Anesthesia & Analgesia最新文献_第10页

Search for a Safer Anesthetic Technique with Lesser Postoperative Pulmonary Complications: The Quest Is Still Open 寻找更安全、术后肺部并发症更少的麻醉技术：探索仍在继续

Anesthesia & Analgesia

Pub Date : 2024-09-04 DOI: 10.1213/ane.0000000000007041

Dipasri Bhattacharya, Pradipta Bhakta, Mohanchandra Mandal

An abstract is unavailable.

没有摘要。

引用次数: 0

Neuromuscular Blocking Agents: One of the Factors Contributing to Postoperative Pulmonary Complications 神经肌肉阻滞剂：导致术后肺部并发症的因素之一

Anesthesia & Analgesia

Pub Date : 2024-09-04 DOI: 10.1213/ane.0000000000006993

Yusuke Miyazaki, Kaoru Suzuki, Kentaro Yamakawa, Hiroshi Sunaga

An abstract is unavailable.

没有摘要。

引用次数: 0

Persistent Postoperative Opioid Use: Progressing From Risk Identification to Risk Reduction 术后持续使用阿片类药物：从识别风险到降低风险

Anesthesia & Analgesia

Pub Date : 2024-09-04 DOI: 10.1213/ane.0000000000007022

Naheed K. Jivraj, Eric Sun, Lauren K. Dunn, Harsha Shanthanna

An abstract is unavailable.

没有摘要。

引用次数: 0

Classifying High-Risk Patients for Persistent Opioid Use After Major Spine Surgery: A Machine-Learning Approach 脊椎大手术后持续使用阿片类药物的高风险患者分类：机器学习方法

Anesthesia & Analgesia

Pub Date : 2024-09-04 DOI: 10.1213/ane.0000000000006832

Sierra Simpson, William Zhong, Soraya Mehdipour, Michael Armaneous, Varshini Sathish, Natalie Walker, Engy T. Said, Rodney A. Gabriel

Five classification models were evaluated to predict persistent opioid use: logistic regression, random forest, neural network, balanced random forest, and balanced bagging. Synthetic Minority Oversampling Technique was used to improve class balance. The primary outcome was persistent opioid use, defined as patient reporting to use opioids after 3 months postoperatively. The data were split into a training and test set. Performance metrics were evaluated on the test set and included the F1 score and the area under the receiver operating characteristics curve (AUC). Feature importance was ranked based on SHapley Additive exPlanations (SHAP). RESULTS: After exclusion (patients with missing follow-up data), 2611 patients were included in the analysis, of which 1209 (46.3%) continued to use opioids 3 months after surgery. The balanced random forest classifiers had the highest AUC (0.877, 95% confidence interval [CI], 0.834–0.894) compared to neural networks (0.729, 95% CI, 0.672–0.787), logistic regression (0.709, 95% CI, 0.652–0.767), balanced bagging classifier (0.859, 95% CI, 0.814–0.905), and random forest classifier (0.855, 95% CI, 0.813–0.897). The balanced random forest classifier had the highest F1 (0.758, 95% CI, 0.677–0.839). Furthermore, the specificity, sensitivity, precision, and accuracy were 0.883, 0.700, 0.836, and 0.780, respectively. The features based on SHAP analysis with the highest impact on model performance were age, preoperative opioid use, preoperative pain scores, and body mass index. CONCLUSIONS: The balanced random forest classifier was found to be the most effective model for identifying persistent opioid use after spine surgery....

评估了五种预测阿片类药物持续使用的分类模型：逻辑回归、随机森林、神经网络、平衡随机森林和平衡袋集。为了提高分类的平衡性，采用了合成少数群体过度取样技术（Synthetic Minority Oversampling Technique）。主要结果是阿片类药物的持续使用，即患者报告术后 3 个月后仍在使用阿片类药物。数据分为训练集和测试集。性能指标在测试集上进行评估，包括 F1 分数和接收器工作特征曲线下面积 (AUC)。特征重要性根据 SHapley Additive exPlanations（SHAP）进行排序。结果：经排除（随访数据缺失的患者）后，2611 名患者被纳入分析，其中 1209 人（46.3%）在术后 3 个月仍在使用阿片类药物。与神经网络（0.729，95% CI，0.672-0.787）、逻辑回归（0.709，95% CI，0.652-0.767）、平衡随机森林分类器（0.859，95% CI，0.814-0.905）和随机森林分类器（0.855，95% CI，0.813-0.897）相比，平衡随机森林分类器的AUC最高（0.877，95% 置信区间[CI]，0.834-0.894）。平衡随机森林分类器的 F1 值最高（0.758，95% CI，0.677-0.839）。此外，特异性、灵敏度、精确度和准确度分别为 0.883、0.700、0.836 和 0.780。根据 SHAP 分析，对模型性能影响最大的特征是年龄、术前阿片类药物使用情况、术前疼痛评分和体重指数。结论：平衡随机森林分类器是识别脊柱手术后持续使用阿片类药物的最有效模型....。

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引用次数: 0

Tranexamic Acid in Liver Transplantation: An Anesthesiologist’s Friend Without Benefits? 肝移植中的氨甲环酸：麻醉师的 "无益之友"？

Anesthesia & Analgesia

Pub Date : 2024-09-04 DOI: 10.1213/ane.0000000000007030

Tricia A. Haynes, Amir L. Butt, Srikiran Ramarapu, Kenichi A. Tanaka

An abstract is unavailable.

没有摘要。

引用次数: 0

Do Not Teach the Landmark Technique for Central Venous Catheterization—Primum Non Nocere! 不要教授中心静脉导管置入的地标技术--"不可忽视原则"！

Anesthesia & Analgesia

Pub Date : 2024-09-04 DOI: 10.1213/ane.0000000000007157

Ola Borgquist, Robin Lundén, Maria Adrian, Thomas Kander