Prediction of 28-day mortality in critically ill patients with COVID-19: Development and internal validation of a clinical prediction model.

BACKGROUND: COVID-19 pandemic has rapidly required a high demand of hospitalization and an increased number of intensive care units (ICUs) admission. Therefore, it became mandatory to develop prognostic models to evaluate critical COVID-19 patients. MATERIALS AND METHODS: We retrospectively evaluate a cohort of consecutive COVID-19 critically ill patients admitted to ICU with a confirmed diagnosis of SARS-CoV-2 pneumonia. A multivariable Cox regression model including demographic, clinical and laboratory findings was developed to assess the predictive value of these variables. Internal validation was performed using the bootstrap resampling technique. The model's discriminatory ability was assessed with Harrell's C-statistic and the goodness-of-fit was evaluated with calibration plot. RESULTS: 242 patients were included [median age, 64 years (56-71 IQR), 196 (81%) males]. Hypertension was the most common comorbidity (46.7%), followed by diabetes (15.3%) and heart disease (14.5%). Eighty-five patients (35.1%) died within 28 days after ICU admission and the median time from ICU admission to death was 11 days (IQR 6-18). In multivariable model after internal validation, age, obesity, procaltitonin, SOFA score and PaO2/FiO2 resulted as independent predictors of 28-day mortality. The C-statistic of the model showed a very good discriminatory capacity (0.82). CONCLUSIONS: We present the results of a multivariable prediction model for mortality of critically ill COVID-19 patients admitted to ICU. After adjustment for other factors, age, obesity, procalcitonin, SOFA and PaO2/FiO2 were independently associated with 28-day mortality in critically ill COVID-19 patients. The calibration plot revealed good agreements between the observed and expected probability of death.

The deep impact of novel CoVID-19 infection in an Orthopedics and Traumatology Department: the experience of the Piacenza Hospital.

Since February 21st, 2020 CoVID-19 spread throughout all Italy expanding like a "tsunami" from Codogno (Lodi, Lombardy, Northern Italy) to neighboring cities. In a few days Lodi, Piacenza, Milano, Brescia and Bergamo were forced to deal with this disaster starting the lockdown at different time. No national plan had been prepared. As result, CoVID-19 has paralyzed the Italian healthcare system. At time of writing, in Italy there are 169 323 infected patients and 22 260 deaths. Italy is fighting hard to manage CoVID-19 crisis even if most hospitals were unprepared to deal with massive influx of critically ill CoVID-19 patients. Piacenza in Emilia-Romagna region (Northern Italy) is one of the epicenters of the Italian pandemic, and the local hospital - Guglielmo da Saliceto - has quickly become a "CoVID-19 hospital" with the great effort of all the medical staff. Here we report the experience of our hospital, particularly the strategy adopted in the Orthopedics and Traumatology Department.

Cancer patients with COVID-19: a retrospective study of 51 patients in the district of Piacenza, Northern Italy.

BACKGROUND: Cancer patients are considered a highly fragile group in the current coronavirus disease 2019 (COVID-19) pandemic. MATERIAL & METHODS: In this study, patients with COVID-19 and cancer, hospitalized in Piacenza, Italy, from 4 April to 4 May 2020 were included. Risk factors for death were analyzed. RESULTS: Fifty-one COVID-19 cancer patients were included, of which the median age was 71.02 years (range: 51-86) and 70.59% were male. Cancer types included gastrointestinal (25.49%), genitourinary (25.49%) and lung (23.53%). Forty-five (88.24%) patients received hydroxychloroquine-based therapy. In addition, 25 of 51 patients died (49%): 12 of 51 (23.53%) owing to cancer and 13 of 51 (25.49%) owing to COVID-19. CONCLUSION: The risks for death were related to later onset of treatment for COVID-19, severe/critical COVID-19, age, elevated basal CRP and elevated lactate dehydrogenase.