Knowledge, Attitude, and Practice of Insulin Pump Among Non-Endocrinology Nurses in South China.

Purpose: To investigate the knowledge, attitude, and practice (KAP) on insulin pump among non-endocrinology nurses in Southern China. Methods: This multicenter cross-sectional study enrolled non-endocrinology nurses in Southern China between November 2020 and December 2020. A structured questionnaire about insulin pumps was designed and used to collect data. Results: A total of 1118 nurses from 29 hospitals participated in the study. The majority of them were female (98.48%), and 513 worked in the department of internal medicine (45.89%), followed by surgery (235, 21.00%), pediatrics (147, 13.14%), gynecology (127, 11.35%), and oncology (96, 8.71%). None of the nurses answered all questions correctly in the knowledge section. The score of knowledge was 50.12 ± 3.42 (total score range, 0 to 85). The attitude score of nurses in the department of gynecology was 47.76 ± 5.11 (total score range, 10 to 50), followed by nurses in the department of internal medicine (47.43 ± 4.65), pediatrics (46.71 ± 4.96), surgery (46.77 ± 5.78) and oncology (46.25 ± 5.87). The practice score of nurses in the internal medicine department was 79.16 ± 9.03 (total score range, 17 to 85), followed by nurses in the department of gynecology (78.76 ± 10.76), surgery (78.14 ± 10.09), oncology (76.89 ± 12.70) and pediatrics (73.35 ± 19.04). Conclusion: There was limited knowledge regarding insulin pumps among nurses, although they had a positive attitude and attached importance to the management of insulin pumps. In clinical practice, their implementation of insulin pump management norms was acceptable.

Exploring the Temporal Correlation of Sarcopenia with Bone Mineral Density and the Effects of Osteoblast-Derived Exosomes on Myoblasts through an Oxidative Stress-Related Gene.

Sarcopenia is an age-related accelerated loss of muscle strength and mass. Bone and muscle are closely related as they are physically adjacent, and bone can influence muscle. However, the temporal association between bone mineral density (BMD) and muscle mass in different regions of the body after adjustment for potential indicators and the mechanisms by which bone influences muscle in sarcopenia remain unclear. Therefore, this study aimed to explore the temporal association between muscle mass and BMD in different regions of the body and mechanisms by which bone regulates muscle in sarcopenia. Here, cross-lagged models were utilized to analyze the temporal association between BMD and muscle mass. We found that low-density lipoprotein (LDL-C) positively predicted appendicular lean mass. Mean whole-body BMD (WBTOT BMD), lumbar spine BMD (LS BMD), and pelvic BMD (PELV BMD) temporally and positively predicted appendicular lean mass, and appendicular lean mass temporally and positively predicted WBTOT BMD, LS BMD, and PELV BMD. Moreover, this study revealed that primary mice femur osteoblasts, but not primary mice skull osteoblasts, induced differentiation of C2C12 myoblasts through exosomes. Furthermore, the level of long noncoding RNA (lncRNA) taurine upregulated 1 (TUG1) was decreased, and the level of lncRNA differentiation antagonizing nonprotein coding RNA (DANCR) was increased in skull osteoblast-derived exosomes, the opposite of femur osteoblast-secreted exosomes. In addition, lncRNA TUG1 enhanced and lncRNA DANCR suppressed the differentiation of myoblasts through regulating the transcription of oxidative stress-related myogenin (Myog) gene by modifying the binding of myogenic factor 5 (Myf5) to the Myog gene promoter via affecting the nuclear translocation of Myf5. The results of the present study may provide novel diagnostic biomarkers and therapeutic targets for sarcopenia.

Computerized Tomography Image Feature under Convolutional Neural Network Algorithm Evaluated for Therapeutic Effect of Clarithromycin Combined with Salmeterol/Fluticasone on Chronic Obstructive Pulmonary Disease.

This study was to explore the use of convolutional neural network (CNN) for the classification and recognition of computerized tomography (CT) images of chronic obstructive pulmonary disease (COPD) and the therapeutic effect of clarithromycin combined with salmeterol/fluticasone. First, the clinical data of COPD patients treated in hospital from September 2018 to December 2020 were collected, and CT and X-ray images were also collected. CT-CNN and X ray-CNN single modal models were constructed based on the LeNet-5 model. The randomized fusion algorithm was introduced to construct a fused CNN model for the diagnosis of COPD patients, and the recognition effect of the model was verified. Subsequently, the three-dimensional reconstruction of the patient's bronchus was performed using the classified CT images, and the changes of CT quantitative parameters in COPD patients were compared and analyzed. Finally, COPD patients were treated with salmeterol/fluticasone (COPD-C) and combined with clarithromycin (COPD-T). In addition, the differences between patients' lung function indexes, blood gas indexes, St. George respiratory questionnaire (SGRQ) scores, and the number of acute exacerbations (AECOPD) before and after treatment were evaluated. The results showed that the randomized fusion model under different iteration times and batch sizes always had the highest recognition rate, sensitivity, and specificity compared to the two single modal CNN models, but it also had longer training time. After CT images were used to quantitatively evaluate the changes of the patient's bronchus, it was found that the area of the upper and lower lung lobes of the affected side of COPD patients and the ratio of the area of the tube wall to the bronchus were significantly changed. The lung function, blood gas index, and SGRQ score of COPD-T patients were significantly improved compared with the COPD-C group (P < 0.05), but there was no considerable difference in AECOPD (P > 0.05). In summary, the randomized fusion-based CNN model can improve the recognition rate of COPD, and salmeterol/fluticasone combined with clarithromycin therapy can significantly improve the clinical treatment effect of COPD patients.

The efficacy and safety of agomelatine, sertraline, and escitalopram for senile post-stroke depression: A randomized double-blind placebo-controlled trial.

OBJECTIVES: This study aims to investigate the efficacy and safety of agomelatine, sertraline, and escitalopram for patients with senile post-stroke depression (SPSD, aged over 65 years). PATIENTS AND METHODS: A total of 165 patients (aged over 65 years) with post-stroke depression (PSD) were recruited. These patients were randomly assigned to one of four groups and given an anti-depressant or a placebo as follows: group A (agomelatine in combination with conventional cerebrovascular disease medication) 48 patients; group B (sertraline in combination with conventional cerebrovascular disease medication) 47 patients; group C (escitalopram in combination with conventional cerebrovascular disease medication) 50 patients; and, a control group (conventional treatment alone) 20 patients. The efficacy of the different treatments was evaluated using the Hamilton Depression Scale (HAMD), the National Institute of Health Stroke Scale (NIHSS), and the Activities of Daily Living (ADL) Barthel index (BI) at one, two, four, and six weeks after treatment began. RESULTS: According to the HAMD, NIHSS score, and BI index, the patients who received one of the three antidepressant treatments showed significant improvement compared with the control group (p < 0.05), but there was no significant difference between the three groups receiving anti-depressant medication (p > 0.05). Laboratory tests showed that the general adverse effects of the treatments were mild in all three groups, and patients generally tolerated the treatments. CONCLUSION: A decrease of HAMD and NIHSS scores and an increase in the BI index could be observed in the patients receiving agomelatine, sertraline, or escitalopram treatment. Thus, it would appear that the condition of SPSD in older patients can be improved with the use of either agomelatine, sertraline, or escitalopram.