Objective To evaluate the reliability and validity of Barriers Questionnaire-Taiwan form (BQT) for cancer patients of mainland China. Methods A cross-sectional study was made among 363 hospitalized cancer patients from 7 hospitals in Beijing in January to March in 2015 with BQT. Methods of Cronbach alpha, split-half reliability, exploratory factor analysis, and content validity index were used to analyze its reliability and validity. Results All the indexes were in the measurement of acceptable range that the Cronbach alpha of BQT was 0.799, the Equal Length coefficient of Spearman-Brown was 0.770, the coefficient of Guttman Split-Half was 0.770,accumulating contribution rate of 11 factors was 63.910%,and the coefficient of content validity index was 0.733. Conclusions The reliability and validity of BQT are good and can be used to evaluate the pain management attitudes for cancer patients of Mainland China.

Objective To analyze the influencing factors and the influencing path of patients′attitudes towards cancer pain management based on"S-O-R"model, Heider balance theory, and Knowledge, Belief and Attitude, Practice Model(KAP/KABP). Methods The conceptual model was built on the basis of research for these three theories. SPSS 22.0 and AMOS 21.0 were used to make statistical analysis. The multiple stepwise regression analysis and structural equation were used to analyze the influencing factors and influencing path. Results The total score of patients′attitude towards cancer pain management was 2.96 ± 0.49. The direct negative effect size of patients′pain knowledge to patients′attitude towards cancer pain management was-0.384. The direct positive effect size of caregiver′s attitude towards cancer pain management to patient′s attitude towards cancer pain management was 0.138. The indirect negative effect of caregivers′pain knowledge to patient′s attitudes towards cancer pain management via caregivers′ attitudes was-0.053. There was positive correlation between patients′ pain knowledge and caregivers′ pain knowledge (coefficient of association was 0.150). Conclusions The results of prevalence study showed that patients′attitudes towards pain management was in low level. It will benefit to improve patients′ attitude towards cancer pain management by increasing pain knowledge level of patients. Caregivers should be brought into the intervention, by raising the level of pain knowledge of caregivers to improve pain management attitude of caregivers.

Objective:To evaluate the relationship between hemoglobin(Hb) level and the risk of diabetic retinopathy(DR) in patients with type 2 diabetes mellitus(T2DM).Methods:This study was a prospective cohort study. A total of 1 730 T2DM patients without DR, who received regular management at the Li′s Clinic in Taiwan, China starting from 2002, were selected as the study population. All patients underwent annual dilated fundus examination by professional ophthalmologists. General patient information and laboratory results were collected and analyzed. Based on the occurrence of DR during patient follow-up, patients were divided into the DR group and the non-DR(NDR) group. The impact of Hb levels on DR was explored using a generalized linear mixed model, and the relationship between Hb levels and DR was studied using Cox proportional hazards regression model.Results:After an average follow-up of 9.79 years, 481 patients with DR were detected. Compared with NDR group, DR group displayed a longer course of diabetes, higher rates of cataract, insulin use, and anemia, and higher systolic blood pressure, HbA 1C, and UACR as well as lower Hb. The results of the generalized linear mixed model showed a negative correlation between Hb and the occurrence of DR( β=-0.015, P<0.001). The Cox proportional hazards regression model showed that, after adjusting for confounding variables and based on quartiles of average Hb levels during follow-up, the risk of developing DR increased by 56.9% in the Q1 group(Hb≤127 g/L) compared to the Q4 group(Hb≥142 g/L). The cumulative risk plot showed that, after adjusting for confounding variables, the Q1 group had the highest cumulative risk of developing DR, and the difference was statistically significant( P<0.05). Conclusion:Hb was negatively correlated with DR, and the lower Hb levels were associated with the occurrence of DR, independent of other influencing factors.

Objective:To explore the relationship between normal serum creatinine(Scr) level and diabetic kidney disease(DKD) in patients with type 2 diabetes mellitus(T2DM).Methods:This was a prospective cohort study. Patients with yet not DKD who were regularly followed up at six centers of Li′s United Clinic in Taiwan, China from January 1, 2002 to December 31, 2018 were selected. At baseline, clinic information and lab tests were collected. According to whether the patients developed DKD during the follow-up period, they were divided into DKD group and non-DKD(NDKD) group. The exposure factor was the Scr(μmol/L) value, and it was used as a categorical variable. According to the quartiles of Scr, they were divided into 4 groups: Q1 group(Scr<57.68 μmol/L), Q2 group(57.68 μmol/L≤Scr<68.51 μmol/L), Q3 group(68.51 μmol/L≤Scr<80.44 μmol/L) and Q4 group(Scr≥80.44 μmol/L). The Cox regression model was used to explore the relationship between Scr level and the incidence of DKD. Receiver operating characteristic(ROC) curve was used to analyze the predictive effect of normal level Scr on DKD. Results:A total of 2 202 T2DM patients without DKD at baseline were included. After a follow-up period of(5.2±2.17) years, there were 966 patients in the DKD group and 1 236 patients in the NDKD group. Compared with the NDKD group, the DKD group had older age, longer duration of diabetes, higher BMI, SBP, DBP, LDL-C, Scr, and UACR(all P<0.05). Cox regression analysis results showed that compared with the Q1 group as the reference, the risk of developing DKD in the Q2, Q3, and Q4 groups after adjusting for confounding factors was 1.394, 1.688, and 2.821 times higher, respectively(all P<0.05). ROC curve analysis results showed that the area under the curve(AUC) for predicting DKD occurrence using normal serum creatinine level was 0.70(95% CI 0.678-0.722), with an optimal cutoff value of 74.27 μmol/L, sensitivity of 0.54, and specificity of 0.76. The cumulative risk plot showed that after adjusting for confounding factors, patients in the Q4 group had a higher cumulative risk of developing DKD compared to the Q1, Q2, and Q3 groups(all P<0.05). Conclusion:Scr is an independent risk factor for developing DKD in patients with T2DM. The higher the Scr level, the greater the risk, especially when Scr is greater than 74.27 μmol/L.

Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance. Results: The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.

Objective To explore the predictive effect of empowerment and theory of planned behavior(TPB)on the four core behaviors of type 2 diabetes mellitus(T2DM)self-management,and analyze the influence path of TPB model and behavioral intention on the four core behaviors.Methods A total of 500 T2DM patients who were hospitalized in the Endocrinology Department of three tertiary general hospitals in different provinces from December 2022 to May 2023 were selected for investigation.Hierarchical multiple regression analysis was used to explore the predictive effects of empowerment and TPB models on self-management behaviors.Bootstrap method was used to analyze the influence path of TPB model and behavior intention on self-management behaviors.Results Empowerment had a predictive effect on self-management behavior,which was improved after the addition of TPB,with medication R2=0.194,blood glucose monitoring R2=0.308,regular diet R2=0.337 and regular exercise R2=0.343,respectively.Mediation effect analyses revealed that attitude,subjective norm,and perceived behavioral control were observed to predict behavior intention across the four behaviors,and the three except through the behavior intention indirectly affect behavior,can also directly affect the behavior.Conclusions Empowerment can predict self-management behavior,and adding TPB to this can improve the prediction effect.Attitude,subjective norms and perceived control can indirectly or directly affect self-management behavior through behavioral intention.