Objective To study the age-dependent relationship between body mass index(BMI)and cognitive impairment in rural population aged 40 years and above.Methods From October 2014 to March 2015,people aged 40 years and above,who lived in two natural villages in Huyi District of Xi'an,were selected as the research subjects.Their general demographic information,lifestyle,medical history,family history,physical examination,and biochemical examination were collected.Mini-Mental State Examination(MMSE)was used to evaluate global cognitive function.Cognitive impairment was defined as an MMSE score lower than the cutoff value,specifically,scores ≤17 for subjects who were illiterate,scores ≤20 for subjects with primary school education,and scores ≤24 for subjects with junior high school education or above.The age-dependent relationship between BMI and cognitive impairment was discussed using stratified analysis,restricted cubic spline(RCS),and multivariate Logistic regression.Results We included a total of 1 792 subjects in the analysis,of whom 230(12.8％)were diagnosed with cognitive impairment.There were 726 males(40.5％);the average age was(55.53±9.92)years,ranging from 40 to 85 years,1 193 subjects aged 40-59 years(66.6％),and 599 subjects aged ≥60 years(33.4％).The average BMI was(25.29±3.14)kg/m2.In the total population,BMI index was fitted as restricted cubic splines in the Logistic regression model,and other confounding factors were corrected.The results showed that BMI index was significantly correlated with cognitive impairment(Poverall=0.023),and there was a trend of nonlinear relationship(P nonlinear=0.097).The specific relationship was that with BMI=25 kg/m2 as the reference(OR=1),when BMI index was＜25 kg/m2,the OR value increased as BMI index decreased.However,when BMI index was ≥25 kg/m2,the OR value did not change significantly as BMI index increased.The population was divided into two subgroups according to age(40-59 years vs.≥60 years).Stratified analysis showed that in the ≥60 years old subgroup,cognitive impairment had significant correlation with BMI index(Poverall=0.038,Pnonlinear=0.097),and the changing trend of the correlation was similar to that of the overall population.By contrast,in the 40-59 years old subgroup,BMI index was not significantly associated with cognitive impairment(Poverall=0.722,Pnonlinear=0.738).Conclusion The relationship between BMI and cognitive impairment is affected by age.No significant association is found in the middle-aged population of 40-59 years old,but there may be a nonlinear association in the elderly population over 60 years old.Specifically,with BMI=25 kg/m2 as the boundary,as BMI decreases,the risk of cognitive impairment gradually increases.As BMI further increases,the risk of cognitive impairment does not change significantly even though it reaches the obesity level.

Objective To study the age-dependent relationship between body mass index(BMI)and cognitive impairment in rural population aged 40 years and above.Methods From October 2014 to March 2015,people aged 40 years and above,who lived in two natural villages in Huyi District of Xi'an,were selected as the research subjects.Their general demographic information,lifestyle,medical history,family history,physical examination,and biochemical examination were collected.Mini-Mental State Examination(MMSE)was used to evaluate global cognitive function.Cognitive impairment was defined as an MMSE score lower than the cutoff value,specifically,scores ≤17 for subjects who were illiterate,scores ≤20 for subjects with primary school education,and scores ≤24 for subjects with junior high school education or above.The age-dependent relationship between BMI and cognitive impairment was discussed using stratified analysis,restricted cubic spline(RCS),and multivariate Logistic regression.Results We included a total of 1 792 subjects in the analysis,of whom 230(12.8％)were diagnosed with cognitive impairment.There were 726 males(40.5％);the average age was(55.53±9.92)years,ranging from 40 to 85 years,1 193 subjects aged 40-59 years(66.6％),and 599 subjects aged ≥60 years(33.4％).The average BMI was(25.29±3.14)kg/m2.In the total population,BMI index was fitted as restricted cubic splines in the Logistic regression model,and other confounding factors were corrected.The results showed that BMI index was significantly correlated with cognitive impairment(Poverall=0.023),and there was a trend of nonlinear relationship(P nonlinear=0.097).The specific relationship was that with BMI=25 kg/m2 as the reference(OR=1),when BMI index was＜25 kg/m2,the OR value increased as BMI index decreased.However,when BMI index was ≥25 kg/m2,the OR value did not change significantly as BMI index increased.The population was divided into two subgroups according to age(40-59 years vs.≥60 years).Stratified analysis showed that in the ≥60 years old subgroup,cognitive impairment had significant correlation with BMI index(Poverall=0.038,Pnonlinear=0.097),and the changing trend of the correlation was similar to that of the overall population.By contrast,in the 40-59 years old subgroup,BMI index was not significantly associated with cognitive impairment(Poverall=0.722,Pnonlinear=0.738).Conclusion The relationship between BMI and cognitive impairment is affected by age.No significant association is found in the middle-aged population of 40-59 years old,but there may be a nonlinear association in the elderly population over 60 years old.Specifically,with BMI=25 kg/m2 as the boundary,as BMI decreases,the risk of cognitive impairment gradually increases.As BMI further increases,the risk of cognitive impairment does not change significantly even though it reaches the obesity level.

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 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 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 investigate the effect of liver X receptor(LXR)-adenosine triphosphate-binding cassette transporter A1(ABCA1) signaling pathway on the free silica(SiO_2)-induced foaming of macrophages. METHODS: Human histiocytic lymphoma U937 cells were induced to differentiate into macrophages by phorbol myristate acetate. The macrophages at logarithmic growth phase were randomly divided into 4 groups: the cells in the control group received no treatment, the cells in the SiO_2 stimulation group were stimulated with SiO_2 suspension at a dose of 50 mg/L, and the cells in the oxidized low-density lipoprotein(ox-LDL) group were treated with ox-LDL at the dosed 50 mg/L, the cells in the combination group were simultaneously stimulated with SiO_2 suspension and ox-LDL at a dose of 50 mg/L. Cells were collected after 48 hours of culture. Macrophage foaming was observed by oil red O staining. The levels of total cholesterol(TC), free cholesterol(FC), cholesteryl ester(CE) and CE specific gravity(CE%) in macrophages were detected using a microplate reader. The expression of LXR and ABCA1 was detected using Western blotting. RESULTS: The results of the oil red O staining showed that all the macrophages in the SiO_2 stimulation group, ox-LDL group and the combination group had foaming changes. The degree of foaming in the macrophages in the combination group was higher than that in the other two groups. The levels of TC, FC, CE and CE% in macrophages increased(P<0.05), and the protein relative expression of LXR and ABCA1 decreased(P<0.05), in SiO_2 stimulation group, ox-LDL group and combination group compared with the control group. The macrophages in the combination group were transformed into foam cells. The levels of TC, FC, CE and CE% in macrophages of the combination group increased(P<0.05), and the protein relative expression of LXR and ABCA1 decreased(P<0.05), compared with the SiO_2 stimulation group and the ox-LDL group. CONCLUSION:sFree SiO_2 can induce foaming of macrophages, and ox-LDL in combination with SiO_2 has a synergistic effect on the formation of foaming of macrophages.The process of macrophage foaming may be achieved by inhibiting the LXR-ABCA1 signaling pathway.