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*

Objective To analyze the detection rate of carbapenem-resistant Klebsiella pneumoniae(CRKP)in Guangdong Provincial Second Hospital of Traditional Chinese Medicine(the hospital)and analyze the main drug resistance genes and virulence genes of CRKP,so as to understand the molecular epidemiologi-cal mechanism of its infection strains.Methods The detection rate of CRKP infection in the hospital from 2020 to 2023 was retrospectively analyzed,and a total of 84 strains of CRKP were collected from July to De-cember 2022 in the hospital.The clinical data of the strains were collected,and the corresponding drug resist-ance genes and virulence genes were amplified by PCR.The modified carbapenem inactivation method(mCIM)was uesd to detect carbapenemase.Results The detection rates of CRKP in the Guangdong Provincial Second Hospital of Traditional Chinese Medicine from 2020 to 2023 were relatively high,and were higher than 46.00％.84 non-repeated CRKP strains were collected from July to December of 2022,and most samples were from respiratory tract,accounting for 55.95％.The patients were mainly from acupuncture and rehabilitation departments,accounting for 34.52％.Drug sensitivity tests showed that CRKP was highly resistant to various cephalosporin and extended spectrum beta lactam drugs,and only showed high sensitivity to tigecycline and polymyxin.The positive rate of mCIM test was 84.52％(71/84),and the other 15.48％results were neutral,which failed to determine whether they produced carbapenemase.A total of 73 strains were detected with car-bapenemase gene,accounting for 86.90％,involving 4 genotypes.The detection rates of blaKPC,blaNDM,blaIMP,and blaOXA-48 were 83.33％,2.38％,1.19％,and 1.19％,respectively.One of them carried both blaKPC and blaNDM genes,and multiple β-lactamases were detected.The detection rates of blaSHV,bla-TEM,blaCTX-M-9,and blaCTX-M-1 were 96.43％,78.57％,64.29％,and 2.38％,respectively.The detection rates of five virulence genes,blaiucA,blarmpA2,blairoB,blapeg-334,and blarmpA,were 42.86％,41.67％,27.38％,3.57％,and 2.38％,respectively.The proportion of strains carrying three or more virulence genes was 17.85％(15/84).Conclusion The detection rate of CRKP in the hospital is relatively high,and the drug resistance situation is serious,with Klebsiella pneumoniae carbapenemase(KPC)as the main drug resistance gene.A high proportion of Carbapenem-resistant hypervirulent Klebsiella pneumoniae(CR-hvKp)strains is found,and the infection prevention and control situation is not optimistic.It is necessary to further strengthen the hospital infection control measures and standardize the scientific and reasonable drug use.

Objective To explore the key targets and signaling pathways in the therapeutic mechanism of Semiliquidambar cathayensis Chang(SC)root against pancreatic cancer network pharmacology and molecular docking studies and cell experiments.Methods The targets of SC and pancreatic cancer were predicted using the network pharmacological database,the protein-protein interaction network was constructed,and pathways,functional enrichment and molecular docking analyses were performed.CCK-8 assay was used to test the inhibitory effect of the aqueous extract of SC root on 8 cancer cell lines,and its effects on invasion,migration,proliferation,and apoptosis of pancreatic cancer cells were evaluated.Western blotting was performed to verify the results of network pharmacology analysis.Results We identified a total of 18 active components in SC,which regulated 21 potential key targets in pancreatic cancer.GO and KEGG pathway enrichment analyses showed that these targets were involved mainly in the biological processes including protein phosphorylation,signal transduction,and apoptosis and participated in cancer signaling and PI3K-Akt signaling pathways.Among the 8 cancer cell lines,The aqueous extract of SC root produced the most obvious inhibitory effect in pancreatic cancer cells,and significantly inhibited the invasion,migration,and proliferation and promoted apoptosis of pancreatic cancer Panc-1 cells(P<0.05).Western blotting confirmed that SC significantly inhibited the phosphorylation levels of PI3K and AKT in Panc-1 cells(P<0.001).Conclusion The therapeutic effect of SC root against pancreatic cancer effects is mediated by its multiple components that act on different targets and pathways including the PI3K-Akt pathway.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.

Objective Analyzes the grouping effect and its influencing factors under DRG payment,provides reference for the reform of DRG payment.Methods Evaluates the effectiveness of DRG grouping using Coefficient of Variation(CV)and Reduction in Variance;using Value of Structure of Variation and Degree of Structure Variation,analyzes hospitalization costs structure changes of different DRG groups,and calculates the degree of correlation between average hospitalization costs through grey relational analysis;using non parametric tests and multiple regression to analyze the influencing factors of hospitalization cost.Results DRG grouping effect was not good,inter-group heterogeneity was not obvious;the structure of hospitalization expenses is unreasonable,and the proportion of consumables expenses is too high,ranking first in the grey correlation degree of hospitalization expenses,comprehensive medical service fees and treatment fees rank third and fifth respectively;the main factors affecting hospitalization costs are treatment methods,length of stay,presence of complications,and first hospitalization,the difference is statistically significant(P＜0.05).Conclusion More grouping nodes or higher CV value standards should be added to enhance the grouping effect of gastric cancer DRG;optimize the structure of hospitalization costs to reflect the labor and technical value of medical personnel;strengthen internal management and control the unreasonable use of drugs and consumables.