Stratification of the risk of developing severe or lethal Covid-19 using a new score from a large Italian population: a population-based cohort study.

OBJECTIVES: To develop a population-based risk stratification model (COVID-19 Vulnerability Score) for predicting severe/fatal clinical manifestations of SARS-CoV-2 infection, using the multiple source information provided by the healthcare utilisation databases of the Italian National Health Service. DESIGN: Retrospective observational cohort study. SETTING: Population-based study using the healthcare utilisation database from five Italian regions. PARTICIPANTS: Beneficiaries of the National Health Service, aged 18-79 years, who had the residentship in the five participating regions. Residents in a nursing home were not included. The model was built from the 7 655 502 residents of Lombardy region. MAIN OUTCOME MEASURE: The score included gender, age and 29 conditions/diseases selected from a list of 61 conditions which independently predicted the primary outcome, that is, severe (intensive care unit admission) or fatal manifestation of COVID-19 experienced during the first epidemic wave (until June 2020). The score performance was validated by applying the model to several validation sets, that is, Lombardy population (second epidemic wave), and the other four Italian regions (entire 2020) for a total of about 15.4 million individuals and 7031 outcomes. Predictive performance was assessed by discrimination (areas under the receiver operating characteristic curve) and calibration (plot of observed vs predicted outcomes). RESULTS: We observed a clear positive trend towards increasing outcome incidence as the score increased. The areas under the receiver operating characteristic curve of the COVID-19 Vulnerability Score ranged from 0.85 to 0.88, which compared favourably with the areas of generic scores such as the Charlson Comorbidity Score (0.60). A remarkable performance of the score on the calibration of observed and predicted outcome probability was also observed. CONCLUSIONS: A score based on data used for public health management accurately predicted the occurrence of severe/fatal manifestations of COVID-19. Use of this score may help health decision-makers to more accurately identify high-risk citizens who need early preventive or treatment interventions.

Social inequalities in total and cause-specific mortality of a sample of the Italian population, from 1999 to 2007.

BACKGROUND: There is extensive documentation on social inequalities in mortality across Europe, showing heterogeneity among countries. Italy contributed to this comparative research, through longitudinal systems from northern or central cities of the country. This study aims to analyse educational inequalities in general and cause-specific mortality in a sample of the Italian population. METHODS: Study population was selected within a cohort of 123,056 individuals, followed up for mortality through record linkage with national archive of death certificates for the period 1999-2007. People aged between 25 and 74 years were selected (n = 81,763); relative risks of death by education were estimated through Poisson models, stratified according to sex and adjusted for age and geographic area of residence. Heterogeneity of risks by area of residence was evaluated. RESULTS: Men and women with primary education or less show 79% and 63% higher mortality risks, respectively, compared with graduates. Mortality risks seem to frequently increase with decreasing education, with a significant linear trend among men. For men, social inequalities appear related to mortality due to diseases of the circulatory system and to all neoplasms, whereas for women, they are related to inequalities in cancer mortality. CONCLUSIONS: Results from the first follow-up of a national sample highlight that Italy presents significant differences in mortality according to the socio-economic conditions of both men and women. These results not only challenge policies aimed at redistributing resources to individuals and groups, but also those policies that direct programmes and resources for treatment and prevention according to the different health needs.