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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.

Background: Health-related quality of life (QoL) has become a crucial outcome in medical care. However, few studies have assessed physician knowledge of QoL and rate of physicians adopting QoL measures in clinical practice. The present study aimed at assessing the level of knowledge of QoL and the perceived importance of incorporating QoL assessment in clinical practice among physicians of a tertiary level academic hospital in Rome, Italy., Materials and Methods: A survey study performed through the distribution of a questionnaire assessing knowledge of QoL studies that used the SF-36 scale, participation in studies evaluating QoL as well as knowledge of journals publishing articles on QoL Physicians and residents at the hospital Policlinico Gemelli, Catholic University of Rome., Results: Three-hundred nine physicians completed the questionnaire. Thirty-eight percent % reported knowing studies on QoL and using their results in clinical practice or for research purposes; 29% reported knowing the SF-36 questionnaire; 30% stated that at least one study assessing QoL had been conducted in their department. Fourty-six percent % stated that QoL must influence much or very much diagnostic choices and an even higher percentage reported that QoL must influence much or very much therapeutic and palliative strategies (70.8% and 91.3%, respectively). Reported barriers to the use of QoL measures in clinical practice were related to time constraints (8.7%) but also to doubts on methodological issues of QoL (30.7%). The large majority of physicians (94.3%) would have used more expensive drugs if these could improve QoL., Conclusions: The present study shows that in a tertiary level academic italian hospital one third of the physicians, reported to know QoL measures and that more than 80% of them would like to use QoL in their daily clinical practice. Future studies are needed to identify the best strategies to implement the use of QoL measures in clinical practice.

Reported are the results of a study on the incidence of nosocomial surgical infections in ten wards of the university hospital A. Gemelli, Rome. One thousand, five hundred five patients were studied and the overall incidence of surgical infections was 8.7%. Factors that influenced infection rates included age, immunosuppressive diseases, and immunosuppressive therapy. We assessed the inutility of antibiotic prophylaxis in clean operations and its usefulness in clean operations with insertion of prostheses or other devices. The importance of the duration of preoperative hospitalization and of the length of the operation were also noted. The most frequent etiological agents proved to be Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli. The average hospital stay for patients with surgical infection was more than double that of patients with no infection (25.7 days v 11.7 days).

The results of a study on the incidence of nosocomial infections in a 1800 bed University hospital are reported. The study, carried out over a 9 months period, included: continuous microbiological surveillance, and a clinical and epidemiological survey. On the basis of the microbiological data collected and analyzed by a computer data system, developed and employed for the control of nosocomial infections, a weekly bed-to-bed survey was carried out by the staff of the Institute of Infectious Diseases. Among 2777 suspected nosocomial infections, as revealed by microbiological monitoring, 701 were confirmed after the bed-to-bed survey. The nosocomial infection rate was 6.75 per 100 discharges. It was higher in the surgical than in the medical wards (7.3 and 6 per 100 discharges, respectively). Nosocomial urinary tract infections were the most frequent (74.2%). The urinary infection rate was higher in the surgical than in the medical wards (5.3 and 4.6 per 100 discharges, respectively). Escherichia coli (19.4%), Pseudomonas aeruginosa (19.3%), Proteus spp. (18.4%) were the pathogens most frequently associated with nosocomial infections. They were followed by Klebsiella pneumoniae (7.8%) and Staphylococcus aureus (6.5%) in frequency. Among the risk factors, involved in nosocomial infections, the importance of catheterization was confirmed: among our patients with nosocomial urinary tract infections, 73.4% and 79.5%--in the medical and surgical wards, respectively--underwent urological instrumentation, mainly catheterization. An analogous and more detailed study is now in progress and will be extended in the next years.