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Medical Psychotropics in Forensic Autopsies in European Countries: Results from a Three-Year Retrospective Study in Spain.

Maira Almeida-GonzálezLuis D BoadaLuis Alberto Henríquez-HernándezOctavio P LuzardoEnrique ZaragozaGuillermo Burillo PutzeMaría Del Pino QuintanaManuel Zumbado
Published in: Toxics (2022)
Medical psychotropics are widely used and prescribed in developed countries. These medications may have an impairing effect on mood or perception and may induce harmful behaviors. Nevertheless, in Europe, studies on their importance from a medico-legal perspective are scarce. To fill this gap, we evaluate the determinants of these drugs in a retrospective study based on data obtained from forensic autopsies. Toxicological analyses were performed on 394 blood samples from compulsory autopsies at the Institute of Legal Medicine of Las Palmas. Of the samples, 41% (159) were positive for at least one psychotropic, with benzodiazepines being the most frequently detected (24.1%), followed by opiates and antidepressants. Benzodiazepines, opiates, and antidepressants were detected more frequently in men who suffered a violent death. More than 30% of the positive samples showed two or more drugs, suggesting a prevalence of polypharmacy among forensic autopsy subjects, with the most frequently combination found being benzodiazepines plus opiates (28.3% of positive samples). A combination of opiates plus antidepressants was also found in subjects involved in violent deaths. Our results suggest that more than 40% of the adult European population involved in medico-legal issues may be under the influence of legal psychotropics. The link between violent deaths and the use of medical psychotropics is particularly worrisome and indicates that these drugs should be carefully monitored in developed countries, in all forensic autopsies, in a similar way to illegal psychotropics.
Keyphrases
  • major depressive disorder
  • healthcare
  • bipolar disorder
  • machine learning
  • big data
  • drug induced
  • depressive symptoms
  • deep learning
  • middle aged
  • artificial intelligence