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.

Objective To investigate the mechanism of Achyranthoside Ⅰ inhibits pyroptosis in chondrocytes through the nuclear factor-κB(NF-κB)/NOD receptor protein structure domain related proteins 3(NLRP3)/cystine containing aspartate specific proteins-1(caspase-1)signaling pathway.Methods Primary mouse chondrocytes were divided into blank group(phosphate buffered solution with the same volume),model group[10 ng·mL-1 interleukin-1β(IL-1 β)],control group(10 ng·mL-1 IL-1β+20 μmol·L-1 celecoxib)and experimental group(10 ng·mL-1 IL-1β+3 μg·mL-1 Achyranthoside Ⅰ).After 24 hours of intervention,the cell proliferation was measured by cell counting kit 8,the levels of superoxide dismutase(SOD),malondialdehyde(MDA),IL-1 and IL-6 were detected by enzyme-linked immunosorbent assay,the protein expression levels of NF-κB p65,NLRP3 and caspase-1 were detected by Western Blot.Results The apoptosis rates in experimental,control,model and blank groups were(13.34±0.61)％,(15.64±1.01)％,(21.81±1.10)％and 0;the SOD levels were(147.03±16.49),(130.09±7.33),(122.03±10.71)and(164.40±22.74)nU·mL-1;the MDA levels were(6.43±0.71),(7.63±1.01),(8.89±1.84)and(5.69±0.81)nmol·L-1;the IL-1 levels were(338.69±40.95),(361.78±32.15),(391.44±30.59)and(289.23±25.19)pg·mL-1;the IL-6 levels were(89.96±8.81),(101.10±11.59),(120.39±14.71)and(60.29±6.03)pg·mL-1;the relative expression levels of NF-κB p65 were 0.68±0.05,0.97±0.05,1.26±0.05 and 0.57±0.05;the relative expression levels of NLRP3 were 0.71±0.08,1.02±0.10,1.50±0.06 and 0.31±0.05;the relative expression levels of caspase-1 were 0.70±0.07,1.29±0.08,1.66±0.07 and 0.51±0.07,respectively.Compared with the model group,the differences of above indexes were statistically significant in the experimental group(all P＜0.05).Conclusion Achyranthoside Ⅰ can improve the oxidative stress status induced by IL-1 β in chondrocytes,reduce the expression of proteins related to the NF-κB signaling pathway,and thereby decrease the occurrence of caspase-1 dependent pyroptosis,providing a protective effect on chondrocytes.

Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]

Objectives:QT interval prolongation during treadmill test exercise is one of the clinical feature of patients with long QT syndrome(LQTS).This study aimed to explore the feasibility and efficacy of treadmill exercise testing as an auxiliary diagnosis tool for LQTS in clinical practice.Methods:We enrolled normal healthy individuals,common cardiovascular disease patients,and clinically diagnosed or suspected LQTS patients,who underwent treadmill exercise test from July 2023 to July 2024 at Fuwai Hospital.A special treadmill exercise testing procedure was designed to record the QT interval correction(QTc)intervals of the twelve lead electrocardiogram at 6 time points when performing the exercise tablet,including supine,sitting,standing,peak exercise,and recovery at 1-minute and 4-minute.The differences in QTc intervals among healthy group,cardiovascular diseases group,and suspected LQTS group were compared.Results:A total of 80 cases were consecutively enrolled,including 37 normal healthy controls,25 patients with common cardiovascular disease,and 18 patients with suspected LQTS.The QTc intervals at 6 points did not differ significantly between normal healthy controls and patients with cardiovascular disease,with QTc intervals less than 480 ms at all measurement.For patients with suspected LQTS,67.7%(12/18)of these patients presented a QTc interval≥480 ms at the 4-minute during recovery period.Among them,5 cases were confirmed to have pathogenic gene mutations of LQTS by genetic testing(including 1 case with a lying electrocardiogram QTc interval of 489 ms diagnosed with LQTS 1 type and a QTc interval of 636 ms during the 4-minute recovery period after exercise);5 clinically diagnosed patients(negative or undetectable in genetic testing)with a Schwartz score≥4,and the remaining 2 patients had a Schwartz score of 3.The remaining 5/18 patients,include 2 patients with clinical Schwartz scores≥4 and 3 patients with clinical suspicion(Schwartz scores 2-3)had a 4 min QTc interval of 445-480 ms during exercise recovery.Another patient with clinical suspicion(Schwartz score 3)had a 4 min QTc interval of<445 ms during exercise recovery and a negative genetic test at a later stage.Receiver operating characteristic curve analysis showed a sensitivity of 83.3%and specificity of 98.4%for QTc interval≥482 ms during the 4-minute recovery period of exercise as the LQTS diagnostic cutoff.Conclusions:This study results suggest that this special treadmill exercise testing protocol is effective in identifying LQTS and has strong feasibility and generalizability for clinical practice.

Objective To explore the value of the ratio between inferior turbinate and nasal cavity morphology in the diagnosis and treatment of inferior turbinate hypertrophy.Methods The clinical and CT imaging data of patients with nasal septum deviation were retrospectively collected.Patients were divided into an inferior turbinate hypertrophy group(experimental group)and a control group without nasal congestion symptoms and related lesions.Based on CT imaging data,four ratios of inferior turbinate to nasal cavity morphology were calculated:inferior turbinate bone to nasal cavity width ratio,lateral mucosa of inferior turbinate to nasal cavity width ratio,medial mucosa of inferior turbinate to nasal cavity width ratio,and inferior turbinate to nasal cavity width ratio.A t-test was used to compare the four ratios between the experimental and control groups.Results The mean values of inferior turbinate bone to nasal cavity width ratio,lateral mucosa of inferior turbinate to nasal cavity width ratio,medial mucosa of inferior turbinate to nasal cavity width ratio,and inferior turbinate to nasal cavity width ratio at the uncinate process level in the experimental group were 0.344±0.046,0.101±0.031,0.108±0.031,and 0.244±0.043,respectively.In the control group,these ratios were 0.061±0.019,0.074±0.018,0.097±0.044,and 0.146±0.038,respectively.All four ratios were significantly higher in the experimental group than in the control group,with statistically significant differences(P＜0.05).The area under the curve(AUC)for diagnosing inferior turbinate hypertrophy using inferior turbinate bone to nasal cavity width ratio,lateral mucosa of inferior turbinate to nasal cavity width ratio,medial mucosa of inferior turbinate to nasal cavity width ratio,and inferior turbinate to nasal cavity width ratio were 0.870,0.907,0.884,and 0.926,respectively.Conclusion The ratios of inferior turbinate to nasal cavity morphology can serve as quantitative indicators for inferior turbinate hypertrophy,providing clinical value for treatment planning.

Objective:To quantitatively evaluate the level of the three medical linkage in China from 2009 to 2022,explore the influencing factors and driving paths of the three medical linkage in China,and provide a new perspective for promoting the development of the three medical linkage.Methods:An optimized coupling coordination degree model was used to calculate the coupling coordination degree between the trinity healthcare systems and different binary systems within the systems in 31 provinces of China(excluding Hong Kong,Macao and Taiwan),and the Fuzzy-set Qualitative Comparative Analysis method was used to explore the condition configurations of multi-factor-driven three medical linkage.Results:From 2009 to 2022,the coupling coordination degree between the trinity healthcare systems in each province of China generally showed an increasing trend year by year.Among the binary systems,the overall coordinated development situation between the medical and medical insurance systems was the best and the regional development was the most balanced.The coupling coordination degree gap between the trinity healthcare system and the internal binary systems among provinces gradually widened,and the multi-polarization trend intensified.The paths to promote high-level three medical linkage can be summarized into two types:internal and external balanced development type(H1)and government-led type(H2,H3),among which the H1 path with per capita GDP and health expenditure as core conditions was the most common.Conclusion:It is suggested to enhance institutional and technological innovation,and integrate resources through a cross-departmental collaboration mechanism and digital technology.Provinces should select high-level optimization paths by leveraging regional endowments to narrow the regional development gap.Meanwhile,under the impetus of high-level policies,the protection and supervision system continues to improve,thereby promoting the three medical linkage.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective:To explore the training method for personalized eyebrow shape design before eyebrow transplantation surgery and to evaluate its effectiveness.Methods:Thirty physicians with similar foundational knowledge in facial aesthetic design and equivalent educational backgrounds were prospectively selected from the Second Hospital of Lanzhou University and Beijing Biliansheng Medical Beauty Clinic from January to December 2023. All the physicians were right-handed. Based on prior experience in eyebrow transplantation surgery, they were divided into two groups: an observation group [ n=20; 10 males, 10 females; aged (27.8±3.9) years] without experience in personalized eyebrow transplantation surgery, and a control group [ n=10; 5 males, 5 females; aged (29.6±4.0) years] with at least 2 years of experience in personalized eyebrow transplantation surgery. All the physicians received 2 hours of theoretical instruction on personalized eyebrow shape design and 8 hours of simulated operation training. Differences in personalized eyebrow design scores between the two groups were compared before and after training. After the assessment, physicians in the observation group performed eyebrow shape design on 20 eyebrow transplantation patients with randomly assigned face shapes, and patient satisfaction was evaluated. Results:Before training, personalized eyebrow design scores were 1.16±0.29 for the observation group and 3.75±0.22 for the control group, showing a statistically significant difference ( P<0.001). After operation training, the scores were 4.51±0.11 for the observation group and 4.89±0.08 for the control group, with no statistically significant difference ( P>0.05). The difference between pre- and post-training scores within the observation group was statistically significant ( P<0.05). Physicians in the observation group designed eyebrow shapes for male and female patients with various face shapes. Immediately after surgery, 80% (16/20) of patients were very satisfied, and 20% (4/20) were satisfied. Conclusion:After training of combined theoretical lectures, simulated practice, and hands-on patient design, physicians in the observation group demonstrate improved ability in personalized eyebrow shape design and achieve high patient satisfaction.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.