Objective To explore the challenges in sedentary behavior modification among patients with lower extremity arteriosclerosis obliterans(ASO),with the goal of informing the development of personalized physical acti-vity interventions to address sedentary behavior patterns.Methods A purposive sample of 16 patients diagnosed with lower extremity ASO was recruited as participants from the department of vascular surgery at a tertiary hospital in Sichuan province between August and November 2024.Semi-structured interviews were conducted to collect data and the Colaizzi 7 steps was used to analyze the data based on Capacity-Opportunity-Motivation-Behavior model.Results 3 themes and 12 sub-themes were identified,namely capacity(lower extremity and somatic dysfunction,psychological perception constraints,disease literacy deficits),motivation(inadequate perceived value of physical activity,diminished self-efficacy,kinesiophobia,negative cognitive framing),opportunity(generalization of guidance on disease knowledge,constrained healthcare resources,the normalization of sedentary entertainment practices,financial burden constraints,inadequate family support).Conclusion The factors influencing sedentary behavior in ASO patients are complex and diverse.Healthcare professionals need to comprehensively assess the multifaceted factors contributing to patients' difficulties in changing sedentary behavior,and develop targeted strategies accordingly to promote improvements in their sedentary habits.

Objective To explore the challenges in sedentary behavior modification among patients with lower extremity arteriosclerosis obliterans(ASO),with the goal of informing the development of personalized physical acti-vity interventions to address sedentary behavior patterns.Methods A purposive sample of 16 patients diagnosed with lower extremity ASO was recruited as participants from the department of vascular surgery at a tertiary hospital in Sichuan province between August and November 2024.Semi-structured interviews were conducted to collect data and the Colaizzi 7 steps was used to analyze the data based on Capacity-Opportunity-Motivation-Behavior model.Results 3 themes and 12 sub-themes were identified,namely capacity(lower extremity and somatic dysfunction,psychological perception constraints,disease literacy deficits),motivation(inadequate perceived value of physical activity,diminished self-efficacy,kinesiophobia,negative cognitive framing),opportunity(generalization of guidance on disease knowledge,constrained healthcare resources,the normalization of sedentary entertainment practices,financial burden constraints,inadequate family support).Conclusion The factors influencing sedentary behavior in ASO patients are complex and diverse.Healthcare professionals need to comprehensively assess the multifaceted factors contributing to patients' difficulties in changing sedentary behavior,and develop targeted strategies accordingly to promote improvements in their sedentary habits.

Objective:To investigate the clinical characteristics of elderly patients with coronavirus disease 2019(COVID-19), in order to provide scientific evidence for the diagnosis and treatment of COVID-19 in elderly patients.Methods:Clinical data of 102 patients with COVID-19 admitted to the B11 East Ward of the Zhongfaxincheng campus and the E1-3 ward of the Guanggu Campus of Tongji Hospital affiliated to Huazhong University of Science and Technology in Wuhan from 1 February 2020 to 28 February 2020 were retrospectively collected and analyzed.Patients were categorized into 2 groups: the elderly group(≥60 years old)and the young and middle-aged group(<60 years old). Differences in epidemiological features, demographics, clinical symptoms, laboratory results and imaging findings between the two groups were retrospectively analyzed.Results:Among 102 patients with COVID-19, 58 were in the elderly group(≥60 years old), with a median age of 67.0(63.8, 71.0)years old, and 44 in the young and middle-aged group(<60 years old), with a median age of 47.5(38.0, 51.8)years old.There was no significant difference in gender ratio between the two groups( χ2=0.033, P=0.855). Of 102 patients, 42.0%(21/50)had close contact with an infected person, 14.0%(7/50)were from infection clusters, and 18.0%(9/50)had suspected hospital-acquired infections.Fever and cough remained the most common symptoms, but gastrointestinal symptoms such as nausea, poor appetite, diarrhea and muscle cramps were also warning signs.Fatigue and cough were the most common presenting symptoms in elderly male patients.Bilateral patchy infiltrates(57.9%, 22/38)and ground-glass opacities(42.1%, 16/38)were the main imaging features and 42.1%(16/38)patients had multiple areas of the lungs involved.Over 50% patients had increased levels of blood glucose, D-dimer, fibrinogen, C-reactive protein, procalcitonin, multiple cytokines and neutrophil-to-lymphocyte ratio, as well as decreased levels of albumin, hemoglobin, hematocrit, lymphocytes and serum calcium.Compared with the young and middle-aged group, the elderly group had higher rates of abnormality in levels of D-dimer and serum calcium( χ2=7.067 and 4.166, P=0.008 and 0.041). Conclusions:Fever and cough are the most common symptoms in elderly patients with COVID-19.Elderly patients with COVID-19 have multiple abnormalities in clinical laboratory test results, which show a certain level of specificity compared with young and middle-aged patients.

Objective To understand the internal circuit contamination of ventilator in mechanical ventilation patients, to evaluate the effect of ventilator internal circuit disinfection and the impact on the incidence of ventilator-associated pneumonia (VAP). Methods A total of 39 patients with mechanical ventilation admitted to intensive care unit (ICU) of Hangzhou Geriatric Hospital from January 2017 to June 2018 were enrolled. Routine mechanical ventilation treatments for patients included pipeline replacement, aseptic operation, prevention of infection, etc. After 2 weeks of mechanical ventilation, the internal circuit of the ventilator was disinfected using the internal circuit sterilizer of the ventilator. Microorganism sampling and detection at 3 cm to the exhalation port of the internal circuit of the ventilator was performed before and after disinfection. The number of colonies was < 5 cfu/cm2 and no pathogenic bacteria could be detected. During the observation period, if the patient was complicated by VAP for anti-infective treatment, the ventilator with internal loop disinfection was replaced after infection control, and was incorporated again into the group for observation. The number of microbial colonies in the internal circuit of the ventilator before and after disinfection, the microbiological test pass rate and the incidences of VAP during the 2 weeks were observed. Results All 39 patients were included in the analysis, with 23 male and 16 female; with age of 65-97 years old, average (78.7±7.6) years old. Before the disinfection, 9 604 strains were detected in the internal circuit of the ventilator, including 8 687 strains of Gram-negative bacilli (90.4%), 902 strains of Gram-positive cocci (9.4%), and 15 strains of fungi (0.2%), which were detected in the lower respiratory tract of the patients. The strain concordance rate was 41%. The qualified rate of microbial detection in the internal circuit of the ventilator was 5.1%; 13 cases (33.3%) of VAP occurred during 2 weeks of mechanical ventilation. After disinfection, 785 strains of pathogens were detected in the internal circuit of the ventilator, and the number of colonies was significantly reduced compared with that before disinfection [cfu/cm2: 0 (0, 20) vs. 150 (15, 500), P < 0.01], of which 688 strains of Gram-negative bacilli (87.7%), 92 strains of Gram-positive cocci (11.7%) and 5 strains of fungi (0.6%) were found; the qualified rate of microbial detection in the internal circuit of ventilator reached 71.8%, which was significantly higher than that before disinfection (P < 0.01); 2 weeks after mechanical ventilation the incidence of VAP decreased slightly during the period [20.5% (8/39) vs. 33.3% (13/39)], but there was no significant difference (P > 0.05). Conclusions The internal circuit of the ventilator can be used to detect the pathogen and the sputum culture of the patients on mechanical ventilation with a high consistency. The disinfection of the pathogen could significantly reduce the air pollution of the ventilator and reduce the occurrence of VAP in the patients.