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 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.

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: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.

Objective:To investigate the epidemiological characteristics of septic cardiomyopathy and explore the relationship between the relevant indexes measured by echocardiography and the prognosis of patients with sepsis.Methods:A case-control study was conducted. The data of patients with sepsis admitted to the department of critical care medicine of Jiangsu Subei People's Hospital Affiliated to Yangzhou University and the department of critical care medicine of Beijing Electric Power Hospital of State Grid Corporation of China from June 2018 to June 2021 were enrolled. The general information and 28-day prognosis were recorded. At the same time, ultrasonic parameters obtained by transthoracic echocardiography within 24 hours after intensive care unit (ICU) admission were recorded. The differences in ultrasound indexes between the death group and the survival group on 28 days were compared. Parameters with significant statistical differences between the death group and the survival group were included in the Logistic regression analysis to find the independent risk factors for the prognosis of patients with sepsis, the predictive value of each index for the prognosis of patients with sepsis was evaluated by receiver operator characteristic curve (ROC curve).Results:A total of 145 patients with sepsis were enrolled, including 106 patients with septic shock. Among the 145 patients, septic cardiomyopathy was found in 73 patients, with the incidence of 50.3%. The incidence of left ventricular diastolic dysfunction cardiomyopathy was 41.4% ( n = 60), the incidence of left ventricular systolic dysfunction cardiomyopathy was 24.8% ( n = 36), and the incidence of right ventricular systolic dysfunction cardiomyopathy was 12.4% ( n = 18). At 28 days, 98 patients survived and 47 died, with the mortality of 32.4%. The peak e' velocity by tissue Doppler imaging (e') and right ventricular myocardial systolic tricuspid annulus velocity (RV-Sm) of the death group were significantly lower than those of the survival group [e' (cm/s): 7.81±1.12 vs. 8.61±1.02, RV-Sm (cm/s): 12.12±2.04 vs. 13.73±1.74, both P < 0.05], left ventricular ejection fraction (LVEF) and left ventricular systolic mitral annulus velocity (LV-Sm) in the death group were slightly higher than those in the survival group [LVEF: 0.550±0.042 vs. 0.548±0.060, LV-Sm (cm/s): 8.92±2.11 vs. 8.23±1.71], without significant differences (both P > 0.05). Parameters with significant statistical differences between the two groups were included in the Logistic regression analysis and showed that e' and RV-Sm were independent risk factors for the 28-day prognosis of patients with sepsis [e': odds ratio ( OR) = 0.623, 95% confidence interval (95% CI) was 0.410-0.947, P = 0.027; RV-Sm: OR = 0.693, 95% CI was 0.525-0.914, P = 0.010]. ROC curve analysis showed that the area under the ROC curve (AUC) of e' for predicting the 28-day prognosis of patients with sepsis was 0.657, 95% CI was 0.532-0.781, P = 0.016, the best cut-off value was 8.65 cm/s, the sensitivity was 62.1%, and the specificity was 73.4%. The AUC of RV-Sm for predicting the 28-day prognosis of patients with sepsis was 0.641, 95% CI was 0.522-0.759, P = 0.030, the best cut-off value was 14.80 cm/s, the sensitivity was 96.6%, and the specificity was 26.6%. Conclusions:The incidence of septic cardiomyopathy is high. The LVEF measured by early echocardiography has no predictive value for 28-day prognosis in septic patients, while RV-Sm and e' are important predictors for 28-day prognosis.

Objective:To evaluate the effect of 2019 novel coronavirus inactivated vaccine on the disease severity of patients with Delta variant of coronavirus disease 2019.Methods:A retrospective analysis was performed on 704 patients with coronavirus disease 2019 infected with Delta variant who were older than 18 years old and admitted in the coronavirus disease 2019 designated hospital of Yangzhou (Subei Hospital New Area Branch) from July 2021 to September 2021. They were divided into severe (severe, critical) group and non-severe (light, ordinary) group according to the clinical characteristics of patients. According to the vaccination status, they were divided into 0-dose group, 1-dose group and 2-dose group. We evaluated the effects of vaccination on the severity of the disease and the production of antibodies, and analyzed the influencing factors leading to the severe group of coronavirus disease 2019.Results:The proportion of severe group in the 2-dose vaccinated group was significantly lower than that in the 1-dose vaccinated group and 0-dose vaccinated group [3.02% (7/232) vs. 9.48% (22/232), 15.83% (38/240), P < 0.05]. The time from onset to admission (day: 1.97±1.66 vs. 2.66±2.70), age (years: 45.3±12.2 vs. 63.6±17.0), direct bilirubin [DBil (μmol/L): 3.70±1.83 vs. 5.30±5.13], lactate dehydrogenase [LDH (U/L): 240.69±74.29 vs. 256.30±85.18], creatinine [SCr (μmol/L): 63.38±19.86 vs. 70.23±25.43], interleukin-6 [IL-6 (ng/L): 7.32 (1.54, 17.40) vs. 18.38 (8.83, 33.43)], creatine kinase [CK (U/L): 66.00 (43.00, 99.75) vs. 78.00 (54.50, 144.00)] and D-dimer [mg/L: 0.30 (0.08, 0.49) vs. 0.41 (0.23, 0.69)] of patients in the 2-dose group were significantly lower than those in the 0-dose group (all P < 0.05), while platelet [PLT (×10 9/L): 176.69±60.25 vs. 149.25±59.07], white blood cell count [WBC (×10 9/L): 5.43±1.77 vs. 5.03±1.88] and lymphocyte [LYM (×10 9/L): 1.34±0.88 vs. 1.17±0.50] were significantly higher than those in the 0-dose group (all P < 0.05). The titer of immunoglobulin G (IgG) in the 2-dose group was significantly higher than those in the 1-dose group and 0-dose group on the 10th day after admission [U/L: 130.94 (92.23, 326.31), 113.18 (17.62, 136.20), 117.85 (33.52, 156.73), both P < 0.05], and higher than 0-dose group on the 16th day [U/L: 156.12 (120.32, 167.76) vs. 126.52 (61.34, 149.57), P < 0.05]. The proportion of complete 2-dose vaccination [10.45% (7/67) vs. 35.32% (225/637)], LYM (×10 9/L: 1.09±0.32 vs. 1.25±0.56) and PLT (×10 9/L: 138.55±68.03 vs. 166.93±59.70) in the severe group were significantly lower than those in the non-severe group ( P < 0.05), while the time from onset to admission (day: 3.01±2.99 vs. 2.25±2.09), the length of hospital stay (day: 28±18 vs. 16±6), male proportion [77.61% (52/67) vs. 34.54% (220/637)], age (years: 69.13±12.63 vs. 52.28±16.53), DBil [μmol/L: 4.20 (3.18, 6.65) vs. 3.60 (2.80, 4.90], LDH (U/L: 310.61±98.33 vs. 238.19±72.14), SCr (μmol/L: 85.67±38.25 vs. 65.98±18.57), C-reactive protein [CRP (μmol/L): 28.12 (11.32, 42.23) vs. 8.49 (2.61, 17.58)], IL-6 [ng/L: 38.38 (24.67, 81.50) vs. 11.40 (4.60, 22.07)], CK [U/L: 140.00 (66.00, 274.00) vs. 72.80 (53.00, 11.00)] and the D-dimer [mg/L: 0.46 (0.29, 0.67) vs. 0.35 (0.19, 0.57)] in the severe group were significantly higher than those in the non-severe group (all P < 0.05). Multivariate regression analysis showed that the odds ratio ( OR) of severe group was 0.430 ( P = 0.010) in the 1-dose group and the 2-dose group compared with the 0-dose group. However, the risk of severe group was 0.381-fold in the 2-dose group compared with the 0-dose group [ OR = 0.381, 95% confidence interval (95% CI) was 0.121-1.199] which was not statistically significant, when the age was included in the regression analysis ( P > 0.05). PLT ( OR = 0.992, 95% CI was 0.986-0.998) were protective factors, but older than 60 years old ( OR = 3.681, 95% CI was 1.637-8.278), CK ( OR = 1.001, 95% CI was 1.000-1.001), IL-6 ( OR = 1.006, 95% CI was 1.002-1.010), SCr ( OR = 1.020, 95% CI was 1.007-1.033) were risk factors for severe group (all P < 0.05). Conclusions:Compared with the 0-dose vaccinated patients, the coronavirus disease 2019 patients infected with delta variant and fully vaccinated with 2-dose 2019 novel coronavirus inactivated vaccine had lower level of IL-6, SCr, CK and D-dimer, and higher PLT, LYM and IgG titer, who were not easy to develop into the severe condition.