Main outcome and patient selection
The main outcome of the study was the difference between Cp and Cm around the maintenance concentration of propofol in surgery, which was evaluated using percentage performance error (PE) as follows: PE (%) = (Cm - Cp)/Cp × 100.
We included patients aged ≥ 20 years, underwent anesthesia (expected anesthesia time ≥ 4 h) in spine and lateral positions by administration of propofol by TCI, and monitored with direct arterial blood pressure. We excluded those with anemia (hemoglobin < 10 g/dl), liver dysfunction (Child-Pugh B or C), renal dysfunction (eGFR < 30 ml/min/1.73m2), American Society of Anesthesiologists-physical status (ASA-PS) class III/IV, hepatic or renal surgery, and psychoneurotic disorders or psychiatric pharmacotherapy.
Of 70 eligible patients, we excluded one outlier of 39-year-old woman with a great discrepancy in Cp and Cm (PE = 267.9%) due to a possible technical error; 69 patients (48 men and 21 women) comprised the study subject. A prior analysis included the excluded patient showed the similar trend (data not shown).
Measurement of propofol concentration and clinical parameters
Anesthesia was induced and maintained with continuous infusion of remifentanil and propofol. A propofol TCI system (TE-371, TERUMO, Tokyo, Japan) was used to administer propofol. The infusion rates of propofol and remifentanil were adjusted by the anesthesiologists in charge according to the patients’ condition. Direct arterial blood pressure, heart rate (HR), ECG, SpO2, central core temperature, and end tidal CO2 were recorded throughout all operations. Bispectral index (BIS, QE-910P, Nihon Kohden, Tokyo, Japan) were applied unless it did not disturb the procedure of the surgeries.
Blood samples were collected from the radial artery at 4 h after initial propofol infusion after matching predicted blood concentration and effect-site concentration displayed on the TCI devices. When the duration of propofol infusion was < 4 h, the sample was collected before changing the target blood concentration. Mean blood pressure (mBP) and HR were recorded at the time of sample collection. Total volume of intravenous fluid was measured from initial propofol infusion to blood sample collection. Blood samples were used for gene polymorphism analysis and measurement of plasma propofol concentration. Although the time of blood pressure before blood sample collection might affect the concentration of propofol, a prior analysis using blood pressure of 10 min before blood sampling showed the same results (data not shown).
The plasma concentration of propofol was determined by a modified method of a previous report [25] by a commercial laboratory, BML, Inc. (Tokyo, Japan), using a reverse phase high-performance liquid chromatography system (Hitachi High-Technologies Corporation, Tokyo, Japan, and Shimadzu Corporation, Kyoto, Japan) with a Hypersil C18 reversed-phase column (3 μm particle size, 100 × 5.0 mm I.D.). The excitation and emission wavelength were 276 and 310 nm, respectively. Blood samples were centrifuged (1150 g for 10 min) and stored at 4 °C. A calibration graph was created by plotting the ratios of the areas for propofol to those for thymol (internal standard) from 0.2 to 5 μg/ml. The limit of quantitation was 0.1 μg/ml.
Genotyping
Genomic DNA was extracted from peripheral blood with a DNA isolation kit (GenTLE; Takara Bio, Ohtsu, Japan). Genotyping of CYP2B6 499 C > G (rs3826711), 785 A > G (rs2279343), 1375 A > G, and 1459 C > T (rs3211371) was performed by polymerase chain reaction with restriction fragment length polymorphism method. CYP2B6 516 G > T (rs3745274), UGT1A9 i399C > T (rs2741049), and 766 G > A (rs58597806) SNPs were identified by validated TaqMan SNP Genotyping Assays (assay ID: C_7817765_60, C_34816143_20, and C_9096281_10, respectively) (Life Technologies, Carlsbad, California, USA) using an ABI 7500 Real-Time PCR system (Life Technologies) and TaqMan®Universal Master Mix II with UNG (Life Technologies) according to the manufacturer’s instruction. CYP2B6 and UGT1A9 genotypes were determined by an investigator blinded to individual information. The observed allelic frequencies conformed to Hardy-Weinberg equilibrium (data not shown).
Statistical analysis
To assess the contribution of sex and polymorphisms for PE separately, crude regression coefficients (β) and 95% confidence intervals (CI) of female sex and CYP2B6 516G > T polymorphisms were, respectively, estimated with linear regression (model 1). In addition, we minimally adjusted for baseline characteristics (age and BMI) in model 2 and fully adjusted for baseline characteristics (age and BMI) and clinical factors (mBP, HR, volume of intravenous fluid, surgical site, head down position, pneumoperitoneum) in model 3. Those covariates were adjusted as mediators for the association; other clinical factors, such as BIS scores and body temperature, were not included for covariates because those did not affect sex differences of PE in a prior analysis (Additional file 1: Table S1).
In mutual adjusted models, we included explanatory variables of female sex and CYP2B6 516G > T polymorphisms simultaneously (model 4). Additionally, we minimally adjusted for baseline characteristics (model 5) and fully adjusted for baseline characteristics and clinical factors (model 6). In the mutual adjusted models, due to the lack of female patients with CYP2B6 516TT polymorphisms, we excluded three male patients with CYP2B6 516TT polymorphisms.
Alpha was set at 0.05, and all p values were two-sided. Data were analyzed using JMP Pro 11.0.0 (SAS Institute Inc., Tokyo, Japan).