Gerald Stanley Zavorsky, Giovanni Barisione, Thomas Gille, Roberto W Dal Negro, Marta Núñez-Fernández, Leigh Seccombe, Gianluca Imeri, Fabiano Di Marco, Jann Mortensen, Elisabetta Salvioni, Piergiuseppe Agostoni, Vito Brusasco
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The dataset included 572 COVID-19 survivors and 72 matched controls from six European centres. Lung function metrics-including spirometry, total lung capacity, DLNO<sub>5s</sub> and DLCO<sub>5s</sub>-were standardised into <i>z</i>-scores. Logistic models were compared using Bayesian Information Criterion and Leave-One-Out Information Criterion. Classification accuracy was assessed with Matthews Correlation Coefficient (MCC) and net reclassification improvement (NRI). Principal Component Analysis examined score structures, and dyspnoea severity was correlated with z-scores. Assessments were conducted 32-575 days post-infection (median=130 days).</p><p><strong>Results: </strong>The number of days between SARS-CoV-2 diagnosis and testing did not affect any of the measured z-scores. Summed DLNO<sub>5s</sub> + DLCO<sub>5s</sub> <i>z</i>-scores consistently outperformed individual metrics. The combined model improved MCC by 0.06 (95% CI 0.01 to 0.11) and NRI by 37% (95% CI 13 to 62%) over DLCO<sub>5s</sub> alone. The top model summed DLNO<sub>5s</sub> + DLCO<sub>5s</sub> model explained 10% of fixed and 59% of random variance. DLCO<sub>5s</sub> alone failed to identify reduced membrane diffusion in approximately 16% of cases. Dyspnoea severity was significantly associated with all diffusion indices (p<0.001), though combined scores showed no stronger correlation than single predictors.</p><p><strong>Conclusion: </strong>Summed DLNO<sub>5s</sub> + DLCO<sub>5s</sub> <i>z</i>-scores enhance classification of post-COVID-19 pulmonary impairment beyond DLCO<sub>5s</sub> alone. The NO-CO double diffusion approach offers improved diagnostic discrimination between previously infected individuals and controls and aligns with symptom severity. 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The dataset included 572 COVID-19 survivors and 72 matched controls from six European centres. Lung function metrics-including spirometry, total lung capacity, DLNO<sub>5s</sub> and DLCO<sub>5s</sub>-were standardised into <i>z</i>-scores. Logistic models were compared using Bayesian Information Criterion and Leave-One-Out Information Criterion. Classification accuracy was assessed with Matthews Correlation Coefficient (MCC) and net reclassification improvement (NRI). Principal Component Analysis examined score structures, and dyspnoea severity was correlated with z-scores. Assessments were conducted 32-575 days post-infection (median=130 days).</p><p><strong>Results: </strong>The number of days between SARS-CoV-2 diagnosis and testing did not affect any of the measured z-scores. Summed DLNO<sub>5s</sub> + DLCO<sub>5s</sub> <i>z</i>-scores consistently outperformed individual metrics. 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引用次数: 0
摘要
背景:COVID-19后持续肺功能障碍很常见,但传统的仅使用一氧化碳弥散量(DLCO)的评估可能会遗漏肺泡-毛细血管损伤。目的:探讨一氧化氮(dlno5)和一氧化碳(dlco5)弥散能力的结合是否能增强对covid -19后肺损伤的检测,以及总z评分在对患者进行分类方面是否优于个体指标。设计和方法:我们使用分层混合效应模型进行了个体参与者数据荟萃分析。该数据集包括来自六个欧洲中心的572名COVID-19幸存者和72名匹配的对照组。肺功能指标(包括肺活量测定、总肺活量、dlno5和dlco5)被标准化为z评分。采用贝叶斯信息准则和留一信息准则对Logistic模型进行了比较。采用马修斯相关系数(MCC)和净重分类改进(NRI)评价分类精度。主成分分析检查了评分结构,呼吸困难严重程度与z评分相关。感染后32-575天(中位数=130天)进行评估。结果:SARS-CoV-2诊断和检测之间的天数不影响任何测量的z分数。总dlno5 + dlco5的z得分始终优于个人指标。与单独的dlco5相比,联合模型使MCC提高0.06 (95% CI 0.01至0.11),NRI提高37% (95% CI 13至62%)。顶层模型将DLNO5s + DLCO5s模型相加,解释了10%的固定方差和59%的随机方差。在大约16%的病例中,仅dlco5不能识别膜扩散减少。呼吸困难严重程度与所有弥散指数均有显著相关性(p)。结论:DLNO5s + DLCO5s z-score相加比单独DLCO5s更能增强covid -19后肺损伤的分类。NO-CO双扩散方法可改善先前感染个体和对照组之间的诊断区别,并与症状严重程度保持一致。这些发现支持在covid - 19后评估中更广泛地整合联合扩散指标。
Enhanced detection of patients with previous COVID-19: superiority of the double diffusion technique.
Background: Persistent pulmonary dysfunction is common after COVID-19, yet traditional assessments using carbon monoxide diffusing capacity (DLCO) alone may miss alveolar-capillary impairment.
Objective: To determine whether combining nitric oxide (DLNO5s) and carbon monoxide (DLCO5s) diffusing capacities enhances detection of post-COVID-19 lung impairment and whether summed z-scores outperform individual measures in classifying affected individuals.
Design and methods: We conducted an individual participant data meta-analysis using hierarchical mixed-effects modelling. The dataset included 572 COVID-19 survivors and 72 matched controls from six European centres. Lung function metrics-including spirometry, total lung capacity, DLNO5s and DLCO5s-were standardised into z-scores. Logistic models were compared using Bayesian Information Criterion and Leave-One-Out Information Criterion. Classification accuracy was assessed with Matthews Correlation Coefficient (MCC) and net reclassification improvement (NRI). Principal Component Analysis examined score structures, and dyspnoea severity was correlated with z-scores. Assessments were conducted 32-575 days post-infection (median=130 days).
Results: The number of days between SARS-CoV-2 diagnosis and testing did not affect any of the measured z-scores. Summed DLNO5s + DLCO5sz-scores consistently outperformed individual metrics. The combined model improved MCC by 0.06 (95% CI 0.01 to 0.11) and NRI by 37% (95% CI 13 to 62%) over DLCO5s alone. The top model summed DLNO5s + DLCO5s model explained 10% of fixed and 59% of random variance. DLCO5s alone failed to identify reduced membrane diffusion in approximately 16% of cases. Dyspnoea severity was significantly associated with all diffusion indices (p<0.001), though combined scores showed no stronger correlation than single predictors.
Conclusion: Summed DLNO5s + DLCO5sz-scores enhance classification of post-COVID-19 pulmonary impairment beyond DLCO5s alone. The NO-CO double diffusion approach offers improved diagnostic discrimination between previously infected individuals and controls and aligns with symptom severity. These findings support broader clinical integration of combined diffusion metrics in post-COVID assessment.
期刊介绍:
BMJ Open Respiratory Research is a peer-reviewed, open access journal publishing respiratory and critical care medicine. It is the sister journal to Thorax and co-owned by the British Thoracic Society and BMJ. The journal focuses on robustness of methodology and scientific rigour with less emphasis on novelty or perceived impact. BMJ Open Respiratory Research operates a rapid review process, with continuous publication online, ensuring timely, up-to-date research is available worldwide. The journal publishes review articles and all research study types: Basic science including laboratory based experiments and animal models, Pilot studies or proof of concept, Observational studies, Study protocols, Registries, Clinical trials from phase I to multicentre randomised clinical trials, Systematic reviews and meta-analyses.