RESUMO
Objective To study the effect of dexmedetomidine (DEX) on postoperative cognitive function and preoperative inflammation in the elderly patients undergoing general anesthesia. Methods 70 elderly patients undergoing general anesthesia operation were chosen and divided into observation group and control group randomly. DEX and physiological saline were applied in observation group on the basis of routine general anesthesia. The cognitive function of patients in both groups were tested by mini-mental state examination (MMSE) and the incidence rate of cognitive dysfunction (POCD) were measured at 1 day before surgery, 1 day, 3 days, 5 days, and 7 days after surgery. The level of interleukin-6 (IL-6) and tumor necrosis factor-α(TNF-α) were tested before anesthesia, during skin incision, rightly after operation and 1h after operation. Results MMSE scores were significantly higher and the incident rates of POCD were lower in observation group than those in control group at 1 day and 3 days after surgery (P<0.05). The levels of IL-6 and TNF-αincreased obviously during skin incision and postoperative period, and they were significantly lower in observation group (P<0.05). The levels of IL-6 and TNF-αdecreased to the levels before anesthesia in observation group, and were still much higher in control group than that of preanesthesia (P < 0.05). Conclusions DEX infusion intraoperatively may effectively decrease the incidence of early POCD, whose mechanism could be reducing inflammation response.
RESUMO
Objective To innovate an early, rapid and efficient approach to the pmgnestic evaluation of sep-sis in order to lower the mortality. Method Forty-five septic rats, induced by cecal ligation and puncture, were divided into surviving group (n=23) and non-survival group (n=22) on six days after onset of sepsis. Serum samples were taken from septic and sham-operated rats (n=25) at 12 hours after surgery. HPLC/MS assays were performed to acquire the serum metabolic profiles, and radial basis function neural network (RBFNN) was em-ployed to build predictive model for prognostic evaluation of sepsis. Results The principal component analysis al-lows differentiating the rots of survive,non-survive and sham-operated from one another in respect of the pathologic characteristics. Six metabolites, linolenic acid, linoleic acid, oleic acid, stearic acid, docosahexaenoic acid and do-cosapentaenoic acid, related to the outcomes of septic rats were then structurally identified. A RBFNN model for outcome predication was built based upon the metabolic profile data from rat sera with the sensitivity of (96.1 ±3.6)% (n=10) and specificity of (91.0±4.3)% (n=10). Condusions HPLC/MS-based metabonomic approach combined with pattern recognition permits accurate outcome prediction of septic rats in the early stage. The proposed approach has advantages of rapid, low-cost and efficiency, and is isph-ing to be applied in clinical prognostic evaluation of septic patients.