Background: Although regional cerebral oxygen saturation (rSO₂) measurements can detect disturbances in cerebral oxygenation, their usefulness is limited in patients with hyperbilirubinemia. We examined the relationship between rSO₂ and other laboratory variables that may affect interpretation of low rSO₂ in awake patients with end-stage liver disease before liver transplantation surgery.
Methods: Before induction of general anesthesia, rSO₂ was measured in 164 patients with liver cirrhosis (Child class A/B/C = 19/41/104) and 8 with fulminant hepatic failure. Patients with West Haven hepatic encephalopathy of grade 3 or 4 were excluded. Relationships between rSO₂ and laboratory variables were evaluated by correlation and multivariate regression, and by receiver operating characteristic curve analysis.
Results: Univariate analyses showed that rSO₂ (median 58.5%, range 15% to 82%) correlated with serum total bilirubin, hemoglobin (Hb), creatinine, sodium, and magnesium concentrations, and prothrombin time (P < 0.001 each), but not with serum concentrations of glucose, albumin, potassium, and ammonia. Multiple logistic regression analysis showed that only elevated total bilirubin (range 0.4 to 66 mg/dL; odds ratio [OR] = 1.31; 95% confidence interval [CI] = 1.18 to 1.45) and low Hb (range 5.3 to 15.7 g/dL; OR = 0.21; 95% CI = 0.11 to 0.43) were independently related to rSO₂ <50%. The optimum cutoff points for observing an rSO₂ < 50% were total bilirubin >7.2 mg/dL (sensitivity 89%, specificity 90%) and Hb <9.6 g/dL (sensitivity 70%, specificity 82%).
Conclusions: High total bilirubin and low Hb concentrations were independently associated with rSO₂ values below 50% in end-stage liver disease patients awaiting liver transplantation. The results of this study identify patients in whom a low rSO₂ may be an artifact rather than cerebral ischemia.
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http://dx.doi.org/10.1213/ANE.0b013e318214b2b0 | DOI Listing |
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Adenosine receptors (A, A, A, A) play critical roles in cellular signaling and are implicated in various physiological and pathological processes, including inflammations and cancer. The main aim of this research was to investigate structure-activity relationships (SAR) to derive models that describe the selectivity and activity of inhibitors targeting Adenosine receptors. Structural information for 16,312 inhibitors was collected from BindingDB and analyzed using machine learning methods.
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