Objective With the development of manned space missions to the moon and space exploration,extravehicular activities become more frequent and extravehicular mission become more complex,which puts forward higher requirements for the extravehicular spacesuit.In order to ensure the ergonomics of spacesuit,the flexible joints are usually adopted in the limbs of spacesuit.The structural design of large angle of movement and low resistance joints is the basic for ensuring the ergonomics of spacesuit.Methods This study established a method of spacesuit joint structure to analysis the motion characteristic of typical joints.Firstly,the structure and activity characteristics of the spacesuit and lunar space suits were comprehensively analyzed,and the activity characteristics of different typical structure are qualitatively analyzed based on existing empirical method.Then,the dynamics of typical structure was analyzed by finite element model.By studying the change trend of motion of spacesuit joint with motion angle,and the motion characteristic curve was obtained.Finally,the model was studied according to different structural size parameters.The influence of structural parameters on the motion characteristics was analyzed,and the curves was obtained to provide a basis for design of spacesuit motion joint structure.Results Through the above analysis,the motion characteristics of different typical structure are obtained qualitatively.And the influence of different structure parameters on the motion characteristics was analyzed.This establishes the method basis for structure design.Conclusion The study was carried out a method based on finite element model for joint motion analysis,which is suitable for the design of typical joint structure of spacesuit.

Objective To prepare 4-sulfonylcalix[6]arene-modified cotton fibers for adsorption and removal of uranium based on the specific complexation of calix[6]arene with uranium (VI). Methods Chemical grafting was used for the modification of cotton, which reacted with α-bromoisobutyryl bromide, glycidyl methacrylate, and 4-sulfonylcalix[6]arene. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and infrared spectroscopy (FTIR) were used to characterize the structure of 4-sulfonylcalix[6]arene-modified cotton (Cotton S-C[6]a). A Franz diffusion cell was used to simulate uranium-contaminated skin. Laser fluorimetry was used to determine the uranium content. Results SEM, XPS, and FTIR showed that cotton fibers were successfully grafted with 4-sulfonylcalix[6]arene. The optimal conditions of Cotton S-C[6]a for the adsorption of uranium (VI) was pH 4.0, duration of 20 min, and 20 mg of adsorbent. The adsorption process fitted well with pseudo-secondary-order kinetics. The uranium removal efficiency of Cotton S-C[6]a was up to 78.46% in aqueous solution and 81.72% on skin. Conclusion The synthesized Cotton S-C[6]a is highly efficient in the removal of uranium (VI) in solution and on contaminated skin.

OBJECTIVE: To observe the expression level of cytokines in patients with sepsis and its effect on prognosis. METHODS: The clinical data of sepsis patients admitted to the intensive care unit (ICU) of the First Affiliated Hospital of Zhengzhou University from January 2020 to December 2022 were analyzed retrospectively, including gender, age, and acute physiology and chronic health evaluation II (APACHE II), blood routine, procalcitonin (PCT), C-reactive protein (CRP), and cytokines levels [interleukins (IL-2, IL-4, IL-6, IL-10, IL-17), tumor necrosis factor-α (TNF-α), and interferon-γ (IFN-γ)] within 24 hours of admission to ICU. The 28-day prognosis of the patients was followed up. The patients were divided into survival group and death group according to the prognosis. The clinical data between the two groups of sepsis patients with different prognosis were compared. Binary Logistic regression analysis was used to analyze the independent risk factors affecting the prognosis of patients with sepsis, and the receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of each risk factor for the prognosis of patients with sepsis. RESULTS: (1) A total of 227 patients with sepsis were enrolled, including 168 patients in the survival group (survival rate 74.0%) and 59 patients in the death group (mortality 26.0%). There were no significant differences in age (years old: 55.97±2.13 vs. 54.67±1.11) and gender (male: 71.2% vs. 57.1%) between the death group and the survival group (both P > 0.05), indicating that the baseline data of the two groups were comparable. (2) The APACHE II (19.37±0.99 vs. 14.88±0.61, P < 0.001) and PCT (μg/L: 12.39±2.94 vs. 4.14±0.90, P < 0.001) in the death group were significantly higher than those in the survival group, while the platelet count [PLT (×10⁹/L): 144.75±12.50 vs. 215.99±11.26, P = 0.001] and thrombocytocrit [(0.14±0.01)% vs. (0.19±0.01)%, P = 0.001] were significantly lower than those in the survival group. (3) The level of IL-6 in the death group was significantly higher than that in the survival group (ng/L: 577.66±143.16 vs. 99.74±33.84, P < 0.001). There were no statistically significant differences in other cytokines, IL-2, IL-4, IL-10, TNF-α, IFN-γ and IL-17 between the death group and the survival group [IL-2 (ng/L): 2.44±0.38 vs. 2.63±0.27, P = 0.708; IL-4 (ng/L): 3.26±0.67 vs. 3.18±0.34, P = 0.913; IL-10 (ng/L): 33.22±5.13 vs. 39.43±2.85, P = 0.262; TNF-α (ng/L): 59.33±19.21 vs. 48.79±29.87, P = 0.839; IFN-γ (ng/L): 6.69±5.18 vs. 1.81±0.16, P = 0.100; IL-17 (ng/L): 2.05±0.29 vs. 2.58±0.33, P = 0.369]. (4) Binary Logistic regression analysis showed that APACHE II and IL-6 were independent risk factors affecting the prognosis of patients with sepsis [odds ratio (OR) and 95% confidence interval (95%CI) were 1.050 (1.008-1.093) and 1.001 (1.000-1.002), P values were 0.019 and 0.026, respectively]. (5) ROC curve analysis showed that APACHE II and IL-6 had certain predictive value for the prognosis of patients with sepsis, the area under the ROC curve (AUC) was 0.754 (95%CI was 0.681-0.827) and 0.592 (95%CI was 0.511-0.673), P values were < 0.001 and 0.035, respectively. When the optimal cut-off value of APACHE II was 16.50 score, the sensitivity was 72.6% and the specificity was 69.9%. When the optimal cut-off value of IL-6 was 27.87 ng/L, the sensitivity was 67.2% and the specificity was 52.8%. CONCLUSIONS APACHE II score and IL-6 level have certain predictive value for the prognosis of patients with sepsis, the higher APACHE II score and IL-6 level, the greater the probability of death in patients with sepsis.
Humans ; Male ; Interleukin-10 ; Interleukin-17 ; Cytokines ; Tumor Necrosis Factor-alpha ; Interleukin-6 ; Retrospective Studies ; Interleukin-2 ; Interleukin-4 ; ROC Curve ; Sepsis/diagnosis* ; Prognosis ; Procalcitonin ; Interferon-gamma ; Intensive Care Units

OBJECTIVE: To explore the relevant clinical test indicators that affect the prognosis of patients with acute fatty liver of pregnancy (AFLP), and to provide a basis for early diagnosis and correct selection of treatment methods. METHODS: A retrospective analysis was conducted. Clinical data of AFLP patients in the intensive care unit (ICU) of the First Affiliated Hospital of Zhengzhou University from January 2010 to May 2021 were collected. According to the 28-day prognosis, the patients were divided into death group and survival group. The clinical data, laboratory examination indicators, and prognosis of the two groups were compared, and further binary Logistic regression analysis was used to analyze the risk factors affecting the prognosis of patients. At the same time, the values of related indicators at each time point (24, 48, 72 hours) after the start of treatment were recorded. The receiver operator characteristic curve (ROC curve) of prothrombin time (PT) and international normalized ratio (INR) for evaluating the prognosis of patients at each time point was drawn, and the area under the ROC curve (AUC) was calculated to evaluate the predictive value of relevant indicators at each time point for the prognosis of AFLP patients. RESULTS: A total of 64 AFLP patients were selected. The patients developed the AFLP during pregnancy (34.5±6.8) weeks, with 14 deaths (mortality of 21.9%) and 50 survivors (survival rate of 78.1%). There was no statistically significant difference in general clinical data between the two groups of patients, including age, time from onset to visit, time from visit to cessation of pregnancy, acute physiology and chronic health evaluations II (APACHE II), hospitalization time in ICU, and total hospitalization cost. However, the proportion of male fetuses and stillbirths in the death group was higher than that in the survival group. The laboratory examination indicators including the white blood cell count (WBC), alanine transaminase (ALT), serum creatinine (SCr), PT extension, INR elevation, and hyperammonia in the death group were significantly higher than those in the survival group (all P < 0.05). Through Logistic regression analysis of the above indicators showed that PT > 14 s and INR > 1.5 were risk factors affecting the prognosis of AFLP patients [PT > 14 s: odds ratio (OR) = 1.215, 95% confidence interval (95%CI) was 1.076-1.371, INR > 1.5: OR = 0.719, 95%CI was 0.624-0.829, both P < 0.01]. ROC curve analysis showed that both PT and INR at ICU admission and 24, 48, and 72 hours of treatment can evaluate the prognosis of AFLP patients [AUC and 95%CI of PT were 0.772 (0.599-0.945), 0.763 (0.608-0.918), 0.879 (0.795-0.963), and 0.957 (0.904-1.000), respectively; AUC and 95%CI of INR were 0.808 (0.650-0.966), 0.730 (0.564-0.896), 0.854 (0.761-0.947), and 0.952 (0.896-1.000), respectively; all P < 0.05], the AUC of PT and INR after 72 hours of treatment was the highest, with higher sensitivity (93.5%, 91.8%) and specificity (90.9%, 90.9%). CONCLUSIONS AFLP often occurs in the middle and late stages of pregnancy, and the initial symptoms are mainly gastrointestinal symptoms. Once discovered, pregnancy should be terminated immediately. PT and INR are good indicators for evaluating AFLP patient efficacy and prognosis, and PT and INR are the best prognostic indicators after 72 hours of treatment.
Humans ; Male ; Prognosis ; ROC Curve ; Retrospective Studies ; Intensive Care Units ; Sepsis/diagnosis*

OBJECTIVE: To explore the characteristics of changes in peripheral blood lymphocyte subsets in patients with sepsis in intensive care unit (ICU) and analyze their predictive value for prognosis. METHODS: The clinical data of sepsis patients admitted to the surgical intensive care unit (SICU) of the First Affiliated Hospital of Zhengzhou University from January 2020 to December 2021 were analyzed retrospectively. The patients met the diagnostic criteria of Sepsis-3 and were ≥ 18 years old. Peripheral venous blood samples were collected from all patients on the next morning after admission to SICU for routine blood test and peripheral blood lymphocyte subsets. According to the 28-day survival, the patients were divided into two groups, and the differences in immune indexes between the two groups were compared. Logistic regression analysis was used to analyze the risk factors of immune indexes that affect prognosis. RESULTS: (1) A total of 279 patients with sepsis were enrolled in the experiment, of which 198 patients survived at 28 days (28-day survival rate 71.0%), and 81 patients died (28-day mortality 29.0%). There were no significant differences in age (years old: 57.81±1.71 vs. 54.99±1.05) and gender (male: 60.5% vs. 63.6%) between the death group and the survival group (both P > 0.05), and the baseline data was comparable.(2) Acute physiology and chronic health evalution II (APACHE II: 22.06±0.08 vs. 14.08±0.52, P < 0.001), neutrophil percentage [NEU%: (88.90±1.09)% vs. (84.12±0.77)%, P = 0.001], procalcitonin [PCT (μg/L): 11.97±2.73 vs. 5.76±1.08, P = 0.011], platelet distribution width (fL: 16.81±0.10 vs. 16.57±0.06, P = 0.029) were higher than those in the survival group, while lymphocyte percentage [LYM%: (6.98±0.78)% vs. (10.59±0.86)%, P = 0.012], lymphocyte count [LYM (×10⁹/L): 0.70±0.06 vs. 0.98±0.49, P = 0.002], and platelet count [PLT (×10⁹/L): 151.38±13.96 vs. 205.80±9.38, P = 0.002], and thrombocytocrit [(0.15±0.01)% vs. (0.19±0.07)%, P = 0.012] were lower than those in the survival group. (3) There was no statistically significant difference in the percentage of lymphocyte subsets between the death group and the survival group, but the absolute value of LYM (pieces/μL: 650.24±84.67 vs. 876.64±38.02, P = 0.005), CD3⁺ absolute value (pieces/μL: 445.30±57.33 vs. 606.84±29.25, P = 0.006), CD3⁺CD4⁺ absolute value (pieces/μL: 239.97±26.96 vs. 353.49±18.59, P = 0.001), CD19⁺ absolute value (pieces/μL: 111.10±18.66 vs. 150.30±10.15, P = 0.049) in the death group was lower than those in the survival group. Other lymphocyte subsets in the death group, such as CD3⁺CD8⁺ absolute value (pieces/μL: 172.40±24.34 vs. 211.22±11.95, P = 0.112), absolute value of natural killer cell [NK (pieces/μL): 101.26±18.15 vs. 114.72±7.64, P = 0.420], absolute value of natural killer T cell [NKT (pieces/μL): 33.22±5.13 vs. 39.43±2.85, P = 0.262], CD4^-CD8^- absolute value (pieces/μL: 41.07±11.07 vs. 48.84±3.31, P = 0.510), CD4⁺CD8⁺ absolute value (pieces/μL: 3.39±1.45 vs. 3.47±0.36, P = 0.943) were not significantly different from those in the survival group. (4)Logistic regression analysis showed that lymphocyte subsets were not selected as immune markers with statistical significance for the prognosis of sepsis. CONCLUSIONS The changes of immune indexes in sepsis patients are closely related to their prognosis. Early monitoring of the above indexes can accurately evaluate the condition and prognosis of sepsis patients.
Humans ; Male ; Adolescent ; Retrospective Studies ; ROC Curve ; Sepsis/diagnosis* ; Lymphocyte Count ; Lymphocyte Subsets ; Prognosis ; Killer Cells, Natural

Objective:To investigate the predictive value of the maximum aggregation rate (MAR) of platelet for septic shock and septic shock with disseminated intravascular coagulation (DIC).Methods:A retrospective case-control study enrolled patients with sepsis admitted to department of critical care medicine of the First Affiliated Hospital of Zhengzhou University from January 2021 to November 2022. The basic data, dynamic platelet aggregation rate, blood routine, inflammation indicators, sequential organ failure assessment (SOFA) and other clinical indicators within 24 hours after admission were collected. Septic patients were divided into the shock group and the non-shock group according to the presence of septic shock; then refer to the International Society on Thrombosis and Hemostasis (ISTH) standard, patients with septic shock were divided into the shock DIC group and the shock non-DIC group according to the presence of dominant DIC. Compared the differences in platelet aggregation function between these groups, and the receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of the MAR for septic shock and septic shock with DIC. Spearman correlation analysis was used to analyze the correlation of MAR with inflammation indicators and the severity of illness in patients with sepsis.Results:A total of 153 sepsis patients were included and 61 with septic shock (including 17 with dominant DIC and 44 without dominant DIC). Compared with the non-shock group, the level of procalcitonin (PCT), C-reactive protein (CRP), and SOFA score were significantly higher in the shock group [PCT (mg/L): 6.90 (2.50, 23.50) vs. 0.87 (0.26, 5.75), CRP (mg/L): 156.48 (67.11, 230.84) vs. 90.39 (46.43, 182.76), SOFA score: 11.00 (8.00, 14.00) vs. 5.00 (3.00, 8.00), all P < 0.05]. The platelet count (PLT) and the MAR induced by adenosine diphosphate (ADP), adrenaline (A), collagen (COL), and arachidonic acid (AA; ADP-MAR, A-MAR, COL-MAR, AA-MAR) in the shock group were significantly decreased [PLT (×10 9/L): 101.00 (49.00, 163.50) vs. 175.50 (108.25, 254.50), ADP-MAR: 28.50% (22.00%, 38.05%) vs. 45.90% (33.98%, 60.28%), A-MAR: 38.90% (30.00%, 55.40%) vs. 65.15% (54.38%, 72.53%), COL-MAR: 27.90% (20.85%, 36.55%) vs. 42.95% (33.73%, 54.08%), AA-MAR: 24.70% (16.40%, 34.20%) vs. 46.55% (28.33%, 59.20%), all P < 0.05]. Subgroup analysis revealed that, compared with the shock non-DIC group, the SOFA scores were significantly higher in patients in the shock DIC group (13.29±5.23 vs. 10.39±3.58, P < 0.05), the PLT and COL-MAR in the shock DIC group were significantly reduced [PLT (×10 9/L): 36.00 (22.00, 67.50) vs. 115.50 (84.25, 203.75), COL-MAR: 21.50% (17.85%, 32.60%) vs. 30.95% (22.98%, 38.53%), all P < 0.05]. ROC curve analysis showed that A-MAR had a higher predictive value for septic shock, and the area under the ROC curve (AUC) was 0.814 [95% confidence interval (95% CI) was 0.742-0.886, P = 0.000]. When the optimal cut-off value was 51.35%, the sensitivity was 68.9%, the specificity was 82.6%, the positive predictive value was 0.724 and the negative predictive value was 0.800. COL-MAR had some predictive value for septic shock with DIC, and the AUC was 0.668 (95% CI was 0.513-0.823, P = 0.044). When the optimal cut-off value was 21.90%, the sensitivity was 52.9%, the specificity was 79.5%, the positive predictive value was 0.500, and the negative predictive value was 0.813. Spearman correlation analysis showed that the MAR induced by each inducer was negatively correlated with inflammatory indicators and SOFA scores in sepsis patients, with A-MAR showing the strongest correlation with SOFA score ( r = -0.327, P = 0.000). Conclusions:MAR, an indicator of platelet aggregation function, shows predictive value for septic shock and septic shock with DIC, and it could be used to for evaluating the severity of patients with sepsis. In addition, tt alsocan be used as a monitoring index to predict the changes of sepsis patients and to guide the treatment.

OBJECTIVE: To investigate the effects of acid-sensing ion channels (ASICs) on electrophysiological epileptic activities of mouse hippocampal pyramidal neurons in the extracellular acidotic condition. METHODS: We investigated effects of extracellular acidosis on epileptic activities induced by elevated extracellular K concentration or the application of an antagonist of GABA receptors in perfusate of mouse hippocampal slices under field potential recordings. We also tested the effects of extracellular acidosis on neuronal excitability under field potential recording and evaluated the changes in epileptic activities of the neurons in response to pharmacological inhibition of ASICs using a specific inhibitor of ASICs. RESULTS: Extracellular acidosis significantly suppressed epileptic activities of the hippocampal neurons by converting ictal-like epileptic activities to non-ictal-like epileptic activities in both high [K ]o and disinhibition models, and also suppressed the intrinsic excitability of the neurons. ASICs inhibitor did not antagonize the inhibitory effect of extracellular acidosis on ictal epileptic activities and intrinsic neuronal excitability, but exacerbated non-ictal epileptic activities of the neurons in extracellular acidotic condition in both high [K]o and disinhibition models. CONCLUSIONS ASICs can differentially modulate ictal-like and non-ictallike epileptic activities via its direct actions on excitatory neurons.
Acid Sensing Ion Channels ; metabolism ; Acidosis ; Animals ; Epilepsy ; physiopathology ; Hydrogen-Ion Concentration ; Mice ; Pyramidal Cells ; pathology ; physiology

OBJECTIVE: To investigate the effects of acid-sensing ion channels (ASICs) on electrophysiological epileptic activities of mouse hippocampal pyramidal neurons in the extracellular acidotic condition. METHODS: We investigated effects of extracellular acidosis on epileptic activities induced by elevated extracellular K concentration or the application of an antagonist of GABA receptors in perfusate of mouse hippocampal slices under field potential recordings. We also tested the effects of extracellular acidosis on neuronal excitability under field potential recording and evaluated the changes in epileptic activities of the neurons in response to pharmacological inhibition of ASICs using a specific inhibitor of ASICs. RESULTS: Extracellular acidosis significantly suppressed epileptic activities of the hippocampal neurons by converting ictal-like epileptic activities to non-ictal-like epileptic activities in both high [K ]o and disinhibition models, and also suppressed the intrinsic excitability of the neurons. ASICs inhibitor did not antagonize the inhibitory effect of extracellular acidosis on ictal epileptic activities and intrinsic neuronal excitability, but exacerbated non-ictal epileptic activities of the neurons in extracellular acidotic condition in both high [K]o and disinhibition models. CONCLUSIONS ASICs can differentially modulate ictal-like and non-ictallike epileptic activities via its direct actions on excitatory neurons.
Acid Sensing Ion Channels ; Acidosis ; Animals ; Hippocampus ; Hydrogen-Ion Concentration ; Mice ; Pyramidal Cells

Objective:To study the effect of Xuebijing on inflammatory response and prognosis in patients with septic shock.Methods:A prospective randomized controlled study was conducted. Eighty septic shock patients admitted to department of critical care medicine of the First Affiliated Hospital of Zhengzhou University from January to December in 2019 were enrolled. The enrolled patients were divided into Xuebijing group and control group by randomized number table method, with 40 cases in each group. Both groups were strictly followed the guidelines for the diagnosis and treatment of septic shock to take comprehensive treatment measures against sepsis. On this basis, Xuebijing group received intravenous 100 mL Xuebijing injection twice a day for 7 days. Baseline data of enrolled patients were recorded. The levels of interleukin-6 (IL-6), procalcitonin (PCT), C-reactive protein (CRP) and heparin binding protein (HBP) were measured before treatment and 3, 7 and 10 days after treatment. Mechanical ventilation time, the length of intensive care unit (ICU) stay, total hospitalization time and 28-day mortality were recorded. The differences of every indicator between the two groups were compared. Independent risk factors affecting patient prognosis were analyzed by binary Logistic regression.Results:① There was no significant difference in baseline data such as gender, age, infection site, acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) and sequential organ failure score (SOFA) between the two groups. ② The levels of serum inflammatory factors in both groups showed a decreasing trend after treatment. Compared with the control group, IL-6 and HBP in the Xuebijing group significantly decreased on day 7 [IL-6 (ng/L): 66.20 (16.34, 163.71) vs. 79.81 (23.95, 178.64), HBP (ng/L): 95.59 (45.23, 157.37) vs. 132.98 (73.90, 162.05), both P < 0.05]; on day 10, PCT, CRP, IL-6 and HBP significantly decreased [PCT (μg/L): 1.14 (0.20, 3.39) vs. 1.31 (0.68, 4.21), CRP (mg/L): 66.32 (19.46, 115.81) vs. 89.16 (20.52, 143.76), IL-6 (ng/L): 31.90 (13.23, 138.74) vs. 166.30 (42.75, 288.10), HBP (ng/L): 62.45 (29.17, 96.51) vs. 112.33 (58.70, 143.96), all P < 0.05]. ③ Compared with the control group, mechanical ventilation time and the length of ICU stay were significantly shortened and the total hospitalization expenses were significantly reduced in Xuebijing group [mechanical ventilation time (hours): 57.0 (0, 163.5) vs. 168.0 (24.0, 282.0), the length of ICU stay (days): 8.80±4.15 vs. 17.13±7.05, the total hospitalization expenses (ten thousand yuan): 14.55±7.31 vs. 20.01±9.86, all P < 0.05]. There was no significant difference in 28-day mortality and the total hospitalization time [28-day mortality: 37.5% vs. 35.0%, the total hospitalization time (days): 13.05±8.44 vs. 18.30±9.59, both P > 0.05]. ④ Patients were divided into death and survival groups according to the prognosis, and univariate analysis showed that white blood cell (WBC), neutrophil percentage (NEU%), CRP, lactic acid (Lac), APACHEⅡ score, IL-6, HBP were the factors influencing the prognosis of patients. The above indicators were further analyzed by Logistic regression, which showed that CRP, IL-6, and APACHE Ⅱ score were independent risk factors for prognosis [odds ratio ( OR) was 1.007, 1.828, 1.229, all P < 0.05]. Conclusions:Combined with Xuebijing to treat septic shock can reduce the body's inflammatory response to a certain extent, thereby reducing the time of mechanical ventilation, shortening the stay of ICU and reducing the total cost of hospitalization. But it cannot reduce the 28-day mortality of patients with septic shock.

Objective:To analyze the influencing factors of prognosis of patients with diabetic kidney disease (DKD) in intensive care unit (ICU), and analyze their predictive value.Methods:Based on the inpatient information of more than 50 000 patients from June 2001 to October 2012 in the latest version of American Intensive Care Medical Information Database (MIMIC-Ⅲ v1.4), the data of DKD patients were screened out, including gender, age, body weight, comorbidities [hypertension, coronary heart disease, chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD)], sequential organ failure assessment (SOFA) score, the length of ICU stay, the incidence of mechanical ventilation, vasoactive drugs and renal replacement therapy during the ICU hospitalization, complications of other diseases [ventilator-associated pneumonia (VAP), urinary tract infection (UTI), diabetic ketoacidosis (DKA), acute myocardial infarction (AKI)] and prognosis of ICU. At the same time, the blood routine and biochemical data of the first 24 hours in ICU and the extremum values during the ICU hospitalization were collected. Multivariate Logistic regression analysis was used to screen the prognostic factors of DKD patients in ICU, and receiver operating characteristic (ROC) curve was plotted to analyze the predictive value of death risk factors.Results:416 DKD patients were screened out, 20 patients were excluded due to data missing, and finally 396 patients were enrolled, including 220 survival patients and 176 dead patients. Compared with the survival group, the patients in the death group were older (years old: 57.13±13.04 vs. 52.61±14.15), with lower rates of hypertension and CKD (11.4% vs. 23.6%, 26.7% vs. 41.4%), higher SOFA scores and baseline values of blood urea nitrogen (BUN), serum creatinine (SCr) and blood K + [SOFA score: 5.86±2.79 vs. 4.49±2.56, BUN (mmol/L): 18.4±10.0 vs. 14.8±9.0, SCr (μmol/L): 387.2±382.8 vs. 284.6±244.9, K + (mmol/L): 4.64±0.99 vs. 4.33±0.86], and longer ICU stay [days: 2.65 (1.48, 5.21) vs. 2.00 (1.00, 4.00)], and the differences were statistically significant (all P < 0.01). Further analysis of laboratory tests extremum values during ICU hospitalization showed that the maximum (max) and minimum (min) values of white blood cell (WBC), BUN and SCr, and K +max in the death group were significantly higher than those in the survival group [WBC max (×10 9/L): 17.3±10.3 vs. 14.5±7.3, WBC min (×10 9/L): 7.9±4.1 vs. 6.7±2.7, BUN max (mmol/L): 23.8±10.4 vs. 18.8±10.2, BUN min (mmol/L): 11.0±6.6 vs. 9.3±6.6, SCr max (μmol/L): 459.7±392.5 vs. 350.1±294.4, SCr min (μmol/L): 246.6±180.3 vs. 206.9±195.4, K +max (mmol/L): 5.35±0.93 vs. 5.09±0.99], and the minimum values of hemoglobin (Hb min) and glucose (Glu min) were significantly lower than those in the survival group [Hb min (g/L): 87.4±14.5 vs. 90.6±16.5, Glu min (mmol/L): 4.0±1.7 vs. 4.6±2.0], and the differences were statistically significant (all P < 0.05). The incidences of mechanical ventilation and vasoactive drugs during ICU hospitalization in the death group were significantly higher than those in the survival group (37.5% vs. 24.1%, 32.4% vs. 20.0%, both P < 0.01), and the incidences of UTI and AMI in the death group were significantly higher than those in the survival group (29.5% vs. 19.1%, 8.5% vs. 3.6%, both P < 0.05). Multivariate Logistic regression analysis showed that age [odds ratio ( OR) = 1.019, 95% confidence interval (95% CI) was 1.003-1.036, P = 0.023], SOFA score ( OR = 1.142, 95% CI was 1.105-1.246, P = 0.003), WBC min ( OR = 1.134, 95% CI was 1.054-1.221, P = 0.001) and BUN max ( OR = 1.010, 95% CI was 1.002-1.018, P = 0.018) were risk factors of death of DKD patients in ICU. ROC curve analysis showed that the area under ROC curve (AUC) of combination of risks factors of death was 0.706, the sensitivity was 61.6%, and the specificity was 73.2%. Conclusions:In order to prevent DKD patients from getting worse in ICU, we should pay close attention to the blood biochemical indexes, especially the renal function indexes, and give timely treatment. At the same time, we should actively prevent the occurrence of complications such as infection and cardiovascular disease.