Is it really advantageous to operate proximal femoral fractures within 48 h from diagnosis? – A multicentric retrospective study exploiting COVID pandemic-related delays in time to surgery

Objectives: Hip fractures in the elderly are common injuries that need timely surgical management. Since the beginning of the pandemic, patients with a proximal femoral fracture (PFF) experienced a delay in time to surgery. The primary aim of this study was to evaluate a possible variation in mortality in patients with PFF when comparing COVID-19 negative versus positive. Methods: This is a multicentric and retrospective study including 3232 patients with PFF who underwent surgical management. The variables taken into account were age, gender, the time elapsed between arrival at the emergency room and intervention, pre-operative American Society of Anesthesiology score, pre-operative cardiovascular and respiratory disease, and 10-day/1-month/6-month mortality. For 2020, we had an additional column, “COVID-19 swab positivity.” Results: COVID-19 infection represents an independent mortality risk factor in patients with PFFs. Despite the delay in time-to-surgery occurring in 2020, no statistically significant variation in terms of mortality was detected. Within our sample, a statistically significant difference was not detected in terms of mortality at 6 months, in patients operated within and beyond 48 h, as well as no difference between those operated within or after 12/24/72 h. The mortality rate among subjects with PFF who tested positive for COVID-19 was statistically significantly higher than in patients with PFF who tested. COVID-19 positivity resulted in an independent factor for mortality after PFF. Conclusion: Despite the most recent literature recommending operating PFF patients as soon as possible, no significant difference in mortality was found among patients operated before or after 48 h from diagnosis

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages