Objective To investigate the effects of arthroscopic modified suture-bridge surgery on shoulder stability,pain and imaging anatomical parameters of elderly patients with full-thickness rotator cuff injury.Methods A total of 104 elderly patients with full-thickness rotator cuff injury admitted to Zhuhai Hospital of Integrated Traditional Chinese and Western Medicine from September 2021 to June 2023 were selected and divided into the suture-bridge group and the modified group according to random number table method,with 52 cases in each group.Patients in the suture-bridge group underwent arthroscopic suture-bridge surgery,and patients in the modified group underwent arthroscopic modified suture-bridge surgery.Perioperative indexes,the range of motion of shoulder joint,American Shoulder and Elbow Surgeons(ASES)score,visual analogue scale(VAS)score,Constant shoulder function score,University of California Los Angeles(UCLA)shoulder score,recovery of shoulder joint,Sugaya classification of imaging before and after surgery,and the rate of complications were compared between the two groups.Results There was no significant difference in the length of incision,operation time,joint perfusion volume,intraoperative blood loss,or hospitalization time of patients between the two groups(P>0.05).The external rotation,forward flexion,and abduction ranges of motion 6 months after surgery of patients in the modified group were greater than those in the suture-bridge group(P<0.05);The ASES,Constant,and UCLA scores 6 months after surgery of patients in the modified group were higher than those in the suture-bridge group,while the VAS score was lower than that in the suture-bridge group,with statistically significant differences(P<0.05);The proportions of patients who experienced complete painlessness in shoulder joint,had the same range of motion as the healthy side,and recovered to work ability before surgery 6 months after surgery in the modified group were higher than those in the suture-bridge group,and the Sugaya classification of imaging in the modified group was better than that in the suture-bridge group,with statistically significant differences(P<0.05);There was no significant difference in the incidence of shoulder joint swelling,limb numbness,bleeding,or retear of patients between the two groups(P>0.05).Conclusion Arthroscopic modified suture-bridge surgery for elderly patients with full-thickness rotator cuff injury can relieve postoperative pain,improve shoulder joint function,expand range of motion of shoulder joint,and improve imaging anatomical parameters without increasing the rate of complications.

Objective To explore the predictive value of intratumor and peritumoral edema radiomics combined with the autoencoder algorithm for human epidermal growth factor receptor(HER-2)status in breast cancer to provide a new idea for preoperative noninvasive prediction of HER-2 status.Methods Totally 145 breast cancer patients from Yancheng Hospital Affiliated to Nanjing University Medical College(Center 1)and 52 ones from Jianhu Hospital Affiliated to Nantong University(Center 2)had their clinical and imaging data collected retrospectively,who were divided into a HER-2 positive group including 87 ones from Center 1 and 30 ones from Center 2 and a HER-2 negative group including 58 ones from Center 1 and 22 ones from Center 2.From December 2018 to October 2024 there were 78 patients with peritumoral edema from Center 1 randomly enrolled into a training set(55 patients)and a validation set(23 patients)in a ratio of 7∶3,and from November 2024 to March 2025 another 26 ones placed into a time validation set.The 52 patients with peritumoral edema from Center 2 were included into an external test set.Firstly,the Mazda software was used to delineate the regions of interest for the largest tumor layer and the peritumoral edema area.Secondly,multivariate analysis of variance(ANOVA),Kruskal-Wallis test,recursive feature elimination(RFE)and Relief algorithm were respectively employed to screen the radiomics features;finally,combined with ten-fold cross validation,the receiver operating characteristic curve was drawn,and the diagnostic efficacy of the models respectively constructed with radiomics parameters and ten types of machine learning algorithms,including auto encoder,support vector machine,linear discriminant analysis,random forest,Logistic regression,Logistic regression via Lasso,adaptive boosting,Gaussian process,native Bayes and decision tree,was evaluated for the HER-2 status in breast cancer.Results The model established by the auto encoder algorithm combined with three feature parameters including intratumor MaxNorm and Variance and peritumoral edema SumAverg behaved the best.The average AUC values of the training and validation sets were 0.808 and 0.735 resepctively,and the AUC values of the time validation and external test sets were 0.746 and 0.732 respectively.Conclusion The model developed with intratumor and peritumoral edema radiomics combined with the auto encoder algorithm can be used for preoperative noninvasive prediction of HER-2 status of breast cancer,which provides references for the preparation of individualized treatment scheme of breast cancer patients.[Chinese Medical Equipment Journal,2025,46(9):9-15]

Objective:To investigate the correlation between imaging features of mixed ground-glass nodules(mGGNs)under dual lung enhanced CT and pathological subtypes of lung adenocarcinoma.Methods:Retrospective analysis of clinical data of 102 isolated mGGN lung adenocarcinoma patients admitted to Dalian Central Hospital from October 2016 to October 2018.The patients were divided into adenocarcinoma in situ(AIS)group,minimally invasive adenocarcinoma(MIA)group and invasive adenocarcinoma(IAC)group according to postoperative pathological examination results.Measure the maximum diameter lesions,the maximum diameter of solid components and the proportion of solid components to evaluate imaging features of three groups.The relationship between pathological subtypes of lung adenocarcinoma and baseline features,imaging features,mGGN lesions,maximum diameter of solid components and proportion of solid components were analyzed.The diagnostic value of the maximum diameter of lesions,the maximum diameter of solid components,and the proportion of solid components in IAC were analyzed by receiver operating characteristic(ROC)curves.Results:102 patients were divided into AIS group(n=20),MIA group(n=29)and IAC group(n=53)based on postoperative pathological diagnosis.There was a statistically significant difference in age among the three groups(P＜0.05).Tumor distribution locations:35 cases in the upper lobe of the right lung,10 cases in the middle lobe of the right lung,and 15 cases in the lower lobe of the right lung;23 cases in the upper lobe of the left lung and 19 cases in the lower lobe of the left lung,the tumor distribution locations in the upper lobe of the right lung was relatively high in various pathological subtypes.The lesions in AIS and MIA groups were mostly circular or elliptical in shape,whiile the lesions in the IAC group was mostly irregular in shape.There was a statistically significant difference in morphological comparisons among the three groups(P＜0.05).There was a statistically significant difference in burr sign between MIA group and IAC group(P＜0.05).There was a statistically significant difference in pleural indentation sign and bronchial inflation sign between MIA group and IAC group(P＜0.05).There was a statistically significant difference in the maximum diameter of lesions and the maximum diameter of solid components among the three groups(P＜0.05).The proportion of solid components in IAC group was higher than that in AIS and MIA groups,and the difference was statistically significant(P＜0.05).The ROC curve shows that,the area under curve(AUC)for diagnosing IAC based on the maximum diameter of the lesion,the maximum diameter of the solid component,and the proportion of the solid component were 0.840,0.966 and 0.816,respectively.The AUC of diagnosing IAC with the maximum diameter of the solid component was greater than the AUC of the maximum diameter of the lesion and the proportion of solid components(P＜0.05).Conclusion:Dual lung enhanced CT can evaluate the imaging features of mGGN,and it can distinguish the pathological subtypes of lung adenocarcinoma,when the maximum diameter of the lesion is ≥ 16.5 mm,the maximum diameter of the solid component is ≥5.5 mm,or the proportion of solid component is ≥47.00％,it can effectively diagnose IAC,the maximum diameter of solid components has the best diagnostic efficiency for IAC.

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 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 investigate the causes and management strategies of anesthetic complications during percutaneous spinal endoscopic surgery under local anesthesia.Methods:A total of 16 800 patients (8 625 males and 8 175 females) who underwent percutaneous spinal endoscopic surgery under local anesthesia (including intravenous basic anesthesia) in Tianjin Hospital, Shandong Public Health Clinical Center and Hebei General Hospital from February 2012 to February 2023 were retrospectively analyzed. The average age was 45.3±21.6 years (range, 12-84 years). There were 220 cases of posterior cervical keyhole endoscopic surgery, 50 cases of thoracic transforaminal endoscopic surgery, 70 cases of thoracic posterior interlaminar endoscopic surgery, 11 670 cases of lumbar transforaminal endoscopic surgery, and 4 790 cases of lumbar posterior interlaminar endoscopic surgery. The occurrence time, clinical manifestations, management of intraoperative anesthesia complications were recorded, as well as surgical segments, puncture sites, complication symptoms, signs, outcome and prognosis.Results:All patients received percutaneous water-mediated uniaxial spinal endoscopic surgery under local anesthesia. There were 9 patients experienced anesthesia complications, including 6 cases of epidural diffusion of anesthetics and 3 cases of anesthetics mistakenly entering the subarachnoid space. There were 4 males and 5 females, aged 48.4±18.2 years (range, 28-84 years). There were 1 case of T 12L 1 disc herniation, 1 case of C 5-6 disc herniation, 3 cases of L 4-5 disc herniation and 4 cases of L 5S 1 disc herniation. Surgical segments and procedures: 1 case of C 5-6 posterior Keyhole endoscopic surgery, 1 case of T 12L 1 transforaminal endoscopic surgery, 2 cases of L 4-5 transforaminal endoscopic surgery, 1 case of L 4-5 interlaminar endoscopic surgery, and 4 cases of L 5S 1 interlaminar endoscopic surgery. Anesthesia complications all appeared 5-10 min after injection of local anesthetics, with symptoms of decreased oxygen saturation, decreased blood pressure, altered consciousness, and sensory and motor dysfunction of limbs. 6 patients with epidural diffusion of anesthetics recovered completely after symptomatic treatment in 5 cases, and 1 case was left with foot drop. Three patients with anesthetics mistakenly entering the subarachnoid space were immediately converted to the supine position, of which one recovered by mask oxygenation; 1 patient improved after emergency tracheal intubation, rehydration, and application of vasoconstrictive medications; and 1 patient developed multiple complications such as multiorgan failure, rhabdomyolysis, and sepsis after tracheal intubation, and recovered at 3 months after surgery with symptomatic treatment. Conclusions:Epidural diffusion and entering into subarachnoid space of anesthetics are serious complications of local anesthesia in percutaneous spinal endoscopic surgery. In addition to sensory and motor dysfunction of the limbs, the functions of the respiratory and circulatory systems can also be affected. It is necessary to be alert to the occurrence of anesthesia-related complications during operation and early identification and treatment.

Objective To explore the predictive value of intratumor and peritumoral edema radiomics combined with the autoencoder algorithm for human epidermal growth factor receptor(HER-2)status in breast cancer to provide a new idea for preoperative noninvasive prediction of HER-2 status.Methods Totally 145 breast cancer patients from Yancheng Hospital Affiliated to Nanjing University Medical College(Center 1)and 52 ones from Jianhu Hospital Affiliated to Nantong University(Center 2)had their clinical and imaging data collected retrospectively,who were divided into a HER-2 positive group including 87 ones from Center 1 and 30 ones from Center 2 and a HER-2 negative group including 58 ones from Center 1 and 22 ones from Center 2.From December 2018 to October 2024 there were 78 patients with peritumoral edema from Center 1 randomly enrolled into a training set(55 patients)and a validation set(23 patients)in a ratio of 7∶3,and from November 2024 to March 2025 another 26 ones placed into a time validation set.The 52 patients with peritumoral edema from Center 2 were included into an external test set.Firstly,the Mazda software was used to delineate the regions of interest for the largest tumor layer and the peritumoral edema area.Secondly,multivariate analysis of variance(ANOVA),Kruskal-Wallis test,recursive feature elimination(RFE)and Relief algorithm were respectively employed to screen the radiomics features;finally,combined with ten-fold cross validation,the receiver operating characteristic curve was drawn,and the diagnostic efficacy of the models respectively constructed with radiomics parameters and ten types of machine learning algorithms,including auto encoder,support vector machine,linear discriminant analysis,random forest,Logistic regression,Logistic regression via Lasso,adaptive boosting,Gaussian process,native Bayes and decision tree,was evaluated for the HER-2 status in breast cancer.Results The model established by the auto encoder algorithm combined with three feature parameters including intratumor MaxNorm and Variance and peritumoral edema SumAverg behaved the best.The average AUC values of the training and validation sets were 0.808 and 0.735 resepctively,and the AUC values of the time validation and external test sets were 0.746 and 0.732 respectively.Conclusion The model developed with intratumor and peritumoral edema radiomics combined with the auto encoder algorithm can be used for preoperative noninvasive prediction of HER-2 status of breast cancer,which provides references for the preparation of individualized treatment scheme of breast cancer patients.[Chinese Medical Equipment Journal,2025,46(9):9-15]

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To summarize the clinical characteristics and key points of diagnosis and treatment in children with TCF3::HLF fusion gene-positive acute lymphoblastic leukemia (ALL).Methods:A case series study was conducted. Clinical data of 8 children diagnosed with TCF3::HLF positive ALL at the Hematology Center of Beijing Children′s Hospital, Capital Medical University and the Hematology Oncology Department of Henan Children′s Hospital between January 2019 and January 2024 were collected. Descriptive analysis was performed on their clinical features, laboratory findings, treatment regimens and prognosis.Results:The cohort included 8 children (3 males and 5 females) with the age of 5.5 (3.5, 7.0) years. Bone pain was the primary clinical manifestation in 4 cases, with multi-site skeletal involvement in 4 cases, hypercalcemia in 5 cases, and coagulation abnormalities in 6 cases. Immunophenotyping revealed common B-cell lineage with myeloid markers in 7 cases and common B-cell phenotype in 1 case. All 8 children were positive for the TCF3::HLF fusion gene. Regarding treatment, 1 case abandoned therapy after diagnosis, while the remaining 7 cases received chemotherapy following the Chinese Children′s Leukemia Group-ALL2018 high-risk protocol. Only 1 case achieved minimal residual disease (MRD) negativity by day 33 of induction therapy. Among the 3 cases with MRD negativity before consolidation therapy, 1 case achieved it via conventional chemotherapy, while 2 cases required additional agents (venetoclax or blinatumomab). One case failed to achieve MRD negativity after consolidation therapy and later discontinued treatment (survival periods: 7months).Of the 4 cases who achieved MRD negativity after consolidation, 2 cases received conventional chemotherapy and 2 cases achieved negativity following chimeric antigen receptor T-cell therapy (CART). All 4 cases underwent hematopoietic stem cell transplantation (HSCT). Two cases in the CART combined with HSCT group survived as of the last follow-up (survival periods: 22 and 13 months). In the conventional chemotherapy combined HSCT group, 1 case relapsed and died (survival: 38 months), and 1 case died from transplant complications (survival: 11 months). The other 2 cases achieved MRD negativity before consolidation therapy but did not receive regular subsequent chemotherapy. After MRD recurrence, they underwent CART therapy without HSCT and remained alive at the last follow-up (survival periods: 49 and 12 months).Conclusions:Children with TCF3::HLF positive ALL often present with bone destruction accompanied by hypercalcemia and coagulopathy at initial diagnosis. This subtype of ALL shows poor response to conventional chemotherapy regimens, characterized by low early remission rates and high relapse risk even after HSCT. Better therapeutic outcomes have been observed with small molecule targeted drugs, immunotherapy and CART therapy.