
doi: 10.1002/mas.21784
pmid: 35603997
AbstractIn the emergency department, it is important to rapidly identify the toxic substances that have led to acute poisoning because different toxicants or toxins cause poisoning through different mechanisms, requiring disparate therapeutic strategies and precautions against contraindicating actions, and diverse directions of clinical course monitoring and prediction of prognosis. Ambient ionization mass spectrometry, a state‐of‐the‐art technology, has been proved to be a fast, accurate, and user‐friendly tool for rapidly identifying toxicants like residual pesticides on fruits and vegetables. In view of this, developing an analytical platform that explores the application of such a cutting‐edge technology in a novel direction has been initiated a research program, namely, the rapid identification of toxic substances which might have caused acute poisoning in patients who visit the emergency department and requires an accurate diagnosis for correct clinical decision‐making to bring about corresponding data‐guided management. This review includes (i) a narrative account of the breakthrough in emergency toxicology brought about by the advent of ambient ionization mass spectrometry and (ii) a thorough discussion about the clinical implications and technical limitations of such a promising innovation for promoting toxicological tests from tier two‐level to tier one level.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 9 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
