Application of triangular fold combined with semilunar fold preconditioning in OSAHS patients undergoing tonsillectomy
Objective To evaluate the effect of trigonal plica combined with semilunar plica pretreatment in tonsil-lectomy for patients with obstructive sleep apnea hypopnea syndrome(OSAHS).Methods The clinical data of 103 pa-tients with OSAHS who underwent surgical treatment from January 2021 to March 2023 were retrospectively analyzed.According to the surgical treatment methods,they were divided into control group(n=50)and study group(n=53).The control group was treated with conventional tonsillectomy,while the study group was treated with pretreatment of triangular fold combined with semilunar fold.The perioperative basic indicators(operation time,wound bleeding time,intraoperative blood loss,and time of albuginea exfoliation)of the two groups were counted.The changes of sleep apnea hypopnea indicators[apnea hypopnea index(AHI),minimum arterial oxygen saturation(LSaO2),oxygen depletion index(ODI)]and sleepiness degree[Epworth sleepiness scale(ESS),Stanford sleepiness scale(SSS)]of the two groups before and after the operation were observed.The occurrence of complications in the two groups within 3 months after the oper-ation was counted.Results There was no significant difference in general clinical data between the two groups(P＞0.05).The operation time and postoperative LSaO2 in study group were higher than those in control group(P＜0.05).The bleeding time of study wound,intraoperative bleeding volume,postoperative time of albuginea detachment,AHI,ODI,ESS,SSS scores and complication rate in study group were lower than those in control group(P＜0.05).Conclu-sion Triangular fold combined with semilunar fold pretreatment in tonsillectomy for patients with OSAHS has good effect,and can effectively promote the rehabilitation of patients,reduce the risk of postoperative complications.It has high safety.
Obstructive sleep apnea hypopnea syndrome(OSAHS)TonsillectomyTriangular foldSemilunar foldSleep hypopnea index
万方数据
维普
