AIM:To evaluate the effectiveness of EYESI binocular indirect ophthalmoscope simulation system as a training platform for fundus examination skills of general practitioner.METHODS:Prospective randomized study. A total of 40 general practitioners who received clinical ophthalmology training at Shenzhen Eye Hospital from January 2021 to December 2024 were selected and randomly divided into two groups by random number table method, with 20 cases in the study group and 20 cases in the control group. The study group was trained by EYESI binocular indirect ophthalmoscope simulation system and the control group was trained by conventional teaching. Training effects of the two groups were analyzed.RESULTS: The general information of the two groups was comparable. Through training with the EYESI binocular indirect ophthalmoscope simulator, the study group showed significant improvements in total examination and drawing scores compared to pre-training results(all P<0.001). Additionally, examination duration, retinal light exposure time, and drawing time were all significantly shorter than those before training(all P<0.001).The study group achieved significantly higher total examination and drawing scores than the control group during the EYESI binocular indirect ophthalmoscope simulator assessment(all P<0.001). Furthermore, examination duration, retinal light exposure time, and drawing time were all significantly shorter in the study group compared to the control group(all P<0.001). Moreover, ratings for the novelty of the training method and overall satisfaction with the training were significantly higher in the study group than in the control group(all P<0.001); while the perceived psychological stress during training was significantly lower in the study group(P<0.001).CONCLUSION:The EYESI binocular indirect ophthalmoscope simulaton system effectively enhances both the proficiency in fundus examination skills and overall training satisfaction among general practitioners.

Objective To investigate the value of multimodal MRI radiomics in predicting muscle-invasive bladder cancer.Methods A total of 178 patients with pathology diagnosis of bladder cancer were retrospectively collected,including 31 cases of muscle invasive bladder cancer(MIBC)and 147 cases of non-muscle invasive bladder cancer(NMIBC).Patients were randomly divided into training group and testing group at a ratio of 7︰3.The range of bladder tumors in T2WI,diffusion weighted imaging(DWI)and apparent diffusion coefficient(ADC)images were segmented as volume of interest(VOI)by using ITK-SNAP software.Radiomics features were extracted through A.K software.The optimal radiomics features were obtained through radiomics algorithm and least absolute shrinkage and selection operator(LASSO)method.Finally,the logistic regression analysis method and random forest model method were used to construct prediction models.The performance of prediction models was evaluated by the receiver operating characteristic(ROC)curve.Results This study constructed four groups of models containing T2WI prediction model,DWI prediction model,ADC prediction model,and T2WI+DWI+ADC prediction model.The area under the curve(AUC)of T2WI,DWI,and ADC prediction models for identifying MIBC and NMIBC were separately 0.920,0.914,and 0.954 in the training group while those were respectively 0.881,0.773,and 0.871 in the testing group.There was no statistical significance between T2WI,DWI,and ADC prediction models.In training and testing groups,the AUC of T2WI+DWI+ADC prediction model were respectively 0.959 and 0.909,which were higher than the single sequence prediction model.The sensitivity and specificity of the training group were 0.905 and 0.853 and the sensitivity and specificity of the testing group were 0.778 and 0.795.Conclusion MRI radiomics prediction model can effectively differentiate MIBC and NMIBC.The T2WI+DWI+ADC prediction model shows better prediction efficiency.

The Choledochal cyst is an extremely rare congenital anomaly of the bile duct. Early cyst resection and Roux-en-Y hepatojejunostomy are the primary surgical methods for treating choledochal cyst. With the emergence of enhanced recovery after surgery, laparoscopic surgery has effectively reduced the incidence of biliary complications and wound infections, but it still does not meet people's requirements for minimally invasive surgery. Robotic surgery system has the potential to enhance surgical precision and the maneuverability of surgeons due to clear surgical visualization and flexible mechanical arms. The authors review the relevant literatures and conduct a Meta-analysis to evaluate the efficacy of robot-assisted surgery and laparoscopic surgery for choledochal cyst.

Objective To investigate the effects of dexmedetomidine used to supplement analgesia on sleep quality in elderly patients after abdominal surgery.Methods Ninety-eight elderly patients,56 males and 42 females,aged 65-80 years,BMI 18.5-25.0 kg/m2,ASA physical status Ⅱ or Ⅲ,who un-derwent elective abdominal surgery under general anesthesia were selected and divided into two groups using the random number table method:dexmedetomidine group(group D)and control group(group C),49 pa-tients in each group.The two groups were used the same drugs for induction and maintenance of anesthesia,with different analgesic formulas after surgery.Analgesia formula in group C was sufentanil 2 μg/kg,tropi-setron 4 mg,and normal saline to 100 ml,and in group D was sufentanil 2 μg/kg,dexmedetomidine 5μg/kg,tropisetron 4 mg,and normal saline to 100 ml.In the form of questionnaire survey,consensus sleep diary(CSD)was used to record the patient's sleep latency,number of awakenings and duration of waking after sleep 1 day before surgery and 1 day,3,and 7 days after surgery,and then the actual sleep time and sleep efficiency were calculated.The patient's venous blood was collected at 5:00 to 7:00 in the morning to detect serum melatonin,interleukin-6(IL-6),interleukin-1β(IL-1β)and tumor necrosis factor(TNF-α)concentration.Extubation time,the incidence of cough,agitation,respiratory depression,postoperative bradycardia,nausea and vomiting,lethargy,urinary retention,and other adverse reactions were recorded.Results Compared with group C,the sleep latency was significantly reduced,the actual sleep time and the sleep efficiency were significantly increased 1 day,3,and 7 days after surgery(P＜0.05).Compared with group C,the concentration of postoperative melatonin in group D were significantly increased 1 day,3,and 7 days after surgery(P＜0.05),the concentration of IL-6,IL-1β and TNF-α in group D were significantly reduced 1 and 3 days after surgery(P＜0.05).There was no significant difference in the incidence of ad-verse reactions between the two groups.Conclusion Patient-controlled intravenous analgesia with dexme-detomidine assisted in elderly patients after abdominal surgery can improve sleep efficiency,increase sleep time and postoperative sleep quality,which may be related to the changes of melatonin and inflammatory factors after surgery.

Objective To explore the comparative study of constructing prediction models for muscle invasive of bladder cancer based on different machine learning algorithms combined with MRI radiomic.Methods A total of 187 bladder cancer patients who underwent MRI examination and were confirmed by pathology were retrospectively selected.Patients were randomly divided into a training set and a test set in a 7∶3 ratio.The patients were divided into muscle invasive bladder cancer(MIBC)group and non-muscle invasive bladder cancer(NMIBC)group according to the surgical pathology results.Tumor volume of interest(VOI)was outlined on the images of T2 WI,diffusion weighted imaging(DWI),and apparent diffusion coefficient(ADC),and the radiomic features were extracted by A.K software,and dimensionality reduction was performed using the maximum relevance minimum redundancy(mRMR)algorithm combined with least absolute shrinkage and selection operator(LASSO).Six machine learning algorithms,including K-nearest neighbor(KNN),decision tree(DT),support vector machine(SVM),logistic regression(LR),random forest(RF),and explainable boosting machine(EBM)were used to construct the radiomic model and calculate the corresponding area under the curve(AUC),accuracy,sensitivity,and specificity,respectively.Results Six machine learning algorithms,including KNN,DT,SVM,LR,RF,and EBM were used to construct the radiomic model,and the AUC values for predicting MIBC in the training set were 0.863,0.838,0.853,0.866,0.977,0.997,and in the test set were 0.748,0.833,0.860,0.868,0.870,0.900.Among them,the MRI radiomic model constructed based on EBM had the highest predictive efficacy for MIBC,with AUC values,accuracy,sensitivity and specificity of 0.997,0.977,0.957 and 0.981 in the training set,and 0.900,0.877,0.800,and 0.894 in the test set,respectively.Conclusion Multiple machine learning algorithms combined with MRI radiomic to construct models have good predictive efficacy for MIBC,and the model constructed based on EBM shows the highest predictive value.

Objective To study the relationship among the sense of organizational fairness, innovative self-efficacy (ISE) and innovative behavior in nurses. Methods A total of 392 nurses from a grade A tertiary hospital were selected as the research subjects using convenience sampling method. The Organizational Fairness Scale, Innovation Self-efficacy Scale, and Innovation Behavior Scale were used to evaluate the sense of organizational fairness, ISE, and innovation behavior, respectively. The mediate equation model was constructed, and Bootstrap analysis was applied for validation. Results The scores for organizational fairness, ISE, and innovative behavior among the nurses were (67.8±15.2), (23.9±3.5), and (30.5±6.7) points, respectively. Organizational fairness score was positively correlated with both innovative behavior and ISE scores ［correlation coefficients (r) were 0.38 and 0.36, respectively, both P<0.01］. ISE score was positively correlated with innovative behavior total score (r=0.51, P<0.01). The results of the mediation analysis indicated that the total effect of organizational fairness on innovation behavior was 0.34 (P<0.01),with a direct effect of 0.17 (P<0.01). ISE plays a mediating role between organizational fairness and innovation behavior among nurses(P<0.01) with standardized mediation effect of 0.17, accounting for 50.0% of the total effect. Conclusion Organizational fairness can influence the ability of innovative behavior directly or through the mediating role of ISE.

【Objective】 To estimate the prevalence, associated factors and patterns of multimorbidity of non-communicable diseases among adults in Shaanxi Province so as to provide evidence for the prevention and control of non-communicable diseases. 【Methods】 We used the data of adults aged 18 years and older collected in the baseline survey of Shaanxi Project in the Regional Ethnic Cohort Study in Northwest China. Multinomial logistic regression was used to explore the associated factors for multimorbidity. Exploratory factor analysis was used to extract patterns of multimorbidity. 【Results】 The prevalence of multimorbidity was 10.7% among the 44 442 participants. Age increase, being males, urban residence, and being overweight or obesity were positively associated with multimorbidity. Compared with women, men had a higher risk of multimorbidity. The OR and 95% CI was 1.25 (1.12-1.39). The risk of multimorbidity increased with age among adults. Compared with participants aged 18.0-34.9 years, the ORs and 95% CIs of those aged 35.0-44.9, 45.0-54.9, 55.0-64.9, and ≥65.0 years were 4.73 (3.47-6.46), 15.61 (11.60-21.00), 41.39 (30.76-55.70) and 90.04 (66.58-121.77), respectively. The primary multimorbidity patterns among adults in Shaanxi were cardiovascular-metabolic multimorbidity (5.4%), viscero-articular multimorbidity (1.0%), and respiratory multimorbidity (0.3%). 【Conclusion】 More than one in ten adults in Shaanxi Province had multimorbidity, and the predominant pattern of multimorbidity was cardiovascular-metabolic multimorbidity. The prevention and control of non-communicable diseases should be reinforced in middle-aged and older people, males, people living in the urban, and overweight or obese people. More attention should be paid to the prevention and control of cardiovascular-metabolic diseases.

【Objective】 To evaluate the dietary quality with the dietary balance index (DBI_16) and the association between dietary quality and bone mass among middle-aged and elderly people in Gansu Province so as to provide evidence for improving dietary quality and bone health status of Gansu population. 【Methods】 Based on the information of the type and quantity of food intake and the bone mass of middle-aged and elderly people aged 35 years and above collected by the Gansu Project in the Regional Ethnic Cohort Study in Northwest China, DBI_16 was used to evaluate the intake level of cereals, vegetables, fruits, milk, beans, fish and shrimp, eggs and other foods, and the degree of inadequate, excessive and unbalanced dietary intake of the participants. Multiple linear regression was used to evaluate the associations of three component indexes of DBI_16, high bound score (DBI_HBS), low bound score (DBI_LBS), diet quality distance (DBI_DQD), and seven single indexes of DBI_16 with bone mass. 【Results】 Analyses of the dietary and bone mass data of 11,840 participants showed that 44.8% of participants consumed excessive amounts of cereals compared to the dietary recommendation. 96.3%, 90.6%, 90.1%, 71.9%, 95.1% and 60.3% of participants’ intake of vegetables, fruits, milk, soybeans, fish and shrimp, and eggs, respectively, were inadequate. 47.7% participants consumed less than 10 types of food. 2.3% participants’ DBI_LBS levels were appropriate. 54.7% participants’ DBI_HBS levels were appropriate. Only 1.2% participants’ DBI_DQD reached a balanced level. The bone mass level in the study population was (2.5±0.6) kg [(2.8±0.5) kg for men and (2.3±0.5) kg for women]. After adjusting for sociodemographic characteristics, lifestyle, total dietary energy intake and body mass index, DBI_LBS and DBI_DQD were negatively associated with bone mass [β and 95% CI was -0.002 01 (-0.003 62--0.000 40) and -0.001 76 (-0.003 09--0.000 43), respectively]. 【Conclusion】 Dietary intake imbalance is common among middle-aged and elderly people in Gansu Province, and the more severe the dietary intake imbalance, the lower the bone mass level.

Objective:To explore the diagnostic value of clinical, multi-parameter magnetic resonance imaging (MP-MRI) combined with transrectal ultrasound elasticity data for prostate cancer.Methods:A retrospective analysis was conducted on patient data from November 2021 to March 2023 when transrectal prostate two-dimensional ultrasound, real-time strain elastography of the prostate, MP-MRI examination of the prostate, and prostate biopsy were performed simultaneously at the Meizhou People′s Hospital. We collected patient age, height, weight, free serum prostate specific antigen (fPSA), total prostate specific antigen (tPSA), fPSA/tPSA, MRI prostate imaging report and data system (PI-RADS) scores, and ultrasound elasticity values. Four predictive models for prostate cancer diagnosis were constructed using multivariate logistic regression for comparison, and the optimal model was selected to construct a column chart. The diagnostic performance of different models was evaluated using receiver operating characteristic (ROC) curves, and the diagnostic performance of column charts was evaluated using calibration curves.Results:This study included a total of 117 patients with 117 prostate lesions, 47 benign prostate lesions, and 70 prostate cancer lesions. There were statistically significant differences in age, fPSA, tPSA, fPSA/tPSA, PI-RADS scores, and ultrasound elasticity values between benign and malignant lesions patients (all P<0.01). The area under the curve (AUC) of the clinical model (age+ tPSA+ fPSA+ fPSA/tPSA), MRI model (PI-RADS score), ultrasound elastic model, and clinical+ MRI+ ultrasound elastic combined model for diagnosing prostate cancer were 0.86, 0.86, 0.92, and 0.98, respectively. Conclusions:Compared with a single diagnostic model, the combination of age, tPSA, fPSA/tPSA, PI-RADS scores, and ultrasound elasticity value model can improve the diagnostic rate of prostate cancer.

Humans ; East Asian People ; Psoriasis/drug therapy* ; Antibodies, Monoclonal, Humanized/therapeutic use* ; Treatment Outcome ; Severity of Illness Index