Objective:To explore the value of predicting new-onset heart failure events in patients with hypertrophic cardiomyopathy (HCM) using clinical and cardiac magnetic resonance (CMR) features based on machine learning algorithms.Methods:The study was a retrospective cohort study. Patients with a confirmed diagnosis of HCM who underwent CMR examinations at Beijing Anzhen Hospital from May 2017 to March 2021 were selected and randomly divided into the training set and the validation set in a ratio of 7∶3. Clinical data and CMR parameters (including conventional parameters and radiomics features) were collected. The endpoint events were heart failure hospitalization and heart failure death, with follow-up ending in January 2023. Features with high stability and P value<0.05 in univariate Cox regression analysis were selected. Subsequently, three machine learning algorithms—random forest, decision tree, and XGBoost—were used to build heart failure event prediction models in the training set. The model performance was then evaluated using the independent validation set, with the performance assessed based on the concordance index. Results:A total of 462 patients were included, with a median age of 51 (39, 62) years, of whom 332 (71.9%) were male. There were 323 patients in the training set and 139 in the validation set. The median follow-up time was 42 (28, 52) months. A total of 44 patients (9.5% (44/462)) experienced endpoint events (8 cases of heart failure death and 36 cases of heart failure hospitalization), with 31 events in the training set and 13 in the validation set. Univariate Cox regression analysis identified 39 radiomic features, 4 conventional CMR parameters (left ventricular end-diastolic volume index, left ventricular end-systolic volume index, left ventricular ejection fraction, and late gadolinium enhancement ratio), and 1 clinical feature (history of non-sustained ventricular tachycardia) that could be included in the machine learning model. In the prediction models built with the training set, the concordance indices for the random forest, decision tree, and XGBoost models were 0.966 (95% CI 0.813-0.995), 0.956 (95% CI 0.796-0.992), and 0.973 (95% CI 0.823-0.996), respectively. In the validation set, the concordance indices for the random forest, decision tree, and XGBoost models were 0.854 (95% CI 0.557-0.964), 0.706 (95% CI 0.399-0.896), and 0.703 (95%CI 0.408-0.890), respectively. Conclusion:Integrating clinical and CMR features of HCM patients through machine learning aids in predicting heart failure events, with the random forest model showing superior performance.

The department of critical care medicine, the clinical base of critical care medicine, is the centralized management unit for the treatment of critical patients. Medicine and nursing are independent disciplines, but both can be fully utilized from different perspectives when dealing with critically ill patients. With the development of critical care medicine understanding and technology, the concept of doctor-nurse integration construction in the department of critical care medicine has emerged. Doctor-nurse integration construction in the department of critical care medicine needs to take severe diseases as the core and academic development as the orientation. Clinical practice should be carried out through medical cooperation, based on critical cognition and unified thinking mode.

Objective:To explore the turnover intention of dental outpatient nurses, and analyze its influencing factors.Methods:From August to September 2021, multi-stage sampling was used to select nurses from 20 stomatology hospitals in 7 geographical regions of North China, East China, South China, Central China, Southwest, Northeast, and Northwest China. The survey was conducted using the General Information Questionnaire, Turnover Intention Scale, Nursing Work Environment Scale, Psychological Capital Scale for Nurses, and Work Engagement Scale.Results:A total of 1 513 questionnaires were collected, including 1 135 valid questionnaires, with a valid rate of 75.02% (1 135/1 513). The total score of turnover intention among 1 135 dental outpatient nurses was (2.22±0.56). Pearson correlation analysis showed a negative correlation between nursing work environment, psychological capital, work engagement, and turnover intention ( r=-0.421, -0.340, -0.446; P<0.01). The structural equation model showed that the nursing work environment had a direct negative effect on the turnover intention of dental outpatient nurses (β=-0.401, P<0.01) and had an indirect negative effect on turnover intention through work engagement (β=-0.106, P<0.01), with a mediating effect of 20.91%. Psychological capital had an indirect negative effect on the turnover intention of dental outpatient nurses through work engagement (β=-0.271, P<0.01), with a mediating effect of 52.83%. Conclusions:The turnover intention of dental outpatient nurses is at a high level. Managers can reduce the turnover intention of dental clinic nurses by improving the nursing work environment, developing psychological capital, and increasing work engagement.

Objective:To observe the difference in the effect of simple titanium plate internal fixation and titanium plate internal fixation combined with titanium nail intermaxillary traction in the treatment of jaw fractures and their impact on the oral and maxillofacial function of patients.Methods:From August 2016 to May 2021, 94 patients with jaw fractures admitted to the Department of Stomatology, Linyi Central Hospital, Shandong (supplementing the gender, age range and average age of the patients), were divided into 47 cases in the control group, and the titanium plates were used alone, combined operation group 47 cases, titanium plate internal fixation combined with intermaxillary traction with titanium nails. The changes of oral and maxillofacial function and fracture healing were measured before operation and 3 months after operation, and the perioperative indicators and postoperative complications were recorded.Results:Three months after operation, the scores of maxillofacial function, mouth function and masticatory function in the combined operation group (0.52±0.09 points, 0.67±0.12 points, 0.58±0.08 points) were significantly lower than those in the control group (1.05±0.21 points, 1.14±0.22 points, 1.02±0.21 points) ( t=15.90, 12.86, 13.42, P<0.05). The effective rate of the combined operation group was 95.74% (45/47), which was significantly higher than that of the control group (80.85%, 38/47) (χ 2=5.05, P<0.05); there was no significant difference in operation time and hospitalization time between the groups ( P>0.05), the fracture healing time in the combined surgery group (65.02±7.06) d was significantly shorter than that in the control group (82.69±10.25) d ( t=9.73, P<0.05). The postoperative complication rate of combined treatment group was 6.38% (3/47), which was significantly lower than the control group 21.28% (10/47) (χ 2=4.37, P<0.05). Conclusions:In the treatment of jaw fractures, titanium plate internal fixation combined with titanium nail intermaxillary traction treatment can significantly improve the oral and maxillofacial function of patients, promote postoperative fracture healing, improve curative effect and reduce the incidence of complications compared with simple titanium plate internal fixation.

Glucagonoma is a rare neuroendocrine tumor of α cells of the pancreas. The tumor excessively secretes glucagon and causes glucagonoma syndrome.70%-90% of patients with glucagonoma will develop necrolytic migratory erythema (NME). We reported a patient of glucagonoma syndrome who was presented to the dermatology outpatient clinic with a 2-year-history of recurrent erythema and scaling on the skin migrating throughout the body. A skin biopsy was performed and resulting features matched with NME, whilst imaging examinations suggested a soft tissue density tumor present in the tail of the pancreas with somatostatin receptor expression and laboratory tests found an elevated levels of serum glucagon. After the diagnosis was confirmed, the patient was treated with surgical resection of the glucagonoma and the skin eruptions resolved rapidly in 4 days. Meanwhile, we reviewed relevant literature published in recent years and summarized its clinical characteristics in order to improve its understanding by clinicians, including clinical manifestations, laboratory and imaging examinations, diagnosis and treatments.

As early as the 20 th century, it has been observed that radiotherapy (RT), as a local therapy, can activate the adaptive immune system, resulting in spontaneous regression of tumors out of the radiation field, which is known as "abscopal effect". Although the occurrence of abscopal effect is still rare, with the gradual increase in the application of immunotherapy, more and more clinical cases of abscopal effect have been reported. Increasing attention has been paid to the therapeutic potential of RT in inducing systemic anti-tumor response. Especially, the combination of RT and immunotherapy enhances the research value of abscopal effect. However, its mechanism has not been fully elucidated, and the optimal timing, dose and fractionation of RT are also under study. How to classify the beneficiary groups is also a key issue. In this article, the history of abscopal effect, and the role of RT and immunotherapy in this phenomenon were briefly introduced, and the existing controversies in clinical application were illustrated, aiming to clarify the direction of current research and development and open a new chapter for tumor treatment in a short period of time.

Objective:To compare safety and efficacy of one-stage laparoscopic common bile duct exploration plus laparoscopic cholecystectomy (LCBDE+ LC) with endoscopic retrodrade cholangiopancreatography plus laparoscopic cholecystectomy (ERCP+ LC) in elderly patients with concomitant gallbladder and common bile duct (CBD) stones.Methods:This is a two-center retrospective study with clinical data on 492 patients aged over 80 years diagnosed with concomitant gallbladder and CBD stones treated between January, 2014 and December, 2020 at The First Affiliated Hospital of Wenzhou Medical University and Quzhou Hospital Affiliated to Wenzhou Medical University. There were 254 males and 238 females, aged (83.9±3.0) years. These patients were divided into two groups based on their operative methods: the one-stage group (LCBDE+ LC, n=186) and the two-stage group (ERCP+ LC, n=306). Differences in surgery, stones and hospitalization costs were compared between the two groups. Results:When compared with the ERCP+ LC group, the LCBDE+ LC group had significantly higher incidences of previous gastrectomy [21.5%(40/186) vs 4.2%(13/306)], multiple stones [77.4%(144/186) vs 49.3%(151/306)], larger stone diameter [13.7(6.4, 18.6)mm vs 10.9(5.7, 16.1) mm], and increased hospitalization expenditure [(2.37±0.31) Wanyuan vs (3.26±0.44) Wanyuan] (all P<0.05). However, the rates of residual stone [2.7%(5/186) vs 1.3%(4/306)], stone recurrence [2.2%(4/186) vs 5.2%(16/306)], postoperatively overall complications [3.2%(6/186) vs 1.3%(4/306)], and total hospital stay [(10.7±6.2) d vs (11.3±5.4) d] were not significantly different between the two groups (all P>0.05). Conclusions:Allowing for the similar safety and effectiveness, and lower hospitalization expenditure, LCBDE+ LC was a preferred choice for patients aged over 80 year, especially in patients who had previous gastrectomy, multiple large CBD stones, or who could not accept endoscopic procedures for treatment of CBD stones.

Objective:To investigate the value of radiomics features derived from cardiac MR (CMR) cine images for predicting late gadolinium enhancement (LGE) in patients with hypertrophic cardiomyopathy (HCM).Methods:Firstly, a total of 300 HCM patients with definite diagnosis who underwent CMR examination in Beijing Anzhen Hospital from May 2017 to August 2021 were retrospectively included, and were divided into a training set and a test set with a proportion of 7∶3 using random stratified sampling method. Then, a total of 89 HCM patients with definite diagnosis who underwent CMR examination in Beijing Anzhen Hospital from January 2022 to May 2023 were included for external validation. The CVI42 software was used to obtain the cardiac function parameters. Intraclass correlation coefficient (ICC), Pearson correlation coefficient and least absolute shrinkage and selection operator (LASSO) were used to select radiomics features. Finally, LASSO regression and three machine learning algorithms (including support vector machine, linear discriminant analysis and naive Bayes) were used to build prediction models. The area under the receiver operating characteristic curve (AUC) was used to evaluate the prediction value of the model.Results:Totally 1 409 features were extracted from each patient, and 19 features were retained to build radiomics signature after dimension reduction. Although no significant differences among the four methods, the prediction performance and stability of LASSO regression were relatively good. The AUC was 0.795 (95%CI 0.735-0.855) in the training set, 0.765 (95%CI 0.668-0.862) in the test set and 0.721(95%CI 0.598-0.845) in the external validation set.Conclusions:The features extracted from CMR cine images can be used to predict LGE in HCM patients. LASSO regression is recommended for model construction.

Objective:To explore the effect of the wearable low-level light therapy (LLLT) device on joint pain and knee function in community patients with knee osteoarthritis.Methods:From September 2021 to February 2022, the convenience sampling was used to select 57 middle-aged and elderly patients with knee osteoarthritis who met the inclusion criteria from 8 communities in Shijiazhuang as the study subject. The patients were randomly divided into intervention group ( n=27) and placebo group ( n=30) based on the community. The intervention group used wearable LLLT device to treat bilateral knee joints, while the placebo group wore the same phototherapy device, with the same frequency and duration as the intervention group, but did not turn on the light source. The patients were investigated with the Graphical Knee Osteoarthritis Patient Self-assessment Questionnaire and knee function test, and the joint pain and knee function of the two groups of patients during the study period were compared. Results:A total of 45 patients with knee osteoarthritis in the community completed the study, including 21 in the intervention group and 24 in the placebo group. The results of the Graphical Knee Osteoarthritis Patient Self-assessment Questionnaire showed that the total pain score of the intervention group were lower than that of the placebo group at the third and eighth weeks, with statistically significant differences ( P<0.01). At the eighth week, the scores of knee rest pain, starting pain and joint chills in the intervention group were significantly lower than those in the placebo group, and the differences were statistically significant ( P<0.01). The score of exercise pain in the third and eighth weeks showed a lower trend than that in the placebo group (0.01< P<0.05). There was no statistical difference in knee function test results between the two groups at the beginning of intervention and at the third week ( P>0.05) . Conclusions:Wearable LLLT devices can relieve the joint pain in patients with knee osteoarthritis in the community, but no significant improvement was found in knee function. The effect of wearable LLLT devices still needs to be further verified by multi-center, large sample and long-term follow-up study.

Objective:To construct the prediction model of knee degeneration in patients with knee osteoarthritis based on bioelectrical impedance index, and evaluate the prediction performance and application efficiency of the model.Methods:This was a cross-sectional study. From May to July 2021, 248 knee joints of 124 patients with knee osteoarthritis at home from Shijiazhuang Yuqiang Community Health Service Center who participated in physical examination were selected by convenience sampling to establish the model. According to Kellgren-Lawrence (K-L) grading system, the knee joints were divided into four groups, namely K-L1 ( n=19) , K-L2 ( n=103) , K-L3 ( n=96) , and K-L4 ( n=30) . The indicators included in the model were selected through analysis of variance or Kruskal-Wallis test, and a prediction model of knee degeneration was established using support vector machine, and the model was optimized using grid parameter optimization method. The prediction performance of the model was evaluated by the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, accuracy, positive predictive value and negative predictive value. Results:The indicators in the model included age, complications, lumbar/back/hip pain, high-risk occupation, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) -pain, WOMAC-function, capacitive reactance and phase angle. The area under the ROC curve of the training set model was 0.999, the prediction accuracy was 0.920, and the 95% confidence interval was 0.868 to 0.957. The area under the ROC curve of the test set model was 0.833, the prediction accuracy was 0.682, and the 95% confidence interval was 0.572 to 0.780.Conclusions:The prediction model of knee degeneration has good prediction performance and is easy to use, which can be used as a screening tool for knee degeneration in patients with knee osteoarthritis.