OBJECTIVE: To investigate the efficacy and safety of chidamide combined with DICE regimen (cisplatin+ ifosfamide + etoposide + dexamethasone) for relapsed/refractory diffuse large B-cell lymphome(R/R DLBCL). METHODS: The clinical data of 31 R/R DLBCL patients treated by chidamide combined with DICE regimen in the Hematology Department of the Fourth Hospital of Hebei Medical University from October 2016 to October 2020 were retrospectively analyzed. The clinical efficacy and adverse events were observed. RESULTS: Among the 31 patients, 20 were male and 11 were female. The median age of the patients was 55 (range: 27-71) years old, 21 cases were < 60 years old, 10 cases were ≥60 years old. 26 cases were refractory and 5 cases were relapsed. There were 13 cases of germinal center B-cell like (GCB), 17 cases of non-GCB, and 1 case had missing Hans type. There were 17 cases of double-expression lymphoma (DEL) and 14 cases of non-DEL. The complete response rate of patients was 38.7%(12/31), the overall response rate was 67.7%(21/31). The median progression-free survival time and the median overall survival time were 9.8(95%CI : 4.048-15.552) months, 13.9(95%CI : 9.294-18.506) months, respectively. Multipvariate analysis showed that GCB and DEL reduced the risk of disease recurrence in R/R DLBCL patients. The main grade 3/4 hematological adverse events in this study were thrombocytopenia, agranulocytosis, anemia and leukopenia. CONCLUSION The chidamide combined with DICE regimen is effective in the treatment of R/R DLBCL, and hematological adverse events should be closely monitored.
Humans ; Lymphoma, Large B-Cell, Diffuse/drug therapy* ; Middle Aged ; Female ; Male ; Adult ; Aged ; Retrospective Studies ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Benzamides/administration & dosage* ; Aminopyridines/administration & dosage* ; Etoposide/therapeutic use* ; Cisplatin/administration & dosage* ; Ifosfamide/administration & dosage* ; Dexamethasone/therapeutic use*

OBJECTIVE: To preliminarily investigate the effect of buccal acupuncture therapy on ameliorating postoperative pain and enhancing recovery quality among patients undergoing radical resection of gastrointestinal cancers. METHODS: Fifty-two participants were randomized at a 1:1 ratio to either the buccal acupuncture or the control group. The acupuncture protocol entailed targeting 5 predetermined acupoints [CA-2 (Upper jiao), CA-3 (Middle jiao), CA-4 (Lower jiao), CA-6 (back), and CA-7 (waist) and two adjustable acupoints [CA-1 (head) and CA-8 (sacrum)] on each side of the face. The outcomes included the Numeric Rating Scale (NRS) scores for each day within 7 days postoperatively, 15-Item Quality of Recovery Scale (QoR-15) scores, analgesics consumption during and after surgery, incidences of postoperative nausea and vomiting, and perioperative levels of interleukin-6 and glucose. Adverse events related to acupuncture were recorded. RESULTS: Of the initial 52 participants, 46 completed the study and were included in the analysis. Findings indicated that the buccal acupuncture group experienced significantly reduced resting NRS scores in post-anesthesia care unit and throughout the postoperative phase (P=0.001 and P=0.003, respectively), along with enhanced QoR-15 scores on the 3rd postoperative day (P=0.008), compared to the control group. No notable differences were identified in the remaining indicators (P>0.05). CONCLUSION Buccal acupuncture therapy demonstrated significant effectiveness in reducing postoperative pain and improving recovery quality for patients undergoing radical resection of gastrointestinal cancers, presenting a viable intervention without associated adverse outcomes. (Trial registration No. ChiCTR2200060441).
Humans ; Male ; Pilot Projects ; Female ; Acupuncture Therapy/methods* ; Pain, Postoperative/therapy* ; Middle Aged ; Gastrointestinal Neoplasms/surgery* ; Aged ; Acupuncture Points ; Adult

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

Objective:To develop and assess a three-class machine learning model for predicting wild-type, 19 del, and 21 L858R mutations of the epidermal growth factor receptor (EGFR) in lung adenocarcinoma using 18F-FDG PET/CT radiomic features and clinical features. Methods:The retrospective data was collected from 703 patients (346 males, 357 females; age (64.3±9.0) years) with lung adenocarcinoma at the First People′s Hospital of Changzhou from January 2018 to June 2023. Patients were divided into the training set (563 cases) and test set (140 cases) at the ratio of 8∶2. Clinical features were selected using recursive feature elimination (RFE). Radiomic features were extracted from PET and CT images, and the optimal feature sets were selected using minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) methods. Base models were constructed by using random forest (RF), logistic regression (LR), support vector machine (SVM), K-nearest neighbors (KNN), and multi-layer perceptron (MLP), and the stacking method was applied to establish the CT and PET ensemble models. Delong test was used to compare the AUC differences between the PET/CT combined model and the clinical + PET/CT integrated model.Results:Among 703 patients, 273 were with EGFR wild-type, 202 were with 19 del mutation, and 228 were with 21 L858R mutation. In the single-modal analysis, the AUCs of CT ensemble model in the training and test sets were 0.893 and 0.667, respectively, while the AUCs of PET ensemble model were 0.692 and 0.660. The AUC of PET/CT combined model were 0.897 in training set and 0.672 in test set. The AUC of clinical + PET/CT integrated model showed further improvement, with AUCs of 0.902 and 0.721 in training and test sets, respectively. Notably, the clinical + PET/CT integrated model outperformed PET/CT combined model in predicting wild-type EGFR (test set AUC: 0.784 vs 0.707; Z=3.28, P=0.001). Conclusion:The three-class model (clinical + PET/CT integrated model) based on 18F-FDG PET/CT radiomics and clinical features effectively predicts EGFR mutation subtypes in lung adenocarcinoma.

OBJECTIVE: The study aim was to investigate the effects of exposure to multiple environmental organic pollutants on cardiopulmonary health with a focus on the potential mediating role of oxidative stress. METHODS: A repeated-measures randomized crossover study involving healthy college students in Beijing was conducted. Biological samples, including morning urine and venous blood, were collected to measure concentrations of 29 typical organic pollutants, including hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), bisphenol A and its substitutes, phthalates and their metabolites, parabens, and five biomarkers of oxidative stress. Health assessments included blood pressure measurements and lung function indicators. RESULTS: Urinary concentrations of 2-hydroxyphenanthrene (2-OH-PHE) ( β = 4.35% [95% confidence interval ( CI): 0.85%, 7.97%]), 3-hydroxyphenanthrene ( β = 3.44% [95% CI: 0.19%, 6.79%]), and 4-hydroxyphenanthrene (4-OH-PHE) ( β = 5.78% [95% CI: 1.27%, 10.5%]) were significantly and positively associated with systolic blood pressure. Exposures to 1-hydroxypyrene (1-OH-PYR) ( β = 3.05% [95% CI: -4.66%, -1.41%]), 2-OH-PHE ( β = 2.68% [95% CI: -4%, -1.34%]), and 4-OH-PHE ( β = 3% [95% CI: -4.68%, -1.29%]) were negatively associated with the ratio of forced expiratory volume in the first second to forced vital capacity. These findings highlight the adverse effects of exposure to multiple pollutants on cardiopulmonary health. Biomarkers of oxidative stress, including 8-hydroxy-2'-deoxyguanosine and extracellular superoxide dismutase, mediated the effects of multiple OH-PAHs on blood pressure and lung function. CONCLUSION Exposure to multiple organic pollutants can adversely affect cardiopulmonary health. Oxidative stress is a key mediator of the effects of OH-PAHs on blood pressure and lung function.
Humans ; Oxidative Stress/drug effects* ; Male ; Cross-Over Studies ; Female ; Young Adult ; Environmental Pollutants/toxicity* ; Environmental Exposure/adverse effects* ; Biomarkers/blood* ; Adult ; Blood Pressure/drug effects* ; Polycyclic Aromatic Hydrocarbons/urine* ; Beijing

Objective:To explore the value of 18F-fluorodeoxyglucose ( 18F-FDG) PET-CT dual-modality habitat imaging technology in predicting the epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma. Methods:This study was designed as a cross-sectional study. Clinical and imaging data of 403 patients with lung adenocarcinoma who underwent 18F-FDG PET-CT imaging with definitive EGFR results from January 2018 to April 2022 at the Third Affiliated Hospital of Soochow University were retrospectively analyzed.The patients were divided into a development set (282 cases) and a validation set (121 cases) using a stratified random sampling method at a 7∶3 ratio. An adaptive clustering algorithm was used to segment the regions of interest, forming different habitats and obtaining derived parameters. Independent samples t-test or Mann-Whitney U test were used to compare clinical, imaging indicators, and habitat-derived parameters between EGFR mutant and wild-type patient. The clinical, imaging indicators, and habitat-derived parameters that showed statistically significant differences in univariate analysis were included in multivariate logistic regression to construct clinical and clinical-habitat combined models, respectively. The receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the model′s ability to predict EGFR mutations in lung adenocarcinoma. Additionally, the net reclassification index (NRI) was employed to assess the model′s classification improvement capability. Results:There were 249 cases of EGFR mutation and 154 cases of wild type. The optimal number of habitats was two, namely Habitat 1 and Habitat 2. The parameters included in the clinical model were smoking history, bronchial sign, pleural indentation sign, and tumor diameter. The parameters incorporated into the clinical-habitat combined model were smoking history, bronchial sign, pleural indentation sign, Habitat 2, and Habitat 1 voxel count. In the development set, the AUCs for predicting EGFR mutations in lung adenocarcinoma using the clinical model and the clinical-habitat combined model were 0.723 and 0.733, respectively, with no statistically significant difference ( Z=0.60, P=0.549); In the validation set, the AUCs were 0.684 and 0.715, respectively, with no statistically significant difference ( Z=1.32, P=0.186). The accuracy (0.694) and specificity (0.609) of the clinical-habitat combined model in the validation set were slightly higher than those of the clinical model (0.686 and 0.565, respectively). NRI analysis confirmed that the clinical-habitat combined model improved the correct classification of EGFR wild-type lung adenocarcinoma by 10.9% compared to the clinical model ( P=0.018). Conclusion:18F-FDG PET-CT dual-modality habitat imaging technology can be used to analyze the microenvironment of lung adenocarcinoma and has the potential in non-invasively predicting EGFR mutation status, providing an important basis for personalized and accurate treatment of patients with lung adenocarcinoma.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective:To evaluate the clinical efficacy of"Shibao Decoction"in the management of late-onset hypogonadism(LOH)caused by deficiency of kidney essence.Methods:Sixty male patients with late-onset hypogonadism of kidney essence defi-ciency type were randomly assigned to the treatment group and the control group,each with 30 cases.The patients in treatment group were treated with oral Shibao Decoction,while the control group was treated with oral Testosterone Undecanoate Capsules.The patients in both groups were treated for 12 weeks.The PADAM symptom score,TCM syndrome score,serum total testosterone(TT),serum free testosterone(FT),sex hormone binding globulin(SHBG),body mass index(BMI),total skeletal muscle mass index(SMI),appendicular skeletal muscle mass index(ASMI),FBG,FINS,and insulin resistance index(HOMA-IR)levels were compared be-tween the two groups.Results:After treatment,PADAM scores for each item and TCM symptoms score decreased,TT and FT in-creased in both groups,all with statistically significant differences from those of pre-treatment(P＜0.05).The level of SHBG in the control group decreased(P＜0.05),which had not changed significantly in the treatment group(P＞0.05).After treatment,SMI and ASMI increased in both groups significantly(P＜0.05).BMI decreased in the control group(P＜0.05),which had not changed significantly in the treatment group(P＞0.05).The level of FINS decreased in the control group(P＜0.05),which had not changed significantly in the treatment group(P＞0.05).FPG had not changed significantly in both groups(P＞0.05),and the insulin resist-ance index(HOMA-IR)had significantly improved in both groups,all with statistically significant differences from those of pre-treat-ment(P＜0.05).After treatment,the total effective rates of PADAM score and TCM syndrome score in the treatment group were 73.3％and 86.6％respectively,and the total effective rates in the control group were 66.7％and 76.6％respectively.The total ef-fective rates of the two scores in the treatment group were slightly higher than those in the control group(P＞0.05).There was no sig-nificant difference in the indicators between the two groups after treatment,and the treatment group is generally comparable with the control group in the therapeutic effects(P＞0.05).And no adverse reactions occurred during treatment in both groups.Conclu-sion:The"Shibao Decoction"has a remarkable therapeutic effect on late-onset hypogonadism caused by deficiency of kidney essence and has good safety.It can be used as an alternative to testosterone undecanoate and is worthy of clinical promotion and application.

Objective:Analyze the risk factors for acute lung injury of postoperative acute lung injury(ALI)in patients with Stanford type A aortic dissection(STAAD),and construct a nomogram predictive model.Methods:A retrospective cohort study design was adopted.A total of 112 patients with STAAD who underwent surgical treatment in our hopital from January 2021 to August 2024 were included.They were divided into two groups according to the occurrence of ALI after the surgical:non-ALI group(73 cases)and ALI group(39 cases).Clinical data were collected from both groups of patients.The influencing factors of postoperative ALI in patients with STAAD were analyzed by multivariate logistic regression.Established nomogram prediction model based on influencing factors and validated.Results:Among 112 patients with STAAD who underwent surgical treatment,39 case postoperative ALI occurred,with an incidence rate of 34.82％.Age,preoperative creatinine,body mass index(BMI),preoperative white blood cell count,preoperative lactate and other aspects compared,The difference were statistically significant(P＜0.05).The length of stay in the intensive care unit(ICU)of the ALI group was longer than that of the non ALI group(P＜0.05).The intraoperative red blood cell transfusion volume and extracorporeal circulation time in the ALI group were higher than those in the non ALI group(P＜0.05).Long intraoperative cardiopulmonary bypass time,high BMI,high intraoperative red blood cell transfusion volume and high preoperative white blood cell count were risk factors for postoperative ALI(P＜0.05).The receiver operating characteristic(ROC)curve analysis results show that,the Area under the curve(AUC)of the nomogram prediction model was 0.871.When the optimal critical value was 0.472,its sensitivity and specificity wew 0.887 and 0.776,respectively.The internal validation results of Bootstrap show that,the C-index of the column chart prediction model was 0.862,with an absolute error of 0.032.The calibration curve is close to the ideal curve and the original curve,with a slope close to 1.Conclusions:Long intraoperative cardiopulmonary bypass time,high BMI,high intraoperative red blood cell transfusion volume and high preoperative white blood cell count are independent risk factors for postoperative ALI in patients with STAAD.The nomogram model constructed based on the above risk factors can effectively evaluate the risk of postoperative ALI in patients with STAAD.

Objective:Analyze the risk factors for acute lung injury of postoperative acute lung injury(ALI)in patients with Stanford type A aortic dissection(STAAD),and construct a nomogram predictive model.Methods:A retrospective cohort study design was adopted.A total of 112 patients with STAAD who underwent surgical treatment in our hopital from January 2021 to August 2024 were included.They were divided into two groups according to the occurrence of ALI after the surgical:non-ALI group(73 cases)and ALI group(39 cases).Clinical data were collected from both groups of patients.The influencing factors of postoperative ALI in patients with STAAD were analyzed by multivariate logistic regression.Established nomogram prediction model based on influencing factors and validated.Results:Among 112 patients with STAAD who underwent surgical treatment,39 case postoperative ALI occurred,with an incidence rate of 34.82％.Age,preoperative creatinine,body mass index(BMI),preoperative white blood cell count,preoperative lactate and other aspects compared,The difference were statistically significant(P＜0.05).The length of stay in the intensive care unit(ICU)of the ALI group was longer than that of the non ALI group(P＜0.05).The intraoperative red blood cell transfusion volume and extracorporeal circulation time in the ALI group were higher than those in the non ALI group(P＜0.05).Long intraoperative cardiopulmonary bypass time,high BMI,high intraoperative red blood cell transfusion volume and high preoperative white blood cell count were risk factors for postoperative ALI(P＜0.05).The receiver operating characteristic(ROC)curve analysis results show that,the Area under the curve(AUC)of the nomogram prediction model was 0.871.When the optimal critical value was 0.472,its sensitivity and specificity wew 0.887 and 0.776,respectively.The internal validation results of Bootstrap show that,the C-index of the column chart prediction model was 0.862,with an absolute error of 0.032.The calibration curve is close to the ideal curve and the original curve,with a slope close to 1.Conclusions:Long intraoperative cardiopulmonary bypass time,high BMI,high intraoperative red blood cell transfusion volume and high preoperative white blood cell count are independent risk factors for postoperative ALI in patients with STAAD.The nomogram model constructed based on the above risk factors can effectively evaluate the risk of postoperative ALI in patients with STAAD.