Objective: To investigate the safety and feasibility of transurethral blue laser vaporization of the prostate (BVP) under intravenous anesthesia without intubation. Methods: Clinical data of 30 benign prostatic hyperplasia (BPH) (prostate volume <40 mL) patients undergoing BVP under intravenous anesthesia without intubation in our hospital during Jul.and Nov.2024 were retrospectively analyzed.Preoperative and 1-month postoperative international prostate symptom score (IPSS), quality of life score (QoL), maximum urinary flow rate (Qmax), and postvoid residual volume (PVR) were compared.The operation time, cumulative blue laser activation time, recovery time, postoperative bladder irrigation time, postoperative catheter indwelling time, postoperative 2-hour visual analog scale (VAS) score and incidence of surgical and anesthetic complications were recorded. Results: All 30 patients successfully completed BVP under intravenous anesthesia without intubation.The operation time was (12.5±5.0) min, cumulative laser activation time (9.8±4.1) min, recovery time (6.8±1.2) min, postoperative bladder irrigation time (11.0±4.6) h, postoperative catheter indwelling time (2.7±1.1) days and postoperative 2-hour VAS score was (3.0±1.3).No cases required conversion to intubated general anesthesia, and no severe perioperative surgical or anesthetic complications occurred.Significant improvements in IPSS, QoL, Qmax, and PVR were observed 1 month postoperatively (P＜0.001). Conclusion: BVP under intravenous anesthesia without intubation in the treatment of prostate volume <40 mL BPH is clinically feasible, significantly improving lower urinary tract symptoms without significant surgical or anesthetic complications.

The prevalence of female pelvic floor dysfunction (PFD) ranges from 17.8% to 74.07%, with approximately 30% of patients experiencing comorbid anxiety, depression, or other psychological disorders, severely impairing their quality of life. Current assessment methods for PFD are primarily based on clinical techniques such as the pelvic organ prolapse quantification and two-dimensional ultrasound. But they are limited by high subjectivity, operational complexity, and the inability to provide real-time dynamic evaluation. In recent years, emerging technologies including high-density electromyography, three-dimensional ultrasound, specific biomarkers, and artificial intelligence have complemented conventional clinical methods by providing dynamic functional data and molecular-level evidence, achieving multidimensional “structure-function-molecular”assessment of PFD. The relevant literature on PFD assessment published in CNKI, PubMed, and other databases from 2019 to 2024 were retrieved. The current application status and value of commonly used clinical techniques, the core characteristics of emerging technology assessments, and the integration path between the two were reviewed, so as to provide the evidence for individualized diagnosis and treatment of PFD.

Microwave thermochemotherapy (MTC) has been applied to treat lip squamous cell carcinoma (LSCC), but a deeper understanding of its therapeutic mechanisms and molecular biology is needed. To address this, we used single-cell transcriptomics (scRNA-seq) and spatial transcriptomics (ST) to highlight the pivotal role of tumor-associated neutrophils (TANs) among tumor-infiltrating immune cells and their therapeutic response to MTC. MNDA⁺ TANs with anti-tumor activity (N1-phenotype) are found to be abundantly infiltrated by MTC with benefit of increased blood perfusion, and these TANs are characterized by enhanced cytotoxicity, ameliorated hypoxia, and upregulated IL1B, activating T&NK cells and fibroblasts via IL1B-IL1R. In this highly anti-tumor immunogenic and hypoxia-reversed microenvironment under MTC, fibroblasts accumulated in the tumor front (TF) can recruit N1-TANs via CXCL2-CXCR2 and clear N2-TANs (pro-tumor phenotype) via CXCL12-CXCR4, which results in the aggregation of N1-TANs and extracellular matrix (ECM) deposition. In addition, we construct an N1-TANs marker, MX2, which positively correlates with better prognosis in LSCC patients, and employ deep learning techniques to predict expression of MX2 from hematoxylin-eosin (H&E)-stained images so as to conveniently guide decision making in clinical practice. Collectively, our findings demonstrate that the N1-TANs/fibroblasts defense wall formed in response to MTC effectively combat LSCC.
Humans ; Neutrophils/metabolism* ; Single-Cell Analysis ; Lip Neoplasms/genetics* ; Hyperthermia, Induced/methods* ; Microwaves/therapeutic use* ; Transcriptome ; Carcinoma, Squamous Cell/immunology* ; Tumor Microenvironment

Objective:To explore the prognostic value of systemic immune-inflammatory index(SII)combined with tumor burden score (TBS) (hereinafter referred to as STS) in patients with intrahepatic cholangiocarcinoma (ICC) after radical resection, and to construct a nomogram model.Methods:The clinical data (including the degree of tumor differentiation, vascular cancer thrombus, and lymph node metastasis, etc.) of 258 ICC patients who received radical resection at People′s Hospital of Zhengzhou University (170 cases, training set) and Cancer Hospital of Zhengzhou University (88 cases, validation set) from January 1, 2016 to January 31, 2020 were retrospectively analyzed and graded by SII, TBS and STS. Multivariate Cox regression analysis were used to identify independent factors affecting the prognosis of patients with ICC. Kaplan-Meier survival curve and receiver operating characteristic curve (ROC) were drawn to evaluate the predictive efficiency of SII, TBS and STS in the overall survival of patients with ICC after radical resection. The nomogram prediction model was constructed and evaluate the performance of nomogram model using consistency index (C-index) and calibration curve.Results:Among 170 ICC patients in the training set, there were 106 cases of SII grade 1 and 64 cases of SII grade 2; 137 cases of TBS grade 1 and 33 cases of TBS grade 2; and 98 cases of STS grade 1, 47 cases of STS grade 2, and 25 cases of STS grade 3. Among 88 ICC patients in the validation set, there were 33 cases of SII grade 1 and 55 cases of SII grade 2; 66 cases of TBS grade 1 and 22 cases of TBS grade 2; and 30 case of STS grade 1, 39 cases of TBS grade 2, and 19 cases of TBS grade 3.The multivariate Cox regression analysis showed that tumor differentiation degree (highly differentiated vs. moderately differentiated HR=0.157, 95% confidence interval(95% CI) 0.045 to 0.546, highly differentiated vs. poorly differentiated HR=0.452, 95% CI 0.273 to 0.750), STS (grade 3 vs. grade 2 HR=1.966, 95% CI 1.148 to 3.469; grade 3 vs. grade 1 HR=1.405, 95% CI 0.890 to 2.216), vascular cancer thrombus ( HR=2.006, 95% CI 1.313 to 3.066), nerve invasion ( HR=1.865, 95% CI 1.221 to 2.850), and lymph node metastasis ( HR=1.802, 95% CI 1.121 to 2.896) were independent influencing factors of overall survival in ICC patients after radical resection (all P<0.05). The Kaplan-Meier survival curve showed that SII, TBS, and STS were independent influencing factors of overall survival in ICC patients (all P<0.05). The results of ROC analysis showed that the areas under the curve of SII, TBS and STS in predicting overall survival of ICC patients after radical resection were 0.566 (95% CI 0.479 to 0.652), 0.585 (95% CI 0.499 to 0.672), and 0.657 (95% CI 0.522 to 0.692), respectively. Tumor differentiation, vascular tumor thrombus, nerve invassion, lymph node metastasis, and STS were included to constract the nomogram model. The C-indexes of the training set and validation set based on the nomogram model were 0.792 (95% CI 0.699 to 0.825) and 0.776 (95% CI 0.716 to 0.833), respectively. The calibration curves of the survival rate of the training set and the validation set were close to the reference lines, and the nomogram model had better predictive ability in both the training set and the validation set. Conclusions:Preoperative STS grading is an effective and practical predictor of overall survival in ICC patients after radical section. Compared with SII and TBS alone, it has better predictive value for the prognosis of patients with ICC.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To construct and validate a machine learning model for preoperative prediction of perineural invasion (PNI) status in intrahepatic cholangiocarcinoma (ICC).Methods:Clincial data of 329 patients, including 245 admitted to Zhengzhou University People's Hospital from January 2018 to June 2023 and 84 admitted to the Affiliated Cancer Hospital of Zhengzhou University from January 2013 to January 2020 were retrospectively analyzed. Patients were divided into a training set ( n=231) and a validation set ( n=98). Clinicopathological data including age, gender, hepatitis B virus (HBV) infection status were collected. Predictive variables were determined using least absolute shrinkage and selection operator (LASSO) regression analysis. Six machine learning algorithms including random forest (RF), logistic regression, and linear kernel-based support vector machine were selected to construct the preoperative prediction model for PNI in ICC. Performance metrics of the model were calculated using a confusion matrix, and the final model was selected. The model performance was evaluated in the validation set. Calibration curves were plotted to evaluate the final model, and a Pareto chart was used to visualize the importance of predictive variables. Results:LASSO regression identified nine predictive variables included in the prediction model, including carbohydrate antigen 19-9 (CA19-9), HBV infection status, alkaline phosphatase, alanine aminotransferase, prothrombin time, total bilirubin, albumin, neutrophil times gamma-glutamyl transferase to lymphocyte ratio, and tumor burden score. Among the trained six models, the area under the curve (AUC) of the RF model was 0.909, with a sensitivity of 0.842 and an accuracy of 0.870. Compared with the AUC of the RF model, the AUCs of the other 5 models were lower (all P<0.05). The AUC of the RF model for predicting PNI in ICC in validation set was 0.736. Calibration curves showed good fit of the RF model's prediction of PNI in ICC in both training and validation sets. The Pareto chart showed that CA19-9 was the most important predictive variable in the model, followed by HBV infection status. Conclusion:The machine learning model based on the RF algorithm has a high accuracy in preoperative prediction of PNI status in ICC.

Objective:To explore the relevant risk factors and prognosis of patients with intrahepatic cholangiocarcinoma (ICC) who experienced recurrence within 6 months after surgeryMethods:This retrospective study included a total of 259 patients with ICC a treated at He'nan Provincial People's Hospital and He'nan Cancer Hospital from Jan 2018 to Jan 2020. The clinical and pathological data ,differences between the group with recurrence within 6 months and the group without recurrence within 6 months were compared using the chi-square test. Logistic regression analysis was used to determine the relevant risk factors for recurrence within 6 months. Kaplan-Meier method was used to construct survival and recurrence curves, and survival rates were calculated.Results:The overall survival and recurrence-free survival of patients in the group with recurrence within 6 months were significantly shorter. CA19-9, tumor longitudinal diameter, microvascular invasion, and neural invasion were identified as independent risk factors for recurrence within 6 months after ICC surgery ( P<0.001). Conclusion:The patient population experiencing recurrence within 6 months after ICC surgery has an extremely poor prognosis and possesses a specific tumor microenvironment. CA19-9, tumor longitudinal diameter, microvascular invasion, and neural invasion were identified as independent risk factors for recurrence within 6 months after ICC surgery.

Polymyxin B, which is a last-line antibiotic for extensively drug-resistant Gram-negative bacterial infections, became available in China in Dec. 2017. As dose adjustments are based solely on clinical experience of risk toxicity, treatment failure, and emergence of resistance, there is an urgent clinical need to perform therapeutic drug monitoring (TDM) to optimize the use of polymyxin B. It is thus necessary to standardize operating procedures to ensure the accuracy of TDM and provide evidence for their rational use. We report a consensus on TDM guidelines for polymyxin B, as endorsed by the Infection and Chemotherapy Committee of the Shanghai Medical Association and the Therapeutic Drug Monitoring Committee of the Chinese Pharmacological Society. The consensus panel was composed of clinicians, pharmacists, and microbiologists from different provinces in China and Australia who made recommendations regarding target concentrations, sample collection, reporting, and explanation of TDM results. The guidelines provide the first-ever consensus on conducting TDM of polymyxin B, and are intended to guide optimal clinical use.
Humans ; Anti-Bacterial Agents/therapeutic use* ; China ; Drug Monitoring/methods* ; Polymyxin B ; Practice Guidelines as Topic

Objective:To study the factors influencing survival after radical resection in patients with intrahepatic cholangiocarcinoma (ICC), and to construct a nomogram on survival prediction.Methods:The clinical data of 139 patients with ICC who underwent radical resection at the People's Hospital of Zhengzhou University from June 2018 to December 2021 were retrospectively analyzed. There are 69 males and 70 females, aged (59.5±10.2) years old. These patients were divided into two groups based on a 3: 1 ratio by using the random number method: the test group ( n=104) and the validation group ( n=35). Data from the test group was used to construct a nomagram and data from the validation group was used to validate the predictive power of the nomagram. Univariate and multivariate Cox regression analyses were used to analyse factors influencing survival on the test group patients and to construct a nomogram. The predictive accuracy of the nomogram was determined by receiver operating characteristic (ROC) curves, concordance index (C-index) and calibration curves. Results:The results of the multivariate regression analysis showed that a combined hemoglobin, albumin, lymphocyte and platelet immunoinflammation (HALP) score <37.1 ( HR=1.784, 95% CI: 1.047-3.040), CA19-9 > 35U/ml ( HR=2.352, 95% CI: 1.139-4.857), poorly differentiated tumor ( HR=2.475, 95% CI: 1.237-4.953) and vascular invasion ( HR=1.897, 95% CI: 1.110-3.244) were independent risk factors that affected prognosis of patients with ICC after radical resection (all P<0.05). The AUCs of the nomogram in the test group in predicting the overall survival at 1, 2 and 3 years of patients with ICC after radical resection were 0.808, 0.853 and 0.859, respectively. There was good consistency between the prediction of the nomogram and actual observation. The predicted C-index of the total survival period of the test group was 0.765 (95% CI: 0.704-0.826), and the C-index of the validation group was 0.759 (95% CI: 0.673-0.845). Conclusion:A HALP score <37.1, CA19-9>35 U/ml, poorly differentiated tumour and vascular invasion were independent risk factors for prognosis of ICC patients after radical resection. The nomogram was established based on the above factors and showed good performance in predicting overall survival after radical resection in patients with ICC.

Objective:To construct a nomogram prediction model for survival after radical surgical resection of intrahepatic cholangiocarcinoma (ICC) based on the albumin-bilirubin index (ALBI), and to evaluate its predictive efficacy.Methods:From January 2016 to January 2020, 170 patients with ICC who underwent radical surgical resection at the People's Hospital of Zhengzhou University were retrospectively analyzed. There were 90 males and 80 females, aged (58.5±10.6) years old. Based on a ratio of 7∶3 by the random number table, the patients were divided into the training set ( n=117) and the internal validation set ( n=53). The training set was used for nomogram model construction, and the validation set was used for model validation and evaluation. Follow up was conducted through outpatient reexamination and telephone contact. The Kaplan-Meier method was used for survival analysis, and a nomogram was drawn based on variables with a P<0.05 in multivariate Cox regression analysis. The predictive strength of the predictive model was evaluated by analyzing the consistency index (C-index), calibration curve, and clinical decision curve of the training and validation sets. Results:Multivariate Cox regression analysis showed that carbohydrate antigen 19-9 (CA19-9) ≥37 U/ml ( HR=1.99, 95% CI: 1.10-3.60, P=0.024), ALBI≥-2.80 ( HR=2.43, 95% CI: 1.40-4.22, P=0.002), vascular tumor thrombus ( HR=2.34, 95% CI: 1.40-3.92, P=0.001), and the 8th edition AJCC N1 staging ( HR=2.18, 95% CI: 1.21-3.95, P=0.010) were independent risk factors affecting postoperative survival of ICC patients after curative resection. The predictive model constructed based on the above variables was then evaluated, and the C-index of the model was 0.76. Calibration curve showed the predicted survival curve of ICC patients at 3 years after surgery based on the model was well-fitted to the 45° diagonal line which represented actual survival. Clinical decision curve analysis showed that the model had a significant positive net benefit in both the training and validation sets. Conclusion:The nomograph model for survival rate after radical resection of ICC was constructed based on four variables: ALBI, CA19-9, vascular tumor thrombus, and AJCC N staging (8th edition) in this study. This model provided a reference for more accurate prognosis evaluation and treatment selection plan for ICC patients.