Background: With the emergence of the coronavirus disease 2019 (COVID-19) and inability of healthcare systems to control the disease, various therapeutic theories with controversial responses have been proposed. Plasmapheresis was administered as a medication.However, the knowledge of its efficacy and indications is inadequate. This study evaluated the use of plasmapheresis in critically ill patients with cancer. Methods: This randomized clinical trial was conducted on 86 patients with malignancies, including a control group (N=41) and an intervention group (N=45) with severe COVID-19 during 2020-21. Both groups were treated with routine medications for COVID-19 management according to national guidelines, and plasmapheresis was applied to the intervention group. C-reactive protein (CRP), D-dimer, ferritin, lactate dehydrogenase, hemoglobin, and white blood cell, polymorphonuclear, lymphocyte, and platelet levels were measured at admission and at the end of plasmapheresis. Other variables included neutrophil recovery, intensive care unit admission, intubation requirements, length of hospital stay, and hospitalization outcomes. Results: CRP (P ＜0.001), D-dimer (P ＜0.001), ferritin (P =0.039), and hemoglobin (P =0.006) levels were significantly different between the groups after the intervention. Neutrophil recovery was remarkably higher in the case than in the control group (P ＜0.001). However, plasmapheresis did not affect the length of hospital stay (P =0.076), which could have significantly increased survival rates (P ＜0.001). Conclusion Based on the study findings, plasmapheresis led to a significant improvement in laboratory markers and survival rate in patients with severe COVID-19. These findings reinforce the value of plasmapheresis in cancer patients as a critical population suffering from neutropenia and insufficient immune responses.

BACKGROUND: Musculoskeletal symptoms often occur in more than one anatomical site. The present study aimed to define specific patterns of multisite musculoskeletal disorders and examine how these patterns are related to common psychological problems. METHODS: Using the data from an interview-based health survey of 358 samples of the industrial manufacturing male employees, we derived major patterns of musculoskeletal complaints using latent class analysis and investigated its association with psychological problems score extracted from depression, anxiety, and stress measured by Depression/Anxiety/Stress Scale (DASS-21). Musculoskeletal disorders were assessed by Nordic Musculoskeletal Questionnaire (NMQ). The statistical analysis was carried out by Mplus 8. RESULTS: Complaints in the lower back (42.1%) and neck (30.7%) had the highest prevalence, and in the hip (15.0%) and ankle (12.2%) the lowest. Three major patterns of musculoskeletal disorders were extracted using latent class analysis. Class 1 (12.9%) was characterized by a high rate of complaints in upper musculoskeletal sites, such as the neck, shoulder, and joints; class 2 (38.2%) was identified by a higher rate of complaints in the lower and upper back; and class 3 (48.9%) was marked by low rates of complaints in all musculoskeletal sites. After adjustment for confounding variables and specifying class 3 as the reference, it turned out that there was a statistically significant association between the psychological problems score and the chance of being in class 1 (OR = 2.47, 95% CI 1.66-3.68), but not a significant association with the chance of being in class 2 (OR = 1.51, 95% CI 0.83-2.72). CONCLUSION Musculoskeletal disorders can be summarized in the latent class-derived patterns in the adult study population and provide additional prognostics. Common psychological problems are significantly associated with the type of musculoskeletal disorder patterns. The findings in this study could be useful for dealing with prevention and treatment programs.
Adult ; Anxiety ; epidemiology ; Cross-Sectional Studies ; Depression ; epidemiology ; Health Surveys ; Humans ; Iran ; epidemiology ; Latent Class Analysis ; Male ; Manufacturing Industry ; statistics & numerical data ; Middle Aged ; Musculoskeletal Diseases ; classification ; epidemiology ; psychology ; Occupational Diseases ; classification ; epidemiology ; psychology ; Prevalence ; Stress, Psychological ; epidemiology