To establish lethal shock models in high-altitude, high-cold, and high-heat environments based on the conventional environment hemorrhagic shock (HS) model established in our laboratory, in order to provide animal models for lethal shock treatment in special environments.

A total of 864 SPF-grade male SD rats (12 weeks old, weighing 200±20 g) were divided into high-altitude environment group (simulated 4 000 m altitude in a low-pressure oxygen chamber, exposed to 22±2 ℃ for 48 h), high-cold environment group (altitude 200 to 300 m, exposure to -20 ℃ for 6 h), high-heat environment group (altitude 200 to 300 m, exposure to 35 ℃ for 12 h), and conventional environment control group (no environmental pretreatment) according to different environmental pretreatment, with 216 animals in each group. After environmental pre-conditioning, 4 types of spleen injury methods were used to induce free intra-abdominal bleeding to construct corresponding uncontrolled HS model. The injury methods were as follows: ① Transverse transection at 3 cm away from the end of the splenic parenchyma; ② Transverse transection separately at 3 and 5 cm away from the end of the splenic parenchyma; ③ Transverse arteriotomy of a small arterial branch at the splenic tail; ④ Transverse arteriotomy of a small arterial branch at the splenic tail combined with transection at 3 cm away from the end of the splenic parenchyma. Free intra-abdominal bleeding was induced by above 4 methods until the mean arterial pressure (MAP) dropped to 40 mmHg, which was defined as successful establishment of the uncontrolled HS model. After successful modeling, lactated Ringer’s (LR) solution was employed to maintain MAP at 50 to 60 mmHg at low pressure for 1 h. After the splenic artery was ligated for complete hemostasis, definitive resuscitation was obtained with LR solution of 2×blood loss volume. MAP, respiratory rate (RR) and heart rate (HR) were monitored, cardiac function [troponin I (TnI)], liver function [aspartate aminotransferase （AST）， alanine aminotransferase（ALT）］、and renal function ［blood urea nitrogen （BUN）， serum creatinine （Scr）］ were evaluated, survival time was observed, and 6-hour survival rate was calculated to screeen the appropriate modeling methods for each environment. Then the obtained modeling methods were applied on Bama pigs to establish HS models for high-altitude, high-cold, and high-heat environments, respectively. After modelling, the pigs were resuscitated according to the aforementioned treatment regimens, and basic physiological indicators (MAP, RR, HR), organ functions (heart, liver, kidney), and survival status were observed to verify the stability of the modeling methods.

There were differences in the appropriate modeling methods for different environments: the conventional environment preferred method ④, the high-altitude environment preferred method ③, the high-cold environment preferred method ①, and the high-heat environment preferred method ②. All the above methods met the model standards of a 6-hour mortality rate >70% after shock, a blood loss >50% after low-pressure resuscitation, and a survival rate >50% after definitive resuscitation. In the state of shock, the MAP of rats was significantly reduced in each group (P<0.001), RR and HR were abnormally changed, the indicators of cardiac, liver, and renal functions (TnI, AST, ALT, BUN, Scr) (P<0.05) were significantly increased, and the survival time was obviously shortened. After LR low-pressure resuscitation combined with definitive resuscitation, the MAP was notably recovered (P<0.01), the organ function indicators were significantly improved, and the survival time was greatly prolonged. The verification results in Bama miniature pigs showed that in the shock group, MAP was decreased to approximately 40 mmHg, RR was significantly reduced, HR was increased, the 6-hour survival rate was 0%, and the indicators of cardiac, liver, and renal functions (TnI, AST, ALT, BUN, and Scr) were notbly elevated (P<0.001). In the resuscitation group, the MAP was significantly increased to 58.6 to 68.4 mmHg (P<0.01), the 6-hour survival rate reached 50.00% to 56.25%, and organ functions were significantly improved. All these findings confirmed the reliability of each model.

Lethal shock models under high-altitude, high-cold, and high-heat environments are successfully established, respectively, and the appropriate standardized modeling methods are identified for each environment. The modelling methods are further verified on Bama miniature pigs, and the constructed models have advantages of stability and reliability for laboratory requirements.

To explore the impact of living at high altitudes for 1.5 years on the retinal blood vessels among healthy non-Tibetan young males and to screen related hematological and physiological indicators, providing a basis for increasing the eye examination items in high-altitude regions.

A cross-sectional survey design was employed. Data screening and collation were conducted between September 2024 and September 2025. The study subjects comprised non-Tibetan young adult males who, by December 2024, had been residing continuously at an altitude of 4 100 m for 1.5 years. Among the 180 participants, 65 had retinal vascular abnormalities and 115 were normal. Two independent samples rank-sum test and multivariate logistic regression analysis were performed to analyze the association between the hematological and physiological indicators and retinal vascular abnormalities.

The incidence of retinal vascular abnormalities was 36.11%. Two independent samples rank-sum test showed no statistical difference between the 2 groups in chronic mountain sickness (CMS) (P=0.527), while the P-values less than 0.2 were observed in term of heart rate (P=0.033), average visual reaction time (P=0.07), γ-glutamyl transferase (P=0.18), total cholesterol (P=0.033), triglycerides (P=0.149), low-density lipoprotein (P=0.095), platelet count (P=0.141), and plateletcrit (P=0.066). Multivariate logistic regression analysis revealed that heart rate (OR=1.033, 95%CI: 1.003 to 1.064, P=0.033) and total cholesterol (OR=1.868, 95%CI: 1.004 to 3.477, P=0.049) were positively, while average visual reaction time (OR=0.035, 95%CI: 0.002 to 0.723, P=0.03) was negatively correlated with the risk of retinal vascular changes.

The incidence of retinal vascular abnormalities is relatively high among healthy young men who have resided in high-altitude areas for 1.5 years. Increased heart rate and elevated total cholesterol level are independent risk factors for retinal vascular changes, while prolonged visual reaction time is associated with a reduced risk of such changes. Countermeasures Regular fundus photography helps identify retinal vascular changes at an early stage, which has important clinical significance for preventing the occurrence and development of high-altitude-related retinopathy and even high-altitude cerebral edema. It is recommended to include fundus photography in the health monitoring system for personnel residing in high-altitude areas.

To assess the predictive value of the pan-immune-inflammation value(PIV) for all-cause and cause-specific mortality among individuals with depressive symptoms.

This prospective cohort study utilized data from the US National Health and Nutrition Examination Survey(NHANES, 2005 to 2018) and the National Death Index(NDI, 2005 to 2019). A total of 8 567 American patients with depression were enrolled. Participants were grouped by PIV quartiles(Q1, Q2, Q3, Q4) or dichotomized(low group, high group). Cox proportional hazards models were employed to estimate the association between PIV and all-cause, cardiovascular, and cancer mortality in patients with depression. Smooth curve fitting was applied to explore potential non-linear dose-response relationships. Threshold effect analysis was conducted to identify an inflection point, upon which a two-piecewise regression model was constructed. Kaplan-Meier survival curves were plotted to examine the association between PIV levels and survival status. Subgroup analyses were performed to evaluate the robustness of the observed associations.

Cox regression showed that higher PIV levels were significantly associated with increased risks of all-cause mortality(HR=1.05, 95%CI: 1.04 to 1.07, P<0.001), cardiovascular mortality(HR=1.07, 95%CI: 1.05 to 1.10, P<0.001), and cancer mortality(HR=1.05, 95%CI: 1.01 to 1.08, P<0.001). Smooth curve fitting revealed a U-shaped relationship between PIV and all-cause mortality, with an inflection point at 80.97(P<0.05). Survival analysis indicated that when PIV>80.97, compared with the low group, the high group had increased all-cause mortality(HR=1.29, 95%CI: 1.12 to 1.48, P<0.001); compared with the Q1 group, the Q4 group also showed increased all-cause mortality(HR=1.53, 95%CI: 1.25 to 1.87, P<0.001). Subgroup analyses revealed stronger associations in specific populations: among females, for all-cause mortality(HR=1.08, 95%CI: 1.05 to 1.10, P=0.038) and cardiovascular mortality(HR=1.11, 95%CI: 1.07 to 1.16, P=0.031); In individuals with diabetes and those of other races(excluding Mexican American, other Hispanic, non-Hispanic White, and non-Hispanic Black), stronger associations were found between PIV and all-cause mortality (diabetes: HR=1.09, 95%CI: 1.06 to 1.10, P=0.023; other races: HR=1.22, 95%CI: 1.11 to 1.35, P=0.032) and cancer mortality (diabetes: HR=1.12, 95%CI: 1.06 to 1.18, P=0.006; other races: HR=2.00, 95%CI: 1.79 to 2.24, P=0.002).

Elevated PIV serves as an independent risk factor for multiple mortality outcomes in individuals with depressive symptoms. This study underscores the potential of PIV as a biomarker for predicting mortality risk. Utilizing PIV could aid in the early identification and targeted management of high-risk individuals, contributing to a comprehensive strategy for reducing the disease burden.

To explore the dynamic developmental trajectory of depressive symptoms among middle-aged and older adults in China, and to analyze the influences of childhood trauma and cognitive function on the trajectory.

Based on data from the China Health and Retirement Longitudinal Study from 2011 to 2020, a prospective cohort study was conducted on 7 916 middle-aged and older adults across 5 waves of surveys (T1=2011, T2=2013, T3=2015, T4=2018, T5=2020). Childhood trauma questionnaire, cognitive function questionnaire, and Center for Epidemiologic Studies Depression Scale were used to measure the experience of childhood trauma, cognitive function level, and depression level respectively. Pearson correlation analysis was employed to explore the correlations among variables. A latent growth curve model was constructed, and the fit of the model was evaluated based on indicators such as comparative fit index (CFI), Tucker-Lewis index (TLI), standardized root mean square residual (SRMR), and root mean square error of approximation (RMSEA). The nonlinear characteristics of the developmental trajectory of depression were depicted through intercept (I), slope (S), and quadratic slope (Q) parameters. The regression coefficient (β) and its 95% confidence interval (CI) were estimated using the Bootstrap method to explore the influencing factors of the developmental trajectory of depression in middle-aged and older adults.

① Childhood trauma was significantly positively correlated with cognitive function at each time point (r=0.044 to 0.077, P<0.001), and with depression at each time point (r=0.057 to 0.095, P<0.001). Cognitive function was significantly negatively correlated with depression at each time point (r=-0.257 to -0.133, P<0.001). ② Quadratic growth model demonstrated good fit (CFI=0.997, TFI=0.995, SRMR=0.017, RMSEA=0.029). Depressive symptoms exhibited a quadratic growth trend of “decreasing first, then increasing” over time (I=8.067, S=-0.158, Q=0.033, P<0.001). ③ After incorporating the variable of childhood trauma, childhood trauma significantly positively predicted the initial level of depression (β=0.294, 95%CI: 0.208 to 0.381, P<0.001), but had no significant predictive effect on the linear slope or quadratic slope. ④After further incorporating the cognitive function variable, the cognitive function at each of the 5 time points could significantly negatively predict the depression at the same time period (TI: β=-0.194, 95%CI: -0.233 to -0.155; T2: β=-0.135, 95%CI: -0.161 to -0.109; T3: β=-0.131, 95%CI:-0.161 to -0.100; T4: β=-0.134, 95%CI: -0.163 to -0.106; T5: β=-0.177, 95%CI:-0.220 to -0.134; all P<0.001).

The development trajectory of depression among middle-aged and older adults displays a nonlinear trend of quadratic growth. Childhood trauma is a risk factor for the initial level of depression in them, while cognitive function serves as a protective factor for the developmental trajectory of depression.

To explore the transition patterns of latent classes of depressive symptoms among postgraduate students and their influencing factors.

A prospective cohort study was conducted. Two waves of survey were carried out on 5 577 postgraduate students from an university in Hubei Province and another one in Anhui Province in October 2021 (T1) and October 2022 (T2). Self-Rating Depression Scale and College Students Mental Health Screening Scale were applied respectively to measure the severities of depressive symptoms and developmental distress. The optimal classification model was determined through the fitting indicators of the latent class model, mainly including indicators such as Entropy value, Lo-Mendell-Rubin (LMR), and Bootstrapped Likelihood Ratio Test (BLRT). Latent transition analysis was used to obtain the transition probabilities of latent class changes at different time points, and multivariate logistic regression analysis was employed to identify the factors influencing the latent class transition of depressive symptoms in the postgraduate students.

① The depressive symptoms could be classified into 3 categories among the postgraduate students (T1: Entropy=0.85, LMRP<0.05, BLRTP<0.001; T2: Entropy=0.88, LMRP<0.001, BLRT P<0.001), that is, a non-depressive symptom group (66.0% vs 64.3%), a mild depressive symptom group (25.6% vs 26.9%), and a moderate depressive symptom group (8.4% vs 8.8%). ② The probabilities of each latent class remaining in the original group at time point T2 were 84.1%, 56.9%, and 26.6%, respectively. The probability of transition from moderate to mild depressive symptom group was 41.3%, and the probability from mild to non-depressive symptom group was 29.3%.③ Adaptation challenges(OR=1.08, 95%CI: 1.02 to 1.16, P<0.05) and employment stress (OR=1.05, 95CI: 1.01 to 1.10, P<0.05) were promoting factors for the transition from non-depressive to mild depressive symptom group. Romantic troubles (OR=0.86, 95%CI: 0.76 to 0.99, P<0.05) was an obstructive factor for the transition from moderate to non-depressive symptom group.

There are 3 latent categories of depressive symptoms among postgraduate students. an obstructive factor for the transition from moderate to non-depressive symptom group.Adaptation challenges, employment stress and romantic troubles are important factors for the development of depressive symptoms.

Benzo(a)pyrene (BaP), as the most common polycyclic aromatic hydrocarbon pollutant, exhibits potent carcinogenic, teratogenic, and inflammatory toxic effects. Previous studies have demonstrated that BaP promotes invasion and migration capabilities of human bronchial epithelial cells following malignant transformation by suppressing ferroptosis; however, whether BaP can regulate tumor cell pyroptosis remains unclear. This study aims to elucidate the mechanism by which BaP promotes lung cancer invasion and migration through suppressing pyroptosis in human lung cancer cell line LTEP-a-2.

Potential target genes of BaP were retrieved from the Comparative Toxicogenomics Database (CTD), and lung cancer-related differentially expressed genes (DEGs) were screened from the Gene Expression Omnibus (GEO) database. Subsequently, an intersection analysis of these 2 gene sets was performed to obtain key candidate genes. Protein-Protein Interaction (PPI) network analysis on these candidate genes was conducted using the STRING database, and topological attribute analysis was performed for topological properties with Cytoscape software to screen key hub target genes based on high node degree values. Survival analysis of these PPI-derived hub genes was performed using the Kaplan-Meier Plotter database. Molecular docking simulations between BaP and each target protein were conducted with AutoDock Vina to predict binding conformations and calculate binding free energies. Visualization and analysis of the docking results were carried out using PyMOL software, and detailed ligand-receptor interactions were visualized and analyzed using 2D interaction diagrams generated by LigPlot+. LTEP-a-2 cells were exposed to gradient concentrations of BaP (0, 0.1, 1, and 10 μmol/L) for 48 h. Subsequently, cell viability was evaluated with CCK-8 assay, invasive and migratory capabilities were assessed with Transwell assay, cytotoxicity was determined by lactate dehydrogenase (LDH) release assay, and apoptosis was detected via Annexin V-FITC/PI flow cytometry. The concentrations of IL-1β and IL-18 in the supernatant were determined by enzyme-linked immunosorbent assay (ELISA). RT-qPCR and Western blotting were performed to measure the expression of key pyroptosis-related molecules (NLRP3, ASC, caspase-1, GSDMD, IL-1β, and IL-18) at mRNA and protein levels. Cell viability and invasive/migratory capabilities were assessed after LTEP-a-2 cells treated with BaP combined with pyroptosis agonists, as well as pyroptosis inhibitors combined with pyroptosis agonists. Concurrently, alterations in pyroptosis-related indicators, including IL-1β/IL-18 release and expression of the aforementioned key molecules, were examined.

In vitro experiments demonstrated that compared to the control group, exposure to 1 or 10 μmol/L BaP significantly promoted the proliferation, invasion, and migration of LTEP-a-2 cells (P<0.01), but did not induced obvious changes in apoptosis. Bioinformatics analysis revealed significant enrichment of BaP-related genes in the pyroptosis pathway. Treatment with different doses of BaP significantly inhibited pyroptosis, as evidenced by reduced LDH release (P<0.05), downregulated secretion levels of the inflammatory cytokines IL-1β and IL-18, and notable decreases in both mRNA and protein expression levels of key molecules in the pyroptosis pathway (NLRP3, ASC, caspase-1, GSDMD, IL-1β, and IL-18) (P<0.05). Conversely, pyroptosis agonist (compared to the control group) induced pronounced pyroptotic phenotypes and suppressed cell proliferation and invasive and migratory capacities (P<0.05). In the BaP or pyroptosis inhibitor combined with pyroptosis agonist treatment groups, the inhibitory effects of the agonists on tumor cell proliferation and invasion/migration were significantly reversed (P<0.01). Bioinformatics prediction and molecular docking analysis indicated that NLRP3 and PTGS2 may serve as potential molecular targets for BaP-mediated regulation of pyroptosis in lung cancer cells.

BaP promotes the invasion and migration of LTEP-a-2 cells by inhibiting the NLRP3-caspase-1-GSDMD pyroptosis signaling pathway.

To construct a machine learning-based prediction model for chronic kidney disease(CKD) in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) and to develop a diagnostic nomogram for guiding clinical management.

This study was based on the National Health and Nutrition Examination Survey (NHANES) database (2007 to 2018). Patients with MASLD, defined as hepatic steatosis with at least one cardiometabolic risk factor, were selected as the analysis sample. After excluding patients with chronic renal failure and other conditions, a total of 2 144 MASLD patients were included, and 34 variables (including demographics, clinical characteristics, and laboratory indicators) were collected. Patients were stratified into a chronic kidney disease (CKD) group (n=347) and a non-CKD group (n=1 797) based on CKD status. The total participants were randomly divided into a training set (n=1 501) and an internal validation set (n=643) using stratified sampling at a 7∶3 ratio. A prospective external validation cohort comprising 110 eligible fatty liver disease patients was recruited from our department during January 2024 and October 2025, adhering strictly to predefined inclusion and exclusion criteria Variables were screened using Least Absolute Shrinkage and Selection Operator (Lasso) regression. Eight machine learning algorithms were then employed to construct the CKD risk prediction models: decision trees (DT), extreme gradient boosting (XGBoost), K-nearest neighbors (KNN), Naive Bayes (NB), support vector machine (SVM), single hidden layer neural networks (NNET), light gradient boosting machine (LightGBM), and random forest (RF). Model performance was comprehensively evaluated using receiver operating characteristic (ROC) curves area under the curve (AUC), sensitivity, specificity, calibration curves, and clinical decision curves. Based on key biomarkers identified through SHAP analysis, a diagnostic nomogram was constructed, and its diagnostic accuracy was assessed using ROC curves.

Using interpretable machine learning algorithms, we identified 10 key biomarkers: SBP, age, diabetes, BUN, BMI, globulin, HDL-C, neutrophil count, uric acid, and gamma-glutamyl transferase. These biomarkers were utilized to construct predictive models through 8 distinct machine learning algorithms. Comprehensive evaluation revealed that the LightGBM model achieved optimal performance, with an AUC of 0.871, a sensitivity of 0.838, a specificity of 0.756, an accuracy of 0.825, an F1 score of 0.889, and a Brier score of 0.091. Calibration curve analysis demonstrated good consistency of the LightGBM-based predictive model across both training and validation sets. Clinical decision curve analysis indicated significant clinical utility of this model in predicting kidney damage risk in patients with MASLD. Based on SHAP values, we developed a diagnostic nomogram with a risk cutoff score of 81.7. This nomogram enabled categorization of patients into high-risk and low-risk subsets for MASLD-related CKD, and exhibited favorable accuracy and robust predictive reliability with an AUC value of 0.816.

The LightGBM model significantly outperforms other models and demonstrates potential for application in early clinical prediction of CKD risk among MASLD patients.

The promotion of enhanced recovery after surgery has shortened hospital stay of patients after radical prostatectomy, with most being discharged during the critical recovery period. These patients are prone to inadequate discharge preparation due to issues such as urinary dysfunction and indwelling catheterization. Although readiness for hospital discharge has been regarded as an important factor influencing patient prognosis, the mechanism by which it affects quality of life remains unclear. Based on the stress and coping theories, this study aims to explore the mediating role of coping styles in the relationship between readiness for hospital discharge and quality of life among patients after radical prostatectomy, providing evidence for developing targeted transitional care interventions.

A prospective longitudinal study design was adopted. From August 2024 to September 2025, 161 patients undergoing radical prostatectomy in the urology departments of 3 tertiary grade A hospitals in Chongqing were conveniently selected as the survey subjects. Within 24 h before discharge, the general information questionnaire, Readiness for Hospital Discharge Scale (RHDS), and Medical Coping Modes Questionnaire (MCMQ) were used for the investigation. Quality of Life (QOL) score was assessed through on-site or telephone evaluation at 1 month after surgery. The Process macro program Model 4 was utilized to construct a mediating effect model to test the mediating effect of coping styles.

The mean RHDS score of the 161 patients after radical prostatectomy was 84.72±17.96. The 3 dimensions of coping styles scored as follows: confrontation 19.02±4.02, avoidance 14.57±2.69, and resignation 8.19±2.57. The QOL score was 46.50±7.11. Pearson correlation analysis showed that the total score of quality of life was positively correlated with the total score of discharge readiness and the scores of each dimension (r=0.485 to 0.618, P<0.01), positively correlated with the confrontation dimension of medical coping modes (r=0.361, P<0.01), not significantly correlated with the avoidance dimension, and negatively with the resignation dimension (r=-0.383, P<0.01). Process mediating effect analysis indicated that the mediating effect value of coping styles between readiness for hospital discharge and quality of life was 0.038, with a 95%CI of 0.014 to 0.068, and the total mediating effect was significant (P<0.01). The mediation effect accounted for 15.89% of the total effect, with confrontation coping and resignation coping accounting for 6.74% and 9.15%, respectively.

Coping styles play a partial mediating role between readiness for hospital discharge and quality of life, with the mediating effect of reducing resignation coping being stronger. This suggests that clinicians should focus on identifying and intervening in patients with resignation coping tendencies to improve quality of life.

To systematically characterize tumor microenvironmental features and spatial cellular interactomes associated with distinct transcriptional meta-program (MP) in gastric cancer, and explore their clinical implications.

We integrated 2 gastric cancer single-cell RNA sequencing (scRNA-seq) datasets to identify malignant cell-derived transcriptional MP. The prognostic value was validated in 3 independent bulk transcriptomic cohorts: The Cancer Genome Atlas (TCGA), GSE15459, and GSE66229. Using scRNA-seq, we dissected MP-specific shifts in microenvironmental cell composition and inferred dominant ligand-receptor interactions. Spatial transcriptomics confirmed the co-localization of implicated cell subsets and signaling pairs. Survival analyses were used to access the associations between key cellular signatures/interaction signatures and patient outcomes.

Four MP from MP1 to MP4 were identified in malignant cells. High expression of MP2 and MP4 significantly correlated with worse overall survival (P<0.05). In MP2-high tumors, SPP1⁺ macrophages were enriched and predicted to interact with T3 neutrophils via the SPP1-CD44 ligand-receptor pair, with spatial co-localization validated. Both SPP1⁺ macrophage signature (P=0.007) and SPP1-CD44 interaction signature (P=0.008) predicted adverse prognosis. In MP4-high tumors, myofibroblastic cancer-associated fibroblast (myCAF) were expanded and showed interaction with exhausted CD8⁺ T cells through the COL6A family-ITGB1 signaling axis, which was also spatially validated. The myCAF signature (P=0.001) and COL6A family-ITGB1 interaction signature (P<0.001) correlated with poorer survival.

MP2 and MP4 delineate 2 distinct immunosuppressive spatial niches in gastric cancer: SPP1⁺ macrophage-T3 neutrophil and myCAF-exhausted CD8⁺ T cell. These niches likely drive tumor progression via SPP1-CD44 and COL6A family-ITGB1 axes, respectively, providing potential targets for precision immunotherapy.

To investigate the impact of propofol-based total intravenous anesthesia(TIVA) versus sevoflurane-propofol intravenous-inhalation combined anesthesia(IICA) on 5-year postoperative survival rates in patients undergoing radical hepatectomy for hepatocellular carcinoma(HCC).

A retrospective cohort study was conducted on the clinical and follow-up data from 504 patients undergoing radical HCC surgery in our hospital between January 2015 and December 2017. According to different anesthesia techniques, the patients were divided into a IICA groups(n=176) and a TIVA group(n=328). The 5-year postoperative survival rates were compared between the 2 groups of patients. Stratified analyses were carried out by age, tumor size and number, Child-Pugh class and model for end-stage liver disease(MELD) score, presence of portal vein tumor thrombus(PVTT), intraoperative transfusion, hepatitis B surface antigen status, alpha-fetoprotein(AFP), tumor node metastasis(TNM) stage, and Barcelona clinic liver cancer(BCLC) stage to compare the impact of the 2 anesthesia methods on postoperative survival rates in subgroups.

Among the cohort, the median 5-year survival was 33.00(14.25 to 60.00) months in the TIVA group with 212 deaths(64.60%), and 27.00(11.00 to 60.00) months in the IICA group with 125 deaths(71.00%). There was no statistically significant difference in 5-year survival rate between groups(HR=1.27, 95%CI: 0.96 to 1.67, P>0.05). Stratified analysis revealed significant increased 5-year mortality risk with CIVA in subgroups with MELD score >7.24(HR=1.61, 95%CI: 1.11 to 2.32, P=0.011), BCLC stage B(HR=1.74, 95%CI: 1.11 to 2.71, P=0.015), absence of PVTT(HR=1.35, 95%CI: 1.04 to 1.74, P=0.026), and no intraoperative transfusion(HR=1.34, 95%CI: 1.02 to 1.75, P=0.034).

Among patients undergoing radical hepatectomy for HCC, there is no difference in 5-year overall survival between propofol-based TIVA and sevoflurane-propofol IICA. However, IICA is associated with significantly increased 5-year mortality risk in specific subgroups: MELD score >7.24, absence of PVTT, BCLC stage B, and no intraoperative transfusion.