Objective:To explore the relationship between glycosylated hemoglobin A 1c/high-density lipoprotein cholesterol ratio (HbA 1c/HDL-C) and urinary albumin-creatinine ratio (UACR) in Chinese adults. Methods:In this cross-sectional study, the clinical data of 43 820 community residents (age>40 years) from the Risk Evaluation of Cancers in Chinese Diabetic Individuals (REACTION study; March-December 2012) across eight centers (Liaoning, Guangdong, Shanghai, Gansu, Guangxi, Henan, Hubei, and Sichuan) in China were collected and analyzed. Participants were divided into three groups based on UACR levels:<10 mg/g, 10-30 mg/g, and >30 mg/g. The HbA 1c/HDL-C ratio was divided into four groups according to quartile division of the subjects: 1st quartile (Q1<3.79), 2nd quartile (3.79≤Q2<4.59), 3rd quartile (4.59≤Q3≤5.66), and 4th quartile (Q4>5.66). Multivariate ordinal logistic regression model was used to analyze the relationship between HbA 1c/HDL-C and UACR. Receiver operating characteristic (ROC) analysis was used to explore the predictive value of HbA 1c/HDL-C to UACR. Results:The 43 820 subjects included 13 452 (30.70%) male and 30 378 (69.30%) female patients, with an average age of (58.00±0.05) years. According to results of one-way analysis of variance analysis, the HbA 1c/HDL-C ratio was significantly associated with the risk of increased UACR ( F=495.73, P<0.001). After adjusting for clinically relevant confounding variables in logistic regression model, compared with participants with the lowest HbA 1c/HDL-C ratio (Q1), women with the highest HbA 1c/HDL-C ratio (Q4) had a 1.483-fold (95% CI 1.376-1.598, P<0.001) and men had a 1.161-fold (95% CI 1.019-1.323, P<0.001) increased risk of UACR. The ROC curve analysis showed that the area under the curve of HbA 1c/HDL-C for predicting increased UACR was 0.623 (95% CI 0.597-0.606), with a sensitivity of 60.18% and a specificity of 54.91%. The HbA 1c/HDL-C ratio showed the highest predictive value of all glycemic and lipidemic parameters. In individuals with well-controlled blood glucose (HbA 1c<6.5%) or lipid levels (HDL-C≥1.0 mmol/L), the HbA 1c/HDL-C ratio was still independently associated with the risk of increased UACR after adjusting for confounding variables [ OR(95% CI) of quartile 4: 1.563 (1.210-2.019, P=0.001) in participants with HbA 1c<6.5% and 1.822 (1.687-1.968, P<0.001) in participants with HDL-C≥1.0 mmol/L]. Conclusion:As a novel compound indicator for evaluating glucose homeostasis and dyslipidemia, the HbA 1c/HDL-C ratio was independently associated with increased UACR in the general population aged>40 years in China, which was superior to both glycemic and lipid parameters alone.

Objective:To study the effects of various parameters in the structural design and usage methods of insulin pen needles on their performance.Methods:Twenty-one conventional needles and five self-destructive needles were selected. A testing machine was used to clamp the needle and make it vertically puncture the test material with a constant speed of 50, 100, 150, 200, and 250 mm/min, respectively. The influence of the needle insertion speed on the puncture force was analyzed. The deformation of the needle on the small contact surface and the large contact surface at 4 N was recorded by a Photron high-speed digital camera. The penetration depth at 1 N and 3 N was measured by an indirect measurement and a direct measurement method, respectively, and the maximum damage width of the damage area was recorded. The tilt resistance of the needle at 6°, 9° and 12° under 2 N pressure was obtained by the testing machine. SPSS 27.0 software was used for statistical analysis of the experimental data, and the LSD multiple comparison method was used for one-way analysis of variance.Results:The difference in puncture force between the needle insertion speed of 50 mm/min and the other four needle insertion speeds was statistically significant (all P < 0.05), while the differences between the other groups were not statistically significant (all P > 0.05). The small contact surface needle was significantly deformed, with a large penetration depth, a large maximum damage width, and low anti-tilting resistance. The large contact surface needle was deformed slightly, with a smaller penetration depth, a smaller maximum damage width, and greater resistance to tilting. Conclusions:The influence of the usage method on the large contact surface of the needle is relatively small. The hexagonal and cross-shaped needle seats have stronger anti-tilt ability than the circular needle seat. The hexagonal needle seat is not easy to change with the rotation axis, and the performance is optimal. In the structural design, the size of the connection part should be reduced, and the appropriate shape of the needle base should be selected.

Objective:To establish and validate a gallstones classification method based on deep learning.Methods:A total of 618 gallstones samples were collected from East Hospital Affiliated to Tongji University, and 1 023 high-definition cross-sectional gallstones profile images were captured to construct a cross-sectional gallstones profile image dataset. Based on the traditional eight-category gallstones classification method, a lightweight network model, MobileNet V3, was trained using deep learning and transfer learning methods. The classification performance of MobileNet was evaluated using a confusion matrix with metrics such as accuracy rate, precision rate, F1 score, and recall rate. The MobileNet V3 was improved and further validated using accuracy and loss values.Results:The accuracy rate (94.17%), precision rate (94.03%), F1 score (92.96%) and recall rate (92.99%) of the improved MobileNet V3 model were better than other networks. The improved MobileNet V3 model achieved the highest accuracy rate (94.17%) in gallstones profile classification and was validated by the test set. The confusion matrix showed a weighted average of accuracy rate (92.0%), precision rate (92.6%), and F1 score (92.2%) for each category of gallstones.Conclusions:Based on deep learning, a high-accuracy gallstones classification method is proposed, which provides a new idea for the intelligent identification of gallstones.

Magnetic resonance (MR) imaging is an important tool for prostate cancer diagnosis, and accurate segmentation of MR prostate regions by computer-aided diagnostic techniques is important for the diagnosis of prostate cancer. In this paper, we propose an improved end-to-end three-dimensional image segmentation network using a deep learning approach to the traditional V-Net network (V-Net) network in order to provide more accurate image segmentation results. Firstly, we fused the soft attention mechanism into the traditional V-Net's jump connection, and combined short jump connection and small convolutional kernel to further improve the network segmentation accuracy. Then the prostate region was segmented using the Prostate MR Image Segmentation 2012 (PROMISE 12) challenge dataset, and the model was evaluated using the dice similarity coefficient (DSC) and Hausdorff distance (HD). The DSC and HD values of the segmented model could reach 0.903 and 3.912 mm, respectively. The experimental results show that the algorithm in this paper can provide more accurate three-dimensional segmentation results, which can accurately and efficiently segment prostate MR images and provide a reliable basis for clinical diagnosis and treatment.
Male ; Humans ; Prostate/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Magnetic Resonance Imaging/methods* ; Imaging, Three-Dimensional/methods* ; Prostatic Neoplasms/diagnostic imaging*

Objective:To establish and evaluate the effect of graded training mode of clinical nutrition nursing in general hospital.Methods:A clinical nutrition nursing group was established, including core management group, quality control group, education and training group and liaison nurse group. Hierarchical training and practice of clinical nutrition nursing was conducted throughout the hospital, and effect of training was evaluated.Results:The nurses' nutrition knowledge increased from (66.60±9.72) to (85.06±7.85) points, nutrition attitude increased from (72.38±5.55) to (92.50±5.10) points, nutrition behavior increased from (66.87 ± 6.83) to (88.76 ± 7.60) points, and the differences were statistically significant ( t values were -15.520, -11.128, -12.238, P<0.01). The nutritional risk screening rate and nutritional intervention rate of patients were improved to 100%, and the academic level of nurses in nutritional nursing was further improved. Conclusion:The application of graded training mode of clinical nutrition nursing can improve nurses' nutritional knowledge and skills, improve nurses' professional and academic level, and improve patient clinical outcomes.

OBJECTIVE: Aiming at the different characteristics of the various stages of medical equipment life cycle in hospital, research on the targeted and meticulous management mode. METHODS: Divides the whole life cycle of medical equipment in hospital into four phases, which are the selection demonstration period, purchase acceptance period, maintenance period, and retirement disposal period, and comparison with human fetal period, infant stage, adult stage and old age. RESULTS: With the meticulous management mode, the service quality of medical equipment in hospital has been improved, and the service benefits have been enhanced. CONCLUSIONS According to the respective characteristics of different stages, the corresponding meticulous management mode is implemented to make the management more scientific and standardized, and the operation is safer and more reliable, which escorts the whole life cycle of medical equipment in hospital.
Equipment and Supplies, Hospital ; Hospitals ; Humans ; Maintenance ; Materials Management, Hospital

Objective To analyze the influence of different geometric parameters on flexibility of the commonly used Z-shaped stent-grafts for treating thoracic aortic aneurysm, as well as the primary and secondary order of such influence. Methods The three-dimensional models of the stent-grafts with different strut numbers, wire diameters, crest height, bending radius were established by SolidWorks and imported to ANSYS software for finite element analysis．The 60° rotation of X-axis was applied to the stent-grafts, and the flexibility of the stent-grafts was evaluated according to 3 evaluation parameters (Von Mises stress, reaction force and bending torque)． Results After bending of the stent-grafts, the maximum stress was concentrated on the inside of the bend；reducing the wire diameter, crest height and strut number of the stent-grafts, the flexibility of the stent-grafts would increase; increasing the bending radius， the flexibility of the stent grafts would increase; the effect of the wire diameter and strut number on flexibility of the stent-grafts was stronger than that from the bending radius and crest height． Conclusions The strut number, wire diameter, crest height, bending radius had a significant impact on flexibility of the stent-grafts. The research findings can provide theoretical references for the selection and optimal design of the stent-grafts in clinic, and have a positive influence on reducing the incidence rate of complications such as new entry.

Objective To explore the value of new and fused conventional texture features extracted from mammograms using improved local ternary patterns (LTP) in predicting risk of breast cancer.Methods Mammograms were segmented.Based on improved LTP,the new and conventional texture features were extracted from segmented mammograms of bilateral breasts.Then the features of bilateral breasts were merged.The high dimensional characteristics were reduced with principal component analysis (PCA).Finally,the new texture features were classified with k-nearest neighbor (KNN),and the fusion features were clustered with logistic alternating decision tree (LADTree) algorithm.Results The area under ROC curve (AUC) of new texture features for predicting breast cancer was 0.732 4 ±0.042 8,and the sensitivity,specificity and prediction accuracy was 72.04％ (67/93),74.51％ (76/102) and 73.33％ (143/195),respectively.Furthermore,AUC of fusion features was 0.865 5± 0.014 8,the sensitivity,specificity and prediction accuracy was 84.95％ (79/93),88.23％ (90/102) and 86.67％ (169/195),respectively.Conclusion The new texture features based on improved LTP have high prediction accuracy for breast cancer,and the prediction efficacy can be improved after fusion with conventional features.

Objective To investigate the value of improving the prediction accuracy of near-term risk for developing breast cancer by transforming the original mammography image and fusing the different types of image features using the algorithm of machine learning.Methods The craniocaudal (CC) full-field digital mammography (FFDM) of 185 women were downloaded from the clinical database at the university of Pittsburgh medical center.Firstly,the original gray images were segmented and transformed into virtual optical density images.Then the asymmetry features were separately extracted from original gray images and virtual optical density images.Two decision tree classifiers of the first stage were trained based on the features extracted from two types of image.And the scores output from the two classifiers were used as input to train the second stage of one decision tree classifier.Leave-one-case-out method was used to validate the prediction performance of near-term risk of breast cancer.Results Using two-stage decision tree fusion method to predict breast cancer,the area under the ROC curve (AUC) was 0.9612±0.0132.And the sensitivity,specificity and prediction accuracy were 96.63％(86/89),91.67％(88/96) and 94.05％(174/185).Conclusion The features extracted from virtual optical density image have higher discriminatory power of predicting breast cancer.Fusing the two kinds of image features twice by two-stage decision tree method can help to improve the prediction accuracy of near-term risk of breast cancer.

Considering the problems such as reposition limited, easily detached and singly fired of the existing clip products, we developed an endoscopic multiple-clip applier which can apply 4 clips fired successively at a time. Th instrument also equipped with an independent grasper which can be used to clamp target tissues. In order to explor its feasibility and effectiveness of endoluminal closure of gastric perforation, 22 pig stomachs were making a 1 cm full-thickness incision from outside and closed by multiple-clip applier (n = 12) in vitro. Outcome was measured by bursting pressure and compared with negative control (n = 5) and hand suture (n = 5). We set a threshold pressure value (10 mm Hg) for a secure closure. Except 2 cases of invalid data, the mean bursting pressures of negative control, multiple-clip applier, hand suture were (1.5 ± 0.3) mm Hg, (46.0 ± 7.1) mm Hg, and (72.5 ± 7.7) mm Hg, respectively. The results showed that bursting pressure of multiple-clip applier was significantly higher than that of negative control (P < 0.05) and threshold value. Multiple-clip applier can be served as an effective and safe device to perform the endoluminal closure of gastric perforation.
Animals ; Endoscopy ; Equipment Design ; Stomach Diseases ; surgery ; Surgical Instruments ; Swine