Objective:To identify latent profiles of emotional intelligence (EI) among undergraduate nursing interns and explore its impact on their ability to protect patient privacy, with the aim of providing a basis for targeted interventions.Methods:A convenience sampling method was used to recruit 470 undergraduate nursing interns from four nursing colleges in Shandong Province between June and September 2024. Data were collected using a general demographic questionnaire, the Wong Law Emotional Intelligence Scale-Chinese Version (WLEIS-C), the Patient Privacy Scale (PPS), the Moral Sensitivity Questionnaire for Nursing Students (MSQ-ST), and the Jefferson Scale of Empathy for Health Professionals (JSE-HP). Mplus 8.7 software was used to conduct latent profile analysis of emotional intelligence, and Logistic regression analysis was employed to identify influencing factors for the different EI profiles.Results:A total of 470 questionnaires were distributed in this study and 444 valid questionnaires were recovered, yielding a response rate of 94.47% (444/470). The EI of nursing interns was categorized into three latent profiles: low EI group ( n=81), moderate EI group ( n=170), and high EI group ( n=193). Logistic regression analysis indicated that liking for the nursing profession, moral sensitivity, and empathy ability were significant predictors of EI profile membership ( P<0.05). Statistically significant differences were observed in total PPS scores and subscale scores among interns across the three EI profiles (all P<0.01) . Conclusions:Emotional intelligence among undergraduate nursing interns exhibits heterogeneity, and interns with different EI profiles show distinct levels of competence in protecting patient privacy. Nursing educators and administrators are advised to establish risk screening mechanisms to identify subgroups with low emotional intelligence. Targeted interventions should be developed based on influencing factors specific to each profile, aiming to enhance both emotional intelligence and privacy protection capabilities in a coordinated manner.

Objective:To identify latent profiles of emotional intelligence (EI) among undergraduate nursing interns and explore its impact on their ability to protect patient privacy, with the aim of providing a basis for targeted interventions.Methods:A convenience sampling method was used to recruit 470 undergraduate nursing interns from four nursing colleges in Shandong Province between June and September 2024. Data were collected using a general demographic questionnaire, the Wong Law Emotional Intelligence Scale-Chinese Version (WLEIS-C), the Patient Privacy Scale (PPS), the Moral Sensitivity Questionnaire for Nursing Students (MSQ-ST), and the Jefferson Scale of Empathy for Health Professionals (JSE-HP). Mplus 8.7 software was used to conduct latent profile analysis of emotional intelligence, and Logistic regression analysis was employed to identify influencing factors for the different EI profiles.Results:A total of 470 questionnaires were distributed in this study and 444 valid questionnaires were recovered, yielding a response rate of 94.47% (444/470). The EI of nursing interns was categorized into three latent profiles: low EI group ( n=81), moderate EI group ( n=170), and high EI group ( n=193). Logistic regression analysis indicated that liking for the nursing profession, moral sensitivity, and empathy ability were significant predictors of EI profile membership ( P<0.05). Statistically significant differences were observed in total PPS scores and subscale scores among interns across the three EI profiles (all P<0.01) . Conclusions:Emotional intelligence among undergraduate nursing interns exhibits heterogeneity, and interns with different EI profiles show distinct levels of competence in protecting patient privacy. Nursing educators and administrators are advised to establish risk screening mechanisms to identify subgroups with low emotional intelligence. Targeted interventions should be developed based on influencing factors specific to each profile, aiming to enhance both emotional intelligence and privacy protection capabilities in a coordinated manner.

Objective:To investigate the predictive value of a radiomics model based on biparametric magnetic resonance imaging(bpMRI)for biochemical recurrence(BCR)after radical prostatectomy(RP)in elderly prostate cancer patients(≥60 years old).Methods:A retrospective analysis was conducted on data from 175 patients treated at Beijing Hospital from August 2017 to December 2021.Based on pathological results, image segmentation was performed on preoperative bpMRI T2, diffusion weighted imaging(DWI), and apparent diffusion coefficient(ADC)sequences.Pyradiomics was utilized to extract radiomic features, and Cox regression, Spearman correlation coefficient, and LASSO regression were employed for feature dimensionality reduction, leading to the construction of radiomic labels.Clinical models and image-clinical combined models were developed using multifactorial Cox regression analysis, and the performance of these models in predicting BCR was evaluated using the concordance index(C-index).Results:The 175 patients were randomly divided into a training set(122 cases)and a test set(53 cases)at a ratio of 7∶3, with 24 cases(19.7%, 24/122)and 11 cases(20.8%, 11/53)experiencing BCR, respectively.A total of 5 775 radiomic features were extracted from the three sequences, and after dimensionality reduction, 5 features were selected to construct the radiomic labels.The radiomics model exhibited C-index values of 0.764(95% CI: 0.655-0.872)and 0.769(95% CI: 0.632-0.906)in the training and test sets, respectively.Multifactorial Cox regression analysis revealed serum prostate-specific antigen(PSA)( HR=1.032, 95% CI: 1.010-1.054), postoperative pathology International Society of Urological Pathology(ISUP)grade grouping( HR=1.682, 95% CI: 1.039-2.722), and positive surgical margins( HR=2.513, 95% CI: 1.094-5.774)as independent predictors of BCR.The clinical model exhibited C-index values of 0.751(95% CI: 0.655-0.846)and 0.753(95% CI: 0.630-0.877)in the training and test sets, respectively.Following combined modeling of clinical factors and radiomic labels, the image-clinical combined model demonstrated the highest C-index values, namely 0.782(95% CI: 0.679-0.874)and 0.801(95% CI: 0.677-0.915)in the training and test sets, respectively. Conclusions:The radiomics model based on bpMRI can predict the occurrence of BCR after RP in elderly prostate cancer patients.Combined modeling of clinical factors and radiomic labels can enhance predictive efficiency.

The clinical data of 160 elderly patients with upper urinary tract stones who underwent flexible ureteroscopic lithotripsy (FURL) in Beijing Hospital from May 2021 to November 2022 were retrospectively analyzed, including 80 patients with ambulatory surgery (study group) and 80 patients with the traditional surgery (control group). The efficacy and safety were compared between two groups. There were no significant differences in the rate of complete stone removal (91.3% (73/80) vs. 90.0% (72/80), P>0.05), operation time (60.0 (41.0, 90.0)min vs.61.0(50.0, 96.5)min, P>0.05), and incidence of postoperative systemic inflammatory response syndrome (SIRS) (8.8% (7/80) vs.12.5% (10/80), P>0.05) between two groups, while the postoperative length of hospital stay (5.0 (5.0, 6.0)h vs. 18.0 (16.2, 30.0)h, P<0.05) was shorter and the medical expenses ((20 696.7±4 645.5)Yuan vs. (31 030.8±6 275.1)Yuan, P<0.05) was less in the study group than those in the control group. The study indicates that the day surgery mode of flexible ureteroscopic lithotripsy has advantages of faster recovery and less cost over the traditional surgery mode for elderly patients.

Objective:To investigate the accuracy and feasibility of applying rapid immunohistochemistry(IHC) with CK5/6 antibodies in prostate biopsy tissues to assist frozen pathology diagnosis.Methods:The data of 41 patients who underwent prostate puncture and frozen tissue rapid IHC with CK5/6 antibody in Beijing Hospital from October 2022 to April 2023 were retrospectively analyzed. The median age of the patients was 76 (69, 79) years old, and the median PSA value was 12.37 (7.07, 26.17) ng/ml.The Prostate Imaging Reporting and Data System (PI-RADS) scores of the target lesions were all ≥3. The PI-RADS score of 9 patients(21.95%) was 3, 15 (36.59%) was 4, and 17(41.46%) was 5. The median diameter of the lesions in the MRI examination was 1.40 (1.09, 2.20) cm.Fourteen lesions (34.14%) were located in the migratory zone, 23 (56.10%) were located in the peripheral zone, and 4 (9.76%) involved both peripheral and migratory zone lesions. Transperineal cognitive fusion targeted combined systematic biopsy was used, and intraoperatively, 1 additional needle was taken from each of the target and non-target areas for frozen pathology section, and hematoxylin eosin(HE) staining and rapid IHC staining with CK5/6 antibody was performed, then the frozen remaining tissue was HE staining and CK5/6 IHC staining. Data such as HE and rapid IHC results of frozen pathology sections and HE and IHC results of routine sections of the frozen remaining tissues, International Society of Urological Pathology (ISUP) grading groupings(GG), and actual diagnostic results of targeted combined systematic puncture were recorded. Using the routine IHC results of the same needle tissue as the gold standard, the sensitivity and positive predictive value of applying rapid IHC frozen pathology to diagnose prostate cancer and the accuracy of its pathological GG were analyzed.Results:Among the 41 patients, a total of 35 cases were diagnosed with prostate cancer(PCa) by HE staining in frozen section of target tissue, with a positivity rate of 85.37%(35/41). Among these, there were 17 cases (48.57%) in ISUP GG 1, 8 cases (22.86%) in GG 2, 4 cases (11.43%) in GG 3, and 6 cases (17.14%) in GG 4 to 5. In addition, a total of 35 cases were diagnosed with PCa by HE staining in frozen remaining section of target tissue, with a positivity rate of 85.37%(35/41). Among these, there were 17 cases (48.57%) in ISUP GG 1, 8 cases (22.86%) in GG 2, 4 cases (11.43%) in GG 3, and 6 cases (17.14%) in GG 4 to 5. The results of rapid IHC of target tissue: 35 cases were negative for CK5/6 expression and 6 cases were positive. The results of routine IHC of target tissue: 35 cases were negative for CK5/6 expression and 6 cases were positive. The results of rapid IHC of non-target tissue: 12 cases were negative for CK5/6 expression and 29 cases were positive. The results of routine IHC of non-target tissue: 12 cases were negative for CK5/6 expression and 29 cases were positive. Thirty-five cases of target tissue rapid IHC diagnosis of PCa were in complete agreement with routine IHC diagnosis, with a false-positive rate of 0, a sensitivity of 100.00% (35/35) and a positive predictive value of 100.00% (35/35). Twelve cases of non-target tissue rapid IHC diagnosis of PCa were in complete agreement with routine IHC diagnosis, with a false-positive rate of 0, a sensitivity of 100.00% (35/35), and a positive predictive value of 100.00% (12/12).Conclusions:The preliminarily study results confirmed that the application of rapid IHC with CK5/6 antibodies in prostate biopsy tissues assisted frozen pathology diagnosis with high accuracy, but the reliability of rapid IHC technology in assisting frozen pathological diagnosis during puncture surgery still needs further validation through large sample size prospective studies.

Background::Lymph node staging of prostate cancer (PCa) is important for planning and monitoring of treatment. 18F-prostate specific membrane antigen positron emission tomography/computerized tomography ( 18F-PSMA PET/CT) has several advantages over 68Ga-PSMA PET/CT, but its diagnostic value requires further investigation. This meta-analysis focused on establishing the diagnostic utility of 18F-PSMA PET/CT for lymph node staging in medium/high-risk PCa. Methods::We searched the EMBASE, PubMed, Cochrane library, and Web of Science databases from inception to October 1, 2022. Prostate cancer, 18F, lymph node, PSMA, and PET/CT were used as search terms and the language was limited to English. We additionally performed a manual search using the reference lists of key articles. Patients and study characteristics were extracted and the QUADAS-2 tool was employed to evaluate the quality of included studies. Sensitivity, specificity, the positive and negative likelihood ratio (PLR and NLR), diagnostic odds ratio (DOR), area under the curve (AUC), and 95% confidence interval (CI) were used to evaluate the diagnostic value of 18F-PSMA PET/CT. Stata 17 software was employed for calculation and statistical analyses. Results::A total of eight diagnostic tests including 734 individual samples and 6346 lymph nodes were included in this meta-analysis. At the patient level, the results of each consolidated summary were as follows: sensitivity of 0.57 (95% CI 0.39-0.73), specificity of 0.95 (95% CI 0.92-0.97), PLR of 11.2 (95% CI 6.6-19.0), NLR of 0.46 (95% CI 0.31-0.68), DOR of 25 (95% CI 11-54), and AUC of 0.94 (95% CI 0.92-0.96). At the lesion level, the results of each consolidated summary were as follows: sensitivity of 0.40 (95% CI 0.21-0.62), specificity of 0.99 (95% CI 0.95-1.00), PLR of 40.0 (95% CI 9.1-176.3), NLR of 0.61 (95% CI 0.42-0.87), DOR of 66 (95% CI 14-311), and AUC of 0.86 (95% CI 0.83-0.89).Conclusions::18F-PSMA PET/CT showed moderate sensitivity but high specificity in lymph node staging of medium/high-risk PCa. The diagnostic efficacy was almost equivalent to that reported for 68Ga-PSMA PET/CT. Registration::International Prospective Register of Systematic Reviews (PROSPERO), No. CRD42023391101.

Objective:To explore the value of conventional magnetic resonance imaging (MRI), diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI) sequence and pathological examination in predicting the efficacy of neoadjuvant chemotherapy (NAC) in advanced breast cancer.Methods:The clinical data of 65 cases of advanced breast cancer with NAC confirmed by pathology in the Affiliated Hospital of Jining Medical University from March 2022 to May 2023 were retrospectively analyzed, including 20 cases in the pathological complete remission (pCR) group and 45 cases in the non pCR group; All patients underwent routine MRI, DWI, DKI examinations and pathological analysis. The clinical pathological data, routine MRI features, apparent diffusion coefficient (ADC) values, mean kurtosis coefficient (MK), and mean diffusion coefficient (MD) between the two groups were analyzed; We compared the differences in various parameters between two groups and plotted receiver operating characteristic (ROC) curves to compare their diagnostic efficacy of NAC in breast cancer.Results:There were significant differences in molecular typing, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her-2) and Ki-67 between pCR group and non pCR group (all P<0.05). In pCR group, Her-2 overexpression type and triple negative breast cancer (TNBC) type breast cancer were more common. ER and PR were mostly negative, Her-2 was mostly positive, and Ki 67 was mainly positive. The difference in tumor T2WI signal between the pCR group and the non pCR group was statistically significant ( P<0.05), with the pCR group showing mostly moderate/low T2WI signal. The ADC and MD values of the pCR group were lower than those of the non pCR group, while the MK value of the pCR group was higher than that of the non pCR group, and the differences were statistically significant (all P<0.001). The area under the ROC curve (AUC) for predicting the efficacy of NAC using a clinical pathological model was 0.829, which was higher than the AUC of molecular subtypes, ER, PR, Her-2, and Ki-67 ( Z=3.008, 2.697, 2.815, 2.131, 2.376, all P<0.05); The AUC of the DKI+ DWI predicting the efficacy of NAC was 0.934, which was higher than that of the DWI single sequence model, and the difference in type was statistically significant ( Z=2.396, P=0.017). The diagnostic efficacy of the DKI+ DWI model was higher than that of the single parameter ADC, MD, and MK, and the differences were statistically significant ( Z=2.396, 2.219, 2.161, all P<0.05); The AUC of the combined imaging and pathology model was 0.983, and its diagnostic efficacy was higher than that of the conventional MRI feature model, pathology model, DWI model, and DKI model, with statistically significant differences ( Z=5.877, 2.961, 3.240, 2.264, all P<0.05). Conclusions:The results of pathology, conventional MRI, DWI and DKI parameters of pCR and non pCR breast cancer patients are significantly different, and the combined model is better than the single model in predicting the efficacy of NAC.

Objective:To develop and verify a predictive model for hip fracture risk in the aged patients with knee osteoarthritis (KOA) on the basis of analysis of the risk factors associated with the hip fracture.Methods:A retrospective study was conducted to analyze the 701 patients who had been diagnosed with KOA (Kellgren-Lawrence grades 1 to 4) at Dongyang Hospital affiliated to Wenzhou Medical University from September 2013 to September 2023. The cohort consisted of 275 males and 426 females with an age of (76.5±8.4) years. The patients were divided into a fracture group ( n=145) and a fracture-free group ( n=556) based on whether a hip fracture occurred during the follow-up period. The 2 groups were compared in terms of age, gender, comorbidities, albumin level, absolute lymphocyte count, and Kellgren-Lawrence grade, etc. The items with P<0.05 were analyzed by a multivariate logistic regression model to identify the risk factors for hip fracture in the aged KOA patients. A clinical prediction model based on the above risk factors was constructed and validated for hip fracture risk in the aged KOA patients. Results:Multivariate logistic regression analysis identified the following as independent risk factors for hip fracture in the aged KOA patients: female ( OR=2.009, 95% CI: 1.280 to 3.154, P=0.002), age ≥75 years ( OR=2.313, 95% CI: 1.493 to 3.583, P=0.001), Kellgren-Lawrence grades of 3-4 ( OR=2.348, 95% CI: 1.533 to 3.596, P=0.001), an albumin level <35 g/L ( OR=0.316, 95% CI: 0.191 to 0.522, P=0.001), and an absolute lymphocyte count <0.8×10 9/L ( OR=0.133, 95% CI: 0.069 to 0.253, P=0.001). The area under the ROC curve (AUC) for the model developed by this study was 0.753 in the training set and 0.815 in the validation set ( P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed that the consistency between the predicted risk and the actual risk was good in the training and validation sets ( P<0.05). The calibration curves for both the training and validation sets closely aligned with the ideal curve. The clinical decision curve analysis showed that the nomogram model had a good net benefit rate and a good predictive potential. Conclusions:Female, age ≥75 years, Kellgren-Lawrence grades of 3-4, an albumin level <35 g/L, and an absolute lymphocyte count <0.8×10 9/L are independent risk factors for hip fracture in the aged KOA patients. Since the nomogram prediction model based on these risk factors is satisfactory in discrimination and calibration, it shows a certain predictive ability and application value in clinic.

Objective:To develop and verify a predictive model for hip fracture risk in the aged patients with knee osteoarthritis (KOA) on the basis of analysis of the risk factors associated with the hip fracture.Methods:A retrospective study was conducted to analyze the 701 patients who had been diagnosed with KOA (Kellgren-Lawrence grades 1 to 4) at Dongyang Hospital affiliated to Wenzhou Medical University from September 2013 to September 2023. The cohort consisted of 275 males and 426 females with an age of (76.5±8.4) years. The patients were divided into a fracture group ( n=145) and a fracture-free group ( n=556) based on whether a hip fracture occurred during the follow-up period. The 2 groups were compared in terms of age, gender, comorbidities, albumin level, absolute lymphocyte count, and Kellgren-Lawrence grade, etc. The items with P<0.05 were analyzed by a multivariate logistic regression model to identify the risk factors for hip fracture in the aged KOA patients. A clinical prediction model based on the above risk factors was constructed and validated for hip fracture risk in the aged KOA patients. Results:Multivariate logistic regression analysis identified the following as independent risk factors for hip fracture in the aged KOA patients: female ( OR=2.009, 95% CI: 1.280 to 3.154, P=0.002), age ≥75 years ( OR=2.313, 95% CI: 1.493 to 3.583, P=0.001), Kellgren-Lawrence grades of 3-4 ( OR=2.348, 95% CI: 1.533 to 3.596, P=0.001), an albumin level <35 g/L ( OR=0.316, 95% CI: 0.191 to 0.522, P=0.001), and an absolute lymphocyte count <0.8×10 9/L ( OR=0.133, 95% CI: 0.069 to 0.253, P=0.001). The area under the ROC curve (AUC) for the model developed by this study was 0.753 in the training set and 0.815 in the validation set ( P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed that the consistency between the predicted risk and the actual risk was good in the training and validation sets ( P<0.05). The calibration curves for both the training and validation sets closely aligned with the ideal curve. The clinical decision curve analysis showed that the nomogram model had a good net benefit rate and a good predictive potential. Conclusions:Female, age ≥75 years, Kellgren-Lawrence grades of 3-4, an albumin level <35 g/L, and an absolute lymphocyte count <0.8×10 9/L are independent risk factors for hip fracture in the aged KOA patients. Since the nomogram prediction model based on these risk factors is satisfactory in discrimination and calibration, it shows a certain predictive ability and application value in clinic.

Objective:To discuss the medication law in prescriptions of Professor Shao Nianfang in the treatment of kidney deficiency and bone marrow loss in senile dementia based on data mining.Methods:Medical cases of kidney deficiency and bone marrow loss in senile dementia in the Geriatric Hospital of Shandong University of Traditional Chinese Medicine from 1st Jan. 2014 to 31st Oct, 2019 were collected. Through hospital electronic medical records system prescription statistics, using ancient and modern medical case cloud platform (V1.2.4), medication frequency, property ans taste, efficacy analysis, correlation rule analysis, clustering analysis and complex network analysis were performed.Results:Totally 110 cases were included in medical cases, involving 238 kinds of Chinese materia medica. The top 10 Chinese materia medica with use frequency were Poria, Acori Tatarinowii Rhizoma, Corni Fructus, Dioscoreae Rhizoma, Rehmanniae Radix Praeparata, Alpiniae Oxyphyllae Fructus, Rehmanniae Radix, Astragali Radix, Chuanxiong Rhizoma, Atractylodis Macrocephalae Rhizoma; the properties were mainly mild, warm slight cold, and cold; the tastes were mainly sweet, bitter, pungent, and light; the meridians were mainly spleen, liver, lung and kidney meridians; the efficacy was clearing dampness and promoting diuresis, clearing heat and promoting blood circulation, calming mind, clearing heat and detoxification, reducing dampness and promote appetizing, tonifying spleen; the association analysis found 15 groups of drug combinations used more than 25 times, they were: Corni Fructus and Poria, Corni Fructus and Dioscoreae Rhizoma, Dioscoreae Rhizoma and Corni Fructus, Rehmanniae Radix Praeparata and Corni Fructus, Dioscoreae Rhizoma and Poria, Astragali Radix and Poria, Alismatis Rhizoma and Poria, Moutan Cortex and Poria, Rehmanniae Radix Praeparata and Poria, Rehmanniae Radix and Poria, Polygalae Radix and Acori Tatarinowii Rhizoma, Moutan Cortex and Corni Fructus, Moutan Cortex and Dioscoreae Rhizoma, Alismatis Rhizoma and Corni Fructus, Alismatis Rhizoma and Dioscoreae Rhizoma; clustering analysis identified four groups of new prescriptions, the first group: Poria, Rehmanniae Radix, Rehmanniae Radix Praeparata, Alismatis Rhizoma, Moutan Cortex, Corni Fructus, Dioscoreae Rhizoma; the second group: Acori Tatarinowii Rhizoma, Cistanches Herba, Morindae Officinalis Radix; the third group: Alpiniae Oxyphyllae Fructus, Chuanxiong Rhizoma, Glycyrrhizae Radix et Rhizoma Praeparata Cum Melle; the fourth group: Atractylodis Macrocephalae Rhizoma, Codonopsis Radix, Astragali Radix, Angelicae Sinensis Radix; the results of complex network analysis showed that the core prescription was modified Liuwei Dihuang Pills. Conclusion:This study found that in view of kidney deficiency and bone marrow loss in senile dementia, Professor Shao pays attention to strengthening the healthy qi, and focuses on tonifying deficiency, taking into account the methods of clearing dampness, clearing heat, detoxification, removing blood stasis and restoring consciousness. The four new prescriptions found in the study can provide a reference for modified medication for syndrome differentiation.