ObjectiveTo construct a multifunctional liposomal delivery system by replacing cholesterol（Chol） in conventional liposomes with saikosaponin D（SSD） and modifying with poloxamer 407（P407） for co-delivery of curcumin（Cur）. The system was evaluated for in vivo tumor targeting and inhibitory effects on mouse subcutaneous solid tumors. MethodsSingle-factor and orthogonal tests combined with information entropy weighting were used to optimize the formulation process of the liposome with encapsulation efficiency and absolute Zeta potential as indexes， and validation studies and liposomal characterization were performed. A subcutaneous solid tumor model was established by injecting H22 hepatocellular carcinoma cells subcutaneously into the dorsal surface of the right forelimb of mice. DiR-loaded traditional Chol liposomes（P407-DiR-Chol-LPs， PDCL） and novel SSD-based liposomes（P407-DiR-SSD-LPs， PDSL） were prepared by the optimized formulation process， and tail vein injection was performed to investigate the impact of SSD on liposome tumor targeting with small animal in vivo imaging. Mice were randomly divided into eight groups， including blank group， model group， free doxorubicin（DOX） group（2 mg·kg^-1）， free Cur group（8 mg·kg^-1）， free SSD group（10 mg·kg^-1）， P407-Cur-Chol-LPs（PCCL） group， P407-SSD-LPs（PSL） group， and P407-Cur-SSD-Lps（PCSL） group. Treatments were administered intraperitoneally every other day for seven doses. Antitumor efficacy and biocompatibility were evaluated by monitoring body weight change， organ indices， tumor volume and mass， relative tumor proliferation rate（T/C）， and tumor growth inhibition rate（TGI）. Histopathological analysis of liver， kidney， and tumor tissues was performed using hematoxylin-eosin（HE） staining. Serum levels of aspartate aminotransferase（AST）， alanine aminotransferase （ALT）， blood urea nitrogen（BUN）， and creatinine（Crea）in mice were quantified by fully automated biochemical analyzer. ResultsOrthogonal test yielded optimal ratios of Cur， SSD， and P407 to soybean phosphatidylcholine（SPC） as 1∶25， 1∶20， and 1∶4. The optimized PCSL exhibited spherical morphology with a particle size of 179.15 nm， a Zeta potential of -47.25 mV， and an encapsulation efficiency of 96.40%. Its in vitro release profile conformed to first-order kinetics， demonstrating excellent storage stability and hemocompatibility. In vivo imaging revealed that the fluorescence signal in tumor tissues and the fluorescence intensity ratio between tumors and organs were significantly higher in the PDSL group than in the PDCL group（P<0.05， P<0.01）. Among the treatment groups， PCSL group showed superior efficacy over free Cur group， free SSD group， PCCL group， and PSL group， with TGI>40% and T/C<60%， indicating pronounced anti-hepatocellular carcinoma effects（P<0.05， P<0.01）. Histopathology and serum biochemistry indicated minimal hepatorenal toxicity and improved hepatic and renal function in PCSL-treated mice. ConclusionReplacing Chol with SSD in preparing multifunctional drug delivery systems not only stabilizes liposomes but also yields superior anti-hepatocellular carcinoma efficacy， achieving the effect of drug-excipient integration. Co-delivery of Cur via this system can be used for treating subcutaneous solid tumors in hepatocellular carcinoma， providing new insights and technical approaches for anti-hepatocellular carcinoma research and the meridian-guiding and messenger-directing theory in traditional Chinese medicine.

OBJECTIVE: To explore the genetic etiology of 46 Chinese pedigrees affected with Hereditary multiple exostoses (HME) and provide genetic counseling and reproductive intervention. METHODS: Whole-exome sequencing and Sanger sequencing were carried out on 87 patients from the 46 pedigrees to analyze the variants of EXT1 and EXT2 genes. Pathogenicity of the variants was assessed based on the guidelines from the American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG/AMP). Prenatal diagnosis and preimplantation genetic testing (PGT) were provided for couples with identified pathogenic mutations. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: LL-SC-SG-2014-010). RESULTS: In total 17 and 22 pathogenic variants were respectively identified in the EXT1 and EXT2 genes, among which 5 EXT1 and 12 EXT2 variants were unreported previously. Three patients with no family history were found to harbor de novo variants of the EXT1 gene. Twenty nine couples had opted for PGT or underwent prenatal diagnosis following natural conception, and 17 healthy babies were born. CONCLUSION This study has clarified the genetic etiology of 45 HME pedigrees and identified 17 novel variants, which has enriched the mutational spectrum of the EXT1 and EXT2 genes. Reproductive intervention through PGT and prenatal diagnosis have prevented the recurrence of HME in these families.
Humans ; Female ; Male ; Pedigree ; Exostoses, Multiple Hereditary/diagnosis* ; N-Acetylglucosaminyltransferases/genetics* ; Adult ; Exostosin 1 ; Asian People/genetics* ; Genetic Testing ; Exostosin 2 ; Mutation ; China ; Prenatal Diagnosis ; Pregnancy ; Genetic Counseling ; Preimplantation Diagnosis ; Exome Sequencing ; East Asian People

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

Objective: This prospective study evaluated the feasibility of chemical exchange saturation transfer (CEST) MRI for assessing disease activity in thyroid-associated ophthalmopathy (TAO). Materials and Methods: A total of 88 patients with active TAO, 76 with inactive TAO, and 30 healthy controls were enrolled. CEST MRI-derived magnetization transfer ratio (MTR) and MTR asymmetry (MTRasym) at 1 ppm, 2 ppm, and 3.5 ppm were calculated. Clinical data, MTR, and MTRasym values for the extraocular muscles (one representative muscle per eye, yielding two measurements per participant) were compared among the groups. Spearman’s correlation was used to examine associations between imaging parameters and the clinical activity score (CAS) in patients with TAO. Logistic regression analysis was used to identify independent associations between imaging parameters and disease activity in patients with TAO (active vs. inactive). Receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic performance for discriminating active from inactive TAO. Results: Patients with active TAO showed lower MTR values (P < 0.001) and higher MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) (all P < 0.001) compared with those with inactive TAO. MTR was negatively correlated with CAS (r = -0.402; P < 0.001), while MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) were positively correlated with CAS (r = 0.369, 0.350, and 0.349, respectively;all P < 0.001). MTR and MTRasym (1 ppm) were independently associated with TAO activity. The areas under the ROC curve (AUCs) for MTR and MTRasym (1 ppm) in discriminating active from inactive TAO were 0.772 and 0.730, respectively. Combining MTR with MTRasym (1 ppm) significantly improved diagnostic performance compared with either parameter alone, achieving an AUC of 0.805 (P = 0.029 and 0.001). Conclusion MTR and MTRasym (1 ppm) were independently associated with TAO activity. Their combination further enhanced diagnostic performance in distinguishing active from inactive TAO, suggesting their potential as quantitative imaging biomarkers to guide treatment in patients with TAO.

Objective To understand the refractive progression of myopic school-aged children in ethnic minority areas of Yunnan and explore related factors.Methods Based on an existing cohort,a first follow-up survey was conducted from October 2020 to June 2021 involving 1,774 students selected from three ethnic minority areas:Dali City(Bai ethnic group),Lijiang Ancient Town(Naxi ethnic group),and Menghai County in Xishuangbanna(Dai and Hani ethnic groups).Among them,816 myopic school-aged children at baseline were selected as research subjects to analyze changes in refractive error(△SE)and the degree of refractive progression(classified as rapid △SE and slow △SE)over one year.Binary logistic regression was used to analyze the influencing factors of refractive progression.Results After one year of follow-up,the change in refractive error for myopic school-aged children was-0.63(-1.00,-0.25)D,with 518 children experiencing rapid △SE and 298 children experiencing slow △SE.Comparisons by educational stage indicated that Dai ethnic group children in primary school were more likely to experience rapid △SE than those in junior high school(P<0.05).Logistic regression results showed that school-age children of Naxi ethnic group(OR=1.879,95%CI:1.132～2.999),and those who used their eyes in the classroom during breaks(OR=1.541,95%CI:1.088～2.181)were at higher risk of rapid refractive progression(P<0.05).Children of school age who engage in outdoor activities for at least 3 hours during the day(OR=0.539,95%CI:0.340～0.853)and those who frequently consume animal liver(OR=0.596,95%CI:0.399～0.892)have a lower risk of rapid myopic progression(P<0.05).Conclusion Myopic school-aged children in ethnic minority areas of Yunnan exhibit rapid refractive progression,with significant ethnic differen-ces.The refractive progression in these children is closely related to lifestyle habits,highlighting the need for targeted myopia prevention and control measures and research for children and adolescents in ethnic minority areas of Yunnan.

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

OBJECTIVES: Whether vortioxetine has a utility as an adjuvant drug in the treatment of bipolar depression remains controversial. This study aimed to validate the efficacy and safety of vortioxetine in bipolar depression. METHODS: Patients with bipolar Ⅱ depression were enrolled in this prospective, two-center, randomized, 12-week pilot trial. The main indicator for assessing treatment effectiveness was a Montgomery-Asberg Depression Rating Scale (MADRS) of ≥50%. All eligible patients initially received four weeks of lurasidone monotherapy. Patients who responded well continued to receive this kind of monotherapy. However, no-response patients were randomly assigned to either valproate or vortioxetine treatment for eight weeks. By comprehensively comparing the results of MADRS over a period of 4‍‒‍12 weeks, a systematic analysis was conducted to determine whether vortioxetine could be used as an adjuvant drug for treating bipolar depression. RESULTS: Thirty-seven patients responded to lurasidone monotherapy, and 60 patients were randomly assigned to the valproate or vortioxetine group for eight weeks. After two weeks of combined valproate or vortioxetine treatment, the MADRS score in the vortioxetine group was significantly lower than that in the valproate group. There was no difference in the MADRS scores between the two groups at 8 and 12 weeks. The incidence of side effects did not significantly differ between the valproate and vortioxetine groups. Importantly, three patients in the vortioxetine group appeared to switch to mania or hypomania. CONCLUSIONS This study suggested that lurasidone combination with vortioxetine might have potential benefits to bipolar II depression in the early stage, while disease progression should be monitored closely for the risk of switching to mania.
Humans ; Bipolar Disorder/drug therapy* ; Vortioxetine/therapeutic use* ; Male ; Female ; Middle Aged ; Adult ; Valproic Acid/administration & dosage* ; Lurasidone Hydrochloride/administration & dosage* ; Prospective Studies ; Treatment Outcome ; Pilot Projects ; Drug Therapy, Combination ; Sulfides/therapeutic use* ; Antidepressive Agents/therapeutic use*

Addressing the enduring challenge of evaluating traditional Chinese medicines (TCMs), the integrated evidence chain-based effectiveness evaluation of TCMs (Eff-iEC) has emerged. This paper explored its capacity through a demonstration study that evaluated the effectiveness evidence of six commonly used anti-hepatic fibrosis Chinese patent medicines (CPMs), including Biejiajian Pill (BP), Dahuang Zhechong Pill (DZP), Biejia Ruangan Compound (BRC), Fuzheng Huayu Capsule (FHC), Anluo Huaxian Pill (AHP), and Heluo Shugan Capsule (HSC), using both Eff-iEC and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The recognition of these CPMs within the TCM academic community was also assessed through their inclusion in relevant medical documents. Results showed that the evidence of BRC and FHC received higher assessments in both Eff-iEC and GRADE system, while the assessments for others varied. Analysis of community recognition revealed that Eff-iEC more accurately reflects the clinical value of these CPMs, exhibiting superior evaluative capabilities. By breaking through the conventional pattern of TCMs effectiveness evaluation, Eff-iEC offers a novel epistemology that better aligns with the clinical realities and reasoning of TCMs, providing a coherent methodology for clinical decision-making, new drug evaluations, and health policy formulation.

OBJECTIVE: To investigate the feasibility and prognostic implications of assessing volume status during early fluid resuscitation in septic patients based on estimated plasma volume status (ePVS). METHODS: A prospective study was conducted. Patients with sepsis admitted to intensive care unit (ICU) of the First Affiliated Hospital of Kunming Medical University from March to December in 2023 were enrolled. The general information and laboratory indicators at ICU admission were recorded, and ePVS, sequential organ failure assessment (SOFA) score, acute physiology and chronic health status evaluation II (APACHE II) score were calculated. The vital signs, arterial blood gas analysis and volume status related indicators before liquid resuscitation (T0h) and 3 hours (T3h) and 6 hours (T6h) of fluid resuscitation were recorded. The diameter and variability of the inferior vena cava (IVC) were measured by ultrasound, and ePVS, percentage change value of estimated plasma volume status (ΔePVS%), difference in central venous-to-arterial partial pressure of carbon dioxide (Pcv-aCO₂), and lactate clearance rate (LCR) were calculated. Patients were divided into sepsis group and septic shock group based on the diagnosis at ICU admission, and septic patients were subdivided into survival group and death group based on their 28-day survival status. The differences in clinical data between the groups were compared. The correlation between ePVS or ΔePVS% and volume status related indicators during early liquid resuscitation was analyzed by Spearman rank sum correlation test. The predictive value of each variable for 28-day survival in patients with sepsis was analyzed by receiver operator characteristic curve (ROC curve), and 28-day death risk factors were analyzed by Logistic regression method. RESULTS: Fifty-four septic patients were enrolled in the final analysis, including 17 with sepsis and 37 with septic shock; 34 survived at 28 days and 20 died, with a 28-day survival rate of 63.0%. Compared with the sepsis group, the septic shock group had a lower venous ePVS at ICU admission [dL/g: 4.96 (3.67, 7.15) vs. 7.55 (4.36, 10.07), P < 0.05]. Compared with the death group, the survival group had higher T6h arterial and venous ΔePVS%, and albumin [Alb; T6h arterial ΔePVS% (%): 11.57% (-1.82%, 31.35%) vs. 0.48% (-5.67%, 6.02%), T6h venous ΔePVS%: 9.62% (3.59%, 25.75%) vs. 1.52% (-9.65%, 7.72%), Alb (g/L): 27.57±4.15 vs. 23.77±6.97, all P < 0.05], lower SOFA score, APACHE II score, AST, T0h Lac, and T3h and T6h norepinephrine dosage [SOFA score: 9.00 (8.00, 10.00) vs. 11.50 (9.25, 14.50), APACHE II score: 18.00 (14.75, 21.25) vs. 25.50 (21.00, 30.00), AST (U/L): 34.09 (23.20, 56.64) vs. 79.24 (25.34, 196.59), T0h Lac (mmol/L): 1.75 (1.40, 2.93) vs. 3.25 (2.33, 5.30), norepinephrine dosage (mg): 0.98 (< 0.01, 3.10) vs. 4.60 (1.05, 8.55) at T3h, 1.82 (0.38, 5.30) vs. 8.20 (2.80, 17.73) at T6h, all P < 0.05]. While there were no significantly differences in other basic data and ePVS at all of the time points before and after resuscitation between the two groups. Correlation analysis showed that T6h venous ePVS was significantly positively correlated with T6h IVC variability in septic patients (r = 0.360, P < 0.05), T0h arterial ePVS was significantly negatively correlated with T3h and T6h liquid intake volume (r₁ = -0.367, r₂ = -0.280, both P < 0.05), and venous ePVS at ICU admission was significantly positively correlated with NT-proBNP at ICU admission (r = 0.409, P < 0.05). T6h venous ΔePVS% was significantly positively correlated with T3h liquid intake volume and T6h LCR (r₁ = 0.286, r₂ = 0.286, both P < 0.05), and significantly negatively correlated with T6h urine volume and T6h change value of Pcv-aCO₂ (ΔPcv-aCO₂; r₁ = -0.321, r₂ = -0.371, both P < 0.05). ROC curve analysis showed that the area under the ROC curve (AUC) of T6h venous ΔePVS% for predicting 28-day survival in septic patients was 0.726 [95% confidence interval (95%CI) was 0.578-0.875, P = 0.006], with a sensitivity of 82.4%, a specificity of 60.0%, and an optimal cut-off value of 3.09%. Binary multifactorial Logistic regression analysis showed that an increase in T6h venous ΔePVS% was a protective factor for 28-day death in patients with sepsis on early fluid resuscitation [odds ratio (OR) = 0.900, 95%CI was 0.834-0.972, P = 0.007]. CONCLUSIONS ePVS may have potential for assessing the volume status of septic patients during early fluid resuscitation. The ΔePVS% during early fluid resuscitation may help to identify septic patients with a poor prognosis.
Humans ; Prognosis ; Fluid Therapy ; Sepsis/physiopathology* ; Prospective Studies ; Plasma Volume ; Intensive Care Units ; Resuscitation ; Male ; Female ; Middle Aged ; Shock, Septic/therapy*