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Abstract: Background: The effect of opioids on inflammation and immune responses is an important subject of investigation because immunoregulatory cytokines are produced in the central nervous system and opioid receptors are widespread in these cells. Objectives: The aim of this study was to evaluate the immunomodulatory effect of morphine on the C3 expression (both constitutive and proinflammatory cytokine-induced C3 expression) in primary rat astrocytes. Methods: Primary rat astrocytes were untreated or treated with morphine in different concentrations (10–6 to 10–2 M) before incubation without or with 5 U/mL tumor necrosis factor-α (TNF-α), and C3 protein and mRNA expressions were measured. Similarly, astrocytes were treated with 10–3 M morphine and stimulated with other proinflammatory cytokines, including 10 ng/mL interleukin-8 (IL-8) and 5 U/mL IL-1β. Astrocytes were exposed to 10–5 M naloxone for 2 hours before adding morphine, and TNF-α and C3 protein was measured. Tumor growth factor-β (TGF-β) was measured from the supernatants of each proinflammatory cytokine. Results: All results are expressed as mean percentages of C3 production by normalizing C3 without morphine or any cytokine treatment as 100%. Constitutive C3 protein production was decreased at morphine 10–3 M (57.2%) and 10–2 M (30.1%). Pretreatment with morphine suppressed induction of C3 expression at both the protein and mRNA levels in astrocytes stimulated with TNF-α, IL-8, and IL-1β (P < 0.05) in a dose-dependent manner. The inhibition of C3 protein production by morphine (10–3 M; 33%) was partially attenuated by naloxone (52.0%) (P < 0.05). The pretreatment of astrocytes with morphine (10–3 M) before stimulation with TNF-α, IL-8, and IL-1β increased by 33% (P < 0.05), decreased by 15.2% (P < 0.05), and did not change the production of TGF-β protein, respectively. Conclusions: Morphine downregulated both constitutive and proinflammatory cytokine-induced C3 expression of astrocytes at the transcriptional level, but not in a cytokine-specific manner. [Copyright &y& Elsevier]

It was previously reported that the Korean predictive model could be used to identify patients at high risk of postoperative nausea and vomiting (PONV). This study investigated whether PONV in the high-risk and very high-risk patients identified by the Korean predictive model could be prevented by multiple prophylactic antiemetics. A total of 2,456 patients were selected from our previous PONV study and assigned to the control group, and 374 new patients were recruited consecutively to the treatment group. Patients in each group were subdivided into two risk groups according to the Korean predictive model: high-risk group and very high-risk group. Patients in the treatment group received an antiemetic combination of dexamethasone 5 mg (minutes after induction) and ondansetron 4 mg (30 min before the end of surgery). The incidences of PONV were examined at two hours after the surgery in the postanesthetic care unit and, additionally, at 24 hr after the surgery in the ward, and were analyzed for any differences between the control and treatment groups. The overall incidence of PONV decreased significantly from 52.1% to 23.0% (p< or =0.001) after antiemetic prophylaxis. Specifically, the incidence decreased from 47.3% to 19.4% (p< or =0.001) in the high-risk group and from 61.3% to 28.3% (p< or =0.001) in the very high-risk group. Both groups showed a similar degree of relative risk reductions: 59.0% vs. 53.8% in the high-risk and very high-risk groups, respectively. The results of our study showed that the antiemetic prophylaxis with the combination of dexamethasone and ondansetron was effective in reducing the occurrence of PONV in both high-risk and very high-risk patients.

Postoperative nausea and vomiting (PONV) is one of the most common and distressing complications after surgery. An identification of risk factors associated with PONV would make it easier to select specific patients for effective antiemetic therapy. We designed a case-controlled study to identify the risk factors for PONV in 5,272 surgical patients. At postoperative 2 and 24 hr, patients were visited and interviewed on the presence and severity of PONV. Thirty nine percent of patients experienced one or more episodes of nausea or vomiting. Five risk factors were highly predictive of PONV: 1) female, 2) history of previous PONV or motion sickness, 3) duration of anesthesia more than 1 hour, 4) non-smoking status, and 5) use of opioid in the form of patient controlled analgesia (PCA), in the order of relevance. The formula to calculate the probability of PONV using the multiple regression analysis was as follows: P (probability of PONV)=1/1+e(-Z), Z=-1.885+0.894 (gender)+0.661 (history)+0.584 (duration of anesthesia)+0.196 (smoking status)+0.186 (use of PCA-based opioid) where gender: female=1, male=0; history of previous PONV or motion sickness: yes=1, no=0; duration of anesthesia:more than 1 hr=1, less than or 1 hr=0; smoking status: no=1, yes=0; use of PCA-based opioid: yes=1, no=0.