Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

Nodal marginal zone B-cell lymphoma(NMZL),the least common subtype of marginal zone lymphoma,represents a low-grade malignancy arising from the marginal zone of lymph node follicles,composed of small B-cells with an inert non-Hodgkin lymphoma nature.It accounts for 1.5% to 1.8% of all non-Hodgkin lymphomas and 10% of all marginal zone lymphomas.The low incidence and lack of typical clinical and pathological features pose a challenge to the diagnosis and clinical management of NMZL.In this article,we reported the diagnosis and treatment of a case of NMZL located in the parapharyngeal space of the left neck and reviewed the relevant literature from both domestic and international sources.We summarized the clinical manifestations,histopathological features,immunohistochemical characteristics,imaging features,diagnosis and treatment modalities,and prognosis of NMZL.
Humans ; Lymphoma, B-Cell, Marginal Zone/pathology* ; Lymph Nodes/pathology* ; Neck/pathology* ; Male

Objective To analyze the research status of in situ simulation in the medical field and explore its hotspots and trends. Methods Relevant literature was searched in China National Knowledge Infrastructure and Web of Science core collection from the inception to February 2024.CiteSpace 6.3.R1 was used to analyze the authors,institutions,and keywords and draw visual knowledge maps. Results A total of 25 Chinese articles and 438 English articles were included.Only 14 English articles were from China.In Chinese articles,the authors with the largest number of articles were Dai Hengmao and Liu Shangkun,and the institution with the largest number of articles was Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology.There was little cooperation between the authors and institutions.In English articles,the author and institution with the largest number of articles was Auerbach Marc and Yale University,respectively,and the cooperation between authors and institutions was close.Emergency medicine,emergency event handling,and on-the-job training were the keywords with high frequency in Chinese articles.Patient safety,medical education,and cardiac arrest were the keywords with high frequency in English articles.A total of 4 clusters were generated for Chinese keywords and 13 clusters for English keywords. Conclusions The application of in situ simulation in the medical field is still in the initial stage,and the development is not balanced at home and abroad.The number of articles published and the cooperation between authors and institutions in China obviously lags behind those abroad.Treatment and care of emergency critical patients,emergency event handling and skill training,identification of latent safety threats,improvement of readiness,and promotion of medical quality improvement are the future research hotspots and research trends in this field.
Bibliometrics ; Humans ; China ; Simulation Training ; Education, Medical ; Emergency Medicine/education*

Objective:To analysis of the latent profiles and influencing factors of body image in patients with postoperative oral cancer.Methods:From July 2024 to March 2025, a total of 332 patients with primary oral cancer confirmed by pathology, aged ≥18 years, and undergoing oral cancer surgery at Hunan Cancer Hospital were selected using simple random sampling and cluster sampling. Among them, 25 were female and 307 were male. The body image scale and the Rosenberg self-esteem scale were used to investigate the patients. The main indicators included the total scale scores and scores on various dimensions of body image, such as appearance evaluation and health focus, with particular attention to satisfaction with facial appearance and oral function.The correlation between self-esteem and body image was analyzed, and differences in scores were compared based on gender, age, self-esteem level, and surgical procedure.Results:Among the 332 patients, 93.4% (310/332) were married, and 6.6% (22/332) were unmarried, divorced, or widowed. A total of 84.3% (280/332) underwent flap transplantation surgery, while 15.7% (52/332) did not. The body image distress in the 332 patients could be categorized into a body image adaptation group [80.12% (266/332)] and a body image disorder group [19.88% (66/332)]. Unmarried/divorced/widowed status ( P=0.020), undergoing flap transplantation ( P=0.006), and self-esteem level ( P<0.001) were identified as influencing factors for postoperative body image disorder in oral cancer patients. Conclusions:Given the varying levels of body image concerns among oral cancer patients, healthcare providers can implement targeted, personalized nursing interventions based on their distinct categories and influencing factors.

Objective To explore the prescription patterns and core medication characteristics of traditional Chinese medicine(TCM)in the real-world treatment of non-small cell lung cancer(NSCLC).Methods Outpatient prescription data for NSCLC patients treated in the department of respiratory medicine at the First Affiliated Hospital of Henan University of Chinese Medicine from January 1,2020,to December 31,2023,were extracted through the Hospital Information System(HIS)to establish a standardized Chinese herbal medicine database.Latent structure models were constructed using Lantern 5.0 software,while association rule analysis was conducted with SPSS Modeler 18.0 software.Additionally,clustering analysis of high-frequency herbs was performed using SPSS 26.0 software to systematically analyse the laws of medicine identification and administration.Results A total of 620 TCM prescriptions involving 329 herbs were included,with a cumulative frequency of 10,461 herb applications.The most frequently used herbs were Citri Reticulatae pericarpium,Poria,Codonopsis radix,and Astragali radix.Tonifying and replenishing herbs constituted the primary category,with warm-natured and sweet-flavored herbs predominating.Most herbs targeted the lung meridian.Twenty core prescriptions,such as Xuefu Zhuyu decoction were identified.Core herb combinations included"Ligustri Lucidi fructus-Glycyrrhizae radix et rhizoma-Astragali radix"and"Solani nigri herba-Coicis semen-Astragali radix,"primarily reflecting therapeutic strategies of supplementing Qi,nourishing yin,detoxifying,and dispersing toxins.Conclusion TCM prescriptions for NSCLC predominantly utilize sweet and warm-natured herbs,adhering to the principle of strengthening the body's resistance and eliminating pathogenic factors.Therapeutic approaches integrate methods such as supplementing qi and nourishing yin,clearing heat and detoxifying,and activating blood circulation and resolving stasis.Core prescriptions are derived from classical formulas like Xuefu Zhuyu decoction and Baihe Gujin decoction through syndrome differentiation.The prescription patterns and core herb groups revealed by real-world data mining provide evidence-based insights for optimizing clinical treatment strategies for NSCLC.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.