
doi: 10.62486/pc202694
Introduction: fentanyl and remifentanil are synthetic opioids widely used in anesthesia and pain management in surgical settings. However, numerous myths surrounding their clinical use persist, which can compromise patient safety and therapeutic efficacy. The objective of this literature review is to identify, analyze, and compare the most frequent myths about these drugs with the available scientific evidence, with a special emphasis on surgical nursing practice. Method: a narrative and critical literature review was conducted using scientific databases (SciELO, Dialnet, PubMed, The Lancet, Redalyc) with keywords in Spanish and English. Original articles, systematic reviews, clinical trials, and official documents published between 2019 and 2026 were included, resulting in a final selection of 28 references. Results: seven prevalent myths were identified, including: that the medical use of fentanyl inevitably leads to addiction, that remifentanil is inherently safer due to its shorter duration of action, and that the opioid crisis is unique to North America. All were refuted by pharmacological and epidemiological evidence. Conclusions: evidence-based training is essential to demystify the use of these opioids in surgical and critical care settings.
| 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). | 0 | |
| 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. | Average | |
| 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. | Average |
