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Table of Content

    25 August 2026, Volume 25 Issue 04 Previous Issue   
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    Expert forum
    Research progress on obstructive sleep apnea-related hypertension
    ZHONG Jiuchang, DONG Zhaojie
    2026, 25 (04):  389-398.  DOI: 10.16150/j.1671-2870.2026.04.001
    Abstract ( 0 )   HTML ( 8 )   PDF (1224KB) ( 2 )  

    Obstructive sleep apnea (OSA)-related hypertension is a complex clinical syndrome involving multisystem damage throughout the body. It is characterized by repeated upper airway obstruction during sleep, leading to apnea, hypopnea, and/or respiratory effort-related microarousals. These events result in chronic intermittent hypoxia, carbon dioxide retention, sympathetic nervous system activation, sleep fragmentation, which in turn contribute to chronic hypoxia and elevated blood pressure. The typical manifestations are refractory hypertension, nocturnal hypertension, and elevated morning blood pressure, presenting a non-dipper or reverse-dipper blood pressure rhythm. OSA-related hypertension can be classified into hypoxic burden type, high-arousal type, high-loop-gain type, upper airway collapse type, high-aldosterone type, mixed type, and other types. Currently, clinical management and treatment goal setting of OSA-related hypertension overly rely on the apnea-hypopnea index (AHI). In clinical practice, there are issues including insufficient consideration of patient heterogeneity and pathophysiological classification, inadequate consideration of comorbidities and confounding factors, poor adherence to continuous positive airway pressure (CPAP), and insufficient effective therapeutic dosage, all of which pose new challenges to disease diagnosis, treatment, and patient management. In addition, OSA-related hypertension often coexists with obesity, tumors, primary aldosteronism, metabolic syndrome, insulin resistance, chronic kidney disease, and other conditions, particularly in elderly patients. Therefore, based on precise heterogeneity and pathophysiological classification, a multidimensional assessment and treatment strategy for OSA-related hypertension centered on AHI and hypoxic burden—combined with lifestyle interventions, effective hypoxic burden reduction, weight loss and sleep management, pharmacotherapy, CPAP therapy, catheter-based renal denervation, surgical intervention, device therapy, technological innovations such as artificial intelligence, policy support, health insurance policies, and patient engagement—should be adopted to establish a new lifelong management and treatment system.

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    Clinical significance and research progress of spread through air spaces (STAS) in non-small cell lung cancer
    ZHONG Hua, HUANG Litang, DU Huawei
    2026, 25 (04):  399-405.  DOI: 10.16150/j.1671-2870.2026.04.002
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    Spread through air spaces (STAS), defined as the presence of tumor cells within the air spaces of the lung parenchyma beyond the edge of the main tumor, represents a novel pattern of invasion in lung cancer. Since its formal definition by the World Health Organization in 2015, STAS has fundamentally reshaped the risk stratification and treatment paradigms for non-small cell lung cancer (NSCLC). With the publication of data from the large-scale JCOG0802/WJOG4607L clinical trials conducted by the Japan Clinical Oncology Group and the West Japan Oncology Group, STAS has evolved from a mere pathological feature into an independent risk factor affecting recurrence-free survival (RFS) and overall survival (OS) in early-stage NSCLC, emerging as a pivotal biomarker for determining the surgical approach (lobectomy or sublobar resection) and postoperative adjuvant therapy decisions. This review systematically outlines the definition, diagnosis, and preoperative multimodal imaging prediction models of STAS. Furthermore, it elucidates the selection of surgical resection extent based on STAS status and presents the latest evidence-based data regarding adjuvant therapy, aiming to provide practical guidance for clinicians in standardizing diagnosis and treatment.

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    Principles of diagnosis and treatment of respiratory comorbidities:an example of comorbidities of chronic obstructive pulmonary disease
    SHI Guochao, NI Yingmeng
    2026, 25 (04):  406-412.  DOI: 10.16150/j.1671-2870.2026.04.003
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    Chronic obstructive pulmonary disease (COPD) is one of the most prevalent chronic airway diseases and frequently coexists with multiple comorbidities such as cardiovascular diseases and lung cancer, substantially increasing disease burden, diagnostic and therapeutic complexity, and mortality risk. Taking COPD comorbidities as an example, this article systematically reviews the principles of diagnosis and treatment for respiratory comorbidities based on the 2026 report of the Global Initiative for Chronic Obstructive Lung Disease (GOLD), as well as the latest domestic and international consensus statements and evidence-based findings. It focuses on COPD complicated by lung cancer and cardiovascular di-seases. The presence of comorbidities may lead to symptom overlap (e.g., dyspnea) and consequently increase missed diagnosis and misdiagnosis rates, while also causing issues such as polypharmacy-related conflicts and restricted treatment options. At the diagnostic level, this article proposes a two‑tier screening strategy based on symptom similarity (e.g., mismatch between symptom severity and objective findings) and shared risk factors/pathogenic mechanisms (e.g., smoking, chronic inflammation), emphasizing early coordinated screening through an approach of "one test, multiple uses." At the therapeutic level, a patient‑centered integrated care model is advocated, encompassing strategies such as concurrent management of comorbidities, prioritization of critical issues, benefit-risk balance, optimization of non‑pharmacological therapies, regular dynamic assessment, multidisciplinary collaboration, and artificial intelligence empowerment, aiming to achieve therapeutic targets for both COPD and its comorbidities. Effective management of COPD comorbidities requires clinicians to develop awareness of comorbidities, overcome disciplinary barriers, and rely on standardized screening pathways, high‑quality evidence, and intelligent decision‑support tools to build a comprehensive care system covering "early screening, concurrent treatment, and full-course management," ultimately improving long‑term outcomes and quality of life for patients.

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    Application of artificial intelligence in comprehensive management of chronic obstructive pulmonary disease:interpretation of GOLD 2026
    SUN Xianwen, LI Qingyun
    2026, 25 (04):  413-418.  DOI: 10.16150/j.1671-2870.2026.04.004
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    The 2026 Global Initiative for Chronic Obstructive Lung Disease (GOLD) has, for the first time, integrated artificial intelligence (AI) technology into the comprehensive management framework of COPD. AI models encompass four major categories: traditional machine learning, deep learning, large foundation models, and generative AI. They demonstrate potential in phenotyping, early warning of acute exacerbations, and prediction of treatment response. AI identifies multiple imaging subtypes of emphysema through unsupervised learning, with different subtypes significantly associa-ted with mortality risk and hospitalization risk. Deep learning models outperform traditional tools in long-term and short-term prediction of acute exacerbations, and early warning systems can effectively reduce hospitalization rates. Machine learning models perform well in predicting the effectiveness of inhaled corticosteroids, improving adherence to pulmonary rehabilitation, and predicting the success rate of lung volume reduction surgery. Additionally, AI applications face ethical challenges such as misdiagnosis, algorithmic bias, data privacy, and attribution of responsibility, which need to be addressed through strategies including full-process validation, dynamic informed consent, and fairness assessment. Overall, AI-empowered COPD management drives a paradigm shift from passive treatment to active prevention, yet a balance still needs to be achieved among innovation, evidence, and ethics.

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    Guidelines and consensus
    Risk management for pulmonary nodule biopsy:Ruijin expert consensus (2026 edition)
    Pulmonary Nodule Diagnosis and Management Disciplinary Group of Ruijin Hospital Shanghai Jiao Tong University School of Medicine
    2026, 25 (04):  419-432.  DOI: 10.16150/j.1671-2870.2026.04.005
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    Low-dose CT screening, as a core approach for detecting early lung cancer, has been demonstrated by substantial evidence from evidence-based medicine to significantly reduce lung cancer mortality. Only a proportion of pulmonary nodules detected by imaging examinations are early-stage lung cancers. Therefore, determining their biological characteristics through standardized and precise biopsy procedures is not only the cornerstone of early diagnosis, but also a prerequisite for perioperative risk management and digital-intelligent diagnosis and treatment decision-making. This consensus, revised by the Pulmonary Nodule Diagnosis and Management Disciplinary Group of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, builds upon the 2022 edition by systematically integrating the latest evidence from evidence-based medicine, high-quality clinical studies from China and abroad, meta-analyses, and clinical practice feedback to develop a comprehensively updated guidance document. Focusing on the two core techniques of percutaneous transthoracic needle biopsy (PTNB) and transbronchial lung biopsy (TBLB), the consensus systematically summarizes standardized operational procedures encompassing preoperative assessment, pathway optimization, and sampling protocols. It elaborates on the incidence, risk factors, and core prevention and control strategies for complications, including pneumothorax, blee-ding, pleural reaction, respiratory failure, arrhythmia, air embolism, and tumor seeding and metastasis, with particular emphasis on stratified management and refined interventions for high-risk populations. This revised consensus underscores that pulmonary nodule biopsy has shifted from traditional experience-based procedures to an individualized, precision-driven model integrating multimodal imaging guidance, AI assistance, and multidisciplinary team (MDT) decision-making. Through standardized workflows and multidisciplinary collaboration, it aims to achieve precise diagnosis while fully ensu-ring patient safety.

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    Chinese expert consensus on the standardization of antithrombin activity testing (2026 Edition)
    Clinical Hematology and Body Fluid Group Chinese Society of Laboratory Medicine, Hemophilia Treatment Center Collaborative Network of China, Hematology and Body Fluid Analysis Division Shanghai Medical Association Branch of Laboratory Medicine, Laboratory Diagnosis and Socialized Services Branch of Chinese Health Culture Association
    2026, 25 (04):  433-441.  DOI: 10.16150/j.1671-2870.2026.04.006
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    Antithrombin (AT) activity testing is widely used for the diagnosis of hereditary or acquired AT deficiency and for therapeutic monitoring in various diseases. However, laboratories in China face various challenges in testing procedures, quality control, and appropriateness evaluation. This consensus integrates relevant Chinese and international literature on AT activity testing and current practices in China to summarize key issues and propose consensus recommendations, with the aim of standardizing AT activity testing, improving laboratory testing quality, and laying the foundation for establishing standards for related individualized therapies.

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    Original articles
    Analysis of clinical characteristics of adult patients with empyema caused by Streptococcus infection
    ZHANG Jingyi, LIU Xu, YUE Wuriliga, WANG Mengcan, CAI Wenlin, HU Ke
    2026, 25 (04):  442-449.  DOI: 10.16150/j.1671-2870.2026.04.007
    Abstract ( 0 )   HTML ( 4 )   PDF (1014KB) ( 1 )  

    Objective This study analyzes the clinical characteristics of adult patients with empyema caused by Streptococcus infection, aiming to inform the formulation of diagnostic and treatment strategies as well as prognostic evaluation. Methods A retrospective analysis was conducted on the clinical characteristics of 28 adult patients with empyema confirmed by pleural fluid culture and/or blood culture for Streptococcus at Renmin Hospital of Wuhan University between December 2019 and September 2025. The patients were divided into a group without risk factors (n=8) and a group with risk factors (n=20) based on the presence of comorbidities and/or immunosuppression. The baseline data, clinical manifestations, laboratory and etiological findings, treatment modalities, and clinical outcomes were collected and compared between the two groups. Results A total of 440 patients with empyema were enrolled in this study, among whom empyema caused by Streptococcus infection accounted for 6.4%. CT images of all 28 patients were consistent with the characteristics of pleural effusion, and most patients (19 cases) exhibited loculated effusion accompanied by adjacent pleural thickening. Among them, bilateral empyema was most common (46.43%), followed by right-sided (35.71%) and left-sided (17.86%) empyema. Streptococcus constellatus was the predominant pathogen causing empyema due to Streptococcus infection (50%). Streptococcus intermedius was detected exclusively in the group without risk factors. Other isolated species included Streptococcus anginosus, Streptococcus mitis, Streptococcus pneumoniae, and Streptococcus oralis. No statistically significant differences were observed between the group without risk factors and the group with risk factors in mean age, proportion of patients with fever, or systemic inflammatory markers [white blood cell count, C-reactive protein, procalcitonin (PCT)] (all P>0.05). Five patients in the group without risk factors developed liver function impairment, and the incidence showed a tendency to be higher than that in the group with risk factors (5/8 vs. 3/20 cases, P=0.05). All strains isolated from both groups were susceptible to first-line β-lactam antibiotics, and no significant differences in resistance rates were observed between the two groups (all P>0.05). Regarding clinical outcomes, no significant differences were found in the duration of anti-infective therapy or hospital stay between the two groups. Three patients (3/20, 15.0%) in the group with risk factors died due to empyema and its directly related complications. Among the 28 patients, eight underwent surgical intervention, all of whom improved and were discharged, regardless of risk factor status. Conclusion Streptococcus constellatus is a major pathogen causing adult empyema. Patients without comorbidities and/or immunosuppression have a higher incidence of liver function impairment. In terms of treatment, antimicrobial susceptibility results indicate that first-line β-lactam antibiotics (penicillins/cephalosporins) remain highly effective. However, widespread resistance to clindamycin and other agents warrants attention. For patients with empyema, closed thoracic drainage should be performed as early as possible on the basis of adequate anti-infective therapy.

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    Clinical and laboratory diagnostic features of acquired von Willebrand syndrome associated with M protein:an analysis of four cases
    LI Yang, WANG Sicong, ZHU Difeng, YAO Junjie, XU Guanqun, LIU Yu, LIANG Qian, DAI Jing, WANG Xuefeng
    2026, 25 (04):  450-456.  DOI: 10.16150/j.1671-2870.2026.04.008
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    Objective This study aims to analyze the clinical and laboratory characteristics of M protein-associated acquired von Willebrand syndrome (AVWS), and to improve clinical recognition and diagnostic capability. Methods Four patients with M protein-associated AVWS identified at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, between October 2024 and April 2026 were consecutively enrolled and retrospectively reviewed. Three patients presented with unexplained bleeding, whereas one was found to have abnormal hemostatic laboratory results during inpatient scree-ning. After von Willebrand factor (VWF)-related testing and differential evaluation for inherited von Willebrand disease(VWD) and other bleeding disorders, serum protein electrophoresis and immunofixation electrophoresis were subsequently performed to detect M protein. Results Among the four patients, three were male and one was female, with ages ranging from 38 to 71 years. None had a long-standing history of abnormal bleeding or a family history of bleeding. Two patients were diagnosed with Waldenström macroglobulinemia (WM) based on bone marrow pathology and molecular pathology fin-dings, whereas two were clinically suspected of having monoclonal gammopathy of undetermined significance (MGUS) wi-thout undergoing bone marrow examination. VWF antigen (VWF:Ag), VWF activity (VWF:Act), and factor Ⅷ coagulant activity (FⅧ:C) were decreased in all four patients. The VWF:Act/VWF:Ag ratio was <0.60 in three patients, whereas the ratio was 0.74 in the remaining patient. Qualitative analysis of VWF multimers showed a marked reduction in high-molecular-weight VWF multimer bands in all four patients compared with normal pooled plasma. Conclusions The main diagnostic features of M protein-associated AVWS include adult onset, absence of a family history of abnormal bleeding, coexisting monoclonal immunoglobulin abnormalities, a disproportionate reduction in VWF activity relative to VWF antigen, and a reduction in high-molecular-weight VWF multimers. In patients with unexplained bleeding or abnormal VWF-related parameters, serum protein electrophoresis, immunofixation electrophoresis, and M protein quantification should be further performed to avoid missed diagnosis and misdiagnosis.

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    Development and verification of risk prediction model for postoperative delirium after radical surgery in elderly patients with pancreatic cancer
    LIU Jingjing, WEI Pingzhu, LUO Cheng, YU Xuchao, WANG Hongchao, WU Tianyi
    2026, 25 (04):  457-466.  DOI: 10.16150/j.1671-2870.2026.04.009
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    Objective To develop a predictive model for postoperative delirium (POD) after radical surgery in elderly patients with pancreatic cancer, thereby providing a practical basis for the early identification and prevention of POD occurrence. Methods Data were retrospectively and consecutively collected from 202 elderly patients who underwent radical surgery for pancreatic cancer at Ruijin Hospital, Shanghai, from January 2025 to June 2025. These patients were included in the modeling group based on inclusion and exclusion criteria. Within 7 days after surgery, trained nursing staff used the confusion assessment method (CAM) daily to assess the occurrence of POD. The modeling group was further divided into delirium and non-delirium subgroups according to the occurrence of POD. Clinical characteristics of both groups were compared, and univariate analysis was used to identify risk factors for POD. Multivariable logistic regression analysis was performed to determine the partial regression coefficients of independent risk factors and construct a predictive model. Model performance was evaluated using the Hosmer-Lemeshow (H-L) test and the area under the curve (AUC) of the receiver operating characteristic (ROC). Additionally, 101 patients who underwent the same type of surgery during the same period and met the same inclusion criteria, including 10 with delirium and 91 without, were selected as the validation group to assess the predictive performance of the model. Results The analysis of risk factors associated with POD revealed significant differences in age, APACHE-Ⅱ score, intraoperative blood loss, diabetes, and preoperative sleep disturbance between the delirium and non-delirium groups (P<0.05). Logistic regression analysis identified age, APACHE-Ⅱ score, intraoperative blood loss, diabetes, and preoperative sleep disturbance as independent risk factors for POD (P<0.05). Based on the regression analysis, the predictive model was constructed by multiplying each independent risk factor by its corresponding regression coefficient: P = e×/(1 + e×) × 100%, where e is the base of the natural logarithm and x = -13.959 + 0.106 × age + 0.357 × APACHE-Ⅱ score + 0.003 × intraoperative blood loss + 1.306 × diabetes status + 1.785 × preoperative sleep disturbance status. The AUC of the predictive model was 0.893 (95% CI: 0.836-0.949). At the maximum value of the Youden index (0.661), the model achieved a sensitivity of 81.0% and a specificity of 85.1% (P<0.001). When the clinical data from the validation group were entered into the predictive model, the model demonstrated a sensitivity of 60.0%, a specificity of 94.5%, and an accuracy of 91.1%. Conclusions Age, APACHE-Ⅱ score, intraoperative blood loss, diabetes, and preoperative sleep disturbance are independent risk factors for POD after radical surgery in elderly patients with pancreatic cancer. The predictive model based on these factors performs well and can help identify patients at low risk of POD, optimize resource allocation, and guide early intervention.

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    Research on construction of osteoporotic fracture prediction models based on machine learning algorithms
    MA Shanyuan, PENG Liang, HOU Yanqiang, LIU Weiwei
    2026, 25 (04):  467-475.  DOI: 10.16150/j.1671-2870.2026.04.010
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    Objective Based on clinical data from patients with osteoporosis, five machine learning algorithms are used to construct osteoporotic fracture risk prediction models, and their performance is evaluated and compared. Methods A total of 333 consecutive patients with osteoporosis (66 males and 267 females; median age, 69 years) who attended Song-jiang Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2020 to December 2025 were selected according to inclusion and exclusion criteria. Patients were divided into a fracture group (n=146) and a non-fracture group (n=187) based on the presence or absence of a history of fragility fractures. Baseline patient data and laboratory indicators were collected, and missing data were handled using multiple imputation by chained equations. Relevant studies were conducted using the R programming language. Feature variables were screened using logistic regression and lasso regression, and variable importance was ranked using random forest. Data were split into a training set and a test set at a 7∶3 ratio. Models were constructed using logistic regression, decision tree (DT), random forest, support vector machine, and extreme gradient boosting (XGBoost) algorithms. The performance of the models in predicting osteoporotic fracture risk was evaluated using indicators such as the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. The optimal model was interpreted using SHAP (SHapley Additive exPlanations) values. Results Univaria-te logistic regression analysis showed that sex, parathyroid hormone (PTH), N-terminal mid-fragment osteocalcin (N-MID-OT), alkaline phosphatase, albumin, calcium, mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), hemoglobin, and phosphorus were significantly associated with osteoporotic fractures. Lasso regression identified seven key features: sex, PTH, N-MID-OT, albumin, calcium, MCHC, and phosphorus. After random forest importance ranking, six variables-sex, PTH, N-MID-OT, calcium, phosphorus, and MCHC-were included in machine learning modeling. Using the test set data as input, the performance of each machine learning model in predicting osteoporotic fractures was compared. The results showed that the XGBoost model performed best with an AUC of 0.974 (95% CI: 0.950-0.998). The other four machine learning models also achieved good prediction performance, with AUCs ranging from 0.891 to 0.964. SHAP results indicated that N-MID-OT, calcium, and PTH had relatively large weights in the model, which was consistent with clinical cognition. Conclusions The XGBoost model constructed based on routine clinical indicators demonstrates good discriminative ability and stability in predicting the risk of osteoporotic fractures, has potential clinical application value, and is suitable for primary hospitals that are unable to conduct complete bone metabolism marker testing.

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    Review articles
    Advances and challenges in diagnostic techniques for nocardiosis
    WANG Shiyang, CHEN Qi, LIU Wenjing, CHEN Ruxuan, SUN Hongli, SHAO Chi, HUANG Hui
    2026, 25 (04):  476-482.  DOI: 10.16150/j.1671-2870.2026.04.011
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    Nocardiosis is an opportunistic infectious disease caused by Nocardia species in humans, with diverse clinical manifestations. It commonly affects the lungs and skin/soft tissues, but can also present as disseminated infection involving the central nervous system and other sites. The disease has a high mortality rate (26% on average). As the population of immunosuppressed individuals continues to grow, the incidence of nocardiosis has been increasing year by year. Due to the slow growth of Nocardia and the lack of specific morphological features, traditional culture and microscopic examination have limitations in clinical diagnosis, such as low detection rates and long turnaround times, which may lead to misdiagnosis or delayed diagnosis. In addition, Nocardia species differ in geographic distribution, common sites of infection, and antimicrobial resistance profiles. In recent years, significant progress has been made in the diagnosis of nocardiosis, driven by advances in molecular biology and high-throughput detection technologies. Techniques targeting 16S rRNA and multilocus sequence analysis have improved the accuracy of species identification and have also revealed various resistance genes associated with resistance phenotypes in antimicrobial susceptibility testing. Metagenomic next-generation sequencing (mNGS) helps improve detection positivity rates and diagnostic speed, while also enabling the effective identification of multiple pathogens in polymicrobial infections. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), with increasingly comprehensive databases, can achieve faster and more cost-effective routine identification compared to molecular detection techniques. Combining traditional diagnostic methods with molecular techniques and rapid mass spectrometric identification in a complementary manner, and selecting appropriate diagnostic methods based on the urgency and severity of the patient's condition and the testing capabilities of the medical institutions may further improve the accuracy and timeliness of nocardiosis diagnosis, ultimately leading to improved patient outcomes.

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    Research progress and clinical significance of obesity classification and staging
    LIAO Shiyu, TANG Shanshan, LIU Chenran, JIANG Linlin, LIAN Fengmei, JI Hangyu
    2026, 25 (04):  483-491.  DOI: 10.16150/j.1671-2870.2026.04.012
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    In recent years, the global population with obesity has increased sharply, becoming a major public health challenge. By 2030, approximately 50% of adults worldwide will be overweight or obesity. According to international criteria, a body mass index (BMI) ≥25 kg/m² is defined as overweight, and a BMI ≥30 kg/m² is defined as obesity. In 2025, 41% of adults in China were overweight and 9% had obesity. By 2030, the number of adults with overweight or obesity will reach 515 million. When China's diagnostic criteria (BMI ≥24 kg/m² for overweight and BMI ≥28 kg/m² for obesity) are applied, the situation will be even more severe. To address the complexity and heterogeneity of obesity, identify high-risk populations more accurately, and guide personalized treatment, classification and staging systems for obesity have continuously evolved. This paper systematically reviews the primary classifications of obesity based on pathogenesis, body shape characteristics, and metabolic status, along with five staging systems, analyzing their respective strengths and limitations in diagnosis, risk prediction, and treatment guidance. Although existing obesity classification and staging systems have evolved from reliance on BMI alone towards multidimensional integration, they still face issues such as inconsistent diagnostic criteria, insufficient risk warning, unclear treatment mapping, and limited clinical applicability. Future efforts should focus on establishing more precise, feasible, and cost-effective classification and staging systems to enable early intervention and personalized health management for obesity.

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    Research progress on BDNF-TrkB signaling pathway in comorbidity of diabetes mellitus and major depressive disorder
    CHEN Tiantian, NIU Xiaojuan
    2026, 25 (04):  492-499.  DOI: 10.16150/j.1671-2870.2026.04.013
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    The comorbidity of diabetes mellitus (DM) and major depressive disorder (MDD) is common in clinical practice. The risk of MDD in patients with DM is 2-3 times higher than that in those without DM. Conversely, MDD may also increase the risk of developing DM. The two conditions interact with and exacerbate each other, which not only reduces patients' quality of life but also increases their economic burden and treatment difficulty. Recent studies have found that the brain-derived neurotrophic factor (BDNF)-tyrosine kinase receptor B (TrkB) signaling pathway is a key "molecular bridge" connecting metabolic disorders and mental disorders. This pathway is closely associated with multiple pathological processes, including hypothalamic-pituitary-adrenal axis dysfunction, imbalance of central monoamine neurotransmitters, chronic low-grade inflammation, insulin resistance, microbiota-gut-brain axis dysregulation, and structural and functional brain remodeling. Its abnormal regulation may be the key pathological basis of DM with MDD (diabetes mellitus with depression, DD). This article systematically elucidates the pivotal role of the BDNF-TrkB signaling pathway in the pathogenesis of DD, providing a reference for the formulation of precise intervention strategies for DD in the future.

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    Case reports
    Multidisciplinary diagnosis and treatment analysis of a case of tuberous sclerosis complex caused by a TSC2 gene variant
    WU Mingming, WANG Gang, WEN Yaqi, CHEN Xiaoying
    2026, 25 (04):  500-505.  DOI: 10.16150/j.1671-2870.2026.04.014
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    This article reports a case of tuberous sclerosis (TSC) caused by a TSC2 gene variant. A 26-year-old male patient presented with widespread papules, nodules, and masses all over the body for over 20 years. The patient had a history of epileptic seizures at the age of 2. Dermatological examination showed densely distributed papules, nodules, and masses of varying sizes on the neck, face, chest, and back. Histopathological examination of the skin lesions showed mild papillomatoid hyperplasia of the epidermis, hyperkeratosis, and a small number of lymphocytes around the dermal blood vessels. Imaging studies indicated nodular and mass-like abnormal signals in the brain, lungs, and kidneys. Genetic testing revealed a decreased signal in exon 17 of the TSC2 gene, suggesting the presence of a pathogenic heterozygous deletion variant at this locus. Based on the above characteristics, the patient was diagnosed with tuberous sclerosis complex. After discussion by the multidisciplinary team (MDT), coordinated multidisciplinary treatment and management were provided. The dermatology department performed laser therapy, and the plastic surgery department conducted surgical treatment. The departments of urology, oncology, and neurosurgery provided pharmacological treatment. The treatment process proceeded smoothly. After discharge, the patient continued to be followed up at the outpatient clinic. As of January 2025, the patient had been followed up for one year and remained clinically stable. A review of the China National Knowledge Infrastructure, Wanfang Data, PubMed, and Embase databases identified 19 patients with tuberous sclerosis who had undergone multidisciplinary diagnosis and treatment. Including the patient reported in this article, a total of 20 cases were identified, and all patients had involvement of two or more organs. In the future, multidisciplinary collaboration in the lifelong disease management of patients with TSC will be crucial for improving the diagnosis and treatment of TSC and patient prognosis, and represents a trend in the treatment of this disease.

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    Medical education
    Application of a multidisciplinary team (MDT) teaching model in the training of subspecialty pathologists in bone and soft tissue pathology
    HUANG Jin, BAI Yueqing, LI Mei, TANG Lina, SHEN Chentian, YANG Qingcheng, LIU Zhiyan
    2026, 25 (04):  506-510.  DOI: 10.16150/j.1671-2870.2026.04.015
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    Current situation and suggestions on medical communication for internal medicine residency programs
    MA Jun, XU Xu, MA Xiaoyu, LU Wenli, XU Jing, YU Yi
    2026, 25 (04):  517-522.  DOI: 10.16150/j.1671-2870.2026.04.017
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