麻醉复苏室全麻术后患者高氧血症风险预测模型的构建与验证

doi:10.3761/j.issn.0254-1769.2025.22.003

摘要/Abstract

摘要：

目的构建麻醉复苏室全麻术后患者高氧血症风险预测模型，并验证其预测效果，为指导临床护理实践提供参考。方法回顾性收集2023年11月—2024年9月进入麻醉复苏室的全麻患者6 219例，按照是否发生高氧血症分为高氧血症组（n=730）和非高氧血症组（n=5 489），并对两组资料进行对比，采用Logistic回归分析影响因素，建立风险预测模型，绘制列线图检验模型预测效果。选取2024年10月—2025年1月1 557例同一单位全麻患者作为验证组进行模型验证。结果建模组全麻术后高氧血症发生率为11.73%。Logistic回归分析结果显示，手术方式、手术部位、手术体位、单肺通气、术中机械通气时长、使用呼气末正压、吸入氧浓度是全麻术后患者高氧血症的影响因素。Hosmer-Lemeshow检验显示，χ²=8.801，P=0.359，受试者操作特征曲线下面积为0.945，最佳临界值为0.839，灵敏度为0.907，特异度为0.932，模型验证准确率为90.82%，提示模型具有较好的拟合效果和较高的预测价值。结论该模型可有效预测全麻术后患者高氧血症的发生，且所有指标在进入复苏室前就可获得，可为医护人员早期识别高氧血症高危患者提供借鉴。

关键词: 全身麻醉, 高氧血症, 麻醉复苏室, 风险预测模型, 护理

Abstract:

Objective To construct a risk prediction model for hyperoxemia in patients after general anesthesia in the post-anesthesia care unit（PACU） and verify its predictive effect. Methods A retrospective collection was conducted on 6 219 patients who underwent general anesthesia and entered the PACU from November 2023 to September 2024. They were divided into a hyperoxemia group（n=730） and a non-hyperoxemia group（n=5 489） based on the occurrence of hyperoxemia. The data of the 2 groups were compared；Logistic regression was used to analyze the influencing factors；a risk prediction model was established；a nomogram was drawn to test the predictive effect of the model. A total of 1 557 patients in the PACU from October 2024 to January 2025 were selected as a validation group for model verification. Results The incidence of hyperoxemia after general anesthesia in the modeling group was 11.73%. Logistic regression analysis showed that surgical method，surgical site，surgical position，one-lung ventilation，duration of mechanical ventilation，use of PEEP，and inhaled oxygen concentration were the influencing factors of hyperoxemia. The Hosmer-Lemeshow test showed that χ²=8.801 and P=0.359. The area under the receiver operating characteristic curve was 0.945；the optimal cut-off value was 0.839；the sensitivity was 0.907；the specificity was 0.932；the model verification accuracy was 90.82%，indicating that the model had a good fitting effect and high predictive value. Conclusion This model can effectively predict the occurrence of hyperoxemia after general anesthesia，and all indicators can be obtained before entering the PACU，which can provide a reference for medical staff to identify early and take preventive nursing interventions for patients.

Key words: General Anesthesia, Hyperoxemia, Post Anesthesia Care Unit, Risk Prediction Model, Nursing Care

盛丽乐, 赵征华, 兰星, 王宇, 张涛, 杨依依, 姚尚龙. 麻醉复苏室全麻术后患者高氧血症风险预测模型的构建与验证[J]. 中华护理杂志, 2025, 60(22): 2702-2708.

SHENG Lile, ZHAO Zhenghua, LAN Xing, WANG Yu, ZHANG Tao, YANG Yiyi, YAO Shanglong. Establishment and validation of a risk prediction model for hyperoxemia in patients after general anesthesia in the post-anesthesia care unit[J]. Chinese Journal of Nursing, 2025, 60(22): 2702-2708.

图/表 5

表1 调查对象的一般资料及发生高氧血症危险因素的单因素分析结果 [例（百分比，%）]

Table 1 Univariate analysis results of general data of study subjects and risk factors for hyperoxemia[cases（percentage，%）]

表2 自变量赋值方式

Table 2 The assignment of the independent variables

表3 高氧血症的logistic回归分析结果（n=6 219）

Table 3 Logistic regression analysis results of hyperoxemia（n=6 219）

图1 麻醉复苏室全麻术后患者高氧血症风险预测列线图

Figure 1 Nomogram for predicting hyperoxemia risk in patients after general anesthesia in the post-anesthesia care unit

图2 麻醉复苏室全麻术后患者高氧血症风险预测模型的校准曲线

Figure 2 Calibration curve of the risk prediction model for hyperoxemia in patients after general anesthesia in the post-anesthesia care unit

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