Smith, B.M.

Abstract Rationale Impaired lung health may serve as a risk factor for, and a post-acute sequela of, SARS-CoV-2 infection. Yet most prior studies of lung health sequelae of COVID-19 lacked information on pre-infection lung health, a major antecedent confounder. To identify associations of COVID-19 with changes in lung health, we leveraged paired pre- and post-pandemic data on respiratory symptoms, lung function, and lung structure in a general population-based cohort. Methods We studied participants in the Multi-Ethnic Study of Atherosclerosis Lung Study with paired pre-pandemic (2016-2018) and post-pandemic (2022-2024) assessments of respiratory symptoms, spirometry, and lung CT. SARS-CoV-2 infection (2020-2023) was ascertained using a composite of questionnaires, serology, and medical record adjudication, and classified as severe (requiring hospitalization) or non-severe (not requiring hospitalization). Lung health was assessed by questionnaire (mMRC grade ≥2 dyspnea, chronic cough, chronic phlegm, chronic bronchitis), pre-bronchodilator spirometry (FEV1, FVC, FEV1:FVC), and lung density on non-contrast lung CT (% low attenuation areas, % high attenuation areas). Each post-pandemic lung health measure was regressed on infection history and the corresponding pre-pandemic lung health measure, adjusting for age at post-pandemic exam, sex, race/ethnicity, smoking status, and vaccination status at infection. Sensitivity analyses were included- (a) restriction to participants without pre-pandemic respiratory symptoms and (b) with additional adjustment for time since infection and variant wave. Results Among 2,015 participants (mean age 77.2±7.5 years; 55% female; 40% non-Hispanic White; 25% Black; 11% Asian; 23% Hispanic/Latino), 59 (3%) experienced severe and 506 (25%) non-severe SARS-CoV-2 infection. The prevalence of respiratory symptoms was similar or slightly higher at the post- vs. pre-pandemic exam (grade ≥2 dyspnea: 14% vs. 10%; chronic cough: 10% vs. 8%; chronic phlegm: 9% vs. 8%; chronic bronchitis: 4% vs. 4%; p-values <0.0001). Compared with participants without infection, those with severe infection had higher odds of chronic cough (OR:2.9, 95%CI:1.3-6.3) and chronic bronchitis (OR:3.3, 95%CI:1.2-9.0) at the post-pandemic exam (Table). Associations were stronger among individuals infected >90 days prior to the post-pandemic assessment and during pre-Omicron waves. Results were similar when restricted to participants without pre-pandemic symptoms. No significant associations were observed for non-severe infection (vs. no infection) or for any other lung health outcomes. Conclusions Controlling for pre-pandemic lung health, severe COVID-19 was associated with increased odds of chronic cough and chronic bronchitis but not with changes in lung function or structure in a general population-based sample. Non-severe COVID-19 was not associated with lung health outcomes. This abstract is funded by: OT2HL156812, R21HL165405, R01HL077612, 75N92025D00022, 75N92025D00026, 75N92020D00002, 75N92025D00024, 75N92025D00027, 75N92025D00025, 75N92025D00028

Abstract RATIONALE: Susceptibility to severe COVID-19 and long COVID may be influenced by pre-existing lung structure. ECG-gated, non-contrast cardiac CT scans, originally acquired for assessing coronary artery calcium, are available in multiple longitudinal cohort studies and have been previously validated against lung CT scans for densitometry; however, protocol variation across cohorts may hinder direct comparison. To address this, we developed a quality control (QC) rubric to grade cardiac CT scans for standardized quantitative lung measures across cohorts. METHODS: C4R assessed SARS-CoV-2 infection and outcomes in 14 NHLBI cohorts, of which 10 (six community-based and four longitudinal case-control studies) included CT scans (12,459 participants with lung and 13,752 with cardiac CTs). Logic rules were applied to categorize scans (Table): Grade “A-B” scans had 2-3.5mm slice thickness, at least 20 axial slices, no lung cropping in axial view and lung and airway volumes greater than the cohort-specific 1st percentile. “C-D” scans had one lung obscured by cropping around the heart, so quantitative measures were restricted to the lung in complete view. “F-H” scans were deemed unusable, suffering from low slice count (<20), severe image cropping, low lung or airway volumes (< 1st%ile). Visual inspection was performed on a sample from each category to ensure accuracy. Percent of lung voxels in low attenuation areas < -950 HU (LAA950), high attenuation areas (-600 to -250 HU, HAA) and 15th percentile HU value (perc15) were measured. Within-participant variability was quantified using the intraclass correlation coefficient (ICC). RESULTS: We performed QC on cardiac CT scans from an initial sample of 6,275 participants from three C4R cohorts (ARIC, CARDIA, MASALA), imaged with GE or Siemens scanners. Of these, 5,125 (81.7%) were graded “A-B”, 496 (7.9%) were “C-D” and 654 (10.4%) were “F-H”. The percentage of “F-H” scans varied widely across cohorts [<1% to 26%] due to image cropping. Among the 5,621 cardiac CT scans graded A-D, the mean±SD for LAA950, HAA and perc15 respectively were 1.1±2.1%, 7.2±4.7% and -887±33 HU. Repeated imaging was available for 107 participants (time interval 5.1±0.7y). For paired scans in grades A-B (n=101/107), the within-participant correlation for LAA950, HAA and perc15 were 0.91, 0.38 and 0.74 respectively. CONCLUSION: Initial application of QC to cardiac CT scans identified scans with high reproducibility, with the aim to provide valid quantitative lung metrics on over 20,000 highly characterized participants in C4R.