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| 老年患者全麻后恢复室低氧血症列线图模型的建立与验证 |
| Development and validation of nomogram model for hypoxemia in the recovery room after general anesthesia in elderly patients |
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| DOI：10.12089/jca.2025.01.008 |
| 中文关键词: 老年 全身麻醉 低氧血症 列线图 |
| 英文关键词: Aged General anesthesia Hypoxemia Nomograms |
| 基金项目:四川省自贡市科技局重点项目（2023-MKY-01-09） |
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| 中文摘要: |
目的：建立老年患者全麻后恢复室低氧血症风险预测模型并进行验证。
方法：选择2022年2月至2023年5月行全麻手术的老年患者492例，男271例，女221例，年龄≥65岁，BMI 18.0～29.9 kg/m2，ASA Ⅰ—Ⅲ级。将患者按7∶3比例分为训练集（n=344）和验证集（n=148）。收集患者一般资料、术前指标及手术相关指标。恢复室低氧血症的定义为拔除气管导管或喉罩后30 min呼吸空气时PaO2＜60 mmHg或SpO2＜ 90%。LASSO回归筛选变量后行多因素Logistic分析，并建立列线图预测模型，采用受试者工作特征（ROC）曲线、校准曲线对模型进行验证。
结果：训练集中共有139例（40.4%）患者出现恢复室低氧血症，验证集中共有61例（41.2%）患者出现恢复室低氧血症。多因素Logistic回归分析结果显示，BMI、ASA分级、吸烟史、手术类型、术后使用镇痛泵、进入恢复室时体温为老年患者全麻后恢复室低氧血症影响因素（P<0.05）。根据多因素分析结果建立老年患者全麻后恢复室低氧血症列线图预测模型。ROC曲线显示，在训练集中，该预测模型预测老年患者全麻后恢复室低氧血症风险的曲线下面积（AUC）为0.739（95%CI 0.686～0.792），验证集中AUC为0.733（95%CI 0.679～0.788）。校准曲线显示，训练集与验证集的预测曲线与标准曲线基本拟合。
结论：老年患者全麻后恢复室低氧血症的影响因素包括BMI、ASA分级、吸烟史、手术类型、术后使用镇痛泵、进入恢复室时体温，基于以上因素建立的列线图模型可有效预测老年患者全麻后恢复室低氧血症风险。 |
| 英文摘要: |
Objective: To develop and validate a predictive model for the risk of hypoxemia in the recovery room after general anesthesia in elderly patients.
Methods: A total of 492 elderly patients, 271 males and 221 females, aged ≥ 65 years, BMI 18.0-29.9 kg/m2, ASA physical status Ⅰ-Ⅲ, who underwent general anesthesia surgery from February 2022 to May 2023 were selected. The patients were divided into a training set (n = 344) and a validation set (n = 148) based on a 7∶3 ratio. The patients' general data, preoperative indicators and surgery-related indicators were collected. The definition of recovery room hypoxemia is PaO2< 60 mmHg or SpO2< 90% on breathing air 30 minutes after removal of the tracheal tube or laryngeal mask. The LASSO regression screened the variables and then performed multifactor logistic analysis, and built nomogram prediction model, which was validated with receiver operating characteristic (ROC) curve and calibration curve.
Results: A total of 139 patients (40.4%) in the training set and 61 patients (41.2%) in the validation set had recovery room hypoxemia. The results of multifactorial logistic regression analysis showed that BMI, ASA physical status, smoking history, type of surgery, postoperative analgesia, and body temperature at the time of entering the recovery room were the factors influencing hypoxemia in the recovery room after general anesthesia in elderly patients (P < 0.05). A nomogram predictive model for hypoxemia in the recovery room after general anesthesia in elderly patients was developed based on the results of multifactorial logistic analysis. ROC analysis showed that the area under the curve (AUC) of the nomogram predictive model for predicting the risk of hypoxemia in the recovery room after general anesthesia in elderly patients was 0.739 (95% CI 0.686-0.792) in the training set, and the AUC in the validation set was 0.733 (95% CI 0.679-0.788). The calibration curve results showed that the prediction curves of the training and validation sets were generally fitted to the standard curve.
Conclusion: Factors influencing recovery room hypoxemia after general anesthesia in elderly patients are BMI, ASA physical status, smoking history, type of surgery, postoperative analgesia, and body temperature at the time of entering the recovery room. The nomogram model established based on the above factors for predicting the risk of recovery room hypoxemia after general anesthesia in elderly patients has a high degree of accuracy. |
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