We propose a strategy to reduce unnecessary prostate biopsies in Chinese patients with total prostate-specific antigen (tPSA) >10 ng ml -1 and Prostate Imaging Reporting and Data System (PI-RADS) scores between 1 and 3. Clinical data derived from 517 patients of The First Affiliated Hospital of USTC (Hefei, China) from January 2020 to December 2023 who met the screening criteria for the study were retrospectively collected. Independent predictors were identified via univariate and multivariate logistic regression analysis. The diagnostic capacity of clinical variables was evaluated using the receiver operating characteristic (ROC) curves and area under the curve (AUC). A prostate biopsy strategy was developed via risk stratification. Of the 517 patients, 17/348 (4.9%) with PI-RADS 1-2 were diagnosed with clinically significant prostate cancer (csPCa), and 27/169 (16.0%) patients with PI-RADS 3 were diagnosed with csPCa. The appropriate prostate-specific antigen density (PSAD) cut-off values were 0.45 ng ml -2 for PI-RADS 1-2 patients and 0.3 ng ml -2 for PI-RADS 3 patients. The appropriate prostate volume (PV) cut-off values were 40 ml for PI-RADS 1-2 patients and 50 ml for PI-RADS 3 patients. The prostate biopsy strategy based on PSAD and PV developed in this study can reduce unnecessary prostate biopsies in patients with tPSA >10 ng ml -1 and PI-RADS 1-3. In the study, 66.5% (344/517) patients did not need to undergo prostate biopsy, at the expense of missing only 1.7% (6/344) patients with csPCa.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Prostate-Specific Antigen/blood* ; Aged ; Middle Aged ; Retrospective Studies ; Prostate/diagnostic imaging* ; Unnecessary Procedures/statistics & numerical data* ; Biopsy/statistics & numerical data* ; China ; ROC Curve

Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

Sacroiliac complex injuries are commonly seen in high-energy pelvic fractures. The injuries make a big difference in treatment patterns due to the diverse injury types, posing considerable challenges in formulating optimal treatment strategies, and hence are persistent clinical difficulties in orthopedic trauma. The clinical management of sacroiliac complex injuries presents several key challenges such as a non-negligible rate of missed diagnoses in associated vascular and visceral injuries, absence of standardized protocols for surgical approaches and reduction-fixation strategies across different injury patterns, and ongoing controversies regarding surgical indications and optimal timing for patients combined with concomitant lumbosacral plexus injuries. Currently, no systematic clinical guidelines are available for the diagnosis and treatment of sacroiliac complex injuries both domestically and internationally. To this end, the Pelvic and Acetabular Surgery Group, Orthopedic Branch, China International Exchange and Promotive Association for Medical and Health Care and Orthopedic Physician Branch, Chinese Medical Doctor Association organized a panel of domestic experts in the field to develop the Clinical guideline for the diagnosis and treatment of sacroiliac complex injuries ( version 2025), based on evidence-based medicine and adhering to the principles of scientific rigor, clinical applicability, and innovation. These guidelines provided 11 recommendations covering diagnosis, therapeutic principles and techniques, management protocols for lumbosacral plexus injuries, outcome evaluation, and postoperative rehabilitation pathways, etc., aiming to standardize the clinical management of sacroiliac complex injuries.

Greater trochanteric pain syndrome(GTPS)is a disease caused by structural lesions of the muscles,fascia,ligaments,and bursae near the greater trochanter of the femur.GTPS causes lateral hip joint pain,severely affecting patients' quality of life.Ultrasound has many advantages,such as real-time diagnosis,portable operation,non-radiation,and high resolution,demonstrating a high application value in the diagnosis and interventional therapy of GTPS.This article reviews the current status of ultrasound in the diagnosis and interventional therapy of GTPS and prospects its application.
Humans ; Ultrasonography ; Femur/diagnostic imaging* ; Hip Joint/diagnostic imaging* ; Arthralgia/therapy*

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To develop and compare prediction models for hyperuricemia(HUA)in perim-enopausal and postmenopausal women using Lasso regression,random forest,and multivariate logistic regres-sion.Methods A multi-stage,stratified cluster sampling method was used to select 12 790 subjects from An-ning City,Yunnan Province.Prediction models for HUA were constructed using Lasso regression,random for-est,and multivariate logistic regression.The efficacy of the model was evaluated by accuracy,sensitivity,speci-ficity,F1 score,and area under the curve(AUC).Results LASSO regression analysis screened 19 variables for inclusion in the model,such as age,waist circumference,diastolic blood pressure,BMI,HDL-C,fasting blood glucose(FBG),etc.The accuracy rate was 0.701,the sensitivity was 0.703,the specificity was 0.680,and the F1 score was 0.806.The AUC(95%CI)was 0.770(0.748-0.792).The results of the random forest model show that variables such as creatinine,triglyceride-glucose index(TyG),TG,BMI,TC,Urea nitrogen(Urea),and ALT were relatively important,with an accuracy rate of 0.663,a sensitivity of 0.653,a specificity of 0.738,and an F1 score of 0.774.The AUC(95%CI)was 0.763(0.741-0.785).Multivariate logistic re-gression results showed that 11 variables including creatinine(Cr),TyG,BMI,Urea,and ALT were included in the model,with an accuracy rate of 0.705,a sensitivity of 0.707,a specificity of 0.686,an F1 score of 0.809,and an AUC(95%CI)of 0.771(0.749-0.793).Conclusion The overall performance of LASSO re-gression and multivariate logistic regression models is better.The random forest model has a strong variable screening ability and high specificity,and can be used as a supplement to provide more accurate predictions.