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Identification of patients at risk for postoperative respiratory complications using a preoperative obstructive sleep apnea screening tool and postanesthesia care assessment.

机译:使用术前阻塞性睡眠呼吸暂停筛查工具和麻醉后护理评估来鉴定有术后呼吸系统并发症风险的患者。

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BACKGROUND: Patients with obstructive sleep apnea are at risk for perioperative morbidity. The authors used a screening prediction model for obstructive sleep apnea to generate a sleep apnea clinical score (SACS) that identified patients at high or low risk for obstructive sleep apnea. This was combined with postanesthesia care unit (PACU) monitoring with the aim of identifying patients at high risk of postoperative oxygen desaturation and respiratory complications. METHODS: In this prospective cohort study, surgical patients with a hospital stay longer than 48 h who consented were enrolled. The SACS (high or low risk) was calculated; all patients were monitored in the PACU for recurrent episodes of bradypnea, apnea, desaturations, and pain-sedation mismatch. All patients underwent pulse oximetry postoperatively; complications were documented. Chi-square, two-sample t test, and logistic regression were used for analysis. The oxygen desaturation index (number of desaturations per hour) was calculated. Oxygen desaturation index and incidence of postoperative cardiorespiratory complications were primary endpoints. RESULTS: Six hundred ninety-three patients were enrolled. From multivariable logistic regression analysis, the likelihood of a postoperative oxygen desaturation index greater than 10 was increased with a high SACS (odds ratio = 1.9, P < 0.001) and recurrent PACU events (odds ratio = 1.5, P = 0.036). Postoperative respiratory events were also associated with a high SACS (odds ratio = 3.5, P < 0.001) and recurrent PACU events (odds ratio = 21.0, P < 0.001). CONCLUSIONS: Combination of an obstructive sleep apnea screening tool preoperatively (SACS) and recurrent PACU respiratory events was associated with a higher oxygen desaturation index and postoperative respiratory complications. A two-phase process to identify patients at higher risk for perioperative respiratory desaturations and complications may be useful to stratify and manage surgical patients postoperatively.
机译:背景:阻塞性睡眠呼吸暂停患者有围手术期发病的风险。作者使用了阻塞性睡眠呼吸暂停的筛查预测模型来产生睡眠呼吸暂停临床评分(SACS),该评分可识别出阻塞性睡眠呼吸暂停高风险或低风险的患者。结合麻醉后监护病房(PACU)监测,目的是确定术后氧饱和度降低和呼吸系统并发症高风险的患者。方法:在这项前瞻性队列研究中,入院手术时间超过48小时的外科手术患者被纳入研究。计算SACS(高风险或低风险);在PACU中对所有患者进行了监测,以检查是否有反复发作,呼吸暂停,呼吸暂停,脱位和镇静不匹配。所有患者术后均接受脉搏血氧饱和度测定。记录了并发症。卡方检验,二样本t检验和logistic回归用于分析。计算氧饱和度指数(每小时的饱和度数)。主要终点为氧饱和度指数和术后心肺并发症发生率。结果:693例患者入选。根据多变量logistic回归分析,较高的SACS(比值= 1.9,P <0.001)和复发性PACU事件(比值= 1.5,P = 0.036)增加了术后氧饱和度指数大于10的可能性。术后呼吸事件也与较高的SACS(比值= 3.5,P <0.001)和复发的PACU事件(比值= 21.0,P <0.001)相关。结论:术前使用阻塞性睡眠呼吸暂停筛查工具(SACS)和复发性PACU呼吸事件的组合与更高的氧饱和度指数和术后呼吸系统并发症相关。识别围手术期呼吸不饱和和并发症风险较高的患者的两阶段过程可能对术后手术患者进行分层和管理很有用。

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