利用 COVID-19 对重症监护室患者进行有创机械通气的预测模型进行推导和外部验证。

IF 5.7 1区 医学 Q1 CRITICAL CARE MEDICINE Annals of Intensive Care Pub Date : 2024-08-21 DOI:10.1186/s13613-024-01357-4
Gabriel Maia, Camila Marinelli Martins, Victoria Marques, Samantha Christovam, Isabela Prado, Bruno Moraes, Emanuele Rezoagli, Giuseppe Foti, Vanessa Zambelli, Maurizio Cereda, Lorenzo Berra, Patricia Rieken Macedo Rocco, Mônica Rodrigues Cruz, Cynthia Dos Santos Samary, Fernando Silva Guimarães, Pedro Leme Silva
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引用次数: 0

摘要

研究背景本研究旨在开发用于预测重症监护病房(ICU)COVID-19 患者有创机械通气(IMV)需求的预后模型,并将其性能与呼吸速率-氧合指数(ROX)进行比较:利用 2020 年 3 月至 2021 年 8 月期间在巴西里约热内卢三家医院收集的数据进行了一项回顾性队列研究。研究筛选了诊断为 COVID-19 的 18 岁及以上 ICU 患者。排除标准包括:在入住 ICU 后 24 小时内接受过 IMV 治疗的患者、怀孕患者、临床决定接受最低限度临终关怀的患者以及主要结果数据缺失的患者。收集了临床和实验室变量。进行多元逻辑回归分析以选择预测变量。模型基于最低的阿凯克信息准则(AIC)和具有显著 p 值的最低 AIC。对预测性能进行了判别和校准评估。使用 DeLong 算法比较了曲线下面积(AUC)。使用国际数据库对模型进行了外部验证:在筛查的 656 名患者中,346 名患者被纳入;155 名患者需要接受 IMV(44.8%),191 名患者不需要(55.2%),207 名患者为男性(59.8%)。根据最低 AIC,动脉高血压、糖尿病、肥胖、序贯器官衰竭评估(SOFA)评分、心率、呼吸频率、外周血氧饱和度(SpO2)、体温、呼吸努力信号和白细胞被确定为入院时 IMV 的预测因素。根据具有显著 p 值的 AIC,SOFA 评分、SpO2 和呼吸努力信号是预测 IMV 的最佳指标;几率比(95% 置信区间)为 1.46(1.07-2.00):分别为 1.46(1.07-2.05)、0.81(0.72-0.90)、9.13(3.29-28.67)。入院时的 ROX 指数,IMV 组低于非 IMV 组(7.3 [5.2-9.8] 对 9.6 [6.8-12.9],P在使用 COVID-19 的 ICU 患者中,SOFA 评分、SpO2 和呼吸努力信号比 ROX 指数更能预测 IMV 的需求。在外部验证人群中,虽然AUC没有显著差异,但与ROX指数相比,使用SOFA评分、SpO2和呼吸努力信号的准确性更高。这表明,这些变量在预测 ICU COVID-19 患者对 IMV 的需求方面可能更有用:Gov 标识符:NCT05663528。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Derivation and external validation of predictive models for invasive mechanical ventilation in intensive care unit patients with COVID-19.

Background: This study aimed to develop prognostic models for predicting the need for invasive mechanical ventilation (IMV) in intensive care unit (ICU) patients with COVID-19 and compare their performance with the Respiratory rate-OXygenation (ROX) index.

Methods: A retrospective cohort study was conducted using data collected between March 2020 and August 2021 at three hospitals in Rio de Janeiro, Brazil. ICU patients aged 18 years and older with a diagnosis of COVID-19 were screened. The exclusion criteria were patients who received IMV within the first 24 h of ICU admission, pregnancy, clinical decision for minimal end-of-life care and missing primary outcome data. Clinical and laboratory variables were collected. Multiple logistic regression analysis was performed to select predictor variables. Models were based on the lowest Akaike Information Criteria (AIC) and lowest AIC with significant p values. Assessment of predictive performance was done for discrimination and calibration. Areas under the curves (AUC)s were compared using DeLong's algorithm. Models were validated externally using an international database.

Results: Of 656 patients screened, 346 patients were included; 155 required IMV (44.8%), 191 did not (55.2%), and 207 patients were male (59.8%). According to the lowest AIC, arterial hypertension, diabetes mellitus, obesity, Sequential Organ Failure Assessment (SOFA) score, heart rate, respiratory rate, peripheral oxygen saturation (SpO2), temperature, respiratory effort signals, and leukocytes were identified as predictors of IMV at hospital admission. According to AIC with significant p values, SOFA score, SpO2, and respiratory effort signals were the best predictors of IMV; odds ratios (95% confidence interval): 1.46 (1.07-2.05), 0.81 (0.72-0.90), 9.13 (3.29-28.67), respectively. The ROX index at admission was lower in the IMV group than in the non-IMV group (7.3 [5.2-9.8] versus 9.6 [6.8-12.9], p < 0.001, respectively). In the external validation population, the area under the curve (AUC) of the ROX index was 0.683 (accuracy 63%), the AIC model showed an AUC of 0.703 (accuracy 69%), and the lowest AIC model with significant p values had an AUC of 0.725 (accuracy 79%).

Conclusions: In the development population of ICU patients with COVID-19, SOFA score, SpO2, and respiratory effort signals predicted the need for IMV better than the ROX index. In the external validation population, although the AUCs did not differ significantly, the accuracy was higher when using SOFA score, SpO2, and respiratory effort signals compared to the ROX index. This suggests that these variables may be more useful in predicting the need for IMV in ICU patients with COVID-19.

Clinicaltrials:

Gov identifier: NCT05663528.

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来源期刊
Annals of Intensive Care
Annals of Intensive Care CRITICAL CARE MEDICINE-
CiteScore
14.20
自引率
3.70%
发文量
107
审稿时长
13 weeks
期刊介绍: Annals of Intensive Care is an online peer-reviewed journal that publishes high-quality review articles and original research papers in the field of intensive care medicine. It targets critical care providers including attending physicians, fellows, residents, nurses, and physiotherapists, who aim to enhance their knowledge and provide optimal care for their patients. The journal's articles are included in various prestigious databases such as CAS, Current contents, DOAJ, Embase, Journal Citation Reports/Science Edition, OCLC, PubMed, PubMed Central, Science Citation Index Expanded, SCOPUS, and Summon by Serial Solutions.
期刊最新文献
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