Ricerc@Sapienza

Since the most frequent symptoms of novel coronavi- rus 2019 disease (COVID-19) are common in influenza A/B (FLU), predictive models to distinguish between COVID-19 and FLU using standardized non-specif- ic laboratory indicators are needed. The aim of our study was to evaluate whether a recently dynamic nomogram, established in the Chinese population and based on age, lymphocyte percentage and monocyte absolute count, might apply to a different context. We collected data from 299 patients (243 with COVID-19 and 56 with FLU) at Policlinico Umberto I, Sapienza University of Rome.

This study aimed to identify clinicopathological factors associated with the outcome of elderly patients with gastric cancer (GC), and to construct a nomogram for individual risk prediction. Tumor characteristics of 143 patients aged ≥ 80 years underwent surgery for GC were collected and analyzed by uni- and multivariate analyses. A prognostic nomogram was constructed using the factors which resulted to be significantly associated with overall survival. Discrimination of nomogram was tested by Kaplan-Meier (KM) curves and boxplots.