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腹腔镜下全子宫切除术麻醉恢复期躁动的危险因素预测模型 被引量:2

Predictive model of risk factors for restlessness during anesthesia recovery period in laparoscopic hysterectomy
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摘要 目的研究腹腔镜下全子宫切除术患者麻醉恢复期躁动的危险因素并构建预测模型。方法选取在我院进行腹腔镜下全子宫切除术的200例患者为研究对象,根据Riker躁动、镇静评分标准,将≤4级的152例患者纳入无躁动组,将≥5级的48例患者纳入躁动组。对比2组患者的临床资料,分析影响腹腔镜下全子宫切除术患者麻醉恢复期躁动的相关因素;采用受试者工作特征(ROC)曲线分析相关因素对腹腔镜下全子宫切除术患者麻醉恢复期躁动的预测价值;Logistic多元回归模型分析影响腹腔镜下全子宫切除术患者麻醉恢复期躁动的独立危险因素;R语言软件4.0“rms”包构建预测腹腔镜下全子宫切除术患者麻醉恢复期躁动的列线图模型。结果与无躁动组相比,躁动组患者年龄较大,ASA分级Ⅲ级比例、术后留置导尿管比例、低氧血症比例、肌松药残留比例较高,采取术后镇痛比例较低,手术时间及麻醉时间较长,差异有统计学意义(P<0.05)。年龄、手术时间、麻醉时间的AUC分别为0.719、0.597、0.610,最佳截断值分别为55岁、83 min、93 min。年龄>55岁、ASA分级Ⅲ级、术后未镇痛、术后留置导尿管、低氧血症、肌松药残留是腹腔镜下全子宫切除术患者麻醉恢复期躁动的独立危险因素。列线图模型预测腹腔镜下全子宫切除术患者麻醉恢复期躁动的C-index为0.796(95%CI:0.613~0.867),阈值>0.19,列线图模型提供临床净收益率均高于独立预测因子。结论本研究基于年龄、ASA分级、术后镇痛、留置导尿管、低氧血症、肌松药残留构建了预测腹腔镜下全子宫切除术患者麻醉恢复期躁动的列线图模型,可用于麻醉恢复期躁动的早期预测及探查,防止躁动对患者造成损伤,确保安全。 Objective To study the risk factors of restlessness during anesthesia recovery period in patients undergoing laparoscopic hysterectomy and to construct a predictive model.Methods A total of 200 patients who underwent laparoscopic hysterectomy in our hospital were selected as the research subjects.According to the Riker restlessness and sedation scoring criteria,152 patients with grade≤4 were included in the non-restlessness group,and 48 patients with grade≥5 were included in the restlessness group.The clinical data of the two groups were compared,and the related factors affecting the restlessness during anesthesia recovery period in patients underwent laparoscopic hysterectomy were analyzed.The receiver operating characteristic(ROC)curve was used to analyze the predictive value of related factors for restlessness during anesthesia recovery period in patients underwent laparoscopic hysterectomy.Logistic multiple regression model was used to analyze the independent risk factors for restlessness during anesthesia recovery period in patients undergoing laparoscopic hysterectomy.R language software 4.0"rms"package was used to construct an nomogram model for predicting the restlessness during anesthesia recovery period in patients undergoing laparoscopic hysterectomy.Results Compared with the non-restlessness group,the patients in the restlessness group were older,with higher proportions of ASA gradeⅢ,postoperative indwelling catheter,hypoxemia,muscle relaxant residue,lower proportion of postoperative analgesia,and longer operation time and anesthesia time(P<0.05).The AUC of age,operation time and anesthesia time were 0.719,0.597 and 0.610,respectively,and the best cut-off values were 55 years old,83 minutes and 93 minutes,respectively.Age>55 years old,ASA gradeⅢ,lack of postoperative analgesia,indwelling catheter after operation,hypoxemia and muscle relaxant residue were the independent risk factors for restlessness during anesthesia recovery period in patients underwent laparoscopic hysterectomy.The C-index of nomogram model for predicting the restlessness during anesthesia recovery period was 0.796(95%CI:0.613 to 0.867)in patients underwent laparoscopic hysterectomy,and the threshold value was>0.19.The clinical net income provided by the nomogram model was higher than those provided by the independent predictors.Conclusion Based on age,ASA grade,postoperative analgesia,indwelling catheter,hypoxemia,and muscle relaxant residue,this study construct an nomogram model for predicting restlessness during anesthesia recovery period in patients undergoing laparoscopic hysterectomy,which can be used for the early prediction and exploration of restlessness during anesthesia recovery period,to prevent damage caused by restlessness to patients,and to ensure safety.
作者 周敏 严康明 周群英 李晓明 ZHOU Min;YAN Kang-ming;ZHOU Qun-ying;LI Xiao-ming(Department of Anesthesiology,Affiliated Hospital of West Anhui Health Vocational College,Lu'an Anhui 237000,China;Department of Obstetrics and Gynecology,Affiliated Hospital of West Anhui Health Vocational College,Lu'an Anhui 237000,China)
出处 《局解手术学杂志》 2023年第5期439-443,共5页 Journal of Regional Anatomy and Operative Surgery
基金 2021年度安徽高校自然科学研究项目(KJ2021A1368) 2020年度安徽高校自然科学研究项目(KJ2020A0956)。
关键词 腹腔镜下全子宫切除术 麻醉恢复期 躁动 危险因素 列线图预测模型 laparoscopic hysterectomy anesthesia recovery period restlessness risk factors nomogram prediction model
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