Objective To analyze the prognosis of patients with sepsis-related liver injury(SRLI)and establish a prediction model for the occurrence of SRLI after ICU admission in sepsis patients u-sing eight machine learning methods.Methods Patients who met the sepsis diagnostic criteria and had no underlying liver or biliary diseases were included from the MIMIC-Ⅳ database,and were clas-sified into SRLI and non-SRLI groups based on liver enzymes ≥ 5 times the upper limit of normal(ULN)or bilirubin ≥2.Omg/dL.Chi-square test,multivariate Logistic regression analysis,and pro-pensity score matching were used to analyze the mortality risk between the two groups.Eight machine learning algorithms[Logistic regression,classification and regression tree(CART),random forest(RF),support vector machine(SVM),K-nearest neighbors(K-NN),naive Bayes method(NBM),extreme gradient boosting(XGBoost),and gradient boosting decision tree(GBDT)]were employed to construct and validate the SRLI prediction model.Results The chi-square test(P＜0.001),multivariate Logistic regression analysis(P＜0.05),and log-rank test after propensity score matching(P＜0.05)all indicated that SRLI increased the mortality risk of patients.Among the SRLI prediction models,RF algorithm had the highest area under the curve(AUC),with its value of 0.866,followed by GBDT(AUC=0.862),Logistic regression(AUC=0.859),SVM(AUC=0.837),NBM(AUC=0.830),CART(AUC=0.771),XGBoost(AUC=0.764),and K-NN(AUC=0.722).Conclusion SRLI increases the mortality risk of patients.The prediction model construc-ted using the RF algorithm has high diagnostic value.

Objective:To establish a risk predictive model nomogram of acute kidney injury (AKI) in critically ill patients by combining urinary tissue inhibitor of metalloproteinase 2 (TIMP2) and insulin-like growth factor-binding protein 7 (IGFBP7), and to verify the predictive value of the model.Methods:A prospective observational study was conducted. The patients with acute respiratory failure or circulatory disorder admitted to the intensive care unit (ICU) of Northern Jiangsu People's Hospital from November 2017 to April 2020 were enrolled. The patients were enrolled within 24 hours of ICU admission, and their general conditions and relevant laboratory test indicators were collected. At the same time, urine was collected to determine the levels of biomarkers TIMP2 and IGFBP7, and TIMP2·IGFBP7 was calculated. Patients were divided into non-AKI and AKI groups according to whether grade 2 or 3 AKI occurred within 12 hours after enrollment. The general clinical data and urinary TIMP2·IGFBP7 levels of patients between the two groups were compared. The indicators with P < 0.1 in univariate analysis were included in the multivariate Logistic regression analysis to obtain the independent risk factors for grade 2 or 3 AKI within 12 hours in critical patients. An AKI risk predictive model nomogram was established, and the application value of the model was evaluated. Results:A total of 206 patients were finally enrolled, of whom 54 (26.2%) developed grade 2 or 3 AKI within 12 hours of enrollment, and 152 (73.8%) did not. Compared with the non-AKI group, the patients in the AKI group had higher body mass index (BMI), pre-enrollment serum creatinine (SCr), urinary TIMP2·IGFBP7 and proportion of using vasoactive drugs, and additional exposure to AKI (use of nephrotoxic drugs before enrollment) was more common. Multivariate Logistic regression analysis showed that BMI [odds ratio ( OR) = 1.23, 95% confidence interval (95% CI) was 1.10-1.37, P = 0.000], pre-enrollment SCr ( OR = 1.01, 95% CI was 1.00-1.02, P = 0.042), use of nephrotoxic drugs ( OR = 2.84, 95% CI was 1.34-6.03, P = 0.007) and urinary TIMP2·IGFBP7 ( OR = 2.19, 95% CI was 1.56-3.08, P = 0.000) was an independent risk factor for the occurrence of grade 2 or 3 AKI in critical patients. An AKI risk predictive model nomogram was constructed based on the independent risk factors of AKI. Bootstrap validation results showed that the model had good discrimination and calibration in internal validation. Receiver operator characteristic curve (ROC curve) analysis showed that the area under the ROC curve (AUC) of urinary TIMP2·IGFBP7 alone in predicting grade 2 or 3 AKI within 12 hours in critical patients was 0.74 (95% CI was 0.66-0.83), the optimal cut-off value was 1.40 (μg/L) 2/1?000 (sensitivity was 66.7%, specificity was 85.0%), and the predictive performance of the model incorporating urinary TIMP2·IGFBP7 was significantly better than that of the model without urinary TIMP2·IGFBP7 [AUC (95% CI): 0.85 (0.79-0.91) vs. 0.77 (0.70-0.84), P = 0.005], net reclassification index (NRI) was 0.29 (95% CI was 0.08-0.50, P = 0.008), integrated discrimination improvement (IDI) was 0.13 (95% CI was 0.07-0.19, P < 0.001). Conclusion:The AKI risk predictive model based on urinary TIMP2·IGFBP7 has high clinical value and is expected to be used to early predict the occurrence of AKI in critically ill patients.

Sepsis-associated liver injury (SALI) is a common complication of sepsis, which is characterized by systemic immune disorders induced by sepsis leading to liver damage. Currently, there are no effective treatments for SALI, which is related to its complex pathophysiological mechanisms. In recent years, the disorder of intestinal environment after sepsis has been considered as an important factor for SALI, but the specific molecular mechanism of the above process is still unclear. This article will review the pathological role and molecular mechanisms between intestinal environmental disturbance and SALI, aiming to analyze the potential research direction of SALI and identify potential therapeutic targets for its treatment.

Sepsis is a life-threatening organ dysfunction caused by the host's dysfunctional response to infection. Sepsis-induced cardiomyopathy (SICM), as a serious complication of sepsis, is an acute reversible cardiac dysfunction syndrome unrelated to myocardial ischemia, which affects the outcome and prognosis of sepsis. As a complex microbial system, gut microbiota has been confirmed to be involved in the development of coronary heart disease, hypertension, heart failure and other cardiovascular diseases, and is also related to the occurrence and development of sepsis. However, there are few studies on the relationship between gut microbiota and SICM. This paper reviews the current research progress on gut microbiota and SICM, aiming at provide a new idea for clinical treatment of SICM.

Objective:This study aimed to investigate the correlation between the levels of serum amyloid A protein (SAA) and apolipoprotein A-Ⅰ (ApoA-Ⅰ) with the severity and prognosis of septic patients, in order to find new clinical prognostic markers for sepsis patients.Methods:This study prospectively included patients admitted to the intensive care unit of Northern Jiangsu People's Hospital from September 2021 to February 2022. Patients were diagnosed with sepsis according to the Sepsis-3 criteria and aged between 18 and 80 years old. Peripheral venous blood samples were collected at 0 h, 24 h, and 72 h after inclusion in the study, measured the levels of ApoA-Ⅰ and SAA, and the 72 h ΔSAA and 72 h ΔApoA-Ⅰwere calculated.. Patient demographics, laboratory parameters, acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) scores, sequential organ failure assessment scores, etc., were recorded. Patients were divided into survival and death groups based on outcomes, and were divided into shock and non-shock groups based on the presence of shock. Logistic regression was used to combine ApoA-I and SAA to establish a new combined index. Receiver Operating Characteristic curve analysis was performed to evaluate the predictive value of SAA, ApoA-Ⅰ, 72 h ΔApoA-Ⅰ, 72 h ΔSAA and the combined SAA and ApoA-Ⅰ for the prognosis of sepsis patients.Results:A total of 108 patients were included in the analysis, with 48 cases in the non-septic shock group and 60 cases in the septic shock group; 77 cases in the survival group and 31 cases in the death group. There were statistically significant differences in SAA and ApoA-Ⅰ levels at each time point between the shock and non-shock groups (all P<0.05), as well as between the death and survival groups (all P<0.05). SAA levels at each time point were positively correlated with APACHEⅡ scores (all P<0.001), while ApoA-Ⅰ levels at each time point were negatively correlated with APACHEⅡ scores (all P<0.01). SAA levels could predict the risk of death in sepsis patients, with the highest area under curve (AUC) value at 24 h SAA (AUC=0.713, P=0.001), sensitivity was 65.3%, and specificity was 72.7% for predicting 28-day mortality in sepsis. ApoA-Ⅰ levels at each time point could also predict the risk of death in sepsis patients, with the highest AUC value at 72 h ApoA-Ⅰ (AUC=0.743, P<0.001), sensitivity was 69.4%, and specificity was 77.1% for predicting 28-day survival in sepsis. The combined detection of 24 h SAA and 72 h ApoA-Ⅰ increased the AUC value (AUC=0.758, P<0.05), but the Z test showed that the prediction of death risk in patients with sepsis was not significantly higher than that of a single index ( P>0.05). Conclusions:Serum levels of SAA and ApoA-Ⅰ could reflect the severity of sepsis in patients and serve as independent indicators for predicting the prognosis of sepsis patients. The overall diagnostic efficacy of the combined SAA and ApoA-Ⅰ was not significantly different from that of a single index.

Optimizing the management of medical service appointment is an important measure to enhance the patient′s medical experience and promote the high-quality development of hospitals. In 2022, a tertiary comprehensive hospital in Jiangsu Province focused on the demand for digital appointments, and carried out coordinated management of intelligent appointment for medical examination both inside and outside the hospital, online and offline. By constructing an intelligent examination appointment system, enriching appointment categories, exchanging appointment information, improving supporting services, and establishing appointment supervision mechanisms, this practice provided intelligent, personalized, and precise examination appointment services for patients in multi-campus hospitals and member units of medical group. The average waiting time of patients for CT, MRI, and ultrasound examinations in this hospital decreased from 7.43 h, 8.75 h, and 4.63 h in 2021 to 4.63 h, 4.72 h, and 2.18 h in 2023, respectively, as well as the average satisfaction rate of patients with examination appointments increased from 90.7% to 96.5%. The intelligent examination appointment management had achieved good results, which could provide references for other hospitals to optimize appointment of medical services.

OBJECTIVE: To investigate the correlation of hemoglobin (Hb) level with prognosis of elderly patients diagnosed as sepsis. METHODS: A retrospective cohort study was conducted. Information on the cases of elderly patients with sepsis in the Medical Information Mart for Intensive Care-IV (MIMIC-IV), including basic information, blood pressure, routine blood test results [the Hb level of a patient was defined as his/her maximum Hb level from 6 hours before admission to intensive care unit (ICU) and 24 hours after admission to ICU], blood biochemical indexes, coagulation function, vital signs, severity score and outcome indicators were extracted. The curves of Hb level vs. 28-day mortality risk were developed by using the restricted cubic spline model based on the Cox regression analysis. The patients were divided into four groups (Hb < 100 g/L, 100 g/L ≤ Hb < 130 g/L, 130 g/L ≤ Hb < 150 g/L, Hb ≥ 150 g/L groups) based on these curves. The outcome indicators of patients in each group were analyzed, and the 28-day Kaplan-Meier survival curve was drawn. Logistic regression model and Cox regression model were used to analyze the relationship between Hb level and 28-day mortality risk in different groups. RESULTS: A total of 7 473 elderly patients with sepsis were included. There was a "U" curve relationship between Hb levels within 24 hours after ICU admission and the risk of 28-day mortality in patients with sepsis. The patients with 100 g/L ≤ Hb < 130 g/L had a lower risk of 28-day mortality. When Hb level was less than 100 g/L, the risk of death decreased gradually with the increase of Hb level. When Hb level was ≥ 130 g/L, the risk of death gradually increased with the increase of Hb level. Multivariate Logistic regression analysis revealed that the mortality risks of patients with Hb < 100 g/L [odds ratio (OR) = 1.44, 95% confidence interval (95%CI) was 1.23-1.70, P < 0.001] and Hb ≥ 150 g/L (OR = 1.77, 95%CI was 1.26-2.49, P = 0.001) increased significantly in the model involving all confounding factors; the mortality risks of patients with 130 g/L ≤ Hb < 150 g/L increased, while the difference was not statistically significant (OR = 1.21, 95%CI was 0.99-1.48, P = 0.057). The multivariate Cox regression analysis suggested that the mortality risks of patients with Hb < 100 g/L [hazard ratio (HR) = 1.27, 95%CI was 1.12-1.44, P < 0.001] and Hb ≥ 150 g/L (HR = 1.49, 95%CI was 1.16-1.93, P = 0.002) increased significantly in the model involving all confounding factors; the mortality risks of patients with 130 g/L ≤ Hb < 150 g/L increased, while the difference was not statistically significant (HR = 1.17, 95%CI was 0.99-1.37, P = 0.053). Kaplan-Meier survival curve showed that the 28-day survival rate of elderly septic patients in 100 g/L ≤ Hb < 130 g/L group was significantly higher than that in Hb < 100 g/L, 130 g/L ≤ Hb < 150 g/L and Hb ≥ 150 g/L groups (85.26% vs. 77.33%, 79.81%, 74.33%; Log-Rank test: χ² = 71.850, P < 0.001). CONCLUSIONS Elderly patients with sepsis exhibited low mortality risk if their 100 g/L ≤ Hb < 130 g/L within 24 hours after admission to ICU, and both higher and lower Hb levels led to increased mortality risks.
Humans ; Male ; Female ; Aged ; Retrospective Studies ; Sepsis/diagnosis* ; Critical Care ; Intensive Care Units ; Prognosis ; Hemoglobins ; ROC Curve

Ferroptosis is a non-apoptotic form of cell death newly discovered in 2012.It is characterized by a lethal accumulation of iron-dependent reactive oxygen species and lipid hydroperoxides,resulting in mitochondrial morphological changes and phospholipid peroxidation damage of cell membrane.As a strong oxidizing agent in biological systems,iron overloaded,can directly cause acute kidney injury(AKI)through oxidative damage.Iron homeostasis disturbance and ferroptosis are directly involved in AKI caused by ischemia-reperfusion,drugs and rhabdomyolysis,etc.This article reviews the relevant evidence and the important mechanism of iron homeostasis and ferroptosis in AKI,and provides new ideas and new targets for further research and treatment of AKI.

Objective:Sepsis patients usually have a fever, but it is still controversial about whether sepsis patients with fever need cooling treatment. This study aimed to evaluate the effect of external physical cooling on the prognosis of sepsis patients.Methods:This study was a single-center, open-label, randomized clinical trial. Adult sepsis patients with body temperature above 38.3 °C admitted to the Critical Care Medicine of Northern Jiangsu People's Hospital from June 2020 to December 2020 were selected, and randomly assigned in a 1∶1 ratio to the cooling group and control group. Patients in the cooling group used external physical cooling methods to reduce their core body temperature to the normal range (36.5-37.5°C) within 4 h of enrollment and maintained for 48 h. Standard care was implemented in the control group at all times, and all antipyretic treatments were prohibited. The 28-day mortality, 72 h-Δ sequential organ failure assessment (SOFA) score (SOFA score at enrollment–SOFA score after 72 h), length of hospital stay and length of ICU stay were compared between the two groups.Results:A total of 53 patients (32 males and 21 females) were enrolled in the study, including 26 patients in the cooling group and 27 patients in the control group. There were no statistical differences in age, sex, source of infection, SOFA score and body temperature between the two groups (all P>0.05). There was no significant difference in the 28-day mortality between the cooling group and the control group ( RR=1.38, 95% CI: 0.62-3.07, P=0.430). The 72 h-ΔSOFA score of the cooling group was significantly higher than that of the control group, the mean difference between the two groups was 1.90 (95% CI: 0.09-3.71, P=0.040), and there was no significant difference in length of hospital stay, length of ICU stay and 28-day mortality between the two groups. Conclusions:External physical cooling management can not significantly reduce the 28-day mortality of sepsis patients. However, external physical cooling can reduce the 72-h SOFA score in sepsis patients, and improve the organ function of patients.

Objective:To study the effect of different crystalloid resuscitation on renal function in septic shock rabbits, and to provide a theoretical basis for the choice of crystalloid for clinical fluid resuscitation.Methods:Thirty-six healthy male New Zealand white rabbits were divided into six groups by random number table: control group, model group, and four crystalloid groups including normal saline (NS) group, lactate Ringer solution (LR) group, acetate Ringer solution (AR) group, and sodium potassium magnesium calcium glucose injection (SPMCG) group, with 6 rabbits in each group. Rabbits were infused with Escherichia coli lipopolysaccharide (LPS) 500 μg/kg via the marginal ear vein (infused at a constant speed within 20 minutes), and then continued to infuse in an increase of 300 μg/kg every 10 minutes, the maximum dose was 2 mg/kg, until the mean arterial pressure (MAP) dropped to 60% of the basal value, the septic shock model was considered to be successfully reproduced. The rabbits in the control group were not injected with LPS, and other operations were the same as in the model group. Different crystalloid groups were given crystal solution immediately after modeling for resuscitation (predetermined fluid volume 60 mL/kg, transfusion within 3 hours). The volume stress test was performed every hour to guide the fluid volume, and the stroke volume index increase rate (ΔSVI) < 15% was the end point of resuscitation. The control group and the model group were given NS 4 mL·kg -1·h -1 to maintain the physiological requirement. All groups were given tracheotomy and mechanical ventilation, and the hemodynamic changes were monitored by pulse-indicated continuous cardiac output (PiCCO). The dynamic changes of hemodynamic indexes, arterial blood gas analysis, electrolytes, blood glucose and renal function biomarkers were monitored before modeling, immediately after modeling and 3, 6, and 12 hours after resuscitation. Results:① Hemodynamic indicators: after modeling, the MAP in the model group and the four fluid resuscitation groups decreased significantly, the cardiac index (CI) increased, and the systemic vascular resistance index (SVRI), global end-diastolic volumn index (GEDVI) decreased. After different crystalloid resuscitation at different time points, MAP, SVRI, and GEDVI increased in the four crystalloid groups. ②Arterial blood gas analysis, electrolytes, blood glucose: blood lactic acid (Lac) in the model group and the four fluid resuscitation groups increased after model success. After fluid resuscitation, the Lac of each crystalloid group began to decrease and reached to the lowest at 12 hours. Compared with the LR, AR and SPMCG groups, the pH value decreased in the NS group at 6 hours and 12 hours of fluid resuscitation (6 hours: 7.29±0.00 vs. 7.40±0.02, 7.35±0.02, 7.37±0.02; 12 hours: 7.27±0.02 vs. 7.38±0.02, 7.39±0.02, 7.35±0.01; all P < 0.05). After fluid resuscitation, blood Cl - levels at 3, 6, and 12 hours in the NS group were significantly higher than those in the LR, AR and SPMCG groups (mmol/L: 113.4±0.6 vs. 101.4±3.6, 108.0±1.1, 106.0±0.8 at 3 hours; 115.1±2.0 vs. 101.1±2.7, 109.0±2.2, 105.3±0.6 at 6 hours; 116.9±0.1 vs. 104.2±4.4, 107.6±1.7, 108.7±0.6 at 12 hours; all P < 0.05). There was no significant difference in blood glucose at each time point among the four crystalloid groups. ③ Biomarkers of renal function: blood and urine neutrophil gelatinase associated lipocalin (NGAL) and cystatin C (Cys C) were significantly increased in the model group and four fluid resuscitation groups. After fluid resuscitation, blood, urine NGAL and Cys C decreased. There was no significant difference in blood, urine NGAL and Cys C at all the time points among the different fluid resuscitation groups. Conclusions:In the rabbit model of septic shock induced by Escherichia coli LPS, hyperchloremia and acidosis occurred after NS resucitation, but did not occur during the recovery of LR, AR and SPMCG. There was no difference in the effects of different crystalloid resuscitation on renal function in septic shock rabbits.