Animal model research on spleen and stomach diseases in traditional Chinese medicine （TCM） is of great significance for elucidating the nature of diseases and syndromes and for revealing the mechanisms of action of Chinese herbal medicinals. At present， studies on classical TCM syndrome models of spleen and stomach diseases mainly focus on spleen deficiency syndrome， liver constraint syndrome， and damp-heat syndrome. Model construction is mostly based on the etiological and pathophysiological characteristics of syndrome， and model evaluation primarily involves macroscopic manifestations and physicochemical indicators. This paper summarizes the current research status of animal models integrating disease and syndrome for seven common spleen and stomach diseases， including chronic gastritis and gastric precancerous lesions， gastroesophageal reflux disease， functional dyspepsia， inflammatory bowel disease， irritable bowel syndrome， functional constipation， and functional diarrhea. The modeling methods and characteristics of disease-syndrome combined animal models for each disease are analyzed. It is proposed that future research on disease-syndrome integration in spleen and stomach diseases should move toward syste-matic， precise， and integrative development， and that interdisciplinary and cross-disciplinary research approaches should be adopted to enhance the predictive value and application efficiency of disease-syndrome combined animal models.

Objective:To explore the feasibility of the multiple-choice auditory graphical interactive check（MAGIC） screening module in childhood hearing screening in children aged 3 to 6 years. Methods:A hearing screening was conducted on 366 children（732 ears） aged between 3 and 6 years. The screening methods included MAGIC, DPOAE, and acoustic immittance.The cooperation, screening time, pass rate, and correlation of the three screening methods were compared. Results:There was a statistically significant difference in the degree of cooperation among the three screeningmethods（P=0.004）.The MAGIC pure tone screening method was 98.6%, the screening DPOAE was 99.5%,and the acoustic immittance screening was 100%. For the screening duration, the MAGIC pure tone screening method was（116.3±59.1）s, the screening DPOAE was（27.2±19.7）s, and the acoustic impedance screening was（24.6±14.6）s. There was a significant statistical significance differences among the three or two groups（P<0.01）. The passing rates of MAGIC pure tone screening,screening DPOAE and acoustic immittance screening were 64.7%, 65.4%, and 69.3%, respectively, and there was no significant statistical difference among the three or two groups（P>0.05）. There was no significant difference between MAGIC pure tone screening method and screening DPOAE（P=0.827>0.05）, and acoustic impedance（P=0.653>0.05）, while the difference between screening DPOAE and acoustic impedance was statistically significant（P<0.01）. Conclusion:MAGIC pure sound screening method has good feasibility, can comprehensively reflect the hearing level of screened children, and can be promoted for hearing screening in children aged between 3 and 6 years.
Humans ; Child, Preschool ; Child ; Female ; Male ; Audiometry, Pure-Tone ; Mass Screening/methods* ; Feasibility Studies ; Acoustic Impedance Tests/methods* ; Hearing Loss/diagnosis* ; Hearing Tests/methods*

Objective:To construct a comprehensive performance evaluation index system based on diagnosis related groups(DRG) and analyze the overall performance of a hospital before and after the implementation of DRG payment using an improved radar chart method.Methods:A literature analysis method was employed to preliminarily determine the performance evaluation framework in combination with the actual situation of the hospital. Subsequently, the Delphi method was used to establish a comprehensive performance evaluation index system based on DRG. Data related to inpatients from 2019 to 2022 (with 2019 being the period before the implementation of DRG payment) were extracted from the hospital information system and medical insurance system of a tertiary general hospital in Liaoning Province. The improved radar chart method was then utilized to conduct a comprehensive performance evaluation of the hospital.Results:The comprehensive performance evaluation index system based on DRG included five first-level indicators (service capacity, service efficiency, medical quality, medical safety, and revenue and costs) and 19 second-level indicators. The weights of medical quality and medical safety were the highest, both at 0.212. The evaluation results using the improved radar chart method showed that the comprehensive performance values of the hospital from 2019 to 2022 were 0.427 0, 0.463 3, 0.505 2, and 0.545 0, respectively. Overall, the five first-level indicators showed an improving trend, but the development of service capacity, service efficiency, medical quality, and revenue and costs was more balanced compared with medical safety.Conclusions:With the implementation of DRG payment reform, the performance of the hospital has improved and was trending towards more balanced development. The evaluation index system constructed in this study is scientifically sound and feasible. Combined with the improved radar chart method, it can more intuitively reflect changes in hospital performance and can serve as a reference for performance evaluation in public hospitals.

Objective:To construct a comprehensive performance evaluation index system based on diagnosis related groups(DRG) and analyze the overall performance of a hospital before and after the implementation of DRG payment using an improved radar chart method.Methods:A literature analysis method was employed to preliminarily determine the performance evaluation framework in combination with the actual situation of the hospital. Subsequently, the Delphi method was used to establish a comprehensive performance evaluation index system based on DRG. Data related to inpatients from 2019 to 2022 (with 2019 being the period before the implementation of DRG payment) were extracted from the hospital information system and medical insurance system of a tertiary general hospital in Liaoning Province. The improved radar chart method was then utilized to conduct a comprehensive performance evaluation of the hospital.Results:The comprehensive performance evaluation index system based on DRG included five first-level indicators (service capacity, service efficiency, medical quality, medical safety, and revenue and costs) and 19 second-level indicators. The weights of medical quality and medical safety were the highest, both at 0.212. The evaluation results using the improved radar chart method showed that the comprehensive performance values of the hospital from 2019 to 2022 were 0.427 0, 0.463 3, 0.505 2, and 0.545 0, respectively. Overall, the five first-level indicators showed an improving trend, but the development of service capacity, service efficiency, medical quality, and revenue and costs was more balanced compared with medical safety.Conclusions:With the implementation of DRG payment reform, the performance of the hospital has improved and was trending towards more balanced development. The evaluation index system constructed in this study is scientifically sound and feasible. Combined with the improved radar chart method, it can more intuitively reflect changes in hospital performance and can serve as a reference for performance evaluation in public hospitals.

Objective:To predict the clinical value of World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading of clear cell renal cell carcinoma (ccRCC) pre-scholarly based on ultrasound imaging group.Methods:Clinical and ultrasound imaging data of patients with surgically pathologically confirmed ccRCC at Tianjin Medical University Cancer Institue and Hospital from January 2021 to October 2022 were retrospectively collected and divided into a low grade group (grade Ⅰ and Ⅱ, 105 cases) and a high grade group (grade Ⅲ and Ⅳ, 70 cases) using WHO/ISUP pathological grading criteria. The clear image of the largest diameter of the tumor was selected and imported into ITK-SNAP software for manual segmentation of the image and extraction of ultrasonographic radiomics features. The patients were randomly divided into a training group and a test group in the ratio of 7∶3, with 122 cases in the training group and 53 cases in the test group. Stable radiomics features were obtained by dimensionality reduction. The support vector machines (SVM) algorithm was applied to predict the pathological grading of ccRCC. Finally, a clinical-ultrasound imaging model, an ultrasonographic radiomics model and a comprehensive model combining the two were constructed. The predictive effects of the three models were analyzed by the area under the ROC curve (AUC). The performance of each model was evaluated by applying the calibration curve. The net benefit of patients was obtained by applying the decision curve.Results:A total of 873 radiomics features were extracted, and 10 features were finally obtained for model construction after dimensionality reduction. Final test results showed that the AUC, sensitivity, specificity and accuracy of the clinical-ultrasound imaging model were 0.68, 0.47, 0.78, 0.66. The AUC, sensitivity, specificity and accuracy of the ultrasonographic radiomics model were 0.74, 0.53, 0.88, 0.74. The AUC, sensitivity, specificity and accuracy of the comprehensive model were 0.84, 0.63, 0.86, 0.77. The AUC of the comprehensive model being larger than that of the clinical-ultrasound imaging model ( Z=-3.224, P=0.001) and ultrasonographic radiomics model ( Z=-2.594, P=0.009). The calibration curves showed that the comprehensive model was more stable than the other two models. The decision curve showed a higher net clinical benefit for the comprehensive model than for the other two models within a threshold of 0.1-1.0. Conclusions:The preoperative prediction of ccRCC pathological grading by the radiomics model based on ultrasound images is effective. The comprehensive model constructed by combining relevant clinical and ultrasound parameters has better performance, which can help predict ccRCC pathological grading preoperatively to a certain extent. It is crucial to help physicians choose the best management plan in the era of personalized medicine.

Objective:To investigate the prediction of National Institute of Healthy (NIH) risk stratification of gastrointestinal stromal tumor(GIST) based on clinical ultrasound model, ultrasonographic radiomics model and combined model by oral contrast enhanced ultrasonography.Methods:The clinical and ultrasound imaging data of 204 gastric GIST patients attending Tianjin Medical University Cancer Institute and Hospital from June 2021 to June 2022 were retrospectively analyzed, among whom a total of 101 patients with high and moderate NIH risk stratification GIST confirmed by postoperative pathology were included in the high risk group, and a total of 103 patients with low and extremely low NIH risk stratification GIST were in the low risk group. The ultrasound images of the largest diameter of the GIST were manually segmented by ITK-SNAP software, and Pyradiomics (v3.0.1) module in Python 3.8.7 was applied to extract ultrasonographic radiomics features from the ROI segmented images. The patients were randomly divided into training and validation sets in the ratio of 7∶3. The XGBoost of Sklearn module was applied to construct the clinical ultrasound imaging model, ultrasonographic radiomics model, and combined model. Then the area under ROC curve (AUC), sensitivity, specificity, and accuracy were evaluated; the predictive ability of the three models was compared by Delong test. Calibration Curve was applied to evaluate the model performance, and the clinical Decision Curve Analysis was applied to determine the net benefit to patients.Results:A total of 578 ultrasonographic radiomics features were extracted from ROI, and 8 ultrasonographic radiomics features were finally retained for modeling after regression and dimensionality reduction. Finally, test results showed that AUC, sensitivity, specificity and accuracy of clinical ultrasound imaging model, ultrasonographic radiomics model and combined model were 0.75, 69.3%, 68.9%, 69.1%; 0.87, 79.2%, 81.6%, 80.4%; 0.91, 80.2%, 83.5%, 81.9%, respectively. Delong test showed that the difference of AUC between ultrasonographic radiomics model and clinical ultrasound imaging model was statistically significant ( Z=2.698, P<0.001), and the combined model was significantly better than clinical ultrasound imaging model ( Z=4.062, P<0.001) and ultrasonographic radiomics model ( Z=2.225, P=0.026). Calibration Curve showed the high performance of combined model, and Decision Curve Analysis showed the superior clinical usefulness of combined model. Conclusions:It is feasible to construct an ultrasonographic radiomics model for GIST NIH risk stratification based on oral contrast enhanced ultrasonography images, and the combined model has more advantageous diagnostic performance, which can identify high risk NIH GIST objectively and stably for clinical purposes.

Objective:To explore the predictive value of ultrasound-based radiomics for liver metastasis in pancreatic neuroendocrine tumors (pNEN).Methods:A retrospective analysis was conducted on clinical, pathological, and ultrasound data of 269 pNEN patients confirmed by pathology at Tianjin Medical University Cancer Institute and Hospital from January 2012 to June 2022, including 94 patients with liver metastasis and 175 without liver metastasis. The regions of interest (ROI) were delineated on the maximum diameter section of the tumor using ITKSNAP software, and radiomics features were extracted using Pyradiomics. Radiomics features with an intra-group correlation coefficient greater than 0.90 were retained, and the optimal features were selected using the maximum relevance minimum redundancy (MRMR) algorithm. The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3, and the random forest algorithm (Rfs) was used to predict pNEN liver metastasis. Three models were constructed, including the clinical ultrasound model, the radiomics model, and the comprehensive model that combined clinical ultrasound and radiomics features. The predictive performance of different models for pNEN liver metastasis was analyzed using the ROC curve, and the predictive performance of different models was compared using the Delong test.Results:A total of 874 features were extracted from the ROI, and 12 highly robust radiomics features were retained for model construction based on inter- and intra-observer correlation grading and feature selection. The area under curve(AUC), sensitivity, specificity, and accuracy of the radiomics model, the clinical ultrasound model, and the comprehensive model for predicting liver metastasis in pNEN patients were 0.800, 0.574, 0.789, 0.714; 0.780, 0.596, 0.874, 0.777; and 0.890, 0.694, 0.874, 0.810, respectively. The Delong test showed that the comprehensive model had the best predictive performance, with an AUC superior to that of radiomics model ( Z=3.845, P=0.000 12) and clinical ultrasound model ( Z=3.506, P=0.000 45). Conclusions:The radiomics model based on ultrasound has good performance in predicting liver metastasis in pNEN, and the comprehensive model that combines clinical ultrasound and radiomics features can further improve the predictive performance of the model.

Objective:To explore the diagnostic value of strain ultrasonic elastography (SUE) supported by Image Pro Plus (IPP) software in distinguishing benign and malignant Breast Imaging Reporting and Data System (BI-RADS) category 4 nodules.Methods:The clinical and ultrasound imaging data of 192 female patients with BI-RADS category 4 nodules diagnosed by breast ultrasound in Tianjin Medical University Cancer Institute and Hospital from January 2020 to January 2021 were retrospectively analyzed. One nodule was selected for each patient, and a total of 192 nodules were analyzed. The ultrasound images and SUE images of each nodule were acquired before surgery, followed by BI-RADS classification scoring and SUE scoring. The IPP software was applied to outline the region of interest of all nodules, and the software automatically counted the SUE area ratio (SUE-IPP-AR) of all nodules. Using pathological diagnosis as the gold standard, SUE-IPP scoring was performed based on the optimal cut-off value of SUE-IPP-AR for distinguishing benign and malignant nodules according to receiver operating characteristic (ROC) curve. The efficacy of BI-RADS classification, SUE score, SUE-IPP score, and SUE-IPP+BI-RADS combined score in the differentiation of benign and malignant breast nodules were analyzed by ROC curve. Kappa coefficient was used to assess inter-observer agreement for SUE and SUE-IPP-AR.Results:Of the 192 nodules, 58 were benign nodules and 134 were malignant nodules diagnosed by pathology. These nodules were classified by BI-RADS, with 46 nodules in BI-RADS category 4A, 57 nodules in BI-RADS category 4B and 89 nodules in BI-RADS category 4C. SUE images 1-6 level were 12, 14, 41, 51, 42, and 32 nodules, respectively. ROC curve analysis showed that the optimal cut-off value of SUE-IPP for determining benign and malignant BI-RADS category 4 breast nodules was 58% [area under the curve (AUC) = 0.729, sensitivity 73%, specificity 69%]. The AUC of SUE-IPP+BI-RADS combined score for determining benign and malignant nodules was the largest (0.871), which was higher than that of BI-RADS score (AUC = 0.829, Z = 2.51, P = 0.012), SUE-IPP score (AUC = 0.729, Z = 3.56, P < 0.001) and SUE score (AUC = 0.695, Z = 4.37, P < 0.001). The sensitivity of SUE-IPP+BI-RADS combined score ≥ 3 points for diagnosing malignant nodules was 86.6%, while the specificity was 82.8%. Therefore, SUE-IPP+ BI-RADS score had the best efficacy for determining benign and malignant nodules. There was good agreement between sonographer with more than 5 years of experience and those with less than 5 years of experience in applying SUE to diagnose breast malignant nodules (Kappa = 0.768, 95% CI 0.711-0.825), and very good diagnostic agreement in applying SUE-IPP (Kappa = 0.946, 95% CI 0.919-0.974). Conclusions:SUE-IPP can improve the diagnostic ability for BI-RADS category 4 breast malignant nodules and can be used as an adjunct to ultrasound diagnosis.

Objective To determine the audiological characteristics in 832 deaf children with biallelic causative mutations in GJB2 ,SLC26A4 gene .Methods The 832 patients received deafness gene screening ,553 were GJB2 gene biallelic causative mutations ,279 were SLC26A4 gene biallelic causative mutations .Patients were divided into four groups according to ages of hearing loss onset :<1 ,1~3 ,3~6 ,6~12 years old ,and the audiological character-istics and prevalence of GJB2 ,SLC26A4 gene mutations at different ages of onset .Results The prevalence of GJB2 gene mutations at four groups was 37 .97% (210/553) ,38 .34% (212/553) ,16 .27% (90/553) ,7 .41% (41/553) ,re-spectively ;the prevalence of SLC26A4 gene mutations at four groups was 25 .45% (71/279) ,44 .80% (125/279) , 20 .07% (56/279) ,9 .67% (27/279) ,respectively .The difference between GJB2 and SLC26A4 gene was significant(P=0 .001) .The prevalence of profound hearing loss with GJB2 gene mutations at four groups were 66 .67% (140/210) ,61 .32% (130/212) ,47 .78% (43/90) ,41 .46% (17/41) ,respectively .The difference was significant (P=0 .004) ,while the difference in 279 patients with SLC26A4 gene mutations was not statistically significant (P= 0 . 083) .Conclusion The age of hearing loss onset in patients with biallelic causative mutations in GJB 2 or SLC26A4 gene refers to 0~3 years -old ,hearing loss in patients with GJB2 ,SLC26A4 gene mutations gives priority to pro-found .The age of hearing loss onset is smaller ,the ratio of profound hearing loss is higher .Patients with severe and profound hearing impairment should be performed the genetic testing when the age of onset under 12 .

Objective To investigate the clinical effect of angioplasty for symptomatic intracranial atherosclerotic stenosis. Methods Eighty-two patients with symptomatic intracranial atherosclerotic stenosis whom underwent angioplasty after the failure of standard medical therapy were enrolled from Nan-jing Stroke Registry Program from September 2010 to June 2013.Nine of them underwent routine balloon angioplasty alone and 73 underwent intracranial stenting.The median time from onset to surgery was 24.5 days.The occurrence of endpoint events (any stroke ≤30 d after procedure,death and ischemic stroke >30 d in guilty vessels or original stenosis had restenosis and needed to be treated again)was assessed. The incidence of restenosis was followed up with imaging (CTA or DSA). Results (1)In the 82 patients, the success rate of operation was 92.7%(n=72 ),and 78 (95.1%)received follow-up,4 were lost to follow-up.The median follow-up time was 22.5 months (range 9 to 29 months ).Ten patients had an endpoint event,7 of them were ischemic stroke,1 was cerebral hemorrhage,and two were severe asymptomatic restenosis who underwent stenting again.The endpoint events of 3 patients occurred at day 30 after procedure (at ≤24 h after procedure).Kaplan-Meier curves showed that the incidences of cumulative endpoint events at 1,6,12,and 24 months were 3.7%,8.6%,11%,and 13%,respectively.(2)60 patients (73.2%)received imaging examination (11 CTA and 49 DSA ).Restenosis occurred in 17 patients (28.3%),among them the incidence of symptomatic restenosis was 5%(n =3 ),and asymptomatic restenosis was 23.3%(n=14). Conclusion After a comprehensive assessment and a rigorous screening, the safety is high and the mid- and long-term efficacy are satisfactory in patients with symptomatic intracranial arterial stenosis who are treated with angioplasty when their medical treatment is invalid.