Changes in inpatient admissions before and during COVID-19 outbreak in a large tertiary hospital in Shanghai

Abstract

Background: The coronavirus disease 2019 outbreak caused a significant strain on healthcare resources and utilization worldwide. However, the impact of COVID-19 outbreak on patient hospitalization was barely known. This study aimed to determine the impact of the outbreak on the pattern of inpatient hospital admissions to help allocate health care resources during a pandemic.Methods: This retrospective study included patients who were hospitalized in a tertiary teaching hospital

Health and lifestyle parameters in peripheral artery disease at two periods of the COVID-19 pandemic: comparison between men and women

“…It is important to highlight that the causes of hospitalization one year after the onset of the COVID-19 pandemic are unclear in subjects with or without PAD. Studies (23)(24)(25)(26) performed on adult subjects without PAD and COVID-19 from different countries during the COVID-19 pandemic (i.e., until August 2020), but without comparing the sex, observed that falls, respiratory disease, stroke, cardiac diseases (i.e., acute myocardial infarction and heart failure), kidney disease, oncological diseases, and metabolic/endocrine diseases have been the causes of hospitalization. This suggests that the same phenomenon may have also occurred longitudinally (i.e., between May and August 2021) in patients with PAD.…”

A dynamic nomogram to predict invasive fungal super-infection during healthcare-associated bacterial infection in intensive care unit patients: an ambispective cohort study in China

“…Our study included a large number of critically ill patients over four and a half years, and ruled out the peak period of COVID-19 infection. Since most of the patients admitted to ICU during this period had COVID-19, the disease spectrum (Yang et al, 2022), clinical treatment pathways (Cai et al, 2022), and HAI prevention and control measures differed to some extent from those of conventional period (Grasselli et al, 2021), which would interfere with the temporal extrapolation of our findings (ie, the prevalence and microbiological characteristics of IFSI, the application of dynamic nomogram). Secondly, from both variable selection and model evaluation, we looked for the optimal model with concise predictors and proper predictive performance: (1) Two variable selection methods which can effectively eliminate multicollinearity and reduce dimension for a large number of variables were adopted.…”

Predictors of Medical Care Delay or Avoidance Among Chinese Adults During the COVID-19 Pandemic

“…Please answer by picking a number between 0 and 10, where 0 stands for not at all and 10 for completely" (An 11-point Likert scale). For the analysis, we have categorized reported levels of general trust in physicians into three groups: low level of trust (0-3), medium level of trust (4)(5)(6), and high level of trust (7)(8)(9)(10). The present study measured the perceived quality of care from provider competence and structural quality.…”

“…[2][3][4] During the COVID-19 pandemic, COVID-19-related factors such as stay-at-home orders, physical distancing measures, and fears of COVID-19 within hospitals have prompted people to delay or avoid seeking medical care. 5,6 Figure 1 shows the proportion of medical care delay or avoidance before and during the COVID-19 pandemic in China. Medical care delay or avoidance has been observed to increase during pandemics.…”