PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

OBJECTIVE: To investigate the application value of pediatric sepsis-induced coagulation (pSIC) score and mean platelet volume/platelet count (MPV/PLT) ratio in the diagnosis of pediatric sepsis and the determination of critical pediatric sepsis. METHODS: A retrospective cohort study was conducted, selecting 112 children with sepsis (sepsis group) admitted to pediatric intensive care unit (PICU) of Liaocheng Second People's Hospital from January 2020 to December 2023 as the study objects, and 50 children without sepsis admitted to the pediatric surgery department of our hospital during the same period for elective surgery due to inguinal hernia as the control (control group). The children with sepsis were divided into two groups according to the pediatric critical case score (PCIS). The children with PCIS score of ≤ 80 were classified as critically ill group, and those with PCIS score of > 80 was classified as non-critically ill group. pSIC score, coagulation indicators [prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (APTT), and fibrinogen (FIB)], and platelet related indicators (PLT, MPV, and MPV/PLT ratio) were collected. Pearson correlation method was used to analyze the correlation between pSIC score and MPV/PLT ratio as well as their correlation with coagulation indicators. Multivariate Logistic regression analysis was used to screen the independent risk factors for pediatric sepsis and critical pediatric sepsis. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the application value of the above independent risk factors on the diagnosis of pediatric sepsis and the determination of critical pediatric sepsis. RESULTS: 112 children with sepsis and 50 children without sepsis were enrolled in the final analysis. pSIC score, PT, INR, APTT, FIB, MPV, and MPV/PLT ratio in the sepsis group were significantly higher than those in the control group [pSIC score: 0.93±0.10 vs. 0.06±0.03, PT (s): 14.76±0.38 vs. 12.23±0.15, INR: 1.26±0.03 vs. 1.06±0.01, APTT (s): 40.08±0.94 vs. 32.47±0.54, FIB (g/L): 3.51±0.11 vs. 2.31±0.06, MPV (fL): 8.86±0.14 vs. 7.62±0.11, MPV/PLT ratio: 0.037±0.003 vs. 0.022±0.001, all P < 0.01], and PLT was slightly lower than that in the control group (×10⁹/L: 306.00±11.01 vs. 345.90±10.57, P > 0.05). Among 112 children with sepsis, 46 were critically ill and 66 were non-critically ill. pSIC score, PT, INR, APTT, MPV, and MPV/PLT ratio in the critically ill group were significantly higher than those in the non-critically ill group [pSIC score: 1.74±0.17 vs. 0.36±0.07, PT (s): 16.55±0.80 vs. 13.52±0.23, INR: 1.39±0.07 vs. 1.17±0.02, APTT (s): 43.83±1.72 vs. 37.77±0.95, MPV (fL): 9.31±0.23 vs. 8.55±0.16, MPV/PLT ratio: 0.051±0.006 vs. 0.027±0.001, all P < 0.05], PLT was significantly lower than that in the non-critically ill group (×10⁹/L: 260.50±18.89 vs. 337.70±11.90, P < 0.01), and FIB was slightly lower than that in the non-critically ill group (g/L: 3.28±0.19 vs. 3.67±0.14, P > 0.05). Correlation analysis showed that pSIC score was significantly positively correlated with MPV/PLT ratio and coagulation indicators including PT, APTT and INR in pediatric sepsis (r value was 0.583, 0.571, 0.296 and 0.518, respectively, all P < 0.01), and MPV/PLT ratio was also significantly positively correlated with PT, APTT and INR (r value was 0.300, 0.203 and 0.307, respectively, all P < 0.05). Multivariate Logistic regression analysis showed that pSIC score and MPV/PLT ratio were independent risk factors for pediatric sepsis and critical pediatric sepsis [pediatric sepsis: odds ratio (OR) and 95% confidence interval (95%CI) for pSIC score was 14.117 (4.190-47.555), and the OR value and 95%CI for MPV/PLT ratio was 1.128 (1.059-1.202), both P < 0.01; critical pediatric sepsis: the OR value and 95%CI for pSIC score was 8.142 (3.672-18.050), and the OR value and 95%CI for MPV/PLT ratio was 1.068 (1.028-1.109), all P < 0.01]. ROC curve analysis showed that pSIC score and MPV/PLT ratio had certain application value in the diagnosis of pediatric sepsis [area under the ROC curve (AUC) and 95%CI was 0.754 (0.700-0.808) and 0.720 (0.643-0.798), respectively] and the determination of critical pediatric sepsis [AUC and 95%CI was 0.849 (0.778-0.919) and 0.731 (0.632-0.830)], and the combined AUC of the two indictors was 0.815 (95%CI was 0.751-0.879) and 0.872 (95%CI was 0.806-0.938), respectively. CONCLUSIONS pSIC score and MPV/PLT ratio have potential application value in the diagnosis of pediatric sepsis and the determination of critical pediatric sepsis, and the combined application of both is more valuable.
Humans ; Sepsis/complications* ; Platelet Count ; Mean Platelet Volume ; Retrospective Studies ; Child ; Blood Coagulation Disorders/diagnosis* ; Intensive Care Units, Pediatric ; Male ; Female ; Partial Thromboplastin Time ; Child, Preschool ; Blood Coagulation ; International Normalized Ratio ; Infant

OBJECTIVE: To explore the relationship between serum sodium level and the risk of delirium in patients with sepsis. METHODS: Based on the Medical Information Mart for Intensive Care-IV (MIMIC-IV), adult patients with sepsis in the intensive care unit (ICU) were enrolled. The serum sodium level prior to the onset of sepsis during hospitalization was used as the exposure variable. Delirium was assessed using the ICU-confusion assessment method (ICU-CAM) as the primary outcome. Patients were divided into delirium and non-delirium groups based on the occurrence of delirium. The relationship between serum sodium level and delirium risk was described using restricted cubic spline (RCS) to determine the optimal reference range for serum sodium. Logistic regression analysis was used to evaluate the effect of blood sodium levels on delirium in sepsis patients. Subgroup analyses were performed to explore potential interactions and further validate the robustness of the results. Receiver operator characteristic curve (ROC curve) analysis was performed to assess the predictive value of serum sodium level for delirium occurrence in patients with sepsis. RESULTS: A total of 13 889 patients with sepsis were included, of which 4 831 experienced delirium. The maximum and mean serum sodium values were significantly higher in the delirium group compared to the non-delirium group, while there were no statistically significant differences in terms of initial and minimum serum sodium values between the two groups. Compared with the non-delirium group, the delirium group had a higher mortality and longer hospital stay. The RCS curve showed that a "U"-shaped relationship between serum sodium level and delirium risk in patients with sepsis, with the optimal reference range for average serum sodium was 135.3-141.3 mmol/L. Group based on this reference range, compared to the group with 135.3 mmol/L ≤ serum sodium ≤ 141.3 mmol/L, the delirium incidence and mortality were significantly higher, and the hospital stay was longer in the groups with serum sodium < 135.3 mmol/L and serum sodium ≥ 141.3 mmol/L [delirium incidence: 36.92%, 40.88% vs. 31.22%; 28-day mortality: 23.08%, 20.15% vs. 13.39%; 90-day mortality: 30.75%, 24.81% vs. 18.26%; in-hospital mortality: 19.53%, 17.48% vs. 11.61%; ICU mortality: 14.35%, 14.05% vs. 9.00%; hospital length of stay (days): 10.1 (6.1, 17.7), 9.4 (5.4, 17.0) vs. 8.9 (5.5, 15.4), length of ICU stay (days): 3.7 (2.1, 7.1), 4.0 (2.1, 8.9) vs. 3.2 (1.9, 6.8); all P < 0.01]. Logistic regression analysis showed that, in the initial model and each factor-adjusted models, compared to the reference group with 135.3 mmol/L ≤ serum sodium < 141.3 mmol/L, serum sodium < 135.3 mmol/L increased the risk of delirium in septic patients by 21% to 29% [odds ratio (OR) was 1.21-1.29, all P < 0.01], while serum sodium ≥ 141.3 mmol/L increased the delirium risk by 28%-52% (OR was 1.28-1.52, all P < 0.01). Subgroup analyses based on gender, age, race, diuretic use, and sequential organ failure assessment (SOFA) score revealed there was no significant interactions between subgroup variables and serum sodium, and the results supported that both serum sodium < 135.3 mmol/L and serum sodium ≥ 141.3 mmol/L were risk factors for delirium in septic patients. ROC curve analysis showed that the area under the curve (AUC) for predicting delirium in septic patients based on serum sodium was 0.614, with a cut-off value of 139.5 mmol/L yielding a specificity of 67.5% and sensitivity of 50.9%. CONCLUSIONS The risk of delirium in patients with sepsis is associated with serum sodium level in a "U"-shaped manner. Both high and low serum sodium levels are associated with increased risk of delirium, higher all-cause mortality, and prolonged hospital stays in patients with sepsis. Abnormal serum sodium levels may have predictive value for sepsis-associated delirium and could serve as an early biomarker for identifying delirium in septic patients, although further validation is needed.
Humans ; Delirium/etiology* ; Sepsis/complications* ; Sodium/blood* ; Intensive Care Units ; Risk Factors ; Male ; Middle Aged ; Female ; Aged ; Logistic Models ; Adult

OBJECTIVE: To assess the relationship between blood pressure reactivity index (BPRI) and in-hospital mortality risk in patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A retrospective cohort study was conducted to collect data from patients admitted to the intensive care unit (ICU) and clinically diagnosed with SA-AKI between 2008 and 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database in the United States. The collected data included demographic characteristics, comorbidities, vital signs, laboratory parameters, sequential organ failure assessment (SOFA) and simplified acute physiology scoreII(SAPSII) within 48 hours of SA-AKI diagnosis, stages of AKI, treatment regimens, mean BPRI during the first and second 24 hours (BPRI_0_24, BPRI_24_48), and outcome measures including primary outcome (in-hospital mortality) and secondary outcomes (ICU length of stay and total hospital length of stay). Variables with statistical significance in univariate analysis were included in LASSO regression analysis for variable selection, and the selected variables were subsequently incorporated into multivariate Logistic regression analysis to identify independent predictors associated with in-hospital mortality in SA-AKI patients. Restricted cubic spline (RCS) analysis was employed to examine whether there was a linear relationship between BPRI within 48 hours and in-hospital mortality in SA-AKI patients. Basic prediction models were constructed based on the independent predictors identified through multivariate Logistic regression analysis, and receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive performance of each basic prediction model before and after incorporating BPRI. RESULTS: A total of 3 517 SA-AKI patients admitted to the ICU were included, of whom 826 died during hospitalization and 2 691 survived. The BPRI values within 48 hours of SA-AKI diagnosis were significantly lower in the death group compared with the survival group [BPRI_0_24: 4.53 (1.81, 8.11) vs. 17.39 (5.16, 52.43); BPRI_24_48: 4.76 (2.42, 12.44) vs. 32.23 (8.85, 85.52), all P < 0.05]. LASSO regression analysis identified 20 variables with non-zero coefficients that were included in the multivariate Logistic regression analysis. The results showed that respiratory rate, temperature, pulse oxygen saturation (SpO₂), white blood cell count (WBC), hematocrit (HCT), activated partial thromboplastin time (APTT), lactate, oxygenation index, SOFA score, fluid balance (FB), BPRI_0_24, and BPRI_24_48 were all independent predictors for in-hospital mortality in SA-AKI patients (all P < 0.05). RCS analysis revealed that both BPRI showed "L"-shaped non-linear relationships with the risk of in-hospital mortality in SA-AKI patients. When BPRI_0_24 ≤ 14.47 or BPRI_24_48 ≤ 24.21, the risk of in-hospital mortality in SA-AKI increased as BPRI values decreased. Three basic prediction models were constructed based on the identified independent predictors: Model 1 (physiological indicator model) included respiratory rate, temperature, SpO₂, and oxygenation index; Model 2 (laboratory indicator model) included WBC, HCT, APTT, and lactate; Model 3 (scoring indicator model) included SOFA score and FB. ROC curve analysis showed that the predictive performance of the basic models ranked from high to low as follows: Model 3, Model 2, and Model 1, with area under the curve (AUC) values of 0.755, 0.661, and 0.655, respectively. The incorporation of BPRI indicators resulted in significant improvement in the discriminative ability of each model (all P < 0.05), with AUC values increasing to 0.832 for Model 3+BPRI, 0.805 for Model 2+BPRI, and 0.808 for Model 1+BPRI. CONCLUSIONS BPRI is an independent predictor factor for in-hospital mortality in SA-AKI patients. Incorporating BPRI into the prediction model for in-hospital mortality risk in SA-AKI can significantly improve its predictive capability.
Humans ; Acute Kidney Injury/mortality* ; Sepsis/complications* ; Retrospective Studies ; Hospital Mortality ; Prognosis ; Blood Pressure ; Intensive Care Units ; Male ; Female ; Length of Stay ; Middle Aged ; Aged ; Adult ; Logistic Models

OBJECTIVE: To identify and validate novel biomarkers for the early diagnosis of sepsis-associated acute kidney injury (SA-AKI) and precise continuous renal replacement therapy (CRRT) using proteomics. METHODS: A prospective multicenter cohort study was conducted. Patients with sepsis admitted to five hospitals in Taizhou City of Zhejiang Province from April 2019 to December 2021 were continuously enrolled, based on the occurrence of acute kidney injury (AKI). Sepsis patients were divided into SA-AKI group and non-SA-AKI group, and healthy individuals who underwent physical examinations during the same period were used as control (NC group). Peripheral blood samples from participants were collected for protein mass spectrometry analysis. Differentially expressed proteins were identified, and functional enrichment analysis was conducted on these proteins. The levels of target proteins were detected by enzyme linked immunosorbent assay (ELISA), and the predictive value of target protein for SA-AKI were evaluated by receiver operator characteristic curve (ROC curve). Additionally, sepsis patients and healthy individuals were selected from one hospital to externally verify the expression level of the target protein and its predictive value for SA-AKI, as well as the accuracy of CRRT treatment. RESULTS: A total of 37 patients with sepsis (including 19 with AKI and 18 without AKI) and 31 healthy individuals were enrolled for proteomic analysis. Seven proteins were identified with significantly differential expression between the SA-AKI group and non-SA-AKI group: namely cystatin C (CST3), β ₂-microglobulin (β ₂M), insulin-like growth factor-binding protein 4 (IGFBP4), complement factor I (CFI), complement factor D (CFD), CD59, and glycoprotein prostaglandin D2 synthase (PTGDS). Functional enrichment analysis revealed that these proteins were involved in immune response, complement activation, coagulation cascade, and neutrophil degranulation. ELISA results demonstrated specific expression of each target protein in the SA-AKI group. Additionally, 65 patients with sepsis (38 with AKI and 27 without AKI) and 20 healthy individuals were selected for external validation of the 7 target proteins. ELISA results showed that there were statistically significant differences in the expression levels of CST3, β ₂M, IGFBP4, CFD, and CD59 between the SA-AKI group and non-SA-AKI group. ROC curve analysis indicated that the area under the curve (AUC) values of CST3, β ₂M, IGFBP4, CFD, and CD59 for predicting SA-AKI were 0.788, 0.723, 0.723, 0.795, and 0.836, respectively, all exceeding 0.7. Further analysis of patients who underwent CRRT or not revealed that IGFBP4 had a good predictive value, with an AUC of 0.84. CONCLUSIONS Based on proteomic analysis, CST3, β ₂M, IGFBP4, CFD, and CD59 may serve as potential biomarkers for the diagnosis of SA-AKI, among which IGFBP4 might be a potential biomarker for predicting the need for CRRT in SA-AKI patients. However, further clinical validation is required.
Humans ; Sepsis/complications* ; Acute Kidney Injury/blood* ; Proteomics ; Prospective Studies ; Biomarkers/blood* ; Male ; Female ; beta 2-Microglobulin/blood* ; Middle Aged ; Cystatin C/blood* ; Aged

OBJECTIVE: To investigate the predictive value of sphinor kinase 1 (sphk1), D-lactic acid, and intestinal fatty acid binding protein (I-FABP) for gastrointestinal injury in patients with sepsis. METHODS: A prospective observational study was conducted. Sixty-eight patients with sepsis and gastrointestinal dysfunction admitted to the department of critical care medicine of the First Affiliated Hospital of Baotou Medical College Inner Mongolia University of Science and Technology from May 2024 to March 2025 were enrolled (sepsis group), and they were divided into acute gastrointestinal injury (AGI) I-IV groups according to the definition and grading criteria of AGI proposed by the European Society of Intensive Care Medicine in 2012. Twenty non-sepsis patients without AGI admitted to the intensive care unit during the same period were enrolled as the control group (non-sepsis group). Within 30 minutes of patient enrollment, plasma sphk1, D-lactic acid, and I-FABP levels were determined by enzyme linked immunosorbent assay (ELISA). General data such as gender, age were recorded, and levels of procalcitonin (PCT), high-sensitivity C-reactive protein (hs-CRP), lactic acid (Lac), and acute physiology and chronic health evaluation II (APACHEII), sequential organ failure assessment (SOFA) were measured. Spearman method was used to analyze the correlation between sphk1, I-FABP, D-lactic acid and other indicators. The receiver operator characteristic curve (ROC curve) was used to evaluate the predictive value of sphk1, D-lactic acid, I-FABP, APACHEII score, and SOFA score for gastrointestinal injury in patients with sepsis. RESULTS: Among the 68 sepsis patients, 13 were classified as AGI grade I, 16 as AGI grade II, 23 as AGI grade III, and 16 had AGI grade IV. There were no statistically significant differences in gender, age, and abdominal infection rate among the groups. The SOFA score and APACHEII score of the sepsis group were significantly higher than those of the non-sepsis group; and the APACHEII score of the AGI IV group was significantly higher than that of the AGI I and AGI II groups. The levels of sphk1, D-lactic acid, I-FABP, PCT, Lac and hs-CRP in the sepsis group were significantly higher than those in the non-sepsis group, and each indicator gradually increased with the increase of AGI grade. Correlation analysis showed that plasma sphk1, D-lactic acid, and I-FABP in patients with sepsis-induced gastrointestinal injury were positively correlated with PCT, Lac, APACHEII score, and AGI grade (all P < 0.05), and sphk1 was positively correlated with I-FABP and D-lactic acid (r values were 0.773 and 0.782, respectively, both P < 0.05). ROC curve analysis showed that sphk1, D-lactic acid, I-FABP, APACHEII score, and SOFA score had high predictive value for gastrointestinal injury in patients with sepsis, with area under the curve (AUC) of 0.996, 0.987, 0.976, 0.901, and 0.934 (all P < 0.05). When the optimal cut-off value of sphk1 was 60.46 ng/L, the sensitivity and specificity were 95.6% and 100%, respectively; when the optimal cut-off value of D-lactic acid was 1 454.3 μg/L, the sensitivity and specificity were 95.6% and 100%, respectively; when the optimal cut-off value of I-FABP was 0.91 ng/L, the sensitivity and specificity were 95.6% and 100%, respectively; when the optimal cut-off value of APACHEII score was 14.5, the sensitivity and specificity were 80.9% and 85.0%, respectively; when the optimal cut-off value of SOFA score was 3.5, the sensitivity and specificity were 85.3% and 95.0%, respectively. CONCLUSIONS The levels of plasma sphk1, I-FABP, and D-lactic acid were significantly elevated in patients with sepsis and gastrointestinal injury. These indicators can serve as sensitive and relatively specific serological markers for early prediction of intestinal mucosal damage.
Humans ; Lactic Acid/blood* ; Fatty Acid-Binding Proteins/blood* ; Sepsis/complications* ; Prospective Studies ; Male ; Female ; Middle Aged ; Predictive Value of Tests ; Adult ; Aged ; Gastrointestinal Diseases/blood* ; Prognosis

OBJECTIVES: To investigate the clinical value of complement-3a receptor 1 (C3aR1) and neutrophil extracellular traps (NETs) in predicting sepsis-induced coagulopathy (SIC). METHODS: A prospective study was conducted among 78 children with sepsis who attended Xuzhou Children's Hospital Affiliated to Xuzhou Medical University from June 2022 to June 2023. According to the presence or absence of SIC, they were divided into two groups: SIC (n=36) and non-SIC (n=42) . The two groups were compared in terms of clinical data and the levels of C3aR1 and NETs. The factors associated with the occurrence of SIC were analyzed. The receiver operating characteristic (ROC) curve was used to evaluate the performance of C3aR1 and NETs in predicting SIC. RESULTS: Compared with the non-SIC group, the SIC group had significantly higher levels of C-reactive protein, interleukin-6 (IL-6), interleukin-10, C3aR1, and NETs (P<0.05). The multivaiate logistic regression analysis showed that the increases in C3aR1, NETs, and IL-6 were closely associated with the occurrence of SIC (P<0.05). The ROC curve analysis showed that C3aR1 combined with NETs had an area under the curve (AUC) of 0.913 in predicting SIC (P<0.05), which was significantly higher than the AUC of C3aR1 or IL-6 (P<0.05), while there was no significant difference in AUC between C3aR1 combined with NETs and NETs alone (P>0.05). CONCLUSIONS There are significant increases in the expression levels of C3aR1 and NETs in the peripheral blood of children with SIC, and the expression levels of C3aR1 and NETs have a high clinical value in predicting SIC.
Child ; Humans ; Extracellular Traps ; Interleukin-6 ; Prospective Studies ; Sepsis/complications* ; C-Reactive Protein ; Blood Coagulation Disorders ; ROC Curve ; Prognosis

OBJECTIVE: To investigate the safety of laparoscopic pancreaticoduodenectomy (LPD) in elderly patients and the related risk factors admitted to the intensive care unit (ICU) after LPD. METHODS: The perioperative data of patients who underwent LPD in Tianjin Medical University General Hospital from February 2017 to June 2023 were retrospectively collected, including basic data, preoperative laboratory indicators, intraoperative and postoperative indicators, pathological results (tumor size, lymph node dissection and pathological type), postoperative complications, ICU postoperative management and prognosis. The patients were divided into the elderly group (≥ 65 years) and the non-elderly group (< 65 years) according to age. Perioperative data between two groups were compared. Kaplan-Meier survival curve was drawn to analyze the survival rate of the elderly group and the non-elderly group, and the pancreatic head carcinoma group and other type of tumors group after LPD. Logistic regression was used to analyze the risk factors of ICU stay (length of ICU stay > 1 day) after LPD in elderly patients. The receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of this risk factor for ICU stay after LPD in elderly patients. RESULTS: A total of 160 patients were enrolled, including 57 cases in the elderly group (17 cases of vascular reconstruction) and 103 cases in the non-elderly group (40 cases of vascular reconstruction). All patients underwent R0 resection and were transferred to the comprehensive ICU for treatment. The follow-up time of patients with malignant tumors was 43 (6, 72) months. The elderly group had significantly longer surgery time, postoperative hospital stay and oral feeding time than the non-elderly group, and the incidence of delayed gastric emptying (DGE) was significantly higher than that in the non-elderly group. There were no significant differences in intraoperative blood transfusion rate, intraoperative blood loss, pathological results, short-term and severe postoperative complications, reoperation rate and 90-day mortality between the two groups. In patients with vascular resection reconstruction, the intraoperative blood loss in the elderly group was significantly higher than that in the non-elderly group, and the operation time and postoperative hospital stay were significantly longer. During ICU, the acute physiology and chronic health evaluation II [APACHE II: 12 (9, 14) vs. 8 (7, 10)], sequential organ failure assessment [SOFA: 6 (4, 8) vs. 3 (2, 5)] within 24 hours after admission to ICU were significantly increased in the elderly group (both P < 0.05), the time of mechanical ventilation [hours: 12 (10, 15) vs. 9 (5, 13)] and the length of ICU stay [days: 2 (1, 2) vs. 1 (1, 1)] were significantly increased in the elderly group (both P < 0.05), and the proportion of multi-disciplinary team (MDT) was also significantly increased in the elderly group (33.3% vs. 17.4%, P < 0.05), there were no significant differences in the levels of hemoglobin (Hb), albumin, and blood lactic acid between the two groups. Logistic regression analysis showed that the APACHE II score was an independent risk factor for ICU stay after LPD in elderly patients (β = 1.737, P = 0.028). ROC curve showed that the prediction performance was the best when the APACHE II score was 13, with the sensitivity of 72.41% and the specificity of 96.43%, and the area under the ROC curve (AUC) of 0.884. The Kaplan-Meier survival curve showed that there were no significant difference in median survival time (months: 24.1 vs. 24.7) and 5-year survival rate (19.01% vs. 19.02%) between the elderly group (52 cases) and the non-elderly group (92 cases) among the 144 patients with malignant tumors (both P > 0.05). The median survival time in the pancreatic head carcinoma group was significantly shorter than that in the other tumors group (63 cases; months: 20.2 vs. 40.1, P < 0.05), 5-year survival rate was significantly lower than that in the other tumors group (21.98% vs. 30.91%, P < 0.05). CONCLUSIONS LPD is a safe and feasible treatment for elderly patients. APACHE II score has a certain predictive value for ICU stay after LPD in elderly patients.
Humans ; Aged ; Middle Aged ; Sepsis/therapy* ; ROC Curve ; Pancreaticoduodenectomy/adverse effects* ; Retrospective Studies ; Blood Loss, Surgical ; Prognosis ; Pancreatic Neoplasms/surgery* ; Postoperative Complications ; Intensive Care Units

OBJECTIVETo investigate the effect of combined application of Xuebijing Injection ( , XBJ) and resolvin D1 (RvD1) on survival rate and the underlying mechanisms in mice with sepsisinduced lung injury.

METHODSThe cecal ligation and puncture (CLP) method was used to develop a mouse sepsis model. Specific pathogen free male C57BL/6 mice were randomly divided into 5 groups (n=20 each): sham, CLP, CLP+XBJ, CLP+RvD1 and CLP+XBJ+RvD1. After surgery, mice in the CLP+XBJ, CLP+RvD1 and CLP+XBJ+RvD1 groups were given XBJ (25 μL/g body weight), RvD1 (10 ng/g body weight), and their combination (the same dose of XBJ and RvD1), respectively. In each group, 12 mice were used to observe 1-week survival rate, while the rest were executed at 12 h. Whole blood was collected for flow cytometric analysis of leukocyte adhesion molecules CD18, lung tissues were harvested for observing pathological changes, and testing the activity of myeloperoxidase (MPO) and the expression of intercellular cell adhesion molecule 1 (ICAM-1).

RESULTSCompared with the CLP group, the histopathological damage of the lung tissues was mitigated, MPO activity was decreased in the CLP+XBJ and CLP+RvD1 groups (P<0.05). In addition, the 1-week survival rate was improved, proportion of CD18-expressing cells in whole blood and ICAM-1 protein expression in lung tissue were decreased in the CLP+XBJ+RvD1 group (P<0.05 or P<0.01).

CONCLUSIONSXBJ together with RvD1 could effectively inhibit leukocyte adhesion, reduce lung injury, and improve the survival rate of mice with sepsis.

Animals ; CD18 Antigens ; metabolism ; Cell Adhesion ; drug effects ; Docosahexaenoic Acids ; administration & dosage ; pharmacology ; therapeutic use ; Drugs, Chinese Herbal ; administration & dosage ; pharmacology ; therapeutic use ; Injections ; Intercellular Adhesion Molecule-1 ; metabolism ; Leukocytes ; drug effects ; metabolism ; pathology ; Lung ; drug effects ; enzymology ; pathology ; Lung Injury ; blood ; complications ; drug therapy ; Male ; Mice, Inbred C57BL ; Peroxidase ; metabolism ; Sepsis ; blood ; complications ; drug therapy ; Survival Analysis

PURPOSE: Urosepsis in adults comprises approximately 25% of all sepsis cases, and is due to complicated urinary tract infections in most cases. However, its mechanism is not fully clarified. Urosepsis is a very complicated disease with no effective strategy for early diagnosis and treatment. This study aimed to identify possible target-related proteins involved in urosepsis using proteomics and establish possible networks using bioinformatics. METHODS: Fifty patients admitted to the Urology Unit of Lanzhou General PLA (Lanzhou, China), from October 2012 to October 2015, were enrolled in this study. The patients were further divided into shock and matched-pair non-shock groups. 2-DE technique, mass spectrometry and database search were used to detect differentially expressed proteins in serum from the two groups. RESULTS: Six proteins were found at higher levels in the shock group compared with non-shock individuals, including serum amyloid A-1 protein (SAA1), apolipoprotein L1 (APOL1), ceruloplasmin (CP), haptoglobin (HP), antithrombin-III (SERPINC1) and prothrombin (F2), while three proteins showed lower levels, including serotransferrin (TF), transthyretin (TTR) and alpha-2-macroglobulin (A2M). CONCLUSION Nine proteins were differentially expressed between uroseptic patients (non-shock groups) and severe uroseptic patients (shock groups), compared with non-shock groups, serum SAA1, APOL1,CP, HP, SERPINC1and F2 at higher levels, while TF, TTR and A2M at lower levels in shock groups.these proteins were mainly involved in platelet activation, signaling and aggregation, acute phase protein pathway, lipid homeostasis, and iron ion transport, deserve further research as potential candidates for early diagnosis and treatment. (The conclusion seems too simple and vague, please re-write it. You may focus at what proteins have been expressed and introduce more detail about its significance.).
Adult ; Aged ; Antithrombin III ; Apolipoprotein L1 ; blood ; Ceruloplasmin ; Female ; Haptoglobins ; Humans ; Male ; Middle Aged ; Prealbumin ; Pregnancy-Associated alpha 2-Macroglobulins ; Proteomics ; Prothrombin ; Sepsis ; blood ; diagnosis ; etiology ; genetics ; Serum Amyloid A Protein ; Transferrin ; Urinary Tract Infections ; complications