ObjectivesThe rRT-PCR test, the current gold standard for the detection of coronavirus disease (COVID-19), presents with known shortcomings, such as long turnaround time, potential shortage of reagents, false-negative rates around 15–20%, and expensive equipment. The hematochemical values of routine blood exams could represent a faster and less expensive alternative.MethodsThree different training data set of hematochemical values from 1,624 patients (52% COVID-19 positive), admitted at San Raphael Hospital (OSR) from February to May 2020, were used for developing machine learning (ML) models: the complete OSR dataset (72 features: complete blood count (CBC), biochemical, coagulation, hemogasanalysis and CO-Oxymetry values, age, sex and specific symptoms at triage) and two sub-datasets (COVID-specific and CBC dataset, 32 and 21 features respectively). 58 cases (50% COVID-19 positive) from another hospital, and 54 negative patients collected in 2018 at OSR, were used for internal-external and external validation.ResultsWe developed five ML models: for the complete OSR dataset, the area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.83 to 0.90; for the COVID-specific dataset from 0.83 to 0.87; and for the CBC dataset from 0.74 to 0.86. The validations also achieved good results: respectively, AUC from 0.75 to 0.78; and specificity from 0.92 to 0.96.ConclusionsML can be applied to blood tests as both an adjunct and alternative method to rRT-PCR for the fast and cost-effective identification of COVID-19-positive patients. This is especially useful in developing countries, or in countries facing an increase in contagions.

Healthcare professionals are considered to be at high risk of exposure and spread of SARS-CoV-2, and have therefore been considered a priority group in COVID-19 vaccination campaign strategies. However, it must be assumed that the immune response is influenced by numerous factors, including sex and gender. The analysis of these factors is an impact element for stratifying the population and targeting the vaccination strategy. Therefore, a large cohort of healthcare workers participating in the Italian vaccination campaign against SARS-CoV-2 has been studied to establish the impact of sex and gender on vaccination coverage using the Gender Impact Assessment approach. This study shows a significant difference in the antibody titers among different age and sex groups, with a clear decreasing trend in antibody titers in the older age groups. Overall, the serological values were significantly higher in females; the reported side effects are more frequent in females than in males. Therefore, disaggregated data point out how the evaluation of gender factors could be essential in COVID-19 vaccination strategies. On this biomedical and social basis, suggestions are provided to improve the SARS-CoV-2 vaccination campaign in healthcare professionals. Still, they could be adapted to other categories and contexts.

Background The first COVID-19 vaccines are being distributed to the general population. However, the shortage of doses is slowing down the goal of reaching herd immunity. The aim of the study was to verify whether previously SARS-CoV-2 infected subjects, a considerable portion of the population, should receive the same vaccination treatment of seronegative individuals. Methods Health-professionals either recovered from COVID-19 or never infected by SARS-CoV-2 were serologically tested at different time-points right before, and several days after, vaccination. Results Previously infected individuals showed humoral immune responses, 21 days after the first dose, that was approximately 10-folds higher than the seronegative group 21 days after the second dose. Seropositivity persists for at least 11 months. Conclusion During a shortage of COVID-19 vaccine doses, previously SARS-CoV-2 infected individuals should be dispensed from the vaccination campaign. When dose availability returns to normality, injection of a single dose for seropositive individuals should be considered.

ObjectivesThe pandemic COVID-19 currently reached 213 countries worldwide with nearly 9 million infected people and more than 460,000 deaths. Although several Chinese studies, describing the laboratory findings characteristics of this illness have been reported, European data are still scarce. Furthermore, previous studies often analyzed the averaged laboratory findings collected during the entire hospitalization period, whereas monitoring their time-dependent variations should give more reliable prognostic information.MethodsWe analyzed the time-dependent variations of 14 laboratory parameters in two groups of COVID-19 patients with, respectively, a positive (40 patients) or a poor (42 patients) outcome, admitted to the San Raffaele Hospital (Milan, Italy). We focused mainly on laboratory parameters that are routinely tested, thus, prognostic information would be readily available even in low-resource settings.ResultsStatistically significant differences between the two groups were observed for most of the laboratory findings analyzed. We showed that some parameters can be considered as early prognostic indicators whereas others exhibit statistically significant differences only at a later stage of the disease. Among them, earliest indicators were: platelets, lymphocytes, lactate dehydrogenase, creatinine, alanine aminotransferase, C-reactive protein, white blood cells and neutrophils.ConclusionsThis longitudinal study represents, to the best of our knowledge, the first study describing the laboratory characteristics of Italian COVID-19 patients on a normalized time-scale. The time-dependent prognostic value of the laboratory parameters analyzed in this study can be used by clinicians for the effective treatment of the patients and for the proper management of intensive care beds, which becomes a critical issue during the pandemic peaks.