Objective To compare ovulation recovery rate and metabolic indicators between ethinyl-estradiol/drospirenone(EE/DRSP)combined with orlistat and EE/DRSP alone in overweight/obese patients with polycystic ovary syndrome(PCOS).Methods This study was a randomized controlled clinical trial conducted based on the 2004 Rotterdam criteria.From October 2020 to December 2023,180 overweight/obese PCOS patients aged 20-40 were recruited from the Department of Department of Gynecological Endocrinology,Beijing Obstetrics and Gynecology Hospital,Capital Medical University.The patients were randomly divided into two groups in a 1∶2 ratio.Among them,60 patients received treatment with EE/DRSP(EE20 μg,DRSP 3 mg),while 120 patients received a combination treatment of EE/DRSP and orlistat(360 mg/d).The height,weight,waist circumference,hip circumference,and blood pressure of the patients were measured before treatment and after 12 weeks of treatment.Laboratory tests included measurements of follicle-stimulating hormone(FSH),luteinizing hormone(LH),fasting insulin(FINS),homeostasis model assessment of insulin resistance(HOMA-IR),free androgen index(FAI),alanine transaminase(ALT),aspartate transaminase(AST),gamma-glutamyl transferase(GGT),fasting plasma glucose(FPG),total cholesterol(TC),triglycerides(TG),high density lipoprotein-cholesterol(HDL-C),low density lipoprotein-cholesterol(LDL-C),lipoprotein(a)[Lp(a)],sex hormone-binding globulin(SHBG),total testosterone(T),and free testosterone(FT).After 12 weeks of treatment,the medication was discontinued,and natural ovulation was observed.Results After 12 weeks of treatment,the ovulation rate of the EE/DRSP combined with orlistat group reached 70.8%,while the natural ovulation rate of the EE/DRSP group alone was only 35%,indicating that the ovulation rate was significantly increased after EE/DRSP combined with orlistat treatment.After 12 weeks of treatment,both groups showed a significant decrease in total testosterone,free testosterone,and low-density lipoprotein levels(all P<0.05),and the decrease in BMI,waist circumference,fasting insulin,and HOMA-IR in the EE/DRSP combined with orlistat group was greater than that in the EE/DRSP group alone(P<0.05).After treatment,both groups showed a significant increase in high-density lipoprotein and triglyceride levels(all P<0.05),with no significant changes in total cholesterol and fasting blood glucose(all P>0.05).Conclusion After 12 weeks of treatment,EE/DRSP combined with orlistat can significantly improve the ovulation rate of PCOS patients.It is superior to EE/DRSP alone in reducing androgen levels,body weight,insulin resistance,and low-density lipoprotein levels.

Objective:To evaluate the application effect and long-term benefits of in situ simulation combined with the forgetting curve training mode in trauma nurse training, and to provide a basis for further promoting the development of trauma nurse training.Methods:From June to September 2022, a total of 78 nurses in the Trauma Center of a grade A tertiary hospital in Changsha, China were selected by the purposive sampling method as the research objects. The nurses were divided into an experimental group and a control group according to the random number table method. The control group received theoretical teaching and skill operation training by traditional teaching methods. The experimental group was trained by the teaching method of in-situ simulation combined with the forgetting curve. The scores of theoretical and operational skills of the two groups were compared by the repeated measures analysis of variance (ANOVA) before training (T1), 1 day after training (T2), 1 month after training (T3), and 6 months after training (T4). The scores of core competence of trauma nurses before and after training were compared between the two groups by the t test. Results:There was no significant difference in theoretical, operational, and core competence scores between the two groups before training ( P>0.05). The results of repeated measures ANOVA showed significant differences in the time effect, inter-group effect, and interaction effect of theoretical and operational scores between the two groups ( P<0.001). The results of one-way repeated measures ANOVA showed that the theoretical and operational scores of the two groups increased first and then decreased with time. The results of multivariate ANOVA showed no significant difference in theoretical and operational scores between the two groups at observation time point T1 ( P>0.05), but significant differences at observation time points T2, T3, and T4, at which the scores in the experimental group were higher than those in the control group ( P<0.001). The results of independent samples t test showed that the core competence score of trauma nurses in the experimental group was significantly higher than that in the control group after training ( P<0.05). Conclusions:The training mode of in situ simulation combined with the forgetting curve is more effective than traditional training mode in improving the professional skill level of trauma nurses and brings long-term training effect and benefits.

Objective:To explore the risk factors for malnutrition after a traumatic brain injury and to construct a model which usefully predicts that risk.Methods:This was a retrospective study of 374 patients with a craniocerebral injury for whom the relevant clinical data were available. Based on their nutritional status, they were stratified into a malnutrition group ( n=220) and a control group ( n=154). Univariate and multivariate logistic regressions were evaluated seeking to identify the independent risk factors associated with malnutrition, and a prediction model was constructed based on the results. The model′s discrimination ability and accuracy were assessed using a receiver operating characteristics (ROC) curve. Results:A total of 220 patients (58.8%) developed malnutrition. Multifactorial logistic regression analysis showed that the independent risk factors for malnutrition were: age ≥60 years, pulmonary infection, dysphagia, cognitive impairment, a GCS score ≤8, or a Barthel index ≤40. In the ROC curve analysis, the area under the curve quantifying the model′s ability to predict malnutrition was 0.924 (95% CI: 0.896, 0.951), with a sensitivity of 0.868 and a specificity of 0.857, indicating its good prediction performance. Conclusions:Age ≥60 years, pulmonary infection, dysphagia, cognitive impairment, a GCS score ≤8 or a Barthel index ≤40 are independent predictors of malnutrition after a traumatic brain injury. The prediction model constructed based on those risk factors has demonstrated useful predictive power for malnutrition.

Objective To explore the current status,hotspots,and frontier directions in the field of hospital research management.Methods Literature related to hospital research management published from January 1987 to March 2025,as in-dexed in the China National Knowledge Infrastructure(CNKI),was retrieved.The visualization software CiteSpace was used to analyze the publication volume,authors,institutions,and keywords.Results A total of 250 Chinese-language articles were in-cluded.The overall publication volume showed a fluctuating upward trend,with the highest number of publications in 2023,reac-hing 26 articles.Notable institutions with higher publication volumes include Chongqing Traditional Chinese Medicine Hospital,the Medical Department of Nanjing General Hospital of the Nanjing Military Region,Tianjin Medical University Cancer Hospital,and Shengjing Hospital of China Medical University.Key authors with more publications include Zhou Laixin,Xu Dixiong,Liu Yuping,and Sun Meng.High-frequency keywords included"research management","hospital","research projects","re-search funding","public hospitals",and"project management",generating 11 clustering labels and 25 emerging terms.Con-clusion The research on hospital research management in China has evolved from conceptual definition and systematic construc-tion to the exploration of innovative strategies,with increasing depth and breadth.The field has yet to form a large-scale,cross-regional author and institutional cooperation network.High-frequency keywords such as"research management","hospital","research projects","research funding","public hospitals",and"project management"represent hotspots in the research.Keywords such as"public hospitals","design",and"research projects"may become the frontier directions for future research in this field.

Objective To compare ovulation recovery rate and metabolic indicators between ethinyl-estradiol/drospirenone(EE/DRSP)combined with orlistat and EE/DRSP alone in overweight/obese patients with polycystic ovary syndrome(PCOS).Methods This study was a randomized controlled clinical trial conducted based on the 2004 Rotterdam criteria.From October 2020 to December 2023,180 overweight/obese PCOS patients aged 20-40 were recruited from the Department of Department of Gynecological Endocrinology,Beijing Obstetrics and Gynecology Hospital,Capital Medical University.The patients were randomly divided into two groups in a 1∶2 ratio.Among them,60 patients received treatment with EE/DRSP(EE20 μg,DRSP 3 mg),while 120 patients received a combination treatment of EE/DRSP and orlistat(360 mg/d).The height,weight,waist circumference,hip circumference,and blood pressure of the patients were measured before treatment and after 12 weeks of treatment.Laboratory tests included measurements of follicle-stimulating hormone(FSH),luteinizing hormone(LH),fasting insulin(FINS),homeostasis model assessment of insulin resistance(HOMA-IR),free androgen index(FAI),alanine transaminase(ALT),aspartate transaminase(AST),gamma-glutamyl transferase(GGT),fasting plasma glucose(FPG),total cholesterol(TC),triglycerides(TG),high density lipoprotein-cholesterol(HDL-C),low density lipoprotein-cholesterol(LDL-C),lipoprotein(a)[Lp(a)],sex hormone-binding globulin(SHBG),total testosterone(T),and free testosterone(FT).After 12 weeks of treatment,the medication was discontinued,and natural ovulation was observed.Results After 12 weeks of treatment,the ovulation rate of the EE/DRSP combined with orlistat group reached 70.8%,while the natural ovulation rate of the EE/DRSP group alone was only 35%,indicating that the ovulation rate was significantly increased after EE/DRSP combined with orlistat treatment.After 12 weeks of treatment,both groups showed a significant decrease in total testosterone,free testosterone,and low-density lipoprotein levels(all P<0.05),and the decrease in BMI,waist circumference,fasting insulin,and HOMA-IR in the EE/DRSP combined with orlistat group was greater than that in the EE/DRSP group alone(P<0.05).After treatment,both groups showed a significant increase in high-density lipoprotein and triglyceride levels(all P<0.05),with no significant changes in total cholesterol and fasting blood glucose(all P>0.05).Conclusion After 12 weeks of treatment,EE/DRSP combined with orlistat can significantly improve the ovulation rate of PCOS patients.It is superior to EE/DRSP alone in reducing androgen levels,body weight,insulin resistance,and low-density lipoprotein levels.

Objective:To explore the risk factors for malnutrition after a traumatic brain injury and to construct a model which usefully predicts that risk.Methods:This was a retrospective study of 374 patients with a craniocerebral injury for whom the relevant clinical data were available. Based on their nutritional status, they were stratified into a malnutrition group ( n=220) and a control group ( n=154). Univariate and multivariate logistic regressions were evaluated seeking to identify the independent risk factors associated with malnutrition, and a prediction model was constructed based on the results. The model′s discrimination ability and accuracy were assessed using a receiver operating characteristics (ROC) curve. Results:A total of 220 patients (58.8%) developed malnutrition. Multifactorial logistic regression analysis showed that the independent risk factors for malnutrition were: age ≥60 years, pulmonary infection, dysphagia, cognitive impairment, a GCS score ≤8, or a Barthel index ≤40. In the ROC curve analysis, the area under the curve quantifying the model′s ability to predict malnutrition was 0.924 (95% CI: 0.896, 0.951), with a sensitivity of 0.868 and a specificity of 0.857, indicating its good prediction performance. Conclusions:Age ≥60 years, pulmonary infection, dysphagia, cognitive impairment, a GCS score ≤8 or a Barthel index ≤40 are independent predictors of malnutrition after a traumatic brain injury. The prediction model constructed based on those risk factors has demonstrated useful predictive power for malnutrition.

Objective Establish a relationship model between the outcome of inpatient rehabilitation treatment and the influencing factors of rehabilitation effect,explore the evaluation method of inpatient rehabilitation service effect.Methods Using a neural network model to construct a functional relationship model between the outcomes of inpatient rehabilitation treatment and the factors affecting rehabilitation effectiveness,in order to predict the expected rehabilitation outcomes of patients receiving inpatient treatment.Compare the distribution of the difference between the actual discharge ICF total score and the predicted ICF total score to determine the effectiveness of rehabilitation treatment.Results As a result,a total of 1 334 hospitalized rehabilitation cases of brain injury patients were included in this study for analysis.Based on the evaluation indicators and standards of prediction accuracy,the optimal model was selected and the rehabilitation effect was evaluated.Conclusion Based on the ICF-RS-17 measurement of patient entry and exit function scores,the functional status of hospitalized rehabilitation patients themselves,and related possible influencing factors,a relationship model between inpatient rehabilitation treatment outcomes and influencing factors is constructed.It provides a certain scientific basis for establishing an effective evaluation method for the actual clinical rehabilitation effect,and also provides reference suggestions for the realization of value-based payment of rehabilitation medical insurance.

Objective To explore the current status,hotspots,and frontier directions in the field of hospital research management.Methods Literature related to hospital research management published from January 1987 to March 2025,as in-dexed in the China National Knowledge Infrastructure(CNKI),was retrieved.The visualization software CiteSpace was used to analyze the publication volume,authors,institutions,and keywords.Results A total of 250 Chinese-language articles were in-cluded.The overall publication volume showed a fluctuating upward trend,with the highest number of publications in 2023,reac-hing 26 articles.Notable institutions with higher publication volumes include Chongqing Traditional Chinese Medicine Hospital,the Medical Department of Nanjing General Hospital of the Nanjing Military Region,Tianjin Medical University Cancer Hospital,and Shengjing Hospital of China Medical University.Key authors with more publications include Zhou Laixin,Xu Dixiong,Liu Yuping,and Sun Meng.High-frequency keywords included"research management","hospital","research projects","re-search funding","public hospitals",and"project management",generating 11 clustering labels and 25 emerging terms.Con-clusion The research on hospital research management in China has evolved from conceptual definition and systematic construc-tion to the exploration of innovative strategies,with increasing depth and breadth.The field has yet to form a large-scale,cross-regional author and institutional cooperation network.High-frequency keywords such as"research management","hospital","research projects","research funding","public hospitals",and"project management"represent hotspots in the research.Keywords such as"public hospitals","design",and"research projects"may become the frontier directions for future research in this field.

Objective:To construct a risk prediction model for early post-injury respiratory failure in patients with traumatic cervical spinal cord injury (TCSCI) and validate its efficacy.Methods:A retrospective cohort study was conducted to analyze the clinical data of 393 TCSCI patients admitted to Zhengzhou Central Hospital Affiliated to Zhengzhou University from January 2020 to October 2024, including 294 males and 99 females, aged 18-82 years [59(45, 72)years]. Among them, 76 patients had respiratory failure (19.3%). The patients were randomly divided into the training set ( n=275) and validation set ( n=118) at a ratio of 7∶3. According to the presence of respiratory failure within one week after admission, 275 patients in the training set were divided into respiratory failure group ( n=53) and non-respiratory failure group ( n=222). The demographic data, injury characteristics, laboratory test results, and imaging findings of the patients were collected. Risk factors were determined through univariate analysis and multivariate Logistic regression analysis and a nomogram prediction model was constructed. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model. Decision curve analysis (DCA) was plotted to evaluate the clinical effectiveness of the prediction model. Results:The results of the univariate analysis showed that there were significant differences in history of respiratory diseases, causes of injury, Glasgow coma scale (GCS), American Spinal Injury Association (ASIA) classification, ASIA-motor score (AMS), injury severity score (ISS), clinical pulmonary infection score (CPIS), hypoproteinemia and cervical vertebra fracture and dislocation between the respiratory failure group and non-respiratory failure group in the training set ( P<0.05). The results of multivariate Logistic regression analysis indicated that GCS, ASIA classification, CPIS, and hypoproteinemia were independent risk factors for early post-injury respiratory failure in TCSCI patients ( P<0.05). Based on the above four variables, a Logistic regression equation was constructed: Logit( P)=2.361-0.675×ASIA classification+0.419×CPIS-0.358×GCS+0.854×hypoproteinemia. In the prediction model established based on this equation, the AUC was 0.96 (95% CI 0.94, 0.99) in the training set and 0.89 (95% CI 0.82, 0.96) in the validation set. In the calibration curves of the training set and validation set, the prediction curve and reference curve were approximately overlapping, with the average absolute errors of 0.04 and 0.03. DCA results demonstrated that both the training and validation sets exhibited positive net benefits when threshold probabilities fell within ranges of 0%-78% and 0%-87%, respectively. Conclusion:The risk prediction model for early post-injury respiratory failure in TCSCI patients based on GCS, ASIA classification, CPIS and hypoproteinemia has good predictive efficacy and clinical practicability.

Objective Establish a relationship model between the outcome of inpatient rehabilitation treatment and the influencing factors of rehabilitation effect,explore the evaluation method of inpatient rehabilitation service effect.Methods Using a neural network model to construct a functional relationship model between the outcomes of inpatient rehabilitation treatment and the factors affecting rehabilitation effectiveness,in order to predict the expected rehabilitation outcomes of patients receiving inpatient treatment.Compare the distribution of the difference between the actual discharge ICF total score and the predicted ICF total score to determine the effectiveness of rehabilitation treatment.Results As a result,a total of 1 334 hospitalized rehabilitation cases of brain injury patients were included in this study for analysis.Based on the evaluation indicators and standards of prediction accuracy,the optimal model was selected and the rehabilitation effect was evaluated.Conclusion Based on the ICF-RS-17 measurement of patient entry and exit function scores,the functional status of hospitalized rehabilitation patients themselves,and related possible influencing factors,a relationship model between inpatient rehabilitation treatment outcomes and influencing factors is constructed.It provides a certain scientific basis for establishing an effective evaluation method for the actual clinical rehabilitation effect,and also provides reference suggestions for the realization of value-based payment of rehabilitation medical insurance.