Christiansunesen7764

We describe a unique phenotype of paraneoplastic arthritis (PA) presenting as a seropositive (RF and ACPA positivity) rheumatoid arthritis (RA) with a good response to both low dose corticosteroids and hydroxychloroquine therapy. We also review the literature of PA, mostly the RA-like pattern, and the association between PA and ACPA positivity. This case highlights the importance of considering underlying cancer in elderly male patients, presenting with polyarthritis and systemic symptoms, even in those with ACPA-positive RA-like arthritis.Objective We aimed to explore the dynamic changes in coagulation function and the effect of age on coagulation function in patients with pneumonia under admission and non-admission treatment. Methods We included 178 confirmed adult inpatients with COVID-19 from Wuhan Union Hospital Affiliated to Huazhong University of Science and Technology (Wuhan, China). Patients were classified into common types, and all were cured and discharged after hospitalization. We recorded the time of the first clinical symptoms of the patients and performed blood coagulation tests at the time of admission and after admission. In total, eight factors (TT, FIB, INR, APTT, PT, DD, ATIII, and FDP) were analyzed. Patients were classified into four groups according to the time from the first symptom onset to hospital admission for comparative analysis. The patients who were admitted within 2 weeks of disease onset were analyzed for the dynamic changes in their blood coagulation tests. Further division into two groups, one group comprisispital, the most significant decreases among the eight factors were between week 2 and 3. There were distinct differences among the eight factors between people older than 55 years and those younger than 55 years. In the first 2 weeks after being admitted, the levels of the eight factors in patients >55 years were significantly higher than those in patients less then 55 years, and after another 2 weeks of treatment, the factor levels in both age groups returned to normal. Conclusion The eight factors all increased within 2 weeks after onset and gradually decreased to normal after 2 weeks regardless of treatment. Compared with patients younger than 55 years, patients older than 55 years have greater changes in their blood coagulation test values.Purpose This systematic review is conducted to explore the relationship between fragility fractures and pain experience. Methods We searched for relevant studies on Pubmed, Embase, Web of Science, and the Cochrane library without restrictions on language from inception until February 4th, 2021. The risk of bias and methodological quality was evaluated using the Newcastle-Ottawa Scale and ROBINS-I tool. Results Twenty-one studies were included in this systematic review. The so-called study reported participants with continuous post-fracture pain. The included studies showed that post- fractured pain can decrease with time, however, the continual pain can last at least 1 year even longer, and some participants would need to self-manage pain. Moreover, the limited range of motion was considered as a factor that might distress the normal development of daily activities. Conclusions The current evidence could not fully support that pain continues to influence patients' lives after a fragility fracture. However, it still showed the pain might come with fracture. The findings also could be useful to help health care providers better recognize and manage this clinical consequence of fractures. Nonetheless, future large-scale longitudinal studies will be required to evaluate the long-term effects of pain in fragility fractures.Introduction Pancreatic cancer continues to have a poor outcome. Many patients are diagnosed with advanced disease, and in a considerable proportion, abutment or invasion of visceral arteries is present. Moreover, some patients have anatomical variations or stenosis of major visceral arteries requiring arterial reconstruction upon pancreatic cancer resection to avoid organ ischemia. Simultaneous arterial reconstruction during resection is associated with relevant morbidity and mortality. This trial evaluates the approach of visceral debranching, that is, arterial reconstruction, prior to neoadjuvant chemotherapy and tumor resection in patients with locally advanced, unresectable pancreatic cancer. Methods and Analysis The trial includes patients with locally advanced, non-metastatic pancreatic cancer with arterial abutment or invasion (deemed primarily unresectable), variations in vascular anatomy, or stenosis of visceral arteries. The participants undergo visceral debranching, followed by current standard neity. C75 trans Trial results will allow for estimating treatment effects and calculating the sample size of a randomized controlled trial, in which the approach will be tested if the feasibility endpoint is met. Clinical Trial Registration clinicaltrials.gov, identifier NCT04136769.Background The tumour immune microenvironment plays an important role in the biological mechanisms of tumorigenesis and progression. Artificial intelligence medicine studies based on big data and advanced algorithms are helpful for improving the accuracy of prediction models of tumour prognosis. The current research aims to explore potential prognostic immune biomarkers and develop a predictive model for the overall survival of ovarian cancer (OC) based on artificial intelligence algorithms. Methods Differential expression analyses were performed between normal tissues and tumour tissues. Potential prognostic biomarkers were identified using univariate Cox regression. An immune regulatory network was constructed of prognostic immune genes and their highly related transcription factors. Multivariate Cox regression was used to identify potential independent prognostic immune factors and develop a prognostic model for ovarian cancer patients. Three artificial intelligence algorithms, random survival forest, multredictive tools for ovarian cancer, which are available at https//zhangzhiqiao8.shinyapps.io/Smart_Cancer_Survival_Predictive_System_17_OC_F1001/ and https//zhangzhiqiao8.shinyapps.io/Gene_Survival_Subgroup_Analysis_17_OC_F1001/. An artificial intelligence survival predictive system could help improve individualised treatment decision-making.