Liver cancer is the third leading cause of cancer-related deaths worldwide， among which hepatocellular carcinoma （HCC） accounts for approximately 90% in primary liver cancer. The advances in diagnostic and treatment tools， along with a deeper understanding of their application， are transforming the treatment modality for patients. The application of these innovations in clinical practice faces challenges and requires guidance， and related clinical practice guidelines provide the latest recommendations for the management of HCC patients and conduct a comprehensive review of related data. In the 2024 EASL guidelines， a multidisciplinary team from multiple specialties conducts a multi-parameter assessment of individual risks and benefits from the perspective of patients.

AIM: To evaluate the effect of remimazolam on early postoperative cognitive function in elderly patients with hip fracture based on a randomized controlled trial. METHODS: A total of 106 elderly patients, aged 65-90 years, ASA grade Ⅱ or III, who underwent hip fracture surgery under combined spinal-epidural anesthesia in the Sixth Affiliated Hospital of Wenzhou Medical University from December 2022 to June 2023 and met the inclusion criteria, were selected and randomized into remimazolam group (group R) and propofol group (group P) according to the random number table, with 53 cases in each group. Patients in group P received a slow intravenous injection of propofol at a dose of 0.3-0.5 mg / kg (injection time of 1min), followed by a pump infusion at 0.5-3 mg · kg

ObjectiveTo analyze the development status and quality of clinical practice guidelines for the treatment of dominant diseases with Chinese patent medicines （CPMs）. MethodsDatabases were searched from Jan. 2019 to Dec.2023 to collect the published clinical practice guidelines of CPMs for the treatment of dominant diseases. The information about the title， the participants， clinical problems， outcomes， evidence grade， recommendations， and recommendation strength in the included clinical practice guidelines were collected， for which the development status was analyzed， and the quality was evaluated with the Scientific， Transparent and Applicable Rankings （STAR） tool for clinical practice guidelines. ResultsTotally， 34 guidelines were included， involving 273 kinds of CPMs. One to ten （with the medium five） clinical problems were proposed from 29 clinical practice guidelines respectively. All the guidelines divided the evidence into four grades according to Grade of Recommendation Assessment， Deve-lopement an Evaluation. And 28 guidelines had five levels of recommendation strength. A total of 344 recommendations were extracted， including 86 strong-recommendations， 191 weak-recommendations （including 36 weak recommendations only based on expert consensus） and 67 recommendations with unclear recommendation strength. All guidelines had high scores in the three areas of “clinical questions （94.20%）”， “evidence （91.45%）” and “recommendations （89.06%）”， while the scores in the three areas of “registry （22.06%）”， “protocol （19.00%）” and “accessibility （31.51%）” were low. The STAR recommended stars of 8 guidelines were 5.0~4.0 stars， while that of 18 guidelines were 3.5~2.5 stars， and 8 guidelines were 2.0~1.0 stars. The three guidelines with the highest recommended stars were depressive disorder， community-acquired pneumonia， and influenza in adult. ConclusionThere is a certain gap in the quality of the published clinical practice guidelines of CPMs， and the quality of the guidelines could be further improved in registry， protocols， funds， and accessibility.

Objective:To retrospectively analyze the treatment status of tyrosine kinase inhibitors (TKI) in newly diagnosed patients with chronic myeloid leukemia (CML) in China.Methods:Data of chronic phase (CP) and accelerated phase (AP) CML patients diagnosed from January 2006 to December 2022 from 77 centers, ≥18 years old, and receiving initial imatinib, nilotinib, dasatinib or flumatinib-therapy within 6 months after diagnosis in China with complete data were retrospectively interrogated. The choice of initial TKI, current TKI medications, treatment switch and reasons, treatment responses and outcomes as well as the variables associated with them were analyzed.Results:6 893 patients in CP ( n=6 453, 93.6%) or AP ( n=440, 6.4%) receiving initial imatinib ( n=4 906, 71.2%), nilotinib ( n=1 157, 16.8%), dasatinib ( n=298, 4.3%) or flumatinib ( n=532, 7.2%) -therapy. With the median follow-up of 43 ( IQR 22-75) months, 1 581 (22.9%) patients switched TKI due to resistance ( n=1 055, 15.3%), intolerance ( n=248, 3.6%), pursuit of better efficacy ( n=168, 2.4%), economic or other reasons ( n=110, 1.6%). The frequency of switching TKI in AP patients was significantly-higher than that in CP patients (44.1% vs 21.5%, P<0.001), and more AP patients switched TKI due to resistance than CP patients (75.3% vs 66.1%, P=0.011). Multi-variable analyses showed that male, lower HGB concentration and ELTS intermediate/high-risk cohort were associated with lower cytogenetic and molecular responses rate and poor outcomes in CP patients; higher WBC count and initial the second-generation TKI treatment, the higher response rates; Ph + ACA at diagnosis, poor PFS. However, Sokal intermediate/high-risk cohort was only significantly-associated with lower CCyR and MMR rates and the poor PFS. Lower HGB concentration and larger spleen size were significantly-associated with the lower cytogenetic and molecular response rates in AP patients; initial the second-generation TKI treatment, the higher treatment response rates; lower PLT count, higher blasts and Ph + ACA, poorer TFS; Ph + ACA, poorer OS. Conclusion:At present, the vast majority of newly-diagnosed CML-CP or AP patients could benefit from TKI treatment in the long term with the good treatment responses and survival outcomes.

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 investigate the risk factors for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage,and construct and verify the nomogram model.Methods A retrospective cohort study was conducted on 558 patients admitted in the First Affiliated Hospital of Chongqing Medical University and the Three Gorges Hospital Affiliated to Chongqing University.And 393 of them who hospitalized from January 2015 to January 2021 were assigned into a modeling group,and the other 165 patients from February 2021 to January 2023 into a validation group.Univariate and multivariate stepwise logistic regression analyses were used to screen out the risk factors associated with pulmonary embolism after spontaneous cerebral hemorrhage surgery.Then a nomogram model was build based on these factors and verified.Results Based on age,blood loss,Glasgow coma scale(GCS)score,surgical treatments,levels of fibrin degradation products,D-dimer and hemoglobin,plasma osmolality,and deep vein thrombosis,a risk model of pulmonary embolism was built.Receiver operating characteristic(ROC)curve analysis showed the model had good discriminability for the presence of pulmonary embolism,and the area under the curve(AUC)value was 0.908.Hosmer-Lemeshow goodness-fit test indicated that the model had a good fit to the verification set(Chi-square=14.805,df=8,P=0.063),the correction curve was close to the ideal curve,and the prediction probability of the model was close to the actual occurrence probability,suggesting the model having good accuracy.Decision curve analysis revealed that the established nomogram model can get benefits under a large range of threshold probabilities.Conclusion We develop a prediction model for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage after surgical treatment,which shows good prediction performance in both the training and validation groups,and can be used for accurate,prompt and quick identification for the occurrence of pulmonary embolism in clinical practice.

[This corrects the article DOI: 10.1016/j.apsb.2022.10.016.].

Objective:To investigate the value of inflammation markers based on blood cell count in the outcome assessment of acute ischemic stroke (AIS).Methods:Patients with AIS admitted to the Department of Neurology, Taizhou People's Hospital from January 2022 to April 2023 were included retrospectively. The demographic and clinical data of the patients were collected, particularly the related inflammatory markers based on blood cell count, including systemic inflammation response index (SIRI) and neutrophil/lymphocyte ratio (NLR). The patients included in the study were randomly divided into a modeling cohort and a validation cohort according to 7∶3. In the modeling cohort, the outcome assessment was performed based on the modified Rankin Scale score at 90 d after onset, and the score >2 was defined as poor outcome. Multivariate binary logistic regression model was used to screen for independent influencing factors on the outcome of patients with AIS. All independent influencing factors were included to construct a nomogram prediction model, and validate its predictive ability in the validation cohort. Results:A total of 389 patients with AIS were included and randomly divided into a modeling cohort ( n=272) and a validation cohort ( n=117) in 7:3. There was no significant difference in demographic and clinical data between the modeling cohort and the validation cohort. In the modeling cohort, 196 patients were in the good outcome group and 76 were in the poor outcome group. Multivariate logistic regression analysis showed that the baseline National Institutes of Health Stroke Scale score (odds ratio [ OR] 1.31, 95% confidence interval [ CI] 1.18-1.45; P<0.001), SIRI ( OR 1.64, 95% CI 1.04-2.58; P=0.033), NLR ( OR 1.18, 95% CI 1.02-1.36; P=0.024), smoking ( OR 2.51, 95% CI 1.16-5.46; P=0.020) and diabetes ( OR 2.48, 95% CI 1.13-5.48; P=0.024) were the independent risk factors for poor outcomes of patients with AIS. The above independent risk factors were included for drawing a nomogram prediction model. The receiver operating characteristic curve analysis showed that the area under the curve of the prediction model was 0.866 (95% CI 0.816-0.917), indicating that the model had good discrimination. The validation conducted in the validation cohort showed that the area under the curve of the prediction model was 0.884 (95% CI 0.804-0.964). The calibration curve and decision curve analysis also proved the reliability of the prediction model. Conclusions:SIRI and NLR are associated with poor outcomes of patients with AIS. The inclusion of SIRI and NLR in the nomogram model can accurately predict the risk of poor outcomes in patients with AIS.

The condition of patients with severe traumatic brain injury (sTBI) complicated by corona virus 2019 disease (COVID-19) is complex. sTBI can significantly increase the probability of COVID-19 developing into severe or critical stage, while COVID-19 can also increase the surgical risk of sTBI and the severity of postoperative lung lesions. There are many contradictions in the treatment process, which brings difficulties to the clinical treatment of such patients. Up to now, there are few clinical studies and therapeutic norms relevant to sTBI complicated by COVID-19. In order to standardize the clinical treatment of such patients, Critical Care Medicine Branch of China International Exchange and Promotive Association for Medical and Healthcare and Editorial Board of Chinese Journal of Trauma organized relevant experts to formulate the Chinese expert consensus on clinical treatment of adult patients with severe traumatic brain injury complicated by corona virus infection 2019 ( version 2023) based on the joint prevention and control mechanism scheme of the State Council and domestic and foreign literatures on sTBI and COVID-19 in the past 3 years of the international epidemic. Fifteen recommendations focused on emergency treatment, emergency surgery and comprehensive management were put forward to provide a guidance for the diagnosis and treatment of sTBI complicated by COVID-19.

Objective:To explore the prognostic value of 18F-FDG PET-based radiomics features by machine learning in older patients(≥60 years) with diffuse large B-cell lymphoma (DLBCL). Methods:A total of 166 older patients (88 males, 78 females, age: 60-93 years) with DLBCL who underwent pre-therapy 18F-FDG PET/CT from March 2011 to November 2019 were enrolled in the retrospective study. There were 115 patients in training cohort and 51 patients in validation cohort. The lesions in PET images were manually drawn and the obtained radiomics features from patients in training cohort were selected by the least absolute shrinkage and selection operator (LASSO), random forest (RF), and extreme gradient boosting (Xgboost), and then classified by support vector machine (SVM) to build radiomics signatures (RS) for predicting overall survival (OS). A multi-parameter model was constructed by using Cox proportional hazard model and assessed by concordance index (C-index). Results:A total of 1 421 PET radiomics features were extracted and 10 features were selected to build RS. The univariate Cox regression analysis showed that RS was a predictor of OS (hazard ratio ( HR)=5.685, 95% CI: 2.955-10.939; P<0.001). The multi-parameter model that incorporated RS, metabolic metrics, and clinical risk factors, exhibited significant prognostic superiority over the clinical model, PET-based model, and the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) in terms of OS (training cohort: C-index: 0.752 vs 0.737 vs 0.739 vs 0.688; validation cohort: C-index: 0.845 vs 0.798 vs 0.844 vs 0.775). Conclusions:RS can be used as a survival predictor for older patients(≥60 years) with DLBCL. Furthermore, the multi-parameter model incorporating RS is able to successfully predict prognosis.