Effect of Different Antitumor Regimens on Incidence and Severity of Corona Virus Disease 2019 Pneumonia in Lung Cancer Patients: A Single-center Retrospective Study / 中国肺癌杂志

BACKGROUND@#Studies have shown that the incidence and severity of corona virus disease 2019 (COVID-19) in patients with lung cancer are higher than those in healthy people. At present, the main anti-tumor treatments for lung cancer include surgery, immunotherapy, chemotherapy, radiotherapy, targeted therapy and anti-angiogenesis therapy. While the effects of different anti-tumor treatments on the occurrence and severity of COVID-19 pneumonia are not uniform. Therefore, we aimed to describe clinical characteristics and antitumor therapy of patients with lung cancer and COVID-19 pneumonia, and examined risk factors for severity in this population.@*METHODS@#From December 1, 2022 to February 15, 2023, a retrospective study was conducted in 217 patients diagnosed with COVID-19 and pathologically confirmed lung cancer in the Jinling Hospital. We collected data about patients' clinical features, antitumor treatment regimen within 6 months, and the diagnosis and treatment of COVID-19. Risk factors for occurrence and severity of COVID-19 pneumonia were identified by univariable and multivariable Logistic regression models.@*RESULTS@#(1) Among the 217 patients included, 51 (23.5%) developed COVID-19 pneumonia, of which 42 (82.4%) were classified as medium and 9 (17.6%) were classified as severe; (2) Univariate and multivariate analysis revealed overweight (OR=2.405, 95%CI: 1.095-5.286) and intrapulmonary focal radiotherapy (OR=2.977, 95%CI: 1.071-8.274) are risk factors for increasing occurrence of COVID-19 pneumonia, while other therapies are not; (3) Chronic obstructive pulmonary disease (COPD) history (OR=7.600, 95%CI: 1.430-40.387) was more likely to develop severe pneumonia and anti-tumor therapies such as intrapulmonary focal radiotherapy, chemotherapy, targeted therapy and immunotherapy did not increase severity.@*CONCLUSIONS@#Intrapulmonary focal radiation therapy within 6 months increased the incidence of COVID-19 pneumonia, but did not increase the severity. However, there was no safety concern for chemotherapy, targeted therapy, surgery and immunotherapy.

Atrial fibrillation in critically ill patients who received prolonged mechanical ventilation: a nationwide inpatient report

Background/Aims@#To evaluate temporal trends of atrial fibrillation (AF) prevalence in critically ill patients who received prolonged mechanical ventilation (MV) in the United States. @*Methods@#We used the 2008 to 2014 National Inpatient Sample to compute the weighted prevalence of AF among hospitalized adult patients on prolonged MV. We used multivariable-adjusted models to evaluate the association of AF with clinical factors, in-hospital mortality, hospitalization cost, and length of stay (LOS). @*Results@#We identified 2,578,165 patients who received prolonged MV (21.27% of AF patients). The prevalence of AF increased from 14.63% in 2008 to 24.43% in 2014 (p for trend < 0.0001). Amongst different phenotypes of critically ill patients, the prevalence of AF increased in patients with severe sepsis, asthma exacerbation, congestive heart failure exacerbation, acute stroke, and cardiac arrest. Older age, male sex, white race, medicare access, higher income, urban teaching hospital setting, and Western region were associated with a higher prevalence of AF. AF in critical illness was a risk factor for in-hospital death (odds ratio, 1.13; 95% confidence interval, 1.11 to 1.15), but in-hospital mortality in critically ill patients with AF decreased from 11.6% to 8.3%. AF was linked to prolonged LOS (2%, p < 0.0001) and high hospitalization cost (4%, p < 0.0001). LOS (–1%, p < 0.0001) and hospitalization cost (–4%, p < 0.0001) decreased yearly. @*Conclusions@#The prevalence of comorbid AF is increasing, particularly in older patients. AF may lead to poorer prognosis, and high-quality intensive care is imperative for this population.

Introduction of joint model and its applications in medical research / 中华流行病学杂志

In medical follow-up studies, longitudinal data and survival data are often accompanied and associated with each other, thus respective analysis of longitudinal and survival data might lead to biased results. Joint model can correct deviations, improve the efficiency of parameter estimation and provide effective inferences by simultaneously processing longitudinal and survival data. It is a popular method in medical research. Joint model has made much progress, whereas the literature about the joint model and its application is limited in China. This paper summarizes the main idea, basic framework, parameter estimation methods of random effect joint model and introduces the analysis on AIDS data set based on the R software package 'JM’ to clarify the advantages of the joint model in processing medical follow-up data and promote the use of the joint model in clinical research.