| 陈福腾,刁怀悦,高顺恒,王 兵,刘乃和.术后患者自控镇痛提前撤泵的危险因素及预测模型的建立与验证[J].,2024,(19):3696-3700 |
| 术后患者自控镇痛提前撤泵的危险因素及预测模型的建立与验证 |
| Risk Factors of Early Withdrawal of Pump and Establishment and Verification of Prediction Model for Patient-Controlled Analgesia after Surgery |
| 投稿时间：2024-05-05 修订日期：2024-05-30 |
| DOI：10.13241/j.cnki.pmb.2024.19.025 |
| 中文关键词: 患者自控镇痛 提前撤泵 危险因素 LASSO回归分析 列线图 |
| 英文关键词: Patient-controlled analgesia Early withdrawal of pump Risk factors LASSO regression analysis Nomogram |
| 基金项目:江苏省社会发展面上基金项目（BE20210610） |
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| 中文摘要: |
| 摘要 目的：探讨术后患者自控镇痛（PCA）提前撤泵的危险因素并构建列线图预测模型。方法：纳入2019年7月至2021年5月2517例使用PCA的手术患者，采用随机抽样法按照7:3比例分为训练集（n=1773）和验证集（n=744）。运用套索法（LASSO）在训练集中进行特征变量筛选，结局相关的独立危险因素筛选采用多因素Logistic回归，使用赤池信息准则（AIC）评估模型拟合情况，进一步构建术后PCA提前撤泵的列线图。使用受试者工作特征曲线（ROC）、校准曲线、Brier分数对列线图在训练集和验证集中预测效能进行评估。结果：以与提前撤泵相关的9个独立危险因素和1个相关因素构建预测术后PCA提前撤泵的列线图。训练集曲线下面积（AUC）为0.880(95%CI：85.87%~90.16%)，验证集AUC为0.888(95%CI：85.55%~92%)。训练集与验证集校准曲线经Hosmer-Lemeshow拟合优度检验显示P值分别为0.004、0.228，Brier评分分别为0.018、0.016。结论：建立的列线图拥有较好的区分度和校准度，对预测术后PCA提前撤泵人群具有一定的参考价值。 |
| 英文摘要: |
| ABSTRACT Objective: To investigate the risk factors of early withdrawal of pump in patient-controlled analgesia (PCA) after surgery and to construct a nomogram prediction model. Methods: A total of 2517 surgical patients who received PCA between July 2019 and May 2021 were enrolled, and then randomized the eligible patients into training group (n=1773) and validation group (n=744) with a ratio of 7:3. The Least Absolute Shrinkage and Selection Operator (LASSO) method was used to screen the characteristic variables in the training set, and multifactorial logistic model was used to select independent risk factors that were associated with outcomes. Akaike Information Criterion (AIC) was used to evaluate the model fit, and the nomogram of PCA early withdrawal was further constructed. In the training and validation sets, Receiver Operation Characteristic curve (ROC curve), calibration curve and Brier score were used to evaluate the prediction efficiency of the nomogram. Results: Nine independent risk factors and one related factor related to early pump withdrawal were used to construct a nomogram for predicting early withdrawal of pump after PCA. The area under the curve (AUC) of the training set was 0.880 (95 % CI : 85.87 % -90.16 %), and the AUC of the validation set was 0.888 (95 % CI : 85.55 % -92 %). The calibration curves of the training set and the validation set were tested by Hosmer-Lemeshow good of fit test. The P values were 0.004 and 0.228, and the Brier scores were 0.018 and 0.016, respectively. Conclusion: The nomogram we established has an ideal discrimination and calibration, which can provide a certain reference value for predicting the high-risk population of early withdrawal of pump in PCA after surgery. |
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