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术前使用美沙酮患者术后呼吸抑制和呼吸并发症的预测。

Prediction of postoperative respiratory depression and respiratory complications in patients on preoperative methadone.

机构信息

Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA.

Department of General Anesthesiology, Department of Outcomes Research, Anesthesiology Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA.

出版信息

J Anesth. 2023 Feb;37(1):79-91. doi: 10.1007/s00540-022-03134-8. Epub 2022 Nov 10.

Abstract

PURPOSE

We developed prediction models for postoperative respiratory depression and respiratory complications for 958 patients who were on methadone preoperatively.

METHODS

The primary outcome was postoperative respiratory depression as defined by respiratory rate < 10/min, oxygen saturation (SpO) < 90%, or requirement of naloxone for 48 h postoperatively. Secondary outcome was the composite of postoperative respiratory complications. Prediction models for postoperative respiratory depression and respiratory complications were constructed using multivariate logistic regression with preoperative and intraoperative characteristics as the predictors.

RESULTS

For the multivariate logistic regression model for postoperative respiratory depression, surgery duration (P = 0.005), body mass index (BMI) (P = 0.008), surgery involving digestive system (P = 0.031), and American Society of Anesthesiologists (ASA) physical status ≥ 4 (P = 0.038) were statistically significant predictors. The area under the receiver operating characteristic curve (AUROC) of the model was 0.581 (0.558-0.601) [median (95% confidence interval (CI))] with fivefold cross-validation. For the model for postoperative respiratory complications, surgery duration (P = 0.001), history of hypertension (P = 0.028), surgery involving musculoskeletal system (P < 0.001), surgery involving integumental system (P = 0.034), surgery categorized to miscellaneous therapeutic procedures (P = 0.028), combined general and regional anesthesia (P = 0.033), ASA physical status 3 (P < 0.001), and ASA physical status ≥ 4 (P < 0.001) were statistically significant predictors, and AUROC of the model was 0.726 (0.712-0.737).

CONCLUSIONS

Multivariate logistic regression models including preoperative, and intraoperative characteristics as the predictors performed poorly to predict postoperative respiratory depression, and moderately for postoperative respiratory complications. Neither model is accurate enough to be subject to clinical use.

摘要

目的

我们为 958 例术前使用美沙酮的患者开发了术后呼吸抑制和呼吸并发症的预测模型。

方法

主要结局为术后呼吸抑制定义为呼吸频率<10/min、氧饱和度(SpO2)<90%或术后 48 小时需要纳洛酮。次要结局为术后呼吸并发症的综合结果。使用多元逻辑回归,将术前和术中特征作为预测因子,构建术后呼吸抑制和呼吸并发症的预测模型。

结果

对于术后呼吸抑制的多元逻辑回归模型,手术时间(P=0.005)、体重指数(BMI)(P=0.008)、涉及消化系统的手术(P=0.031)和美国麻醉医师协会(ASA)身体状况≥4(P=0.038)是统计学显著的预测因子。该模型的受试者工作特征曲线(ROC)下面积(AUROC)为 0.581(0.558-0.601)[中位数(95%置信区间(CI))],经五倍交叉验证。对于术后呼吸并发症的模型,手术时间(P=0.001)、高血压病史(P=0.028)、涉及肌肉骨骼系统的手术(P<0.001)、涉及皮肤系统的手术(P=0.034)、归类为多种治疗程序的手术(P=0.028)、全身麻醉和区域麻醉联合(P=0.033)、ASA 身体状况 3(P<0.001)和 ASA 身体状况≥4(P<0.001)是统计学显著的预测因子,该模型的 AUROC 为 0.726(0.712-0.737)。

结论

包括术前和术中特征作为预测因子的多元逻辑回归模型预测术后呼吸抑制的效果较差,预测术后呼吸并发症的效果中等。这两种模型都不够准确,不能用于临床。

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