Researchers analyzed data from 620 patients undergoing myomectomy to remove uterine fibroids. They compared a newer technique called vNOTES to traditional laparoscopic methods. The study looked at several factors, including surgery time, blood loss, and how quickly patients recovered after the procedure.
The results showed that patients who had the vNOTES procedure experienced earlier first flatus, which is a sign of bowel recovery. While the length of stay in the hospital was also shorter for vNOTES patients, the data for this specific finding was inconsistent. Other factors like operative time and blood loss did not show a clear difference between the two methods.
Some safety concerns were noted, including a small number of rectal injuries and infections in the vNOTES group. Because the evidence is based on a small number of events and is not yet definitive, these results are currently used to help experts understand potential risks. More large-scale studies are needed to confirm the long-term safety and effectiveness of this technique.
Common questions
What is vNOTES and how does it compare to other surgeries?
vNOTES is a type of surgery used to treat uterine fibroids. In this study, it was compared to multi-port or single-site laparoscopic surgery. While vNOTES showed a trend toward faster bowel recovery, there was no clear difference in total surgery time or the amount of blood lost during the procedure.
Are there any risks associated with vNOTES surgery?
The study reported a small number of rectal injuries (1.15%) and some vaginal or cuff infections in the vNOTES group. Because these events were rare, experts consider them as signals to watch rather than confirmed risks. You should talk to your doctor about the specific risks of any surgical method.
Does vNOTES help patients stay in the hospital for less time?
Patients who underwent vNOTES had a shorter hospital stay on average. However, the researchers noted that this specific finding was inconsistent across different groups. Because the evidence for this is currently considered low-certainty, it is not yet a definitive way to predict recovery time.