With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Objective:To investigate the correlation of the emm genotypes and virulence genes with the isolation sites of Group A Streptococcus (GAS). Methods:It was a retrospective study.The specimens were collected from children with impetigo in Beijing Children′s Hospital, Capital Medical University from 2006 to 2008 for GAS isolation and identification.A total of 24 GAS strains were isolated from 16 children with impetigo, among which 7 pairs of strains were isolated from the throat and skin of 7 children, and 1 pair of strains was isolated from the vulva and skin of one child, and the remaining 8 GAS strains were isolated from the skin pus samples of 8 children.Polymerase chain reaction was applied to detect the emm genotypes and 13 virulence genes ( speA, speB, speC, speF, speG, speH, speI, speJ, speK, speL, speM, smeZ and ssa). The correlation of the emm genotypes and virulence genes with the isolation sites of GAS strains was analyzed. Results:In this study, four emm genotypes were detected, including emm1.0 (15/24), emm12.0 (4/24), emm22.0 (2/24) and emm160.0 (1/24), and one subtype emm12.19 (2/24) was detected as well.The carrying rates of 13 virulence genes speA, speB, speC, speF, speG, speH, speI, speJ, speK, speL, speM, smeZ and ssa were 58.3%, 100%, 91.7%, 100%, 50.0%, 12.5%, 54.2%, 66.7%, 16.7%, 25.0%, 12.5%, 100% and 91.7%, respectively.All strains carried 5 to 11 virulence genes and they all carried speB, speF and smeZ.There were significant differences in the carrying rate of speA and speJ among the strains with different emm genotypes (all P<0.05). There was no significant difference in the distribution of virulence genes between skin isolates and pharyngeal isolates, including the 5 pairs of strains carrying the emm1.0 genotype (all P>0.05). Conclusions:The distribution of virulence gene of GAS in children with impetigo is significantly correlated with the emm genotype, rather than the isolation site.

Objective:To investigate the prognosis of patients with initially resectable gastric cancer liver metastasis (GCLM) who were treated by different modalities, and analyze the influencing factors for prognosis of patients.Methods:The retrospective cohort study was conducted. The clinicopathological data of 327 patients with initially resectable GCLM who were included in the database of a nationwide multicenter retrospective cohort study on GCLM based on real-world data from January 2010 to December 2019 were collected. There were 267 males and 60 females, aged 61(54,68)years. According to the specific situations of patients, treatment modalities included radical surgery combined with systemic treatment, palliative surgery combined with systemic treatment, and systemic treatment alone. Observation indicators: (1) clinical characteristics of patients who were treated by different modalities; (2) prognostic outcomes of patients who were treated by different modalities; (3) analysis of influencing factors for prognosis of patients with initially resectable GCLM; (4) screening of potential beneficiaries in patients who were treated by radical surgery plus systemic treatment and patients who were treated by palliative surgery plus systemic treatment. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the rank sum test. Count data were described as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test. The Kaplan-Meier method was used to calculate survival rate and draw survival curve, and Log-Rank test was used for survival analysis. Univariate and multivariate analyses were conducted using the COX proportional hazard regression model. The propensity score matching was employed by the 1:1 nearest neighbor matching method with a caliper value of 0.1. The forest plots were utilized to evaluate potential benefits of diverse surgical combined with systemic treatments within the population. Results:(1) Clinical characteristics of patients who were treated by different modalities. Of 327 patients, there were 118 cases undergoing radical surgery plus systemic treatment, 164 cases undergoing palliative surgery plus systemic treatment, and 45 cases undergoing systemic treatment alone. There were significant differences in smoking, drinking, site of primary gastric tumor, diameter of primary gastric tumor, site of liver metastasis, and metastatic interval among the three groups of patients ( P<0.05). (2) Prognostic outcomes of patients who were treated by different modalities. The median overall survival time of the 327 pati-ents was 19.9 months (95% confidence interval as 14.9-24.9 months), with 1-, 3-year overall survival rate of 61.3%, 32.7%, respectively. The 1-year overall survival rates of patients undergoing radical surgery plus systemic treatment, palliative surgery plus systemic treatment and systemic treatment alone were 68.3%, 63.1%, 30.6%, and the 3-year overall survival rates were 41.1%, 29.9%, 11.9%, showing a significant difference in overall survival rate among the three groups of patients ( χ2=19.46, P<0.05). Results of further analysis showed that there was a significant difference in overall survival rate between patients undergoing radical surgery plus systemic treatment and patients undergoing systemic treatment alone ( hazard ratio=0.40, 95% confidence interval as 0.26-0.61, P<0.05), between patients undergoing palliative surgery plus systemic treatment and patients under-going systemic treatment alone ( hazard ratio=0.47, 95% confidence interval as 0.32-0.71, P<0.05). (3) Analysis of influencing factors for prognosis of patients with initially resectable GCLM. Results of multivariate analysis showed that the larger primary gastric tumor, poorly differentiated tumor, larger liver metastasis, multiple hepatic metastases were independent risk factors for prognosis of patients with initially resectable GCLM ( hazard ratio=1.20, 1.70, 1.20, 2.06, 95% confidence interval as 1.14-1.27, 1.25-2.31, 1.04-1.42, 1.45-2.92, P<0.05) and immunotherapy or targeted therapy, the treatment modality of radical or palliative surgery plus systemic therapy were independent protective factors for prognosis of patients with initially resectable GCLM ( hazard ratio=0.60, 0.39, 0.46, 95% confidence interval as 0.42-0.87, 0.25-0.60, 0.30-0.70, P<0.05). (4) Screening of potentinal beneficiaries in patients who were treated by radical surgery plus systemic treatment and patients who were treated by palliative surgery plus systemic treatment. Results of forest plots analysis showed that for patients with high-moderate differentiated GCLM and patients with liver metastasis located in the left liver, the overall survival rate of patients undergoing radical surgery plus systemic treatment was better than patients undergoing palliative surgery plus systemic treatment ( hazard ratio=0.21, 0.42, 95% confidence interval as 0.09-0.48, 0.23-0.78, P<0.05). Conclusions:Compared to systemic therapy alone, both radical and palliative surgery plus systemic therapy can improve the pro-gnosis of patients with initially resectable GCLM. The larger primary gastric tumor, poorly differen-tiated tumor, larger liver metastasis, multiple hepatic metastases are independent risk factors for prognosis of patients with initial resectable GCLM and immunotherapy or targeted therapy, the treatment modality of radical or palliative surgery plus systemic therapy are independent protective factors for prognosis of patients with initially resectable GCLM.

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period，9 035 strains of Gram-negative bacteria were collected from 51 hospitals，of which 7 895（87.4%）were Enterobacteriaceae and 1 140（12.6%）were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli（ n=4 510，49.9%）， Klebsiella pneumoniae（ n=2 340，25.9%）， Pseudomonas aeruginosa（ n=534，5.9%）， Acinetobacter baumannii complex（ n=405，4.5%）and Enterobacter cloacae（ n=327，3.6%）. The ESBLs-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus spp. were 47.1%（2 095/4 452），21.0%（427/2 033）and 41.1%（58/141），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（58/4 510）and 13.1%（307/2 340）；62.1%（36/58）and 9.8%（30/307）of CREC and CRKP were resistant to ceftazidime/avibactam combination，respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 59.5%（241/405），while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 18.4%（98/534）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions，with statistically significant differences in the prevalence of CRKP and CRPA（ χ2=20.489 and 20.252， P<0.001）. The prevalence of CREC，CRKP，CRPA，CRAB，ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals（ χ2=11.953，81.183，10.404，5.915，12.415 and 6.459， P<0.01 or <0.05），while the prevalence of CRPA was higher in economically developed regions（per capita GDP ≥ 92 059 Yuan）than that in economically less-developed regions（per capita GDP <92 059 Yuan）（ χ2=6.240， P=0.012）. Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend，and Escherichia coli is ranked in the top，while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different，and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.

The acupoint sensitization theory,a breakthrough in acupuncture and moxibustion over the past two decades,has greatly enhanced the understanding of meridians and acupoints while increasing the effectiveness of clinical diagnosis and treatment in acupuncture and moxibustion practices.The number of studies on surface sensitization site detection for different diseases is increasing.However,systematic sorting and a summary of the detection mode of surface sensitization points are lacking.Therefore,this study categorizes the method of surface sensitization point detection into two modes:pan-scanning and focused scanning.The classification is based on the characteristics of the openness of the research purpose,the precision of the target range,and the degree of variation during detection.The two modes have considerable differences in the exploration efficiency and the presentation of result.The pan-scanning mode can be further subdivided into holistic and localized pan-scanning modes,whereas the focused-scanning mode can be subdivided into fixed-and variable-focused scanning modes.This study analyzes the application scenarios,characteristics,advantages,and limitations of each detection mode and presents opinions on mode selection,mode innovation,and future development directions.This study aims to provide valuable insights and guidance for the follow-up research on surface sensitization site detection of various diseases.

Objective To investigate the key elements for model establishment and determine the evaluation indicators of animal models for pelvic inflammatory disease(PID),providing a reference for improving modelling methods and optimizing the application of PID animal models.Methods The search query"Pelvic Inflammatory Disease"AND"Animal Model"OR"Rat"OR"Mouse"OR"Guinea Pig"OR"Rabbit"OR"Dog"OR"Pig"was used to retrieve relevant literature on PID animal models published from 2013 to 2023 in China Knowledge Network Infrastructure(CNKI),Wanfang,and PubMed databases.The studies were analyzed and categorized based on experimental animal types,modelling methods,modelling cycles,detection indicators,positive control drugs,and administration duration.A database was established for statistical analysis.Results A total of 214 research articles on PID animal models meeting the inclusion criteria were identified.The most commonly used model animals are Sprague Dawley(SD)rats,followed by Wistar rats.The most frequently employed modelling method is a combination of mechanical injury and bacterial infection,followed by the phenol mucilage method.The most common modelling cycles for acute pelvic inflammatory disease(APID)and chronic pelvic inflammatory disease(CPID)/sequelae of pelvic inflammatory disease(SPID)are 8 to 14 days,while for PID models without specific staging,the cycles are 7 days.High-frequency detection methods and indicators include histopathological observation using hematoxylin-eosin staining,enzyme-linked immunosorbent assay(ELISA)for serum-related indicators,morphological changes of tissues observed with the naked eye,and immunohistochemical detection of related protein expression in uterine tissues,and pathological scoring.The most frequently used positive control drugs are Fuke Qianjin Tablets,followed by Jingangteng Capsules.The most common administration duration for APID is 7 days,and for CPID/SPID models,it ranges from 15 to 21 days.Conclusion Currently,SD rats and Wistar rats are commonly used as experimental animals for PID models.The dual modelling method of mechanical injury combined with mixed bacterial infection aligns closely with clinical pathogenesis and can be used to establish a PID model that simulates postoperative uterine cavity infection.Depending on the research objectives,different positive drugs and detection indicators should be selected for comprehensive evaluation.Most existing PID animal model studies are based on western medical diagnosis,with fewer studies focusing on Traditional Chinese Medicine(TCM)syndromes.There is a need to integrate TCM theories of etiology and pathogenesis to construct PID animal models that are more in line with TCM clinical symptoms.

Objective:To investigate the incidence of postoperative complications in Chinese patients with gastric or colorectal cancer, and to evaluate the risk factors for postoperative complications.Methods:This was a national, multicenter, prospective, registry-based, cohort study of data obtained from the database of the Prevalence of Abdominal Complications After Gastro- enterological Surgery (PACAGE) study sponsored by the China Gastrointestinal Cancer Surgical Union. The PACAGE database prospectively collected general demographic characteristics, protocols for perioperative treatment, and variables associated with postoperative complications in patients treated for gastric or colorectal cancer in 20 medical centers from December 2018 to December 2020. The patients were grouped according to the presence or absence of postoperative complications. Postoperative complications were categorized and graded in accordance with the expert consensus on postoperative complications in gastrointestinal oncology surgery and Clavien-Dindo grading criteria. The incidence of postoperative complications of different grades are presented as bar charts. Independent risk factors for occurrence of postoperative complications were identified by multifactorial unconditional logistic regression.Results:The study cohort comprised 3926 patients with gastric or colorectal cancer, 657 (16.7%) of whom had a total of 876 postoperative complications. Serious complications (Grade III and above) occurred in 4.0% of patients (156/3926). The rate of Grade V complications was 0.2% (7/3926). The cohort included 2271 patients with gastric cancer with a postoperative complication rate of 18.1% (412/2271) and serious complication rate of 4.7% (106/2271); and 1655 with colorectal cancer, with a postoperative complication rate of 14.8% (245/1655) and serious complication rate of 3.0% (50/1655). The incidences of anastomotic leakage in patients with gastric and colorectal cancer were 3.3% (74/2271) and 3.4% (56/1655), respectively. Abdominal infection was the most frequently occurring complication, accounting for 28.7% (164/572) and 39.5% (120/304) of postoperative complications in patients with gastric and colorectal cancer, respectively. The most frequently occurring grade of postoperative complication was Grade II, accounting for 65.4% (374/572) and 56.6% (172/304) of complications in patients with gastric and colorectal cancers, respectively. Multifactorial analysis identified (1) the following independent risk factors for postoperative complications in patients in the gastric cancer group: preoperative comorbidities (OR=2.54, 95%CI: 1.51-4.28, P<0.001), neoadjuvant therapy (OR=1.42, 95%CI:1.06-1.89, P=0.020), high American Society of Anesthesiologists (ASA) scores (ASA score 2 points:OR=1.60, 95% CI: 1.23-2.07, P<0.001, ASA score ≥3 points:OR=0.43, 95% CI: 0.25-0.73, P=0.002), operative time >180 minutes (OR=1.81, 95% CI: 1.42-2.31, P<0.001), intraoperative bleeding >50 mL (OR=1.29,95%CI: 1.01-1.63, P=0.038), and distal gastrectomy compared with total gastrectomy (OR=0.65,95%CI: 0.51-0.83, P<0.001); and (2) the following independent risk factors for postoperative complications in patients in the colorectal cancer group: female (OR=0.60, 95%CI: 0.44-0.80, P<0.001), preoperative comorbidities (OR=2.73, 95%CI: 1.25-5.99, P=0.030), neoadjuvant therapy (OR=1.83, 95%CI:1.23-2.72, P=0.008), laparoscopic surgery (OR=0.47, 95%CI: 0.30-0.72, P=0.022), and abdominoperineal resection compared with low anterior resection (OR=2.74, 95%CI: 1.71-4.41, P<0.001). Conclusion:Postoperative complications associated with various types of infection were the most frequent complications in patients with gastric or colorectal cancer. Although the risk factors for postoperative complications differed between patients with gastric cancer and those with colorectal cancer, the presence of preoperative comorbidities, administration of neoadjuvant therapy, and extent of surgical resection, were the commonest factors associated with postoperative complications in patients of both categories.

Objective:To examine the impact of varied surgical treatment strategies on the prognosis of patients with initial resectable gastric cancer liver metastases (IR-GCLM).Methods:This is a retrospective cohort study. Employing a retrospective cohort design, the study selected clinicopathological data from the national multi-center retrospective cohort study database, focusing on 282 patients with IR-GCLM who underwent surgical intervention between January 2010 and December 2019. There were 231 males and 51 males, aging ( M(IQR)) 61 (14) years (range: 27 to 80 years). These patients were stratified into radical and palliative treatment groups based on treatment decisions. Survival curves were generated using the Kaplan-Meier method and distinctions in survival rates were assessed using the Log-rank test. The Cox risk regression model evaluated HR for various factors, controlling for confounders through multivariate analysis to comprehensively evaluate the influence of surgery on the prognosis of IR-GCLM patients. A restricted cubic spline Cox proportional hazard model assessed and delineated intricate associations between measured variables and prognosis. At the same time, the X-tile served as an auxiliary tool to identify critical thresholds in the survival analysis for IR-GCLM patients. Subgroup analysis was then conducted to identify potential beneficiary populations in different surgical treatments. Results:(1) The radical group comprised 118 patients, all undergoing R0 resection or local physical therapy of primary and metastatic lesions. The palliative group comprised 164 patients, with 52 cases undergoing palliative resections for gastric primary tumors and liver metastases, 56 cases undergoing radical resections for gastric primary tumors only, 45 cases undergoing palliative resections for gastric primary tumors, and 11 cases receiving palliative treatments for liver metastases. A statistically significant distinction was observed between the groups regarding the site and the number of liver metastases (both P<0.05). (2) The median overall survival (OS) of the 282 patients was 22.7 months (95% CI: 17.8 to 27.6 months), with 1-year and 3-year OS rates were 65.4% and 35.6%, respectively. The 1-year OS rates for patients in the radical surgical group and palliative surgical group were 68.3% and 63.1%, while the corresponding 3-year OS rates were 42.2% and 29.9%, respectively. A comparison of OS between the two groups showed no statistically significant difference ( P=0.254). Further analysis indicated that patients undergoing palliative gastric cancer resection alone had a significantly worse prognosis compared to other surgical options ( HR=1.98, 95% CI: 1.21 to 3.24, P=0.006). (3) The size of the primary gastric tumor significantly influenced the patients′ prognosis ( HR=2.01, 95% CI: 1.45 to 2.79, P<0.01), with HR showing a progressively increasing trend as tumor size increased. (4) Subgroup analysis indicates that radical treatment may be more effective compared to palliative treatment in the following specific cases: well/moderately differentiated tumors ( HR=2.84, 95% CI 1.49 to 5.41, P=0.001), and patients with liver metastases located in the left lobe of the liver ( HR=2.06, 95% CI 1.19 to 3.57, P=0.010). Conclusions:In patients with IR-GCLM, radical surgery did not produce a significant improvement in the overall prognosis compared to palliative surgery. However, within specific patient subgroups (well/moderately differentiated tumors, and patients with liver metastases located in the left lobe of the liver), radical treatment can significantly improve prognosis compared to palliative approaches.