Zhongguo wei zhong bing ji jiu yi xue = Chinese critical care medicine = Zhongguo weizhongbing jijiuyixue最新文献

Objective: To explore the regularity of changes in total adiponectin (APN) and high molecular bodyweight adiponectin (HAP) in sepsis, and its correlation with infection and its role on predicting prognosis.

Methods: A prospective study was conducted. Eighty patients with sepsis in intensive care unit (ICU) of Shengjing Hospital of China Medicine University from June to November in 2011 were enrolled in this study. The plasma APN (both total APN and HAP), procalcitonin (PCT), and endotoxin were determined with enzyme linked immunosorbent assay (ELISA) at 2 hours, 2 days, and 6 days after ICU admission. The acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), and simplified acute physiology score II (SAPS II) scores were recorded, and insulin resistance index was calculated. Twenty healthy volunteers and 21 patients with systemic inflammation response syndrome (SIRS) were enrolled as controls and SIRS group.

Results: Plasma total APN and HAP in sepsis patients at 2 hours after ICU admission were significantly decreased compared with control group and SIRS group [total APN: 2.87 (2.28, 3.89) mg/L vs. 6.48±1.53 mg/L, 3.72 (2.67, 4.59) mg/L; HAP: 2.64 (2.07, 3.75) mg/L vs. 5.12±1.98 mg/L, 3.33 (2.23, 4.24) mg/L, P<0.05 or P<0.01]. A negative correlation was found between total APN and HAP in plasma and PCT (total APN r=-0.559, HAP r=-0.530, both P<0.01), but no correlation with endotoxin. Those correlations remained significantly in partial correlation analysis controlled by insulin resistance status. There were significances in APN among sepsis, severe sepsis and septic shock groups, and negative correlations were found between APN and APACHE II, SOFA, and SAPS II scores (total APN r value, -0.868, -0.766, -0.725; HAP r value, -0.859, -0.715, -0.692, all P<0.01). Total APN and HAP in plasma of survivors with sepsis (n=41) was gradually increased following the recovery of the disease (total APN χ(2)=34.520, HAP χ(2)=27.802, both P<0.01) and the level in non-survivors (n=7) was decreased (total APN χ(2)=3.938, HAP χ(2)=3.938, both P>0.05). The significantly negative correlations were found between total APN and HAP at 2 hours after ICU admission and ICU duration (total APN r=-0.275, P=0.014; HAP r=-0.299, P=0.007) and ventilation time (total APN r=-0.393, HAP r=-0.519, both P<0.01).

Conclusions: Plasma total APN and HAP was decreased in septic patients, and negatively correlated with PCT. Plasma total APN and HAP played a role in diagnosis of infection and predicting the outcomes, and correlated with severity of sepsis.

Objective: To investigate diagnostic value of creatinine clearance rate (CCr) based on serum cystatin C (SCys C) in acute kidney injury (AKI), and whether it could predict the need for renal replacement therapy (RRT).

Methods: The patients enrolled with the length of intensive care unit (ICU) stay over 3 days were collected from August 2010 to May 2011. According to the diagnosis of AKI during the ICU stay, patients were divided into the AKI group (n=21) and non-AKI group (n=30). After patients were admitted, the level of SCys C and creatinine (SCr) were measured so as to count CCr based on SCys C (SCys C-CCr) or on SCr (SCr-CCr) respectively, meanwhile urine volume and acute physiology and chronic health evaluation II (APACHE II) score were monitored. The value of CCr counted by SCys C and SCr on predict AKI and the correlations between RRT were compared.

Results: SCr-CCr and SCys C-CCr in AKI group both were significantly lower than non-AKI group all the way through on admission, and 2 days and 1 day before AKI diagnosed and the day AKI diagnosed. The level of SCys C-CCr on 2 days prior to AKI diagnosed was significantly lower than the day admitted (70.6±8.4 ml×min(-1)×1.73 m(-2) vs. 114.8±15.8 ml×min(-1)×1.73 m(-2), P<0.01), whereas the level of SCr-CCr were not significantly changed (76.4±19.3 ml×min(-1)×1.73 m(-2) vs. 78.7±22.1 ml×min(-1)×1.73 m(-2), P>0.05). Receptor operative curve (ROC) analysis indicated that SCys C-CCr could predict AKI earlier than SCr-CCr, as the area under curve (AUC) of SCys C-CCr and SCr-CCr on 2 days prior to AKI diagnosed were 0.859 and 0.664, respectively, and the sensitivity were 90.5% and 47.6%, the specificity were 76.2% and 81.0%. In AKI group 6 patients were treated with RRT, the AKI patients receiving RRT had significantly higher APACHE II score on admission (29.6±4.5 vs. 17.0±5.6, P<0.05) and less urine volume within 24 hours (740±465 ml vs. 1780±1230 ml, P<0.05) than patients not received RRT, however, SCys C-CCr has no significant difference between the sub-group (50.4±11.2 ml×min(-1)×1.73 m(-2) vs. 53.0±8.4 ml×min(-1)×1.73 m(-2), P>0.05). SCys C-CCr did not predict the need of RRT on the day to diagnose AKI (AUC=0.65).

Conclusions: The sensitivity of SCys C-CCr were high, but its specificity not. The SCys C-CCr may be helpful for excluding diagnose of AKI in high risk patients. However, it could not predict the need for renal replacement therapy on the day AKI diagnosed.

Objective: To probe the clinical value of estimated glomerular filtration rate (GFR) formulas for adults Chinese based on the serum cystatin C(SCys C, SCysCAC).

Methods: GFRs for 96 cases of patient in hospital suffering from the kidney diseases without dialysis from January to December in 2011 were measured using clearance rate of (99m) Tc-diethylene triamine pentaacetic acid ((99m) Tc- DTPA, Tc-GFR) by prospective control study method. Based on the renal function, 96 patients were sorted into renal function insufficient group (RFI, n=54) and renal function normal group (RFN, n=42). The SCys C, serum creatinine (SCr) and blood urea nitrogen (BUN) were measured at the same day for calculating GFRs simultaneously by nine formulas such as SCysCAC, Arnal-Dade, Grubb, Filler, Grubb, Hojs, Larsson, Macisaac, Rule etc. The comparison were performed for the estimated GFRs (eGFRs) of renal insufficiency patients and those with normal renal function and the correlation analysis were done between the calculations and Tc-GFR respectively.

Results: eGFRs calculated by SCysCAC, Arnal-Dade, Larsson and Rule formulae always were close to those of Tc-GFR and that were 37.96±32.65 ml×min(-1)×1.73 m(-2), 33.69±25.24 ml×min(-1)×1.73 m(-2), 34.16±33.65 ml×min(-1)×1.73 m(-2), 33.02±30.88 ml×min(-1)×1.73 m(-2) vs. 36.21±31.16 ml×min(-1)×1.73 m(-2) in RFI group, 112.99±39.26 ml×min(-1)×1.73 m(-2), 101.86±72.29 ml×min(-1)×1.73 m(-2), 102.69±71.78 ml×min(-1)×1.73 m(-2), 99.12±69.54 ml×min(-1)×1.73 m(-2) vs. 110.54±48.98 ml×min(-1)×1.73 m(-2) in RFN group (all P>0.05). The absolute value difference between eGFR by SCysCAC, Larsson and Arnal-Dade formulae and Tc-GFR in RFN or RFI group showed no significant change and the absolute value of the value difference between SCysCAC-eGFR and Tc-GFR was the least among the three absolute values and showed that eGFRs from the three formulas could all reflect the GFR accurately and the SCysCAC formula was the best. The correlation analysis showed the eGFRs from every formula could all to some extent reflect the glomerular function or GFR accurately.

Conclusion: The SCysCAC formula was a quickly and accurate method for estimating GFR and may apply clinically.

Objective: To explore the relationship between the levels and variability of blood glucose and the prognosis of critical patients.

Methods: A prospective study was conducted. Blood glucose monitoring and prognosis observation were performed for the adult nondiabetic patients admitted in intensive care unit (ICU) from June 2011 to January 2012. Blood glucose monitoring terminal was 72 hours after admitting in ICU, prognosis was observed for 28 days after the end of turning into ICU. Acute physiology and chronic health evaluation II(APACHE II) scores when transferred into ICU and blood glucose variability [standard deviation (SD) of blood glucose, mean absolute blood glucose fluctuation amplitude (MAGE) and glycemic instability index (GLI)] were calculated. Patients were divided into death group and survival group according to the outcome, and the APACHE II score, mean blood glucose and blood glucose variability were compared between the two groups. Patients were divided into different groups based on the blood glucose, and the APACHE II score, blood glucose variability and 28-day mortality were compared among groups.

Results: Total 85 cases were enrolled. Compared with survivor group (n=58), in death group (n=27), APACHE II score (28.9±6.6 vs. 23.8±5.9), mean blood glucose (11.9±2.9 mmol/L vs. 9.4±1.8 mmol/L), SD of blood glucose (3.7±1.6 mmol/L vs. 2.4±1.0 mmol/L), MAGE (0.86±0.46 mmol/L vs. 0.54±0.25 mmol/L) and GLI (255.9±232.7 vs. 111.7±110.9) were increased (all P<0.05). SD of blood glucose (4.3±1.4 mmol/L), MAGE (1.1±0.4 mmol/L), GLI (345.3±210.3) and 28-day mortality (63.6%) in blood glucose >11.1 mmol/L group (n=22) were higher than those in ≤11.1 mmol/L group (n=63, 2.3±0.9 mmol/L, 0.5±0.2 mmol/L, 91.9±91.2, 20.6%, respectively, all P<0.05) and 7.8-11.1 mmol/L group (n=52, 2.3±0.9 mmol/L, 0.5±0.2 mmol/L, 85.2±66.4, 25.0%, respectively, all P<0.05). There were no significant differences between 7.8-11.1 mmol/L group and <7.8 mmol/L group (n=11) in SD of blood glucose (2.0±0.9 mmol/L), MAGE (0.5±0.3 mmol/L), GLI (123.8±166.7) and 28-day mortality (0, all P>0.05).

Conclusion: Blood glucose variability is associated with critical patient's 28-day mortality, and may predict mortality as good as APACHE II score.

Objective: To construct the short hairpin RNA (shRNA) targeting high mobility group box-1 (HMGB1) and culture the stable human umbilical vein endothelial cell (HUVEC) line expressing this shRNA.

Methods: Based on the HMGB1 gene sequence, shRNA was designed, synthesized and subcloned into the pRNA-u6.1/Neo vector, while negative controls were also established. Then the recombinant vector was transfected into HUVEC cell line and the cell was screened with G418 and assayed by using real time reverse transcription-polymerase chain reaction (RT-PCR) and Western blotting.

Results: Restriction endonuclease digestion test and sequencing verification showed that the recombinant pRNA-u6.1/Neo vector expressing this shRNA targeting HMGB1 was successfully constructed and the stable HUVEC cell line expressing this shRNA was developed. The real time RT-PCR and Western blotting was used to detect that recombinant plasmid in HUVEC cell effect on expression of HMGB1 was reduced. (mRNA: 0.4635 ± 0.0342 vs. 1.0340 ± 0.0352, protein: 0.4510 ± 0.0200 vs. 1.0210 ± 0.0110, both P<0.05).

Conclusion: The recombinant pRNA-u6.1/Neo vector expressing shRNA targeting HMGB1 was successfully constructed and the stable HUVEC cell line expressing this shRNA was developed, and therefore allowed further investigation regarding the function of HMGB1 gene in the HUVEC cell line.