tetano
Editor, Senior Moderator
BMJ Open Respir Res
. 2025 Aug 25;12(1):e002561.
doi: 10.1136/bmjresp-2024-002561. Enhanced detection of patients with previous COVID-19: superiority of the double diffusion technique
Gerald Stanley Zavorsky[SUP] 1 [/SUP], Giovanni Barisione[SUP] 2 [/SUP], Thomas Gille[SUP] 3 [/SUP], Roberto W Dal Negro[SUP] 4 [/SUP], Marta Núñez-Fernández[SUP] 5 6 [/SUP], Leigh Seccombe[SUP] 7 8 [/SUP], Gianluca Imeri[SUP] 9 10 [/SUP], Fabiano Di Marco[SUP] 9 10 [/SUP], Jann Mortensen[SUP] 11 [/SUP], Elisabetta Salvioni[SUP] 12 [/SUP], Piergiuseppe Agostoni[SUP] 12 13 [/SUP], Vito Brusasco[SUP] 14 [/SUP]
Affiliations
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 (DLNO[SUB]5s[/SUB]) and carbon monoxide (DLCO[SUB]5s[/SUB]) 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, DLNO[SUB]5s[/SUB] and DLCO[SUB]5s[/SUB]-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 DLNO[SUB]5s[/SUB] + DLCO[SUB]5s[/SUB] z-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.
Conclusion: Summed DLNO[SUB]5s[/SUB] + DLCO[SUB]5s[/SUB] z-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. These findings support broader clinical integration of combined diffusion metrics in post-COVID assessment.
Keywords: COVID-19; Respiratory Function Test; Respiratory Measurement.
. 2025 Aug 25;12(1):e002561.
doi: 10.1136/bmjresp-2024-002561. Enhanced detection of patients with previous COVID-19: superiority of the double diffusion technique
Gerald Stanley Zavorsky[SUP] 1 [/SUP], Giovanni Barisione[SUP] 2 [/SUP], Thomas Gille[SUP] 3 [/SUP], Roberto W Dal Negro[SUP] 4 [/SUP], Marta Núñez-Fernández[SUP] 5 6 [/SUP], Leigh Seccombe[SUP] 7 8 [/SUP], Gianluca Imeri[SUP] 9 10 [/SUP], Fabiano Di Marco[SUP] 9 10 [/SUP], Jann Mortensen[SUP] 11 [/SUP], Elisabetta Salvioni[SUP] 12 [/SUP], Piergiuseppe Agostoni[SUP] 12 13 [/SUP], Vito Brusasco[SUP] 14 [/SUP]
Affiliations
- PMID: 40854805
- PMCID: PMC12382503
- DOI: 10.1136/bmjresp-2024-002561
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 (DLNO[SUB]5s[/SUB]) and carbon monoxide (DLCO[SUB]5s[/SUB]) 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, DLNO[SUB]5s[/SUB] and DLCO[SUB]5s[/SUB]-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 DLNO[SUB]5s[/SUB] + DLCO[SUB]5s[/SUB] z-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.
Conclusion: Summed DLNO[SUB]5s[/SUB] + DLCO[SUB]5s[/SUB] z-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. These findings support broader clinical integration of combined diffusion metrics in post-COVID assessment.
Keywords: COVID-19; Respiratory Function Test; Respiratory Measurement.