开发临床工具,估算高流量氧疗时的呼吸强度:多中心队列研究。

IF 10.4 2区 医学 Q1 RESPIRATORY SYSTEM
A Protti, R Tonelli, F Dalla Corte, D L Grieco, E Spinelli, S Spadaro, D Piovani, L S Menga, G Schifino, M L Vega Pittao, M Umbrello, G Cammarota, C A Volta, S Bonovas, M Cecconi, T Mauri, E Clini
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引用次数: 0

摘要

导言和目标:量化未插管患者的呼吸强度非常重要,但却很困难。我们旨在开发两种模型来估算接受高流量氧疗患者的呼吸强度:我们分析了以往研究中接受高流量氧疗的 260 名患者的数据。他们的呼吸强度是通过食管压力的最大偏转(ΔPes)来测量的。我们建立了一个多变量线性回归模型来估算 ΔPes(以 cmH2O 为单位),并建立了一个多变量逻辑回归模型来预测 ΔPes >10 cmH2O 的风险。候选预测因子包括年龄、性别、冠状病毒疾病诊断2019(COVID-19)、呼吸频率、心率、平均动脉压、动脉血气分析结果(包括碱过量浓度(BEa)和动脉张力与吸入氧分数比值(PaO2:FiO2))以及COVID-19与PaO2:FiO2的乘积项:我们发现,ΔPes 可通过是否存在 COVID-19、BEa、呼吸频率、PaO2:FiO2 以及 COVID-19 与 PaO2:FiO2 之间的乘积项来估算。调整后的 R2 为 0.39。根据 BEa、呼吸频率和 PaO2:FiO2 可以预测 ΔPes >10 cmH2O 的风险。接收者操作特征曲线下的面积为 0.79(0.73-0.85)。我们将这两个模型称为 BREF,其中 BREF 代表 BReathing EFfort,三个常用的预测因子分别是:BEa (B)、呼吸频率 (B)、PaO2:FiO2:结论:我们开发了两个模型来估算接受高流量氧疗患者的呼吸强度。我们的初步研究结果很有希望,表明这些模型值得进一步评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of clinical tools to estimate the breathing effort during high-flow oxygen therapy: A multicenter cohort study.

Introduction and objectives: Quantifying breathing effort in non-intubated patients is important but difficult. We aimed to develop two models to estimate it in patients treated with high-flow oxygen therapy.

Patients and methods: We analyzed the data of 260 patients from previous studies who received high-flow oxygen therapy. Their breathing effort was measured as the maximal deflection of esophageal pressure (ΔPes). We developed a multivariable linear regression model to estimate ΔPes (in cmH2O) and a multivariable logistic regression model to predict the risk of ΔPes being >10 cmH2O. Candidate predictors included age, sex, diagnosis of the coronavirus disease 2019 (COVID-19), respiratory rate, heart rate, mean arterial pressure, the results of arterial blood gas analysis, including base excess concentration (BEa) and the ratio of arterial tension to the inspiratory fraction of oxygen (PaO2:FiO2), and the product term between COVID-19 and PaO2:FiO2.

Results: We found that ΔPes can be estimated from the presence or absence of COVID-19, BEa, respiratory rate, PaO2:FiO2, and the product term between COVID-19 and PaO2:FiO2. The adjusted R2 was 0.39. The risk of ΔPes being >10 cmH2O can be predicted from BEa, respiratory rate, and PaO2:FiO2. The area under the receiver operating characteristic curve was 0.79 (0.73-0.85). We called these two models BREF, where BREF stands for BReathing EFfort and the three common predictors: BEa (B), respiratory rate (RE), and PaO2:FiO2 (F).

Conclusions: We developed two models to estimate the breathing effort of patients on high-flow oxygen therapy. Our initial findings are promising and suggest that these models merit further evaluation.

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来源期刊
Pulmonology
Pulmonology Medicine-Pulmonary and Respiratory Medicine
CiteScore
14.30
自引率
5.10%
发文量
159
审稿时长
19 days
期刊介绍: Pulmonology (previously Revista Portuguesa de Pneumologia) is the official journal of the Portuguese Society of Pulmonology (Sociedade Portuguesa de Pneumologia/SPP). The journal publishes 6 issues per year and focuses on respiratory system diseases in adults and clinical research. It accepts various types of articles including peer-reviewed original articles, review articles, editorials, and opinion articles. The journal is published in English and is freely accessible through its website, as well as Medline and other databases. It is indexed in Science Citation Index Expanded, Journal of Citation Reports, Index Medicus/MEDLINE, Scopus, and EMBASE/Excerpta Medica.
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