OBJECTIVE To conduct a clinical rapid evaluation of the marketed proprotein convertase subtilisin/kexin type 9 （PCSK9） inhibitors in China， including evolocumab， tafolecimab， recaticimab， ebronucimab， ongericimab and inclisiran. METHODS Based on the Rapid Guide for Drug Evaluation and Selection in Chinese Medical Institutions （second edition）， drug instructions， clinical diagnosis and treatment guidelines， and literature for six drugs were retrieved from CNKI， Wanfang Data， VIP， PubMed， Embase， Cochrane Library and related official websites. The clinical rapid evaluation was conducted from five aspects： pharmaceutical characteristics， effectiveness， safety， economy， and other attributes. RESULTS The pharmaceutical characteristics， effectiveness， safety， economy， other attributes， and total score of evolocumab scored 24， 27， 15.7， 10， 5.3， and 82 points， respectively. Tafolecimab scored 23.5， 23， 11.5， 9.97， 4.6， and 72.57 points， respectively. Recaticimab scored 20.5， 22， 15.5， 6.37， 3.5， and 67.87 points. Ebronucimab scored 20， 23， 11， 6.48， 3.5， and 63.98 points. Ongericimab scored 20.5， 23， 8.5， 4.83， 3.5， and 60.33 points. Inclisiran scored 25.5， 24， 13， 6.48， 5， and 73.98 points. CONCLUSIONS Evolocumab is the optimal choice for treating hypercholesterolemia and is recommended as the first-line option. Tafolecimab is the second-line option， and recaticimab is suitable for patients who are sensitive to drug adverse reactions. Inclisiran is suitable for patients with poor compliance. Ebronucimab and ongericimab are weakly recommended due to their later market introduction. Clinicians should make individualized drug selections based on factors such as patient risk level and compliance requirements.

Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

[Objective] To explore the clinical significance and application value of establishing a database for red blood cell alloantibody detection. [Methods] Patients who were scheduled for blood transfusion in our hospital from January 1, 2020 to May 1, 2024 were selected as the research subjects. A red blood cell alloantibody detection database was established using Microsoft Office Excel software to register the detection data of patients' alloantibodies and antibodies of undetermined specificity (AUS). A retrospective analysis was conducted on the clinical characteristics, antibody distribution, antibody decay and repeat positivity of the patients in the database. The LISS-IAT method was routinely used for antibody screening and identification. [Results] Among the alloantibodies, the Rh blood group system had the highest detection rate, followed by antibodies of the MNS blood group system and the Lewis blood group system. The predominant antibody in the Rh blood group system was anti-E. In the univariate analysis, the positivity of antibody was significantly associated with the patient's gender, age, blood transfusion history, pregnancy history and type of disease (all P<0.001). In the database, 48 patients experienced antibody decay, accounting for 15.24%(48/315), with an average time span of antibody decay ranging from 22 to 1 324 days. Six cases showed repeat positivity after decay, which were related to blood transfusions. The shortest interval between blood transfusions that led to antibody repeat positivity was 3 days, and the longest interval was 427 days. Among 58 cases with AUS, 3 converted into alloantibodies, among which 2 were anti-E and 1 was anti-Lea. [Conclusion] Establishing a red blood cell alloantibody detection database is an effective way to guide ambiguous cross-matching in clinical practice and is also an effective measure for the management of transfusion risks.

OBJECTIVE To evaluate the safety of fondaparinux in pregnancy and provide reference for its rational clinical application. METHODS A search was conducted in databases including CNKI， Wanfang， PubMed， Embase， and Elsevier （the search time was from the construction of the database to December 17， 2024） to collect case report literature on fondaparinux use during pregnancy. Patient demographic information， fondaparinux use during pregnancy， concomitant medications， clinical manifestations， and treatment details were extracted for descriptive statistical analysis. RESULTS A total of 17 case reports regarding the use of fondaparinux during pregnancy were collected， involving 42 patients from 11 countries and 47 pregnancy records. Among these， 20 cases involved the use of fondaparinux for the prevention of pregnancy-related venous thromboembolism （VTE）， while 27 cases were fondaparinux treatment due to related conditions. A total of 29 occurrences of the patients were treated with fondaparinux due to a （family） history of VTE. Nine occurrences of complicated pregnancies were reported， and 35 patients had records of comorbidities or relevant medical histories. The adverse events that occurred during pregnancy with the use of fondaparinux include postpartum hemorrhage （7 cases） and excessive anticoagulation caused by inappropriate dosage （1 case）. Among the 7 cases of postpartum hemorrhage， 3 cases had a blood loss of no less than 1 000 mL （including 2 cases with uterine atony）， 3 cases had a drug discontinuation time of ≤12 h. CONCLUSIONS Based on the existing literature， the safety of fondaparinux during pregnancy is generally manageable， with the main adverse event being postpartum hemorrhage. The dosage， interval between discontinuation，comorbidities/medical history， and concomitant medications of fondaparinux may be the main causes of its adverse events.

Hereditary angioedema (HAE) is a rare, autosomal dominant inherited disorder with an incidence of approximately 1 in 50,000. Among its various tapes, HAE with normal C1 inhibitor levels (HAE-nC1-INH) is exceptionally rare.[1] HAE symptoms include recurrent episodes of skin and mucosal edema that can occur anywhere in the body.[1-4] Laryngeal edema is life-threatening, as it can lead to airway obstruction and potentially fatal suffocation.[1-3] Edema of the gastrointestinal mucosa may cause abdominal pain, vomiting, and symptoms that are often misdiagnosed as acute abdomen.[1-4] This study included four patients, including one with HAE-nC1-INH (genetic testing revealed a heterozygous mutation in the KNG1 gene (c.1404G>C: p.Q468H)) and three with HAE due to C1 inhibitor deficiency (HAE-C1-INH). This case series aims to increase knowledge of HAE by illustrating its diverse clinical presentations and emphasizing features that may prompt clinical suspicion and facilitate timely diagnosis.

OBJECTIVE To summarize the current status of position training for clinical pharmacists in China and provide references for the continuous optimization of such training programs. METHODS SinoMed， CNKI，VIP and Wanfang Data were electronically searched to collect position training of clinical pharmacists studies from the inception until November 5th 2024. After data extraction and quality evaluation， descriptive analysis was performed on the results of the included studies. RESULTS & A total of 68 pieces of relevant literature were included in the study. Among them， 50 studies reported on training content， 49 involved the allocation of teaching resources in the bases， 48 addressed training methods， and 39 focused on training evaluation； only 2 studies mentioned faculty development. There were notable variations in the clinical pharmacist training programs across different bases， particularly in the allocation of teaching resources， such as the composition of the teaching team and the utilization of auxiliary teaching tools. Additionally， differences existed in training approaches， such as those employing a single method versus a blended approach. Conversely， the core training content of each base generally revolved around clinical pharmacy practice， demonstrating a degree of consistency. Moreover， the overall emphasis on teacher training and assessment tended to be obviously insufficient. Each base can focus on enhancing the competence of clinical pharmacists by allocating teaching resources， selecting training methods， improving training content， and using evaluation tools， to further enhance the quality of clinical pharmacist training.

The implantation of left ventricular assist device (LVAD) has significantly improved the quality of life for patients with end-stage heart failure. However, it is associated with the risk of complications, with unplanned readmissions gaining increasing attention. This article reviews the influencing factors, prediction methods and models, and intervention measures for unplanned readmissions in LVAD patients, aiming to provide scientific guidance for clinical practice, assist healthcare professionals in accurately assessing patients' conditions, and develop rational care plans.

Gliomas, especially high-grade gliomas such as glioblastoma multiforme (GBM), are primary malignant tumors of the central nervous system, characterized by high proliferative capacity, invasiveness, and therapeutic resistance. The development of GBM relies heavily on continuous metabolic reprogramming to adapt to the unique intracranial microenvironment, with nicotinamide adenine dinucleotide (NAD⁺) metabolic remodeling playing a pivotal role. Dysregulation of NAD⁺ and its associated metabolic pathways sustains increased intracellular NAD⁺ levels, which drive the malignant proliferation and invasive potential of GBM, correlating with worsened patient prognosis. This review systematically summarizes the current research landscape of NAD⁺ metabolic remodeling in GBM, elucidates the mechanisms by which NAD⁺ contributes to GBM pathogenesis and progression, and explores the clinical potential of NAD⁺-targeted diagnostic and therapeutic strategies to provide novel insights and directions for the clinical management of GBM.

Objective To explore the longitudinal associations of body roundness index (BRI), visceral adiposity index (VAI), and metabolic score for visceral fat (METS-VF) with the risk of new-onset atrial fibrillation (AF). Methods This study included participants from the UK Biobank who were free of AF or pregnancy at baseline and completed the first and second assessments of BRI, VAI, and METS-VF. The changes in BRI, VAI, and METS-VF were classified using K-means clustering analyses, and the cumulative adiposity indices were also calculated. The primary outcome was new-onset AF. Three Cox regression models were employed to investigate the longitudinal associations of the BRI, VAI, and METS-VF changes with the risk of incident new-onset AF. The results were presented as hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs). Restricted cubic spline analyses were performed to explore potential non-linear associations between baseline or cumulative adiposity indices and the risk of new-onset AF. C-index analyses were conducted to evaluate the predictive value of BRI, VAI, and METS-VF for new-onset AF. Subgroup analyses were performed according to age, gender, race, smoking status, alcohol consumption, and physical activity. Polygenic risk scores were applied to account for genetic susceptibility and investigate potential interactions between adiposity indices and genetic risk. Univariate linear regression analyses were performed to evaluate the relationships of cumulative adiposity indices and magnetic resonance imaging and dual X-ray absorptiometry parameters, including visceral adipose tissue (VAT) volume, VAT mass, trunk fat volume, and trunk fat mass. We further applied the eXtreme Gradient Boosting (XGBoost) algorithm, with the feature importance being measured to evaluate the predictive value of each adiposity index for imaging parameters. Mendelian randomization analysis was further conducted to investigate the potential causal relationship between trunk fat mass and AF. Results A total of 12 776 participants were included. Over a median follow-up of 9.60 years, 761 (5.96%) new-onset AF events were recorded. Participants were divided into four classes based on the changes in adiposity indices. In the fully adjusted model, compared to participants in Class 1 of BRI, those in Class 3 (HR＝1.30, 95%CI 1.04-1.63, P＝0.023) and Class 4 (HR＝2.17, 95%CI 1.61-2.93, P＜0.001) were associated with significantly higher risks of new-onset AF. Regarding METS-VF, participants in Class 4 of METS-VF also demonstrated a significantly higher risk of new-onset AF compared to those in Class 1 (HR＝1.66, 95%CI 1.15-2.39, P＝0.007). However, no significant association was observed between different classes of VAI and the risk of new-onset AF. For every 1 standard deviation increase in cumulative BRI, VAI, and METS-VF, the fully adjusted HRs of new-onset AF were 1.23 (95%CI 1.13-1.35), 1.02 (95%CI 0.94-1.10), and 1.23 (95%CI 1.12-1.35), respectively. Cumulative adiposity indices (BRI, VAI, and METS-VF) were divided into quartiles. Using the first quartile as reference, participants in the highest quartiles of BRI (HR＝1.40, 95%CI 1.10-1.79, P＝0.007) and METS-VF (HR＝1.44, 95%CI 1.13-1.83, P＝0.003) both exerted a significantly higher risk of new-onset AF. Regarding VAI, no significant association was observed (HR＝1.00, 95%CI 0.81-1.23, P＝0.988). Restricted cubic spline analyses revealed non-linear relationships between cumulative BRI, baseline/cumulative VAI, and baseline/cumulative METS-VF with new-onset AF risk (all P_overall＜0.05, P_non-linear＜0.05). In the C-index analysis, BRI demonstrated the highest predictive performance for new-onset AF, followed by METS-VF and VAI. Subgroup analysis indicated a stronger association between METS-VF and the risk of new-onset AF amongst participants younger than 60 years (P_interaction＝0.008). Polygenic risk score analysis stratified by genetic risk demonstrated a synergistic effect between BRI and genetic risk with new-onset AF, with the overall risk of new-onset AF increasing as both BRI and genetic risk increased. Linear regression analysis revealed a positive correlation between cumulative BRI with VAT volume, VAT mass, trunk fat volume, and trunk fat mass. The feature importance plot derived from the XGBoost algorithm indicated that cumulative BRI had the greatest predictive value on VAT volume, VAT mass, trunk fat volume, and trunk fat mass. Mendelian randomization analysis confirmed a significant causal relationship between trunk fat mass and AF. Conclusions There are significant non-linear associations between BRI, METS-VF, and VAI with new-onset AF. Higher BRI and METS-VF are significantly associated with a higher risk of new-onset AF, whereas no significant association is observed for the VAI. BRI exhibits a positive correlation with VAT and trunk fat, and demonstrates superior performance in predicting new-onset AF compared to VAI and METS-VF. Monitoring and managing BRI may be important in the early detection and intervention of AF.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.