vaccination with COVID-19 mRNA vaccines in persons aged 12 to 39 years in Italy: A multi-database, self-controlled case series study

Myocarditis and pericarditis following the Coronavirus Disease 2019 (COVID-19) mRNA vaccines administration have been reported, but their frequency is still uncertain in the younger population. This study investigated the association between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) mRNA vaccines, BNT162b2, and mRNA-1273 and myocarditis/pericarditis in the population of vaccinated persons aged 12 to 39 years in Italy