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Validation of a HS–GC–FID Method for the Quantification of Sevoflurane in the Blood, Urine, Brain and Lungs for Forensic Purposes

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  • معلومة اضافية
    • بيانات النشر:
      Multidisciplinary Digital Publishing Institute
    • الموضوع:
      2023
    • Collection:
      MDPI Open Access Publishing
    • نبذة مختصرة :
      Background: Sevoflurane is a polyfluorinated compound extensively used as an inhalation anesthetic in patients undergoing surgery. If administered outside the operating room, sevoflurane is dangerous and potentially lethal, and toxicologists may be asked to investigate its presence in biological matrices for forensic purposes. The aim of the present study is to develop and validate a method for the detection and the quantification of sevoflurane in biological fluids and organs through gas chromatography coupled to flame ionization detection (GC–FID). Methods: The method was optimized based on the maximization of the signal-to-noise ratio. The GC–FID instrument was equipped with a Zebron capillary column ZB-624 (30 m, 0.32 mm ID, 1.80 µm film thickness). Results: The method was validated over a concentration range of 1.0–304.0 µg/mL (blood and urine) and µg/g (brain, lungs). The lower limit of quantitation was 1.0 µg/mL or µg/g. Both the intra- and interassay imprecision and inaccuracy were ≤15% at all quality control concentrations in all the matrices. The method was successfully applied to measure the sevoflurane concentrations for 20 negative controls and for a real forensic case. Conclusions: The present method is suitable for the identification and quantification of sevoflurane in fluids and organs and can be a reliable tool in forensic casework.
    • File Description:
      application/pdf
    • Relation:
      Analytical Methods, Instrumentation and Miniaturization; https://dx.doi.org/10.3390/chemosensors11020133
    • الرقم المعرف:
      10.3390/chemosensors11020133
    • الدخول الالكتروني :
      https://doi.org/10.3390/chemosensors11020133
    • Rights:
      https://creativecommons.org/licenses/by/4.0/
    • الرقم المعرف:
      edsbas.65D59223