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The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the case-fatality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48 h after admission (adjusted R-squared = 0.48). We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients in the Emergency Department, or during hospitalization. Although it is reasonable to assume that the model is also applicable in not-hospitalized persons, only appropriate studies can assess the accuracy of the model also for persons at home., (© 2021. The Author(s).)

Healthcare workers are at the forefront against COVID-19, worldwide. Since Fondazione Policlinico Universitario A. Gemelli (FPG) IRCCS was enlisted as a COVID-19 hospital, the healthcare workers deployed to COVID-19 wards were separated from those with limited/no exposure, whereas the administrative staff were designated to work from home. Between 4 June and 3 July 2020, an investigation was conducted to evaluate the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin (IgG) antibodies among the employees of the FPG using point-of-care (POC) and venous blood tests. Sensitivity, specificity, and predictive values were determined with reverse-transcription polymerase chain reaction on nasal/oropharyngeal swabs as the diagnostic gold standard. The participants enrolled amounted to 4777. Seroprevalence was 3.66% using the POC test and 1.19% using the venous blood test, with a significant difference ( p < 0.05). The POC test sensitivity and specificity were, respectively, 63.64% (95% confidence interval (CI): 62.20% to 65.04%) and 96.64% (95% CI: 96.05% to 97.13%), while those of the venous blood test were, respectively, 78.79% (95% CI: 77.58% to 79.94%) and 99.36% (95% CI: 99.07% to 99.55%). Among the low-risk populations, the POC test's predictive values were 58.33% (positive) and 98.23% (negative), whereas those of the venous blood test were 92.86% (positive) and 98.53% (negative). According to our study, these serological tests cannot be a valid alternative to diagnose COVID-19 infection in progress.

Objective: Few studies report that Mediterranean dietary (MD) pattern has a beneficial role in the progression of non-alcoholic fatty liver disease (NAFLD). Evidence on its potential effect on the onset of disease are, however, scanty. With our study, we evaluated whether MD affects the risk of NAFLD with a large case-control study performed in Italy., Patients and Methods: Three hundred and seventy-one cases of NAFLD and 444 controls were questioned on the demographic data and their dietary habits before diagnosis. Additionally, information about lifestyles and other related diseases, such as hypertension and diabetes mellitus were collected. The MD adherence was assessed using a pre-defined Mediterranean Diet Score (MDS). Odds ratios (OR) and 95% confidence intervals (CI) were obtained using a multiple logistic regression model., Results: A high adherence to the MD is significantly associated with decreased risk of NAFLD (OR: 0.83 95% CI: 0.71-0.98). When the different MD components were examined separately, higher legumes consumption (OR: 0.62 95% CI: 0.38-0.99) and high fish consumption (OR 0.38 95% CI: 0.17-0.85) were reported to be protective against NAFLD., Conclusions: Our study shows that a high adherence to the MD decreases the risk of NAFLD.

The prevention of Legionella colonization of water systems is one of the goals of hospital management. Among chemical disinfection methods, chlorine dioxide (ClO 2 ) has been largely used to control Legionella spp. in water systems. We performed a retrospective study to analyse data deriving from the surveillance plan of the water system in a large academic hospital in Rome (Italy) during the period August 2011 and August 2018. We collected the data deriving from the routine water samples used to monitor Legionella spp. colonization. Data from the water samples collected from 163 selected sampling points (hot water tanks, the return loop and distal outlets) was analysed using a life table analysis in order to investigate the duration of the effectiveness of the ClO 2 method in eradicating Legionella spp. The colonization of the water sample by Legionella spp. was considered as the outcome. Our results show that in 81,59% of the sampling points Legionella spp. were never detected at four years of follow up. Chemical and physical characteristics of the water were also compared between the samples which were positive for Legionella spp. and those which were not. No association was found between these factors. The knowledge of the duration over time of the effectiveness of the ClO 2 disinfection method could support decision-making processes in the framework of Risk Management activities in hospitals. Future studies could also be conducted in hospitals to compare the long-term cost-effectiveness of different Legionella spp. colonization prevention methods., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The aims of this study were to identify the best threshold value for the real-time PCR method in detecting the presence of Legionella pneumophila in water samples, and to evaluate the prognostic significance of negative results obtained with the molecular method. From 2011 to 2014, 77 water samples were collected from hospital wards of a large University teaching hospital in Rome (Italy) and screened for L.pneumophila by the standard culture method and by real-time PCR. The high sensitivity and negative predictive value of real-time PCR make this method suitable as a quick screening tool to exclude the presence of L. pneumophila in water samples in the hospital setting.

Objective: Women affected by PCOS and psoriasis are more likely to have insulin-resistance, hyperinsulinemia, reduced HDL cholesterol levels and a more severe degree of skin disease than those with psoriasis alone. The mechanism underlying this association between PCOS and psoriasis is currently unknown. The aim of the present study was to evaluate the features of psoriasis and the psoriasis severity scores in the different PCOS phenotypes and in age and body mass index (BMI)-matched psoriatic control patients., Study Design: A cross-sectional study was performed on 150 psoriatic patients: 94 PCOS and 56 age- and BMI-matched controls. PCOS patients were diagnosed and divided into four phenotypes according to Rotterdam criteria: A - patients with complete phenotype with hyperandrogenism (H) plus oligoamenorrhea (O) plus polycystic ovary (PCO) on ultrasound examination; B - patients with H plus O (without PCO); C - patients with H plus PCO (ovulatory phenotype); D - patients with O plus PCO (without H). The patient's Psoriasis Area and Severity Index (PASI) as well as the Physician's Global Assessment (PGA) were calculated. A PASI score ≥10 was correlated with common indicator of severe disease. A PGA ≥4 was considered as a condition of moderate to severe disease., Results: Among the four phenotypes investigated, the group with complete phenotype (H plus O plus PCO) had a higher prevalence of patients with patient's PASI ≥10 compared to controls (Odds Ratio (OR) 4.71, 95% confidence intervals (CI) 1.59-13.95). The group with O plus PCO had a higher prevalence of patients with PGA ≥4 compared to controls (OR 26.79, 95% CI 3.40-211.02) while the ovulatory group had a lower prevalence of patients with PGA ≥4 (OR 0.06, 95% CI 0.01-0.51)., Conclusions: The ovulatory phenotype displays a milder psoriasis form than other phenotypes while the phenotypes with oligoamenorrhea presented higher severity scores of disease than other phenotypes and control group., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

We describe an outbreak of Candida albicans systemic infection involving five premature infants in a neonatal intensive care unit. Molecular and epidemiologic characterization of all C. albicans isolates was performed by DNA fingerprinting with the 27A probe. This genotypic analysis demonstrated that the isolates were identical, providing evidence for the circulation of a unique C. albicans strain.