ObjectiveTo investigate the effect of preoperative gum chewing on the postoperative rehabilitation of patients undergoing gynecologic laparoscopic surgery.MethodsA total of 160 patients undergoing elective gynecologic laparoscopic surgery between January and May 2013 were selected to participate in the study. Each patient was randomly assigned to one of the two groups: the trial group (n=80) or the control group (n=80). Thirty to sixty minutes before the surgery, the patients in the trial group chewed one piece of sugarless gum for at least 30 minutes, and then removed the gum before being taken to the operating room; while the patients in the control group chewed nothing. The time to first passage of flatus and the time to first defecation after surgery, length of hospital stay, the degrees of pain at 2-, 4-, 6-, 8-, 24-, 48-hour after surgery, the incidences of postoperative nausea, vomiting, and abdominal distension, postoperative analgesic and antiemetic drug requirement were recorded.ResultsThe mean time to first passage of flatus was significantly earlier in the trial group than that in the control group [(16.49±7.64) vs. (20.25±7.94) hours, P=0.003]. The mean time to first defecation was significantly earlier in the trial group than that in the control group [(48.16±15.25) vs. (55.80±18.97) hours, P=0.006]. The degree of pain at 2-hour after surgery was significantly lighter in the trial group than that in the control group (P<0.05). Fewer participants in the trial group than in the control group experienced postoperative nausea (43.75% vs. 61.25%, P=0.027). There were no significant differences in the length of hospital stay, the degrees of pain at 4-, 6-, 8-, 24- and 48-hour after surgery, incidences of postoperative vomiting and abdominal distension, postoperative analgesic, or antiemetic drug requirement between the two groups (P>0.05).ConclusionsGum chewing before surgery can promote the recovery of gastrointestinal function, reduce postoperative short-term pain, and promote postoperative rehabilitation in patients undergoing gynecologic laparoscopic surgery. Gum chewing before surgery can be used clinically as an easy, inexpensive, safe, and effective procedure.
Currently, the types of kidney stones before surgery are mainly identified by human beings, which directly leads to the problems of low classification accuracy and inconsistent diagnostic results due to the reliance on human knowledge. To address this issue, this paper proposes a framework for identifying types of kidney stones based on the combination of radiomics and deep learning, aiming to achieve automated preoperative classification of kidney stones with high accuracy. Firstly, radiomics methods are employed to extract radiomics features released from the shallow layers of a three-dimensional (3D) convolutional neural network, which are then fused with the deep features of the convolutional neural network. Subsequently, the fused features are subjected to regularization, least absolute shrinkage and selection operator (LASSO) processing. Finally, a light gradient boosting machine (LightGBM) is utilized for the identification of infectious and non-infectious kidney stones. The experimental results indicate that the proposed framework achieves an accuracy rate of 84.5% for preoperative identification of kidney stone types. This framework can effectively distinguish between infectious and non-infectious kidney stones, providing valuable assistance in the formulation of preoperative treatment plans and the rehabilitation of patients after surgery.