单肺通气时低氧血症风险分层的术前多变量模型。

IF 4.6 2区 医学 Q1 ANESTHESIOLOGY
Andres Zorrilla-Vaca, Michael C Grant, Laura Mendez-Pino, Muhammad J Rehman, Pankaj Sarin, Sula Nasra, Dirk Varelmann
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引用次数: 0

摘要

背景:低氧血症在单肺通气(OLV)中发生的频率相对较高,尽管气道管理有所进步。肺灌注扫描被认为是预测OLV期间低氧血症最准确的方法之一,但其复杂性和成本是众所周知的局限性。缺乏术前分层模型来估计胸外科手术患者术中低氧血症的风险。我们的主要目的是建立一个基于术前临床变量的低氧血症风险分层模型。方法:这是一项单中心、回顾性队列研究,包括3228例2017年至2022年在美国一家三级学术医疗中心接受OLV肺切除术的患者。生命体征和呼吸机设置每分钟被检索。术中低氧血症被定义为氧去饱和发作(Spo2)结果:OLV期间低氧血症的发生率为8.9%(95%可信区间[CI], 8.0-10.0)。多变量logistic回归识别出9个危险因素并进行相应评分:术前Spo2 60岁(4分)、男性(4分)、体重指数>30 kg/m2(8分)、糖尿病(4分)、充血性心力衰竭(7分)、高血压(3分)、右侧手术(3分)。自举校正后模型的AUC为0.708 (95% CI, 0.676-0.74)。基于最高约登指数,预测术中低氧血症的最佳得分为13分。低氧血症的风险从第一个四分位数的4.7%(0-13分)增加到第三个四分位数的32%(27-39分),第四个四分位数的83.3% (bb0 -39分)。在20分及以上时,模型的特异性超过90%,达到80%的阳性预测值。结论:OLV术中低氧血症的风险可通过可获得的临床变量进行术前分层。我们的风险模型校准得很好,但在预测术中低氧血症方面表现出适度的辨别能力。术前低氧血症风险分层模型的准确性应在前瞻性研究中进行探讨。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Preoperative Multivariable Model for Risk Stratification of Hypoxemia During One-Lung Ventilation.

Background: Hypoxemia occurs with relative frequency during one-lung ventilation (OLV) despite advances in airway management. Lung perfusion scans are thought to be one of the most accurate methods to predict hypoxemia during OLV, but their complexity and costs are well-known limitations. There is a lack of preoperative stratification models to estimate the risk of intraoperative hypoxemia among patients undergoing thoracic surgery. Our primary objective was to develop a risk stratification model for hypoxemia during OLV based on preoperative clinical variables.

Methods: This is a single-center, retrospective cohort study including 3228 patients who underwent lung resections with OLV from 2017 to 2022, at a tertiary academic health care center in the United States. Vital signs and ventilator settings were retrieved minute by minute. Intraoperative hypoxemia was defined as an episode of oxygen desaturation (Sp o2 <90%) for at least 5 minutes. Demographic and clinical characteristics were included in a stepwise logistic regression, which was used for the selection of predictors of the risk score model. All patients included in this cohort underwent elective lung surgery in lateral decubitus position, with double lumen tube and placement confirmation with fiberoptic bronchoscopy. Our model was validated internally using area under the receiver operating curves (AUC) with bootstrapping correction.

Results: The incidence of hypoxemia during OLV was 8.9% (95% confidence interval [CI], 8.0-10.0). Multivariable logistic regression identified 9 risk factors with their corresponding scoring: preoperative Sp o2 <92% (15 points), hemoglobin <10 g/dL (6 points), age >60 years old (4 points), male sex (4 points), body mass index >30 kg/m 2 (8 points), diabetes mellitus (4 points), congestive heart failure (7 points), hypertension (3 points), and right-sided surgery (3 points). The AUC of the model after bootstrap correction was 0.708 (95% CI, 0.676-0.74). Based on the highest Youden index, the optimal score for predicting intraoperative hypoxemia was 13. The risk of hypoxemia increased from 4.7% in the first quartile of scores (0-13 points), to 32% in the third quartile (27-39 points), and 83.3% in the fourth quartile (>39 points). At scores of 20 or greater, the specificity of the model exceeded 90% and reached a positive predictive value of 80%.

Conclusions: The risk of hypoxemia during OLV can be stratified preoperatively using accessible clinical variables. Our risk model is well calibrated but showed moderate discrimination for predicting intraoperative hypoxemia. The accuracy of preoperative models for risk stratification of hypoxemia during OLV should be explored in prospective studies.

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来源期刊
Anesthesia and analgesia
Anesthesia and analgesia 医学-麻醉学
CiteScore
9.90
自引率
7.00%
发文量
817
审稿时长
2 months
期刊介绍: Anesthesia & Analgesia exists for the benefit of patients under the care of health care professionals engaged in the disciplines broadly related to anesthesiology, perioperative medicine, critical care medicine, and pain medicine. The Journal furthers the care of these patients by reporting the fundamental advances in the science of these clinical disciplines and by documenting the clinical, laboratory, and administrative advances that guide therapy. Anesthesia & Analgesia seeks a balance between definitive clinical and management investigations and outstanding basic scientific reports. The Journal welcomes original manuscripts containing rigorous design and analysis, even if unusual in their approach.
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