Objective To establish a method for the determination of bilirubin in Xihuang capsules.Methods HPLC method was applied and the chromatographic conditions were as follows: Hypersil BDS C18 column(150 mm ? 4.6 mm,5 ?m)with methanol-chloroform-1 % phosphoric acid(84︰9︰7)as the mobile phase.The flow rate was 1.0 mL ? min-1 with the detected wavelength at 450 nm and the column temperature at 25 ℃.Results The calibration curve for bilirubin was linear in the range of 0.01 ~ 0.07 ?g.The average recovery was 98.07 %(RSD = 1.05 %).Conclusion This method is simple,accurate,specific and could be used for the quality control of bilirubin in Xihuang capsules.

OBJECTIVE:To reduce the incidence of irrational medical orders for parenteral nutrition,and promote the rational use of parenteral nutrition. METHODS:The medical orders for parenteral nutrition of the first quarter of 2016 in general surgery de-partment of our hospital were collected,and the number and types of its irrational medical orders were summed up. Then FO-CUS-PDCA(Find-organize-clarify-understand-select-plan-do-check-act)cycle management was adopted to analyze and improve the existing problems in issuing medical orders for parenteral nutrition. The improved(the third quarter of 2016)medical orders for par-enteral nutrition were collected,the number and types of its irrational medical orders were summed up,and management effect was evaluated. RESULTS:Establishing nutrition support group,strengthening the training and communication of medical staff,adding prescription evaluation module for parenteral nutrition in hospital information system and a number of measures had made the inci-dence of irrational medical orders for parenteral nutrition in general surgery department declined from 48.25%(1433/2970)before improvement to 5.67%(120/2118)after improvement. The incidences of cation excess,inappropriate selection of drugs and inap-propriate compatibility in irrational types were 0. CONCLUSIONS:FOCUS-PDCA cycle management can reduce the irrational rate of medical orders for parenteral nutrition and promote the rational use of parenteral nutrition in hospital.

Objective To establish an analytical method combining gas chromatography-tandem mass spectrometry(GC-MS)and liquid chromatography-tandem mass spectrometry(LC-MS)to detect diazepam residue in bait nest materials and fish samples,and improve the pretreatment steps of samples to make the experimental results accurate and the sample processing convenient and fast.Methods Taking diazepam as the research object,samples were extracted with methanol and dichloromethane/n-hexane as solvents according to the type,and the supernatant was taken for detection after centrifugation.Results The diazepam standard sample showed a good linear relationship in the range of 10～10 000 ng/mL.The retention times in methanol and mixed solvent were 13.54 min and 13.83 min,respectively,and the correlation coefficients were 0.998 and 0.999,respectively;The limit of detection(LOD)of using methanol as extraction solvent was 2 ppb,and limit of quantification(LOQ)was 6 ppb.The LOD of using mixed solvents was 5 ppb,and the LOQ was 15 ppb.When the sample is a bait nest material,the GC-MS spectrum was clear and standard,and the peak shape was sharp and prominent;When the sample is biological specimen,the GC-MS spectra are disturbed by matrix,while the LC-MS data is more accurate and faster.Conclusion It is more appropriate to use GC-MS to determine the content of bait nest materialsamples,and it is more accurate to LC-MS to determine the content of fish samples due to the complexity of the organism.

OBJECTIVE： To improve the efficiency and accuracy of checking total parenteral mutrition （TPN） prescription. METHODS： Excel vba technology was used to edit vba code and construct TPN prescription algorithm. The key indicators and standard of TPN prescription checking were determined. Established algorithm was used to check the prescriptions from PIVAS of our hospital in May 2018， results of which was compared with the results of manual checking （using potassium concentration， monovalent cation concentration and alanyl-glutamine combined with amino acid as indexes）. RESULTS： TPN prescription algorithm was established through confirming 17 key indicators as glycolipid ratio， heat-nitrogen ratio， monovalent cation concentration， the checking standard was set as. It took 15 seconds to check 2 638 TPN prescriptions received within one month in PIVAS of our hospital； 449 irrational prescriptions （excessive dose， incompatibility， inappropriate proportion and volume of nutrition） of them and reasons had been marked out. By comparing 3 evaluation indexes， 1， 1， 0 irrational prescriptions were checked by manually and 4， 12， 4 checked by established algorithm， respectively. CONCLUSIONS： TPN prescription algorithm can check prescription in batches based on Excel vba technology， and mark out the substandard prescription automatically. Hereby， it improves the efficiency and accuracy of TPN prescriptions by PIVAS.